Advances in Computer Science, Part I - CSEE 2011

Communications in Computer and Information Science

214

Song Lin Xiong Huang (Eds.)

Advances in Computer Science, Environment, Ecoinformatics, and Education International Conference, CSEE 2011 Wuhan, China, August 21-22, 2011 Proceedings, Part I

13

Volume Editors Song Lin International Science & Education Researcher Association Wuhan Branch, No.1, Jiangxia Road, Wuhan, China E-mail: [email protected] Xiong Huang International Science & Education Researcher Association Wuhan Branch, No.1, Jiangxia Road, Wuhan, China E-mail: [email protected]

ISSN 1865-0929 e-ISSN 1865-0937 ISBN 978-3-642-23320-3 e-ISBN 978-3-642-23321-0 DOI 10.1007/978-3-642-23321-0 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: Applied for CR Subject Classification (1998): I.2, C.2, H.4, H.3, D.2, H.5

© Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

The International Science & Education Researcher Association (ISER) puts its focus on the study and exchange of academic achievements of international teaching and research staff. It also promotes educational reform in the world. In addition, it serves as an academic discussion and communication platform, which is beneficial for education and scientific research, aiming to stimulate the interest of all researchers. The CSEE-TMEI conference is an integrated event concentrating on the field of computer science, environment, ecoinformatics, and education. The goal of the conference is to provide researchers working in this field with a forum to share new ideas, innovations, and solutions. CSEE 2011-TMEI 2011 was held during August 21–22, in Wuhan, China, and was co-sponsored by the International Science & Education Researcher Association, Beijing Gireida Education Co. Ltd, and Wuhan University of Science and Technology, China. Renowned keynote speakers were invited to deliver talks, giving all participants a chance to discuss their work with the speakers face to face. In these proceeding, you can learn more about the field of computer science, environment, ecoinformatics, and education from the contributions of several researchers from around the world. The main role of the proceeding is to be used as means of exchange of information for those working in this area. The Organizing Committee made a great effort to meet the high standards of Springer’s Communications in Computer and Information Science (CCIS) series. Firstly, poor-quality papers were rejected after being reviewed by anonymous referees. Secondly, meetings were held periodically for reviewers to exchange opinions and suggestions. Finally, the organizing team held several preliminary sessions before the conference. Through the efforts of numerous people and departments, the conference was very successful. During the organization, we received help from different people, departments, and institutions. Here, we would like to extend our sincere thanks to the publishers of CCIS, Springer, for their kind and enthusiastic help and support of our conference. Secondly, the authors should also be thanked for their submissions. Thirdly, the hard work of the Program Committee, the Program Chairs, and the reviewers is greatly appreciated. In conclusion, it was the team effort of all these people that made our conference such a success. We welcome any suggestions that may help improve the conference and look forward to seeing all of you at CSEE 2012-TMEI 2012. June 2011

Song Lin

Organization

Honorary Chairs Chen Bin Hu Chen Chunhua Tan Helen Zhang

Beijing Normal University, China Peking University, China Beijing Normal University, China University of Munich, Germany

Program Committee Chairs Xiong Huang Li Ding Zhihua Xu

International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China

Organizing Chairs ZongMing Tu Jijun Wang Quan Xiang

Beijing Gireida Education Co. Ltd, China Beijing Spon Technology Research Institution, China Beijing Prophet Science and Education Research Center, China

Publication Chairs Song Lin Xiong Huang

International Science & Education Researcher Association, China International Science & Education Researcher Association, China

International Program Committee Sally Wang Li Li Bing Xiao Z.L. Wang Moon Seho Kongel Arearak Zhihua Xu

Beijing Normal University, China Dongguan University of Technology, China Anhui University, China Wuhan University, China Hoseo University, Korea Suranaree University of Technology, Thailand International Science & Education Researcher Association, China

VIII

Organization

Co-sponsored by International Science & Education Researcher Association, China VIP Information Conference Center, China

Reviewers Chunlin Xie Lin Qi Xiong Huang Gang Shen Xiangrong Jiang Li Hu Moon Hyan Guang Wen Jack H. Li Marry. Y. Feng Feng Quan Peng Ding Song Lin XiaoLie Nan Zhi Yu Xue Jin Zhihua Xu Wu Yang Qin Xiao Weifeng Guo Li Hu Zhong Yan Haiquan Huang Xiao Bing Brown Wu

Wuhan University of Science and Technology, China Hubei University of Technology, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China Wuhan University of Technology, China Linguistic and Linguidtic Education Association, China Sungkyunkwan University, Korea South China University of Technology, China George Mason University, USA University of Technology Sydney, Australia Zhongnan University of Finance and Economics, China Hubei University, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China International Science & Education Researcher Association, China Wuhan University of Science and Technology, China, Wuhan University of Science and Technology, China Hubei University of Technology, China Wuhan University, China Sun Yat-Sen University, China

Table of Contents – Part I

Convergence of the Stochastic Age-Structured Population System with Diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dongjuan Ma and Qimin Zhang

1

Parallel Computer Processing Systems Are Better Than Serial Computer Processing Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zvi Retchkiman Konigsberg

8

Smooth Path Algorithm Based on A* in Games . . . . . . . . . . . . . . . . . . . . . . Xiang Xu and Kun Zou

15

The Features of Biorthogonal Binary Poly-scale Wavelet Packs in Bidimensional Function Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhihao Tang and Honglin Guo

22

The Traits of Dual Multiple Ternary Fuzzy Frames of Translates with Ternary Scaling Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ShuKe Zhou and Qingjiang Chen

29

The Characteristics of Multiple Affine Oblique Binary Frames of Translates with Binary Filter Banks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . YongGan Li

36

Generation and Characteristics of Vector-Valued Quarternary Wavelets with Poly-scale Dilation Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ping Luo and Shiheng Wang

42

A Kind of New Strengthening Buffer Operators and Their Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ran Han and Zheng-peng Wu

49

Infrared Target Detection Based on Spatially Related Fuzzy ART Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BingWen Chen, WenWei Wang, and QianQing Qin

55

A Novel Method for Quantifying the Demethylation Potential of Environmental Chemical Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yan Jiang and Xianliang Wang

62

Study of Quantitative Evaluation of the Effect of Prestack Noise Attenuation on Angle Gather . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Junhua Zhang, Jing Wang, Xiaoteng Liang, Shaomei Zhang, and Shengtao Zang

72

X

Table of Contents – Part I

A User Model for Recommendation Based on Facial Expression Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Quan Lu, Dezhao Chen, and Jiayin Huang An Improved Sub-pixel Location Method for Image Measurement . . . . . . Hu Zhou, Zhihui Liu, and Jianguo Yang The Dynamic Honeypot Design and Implementation Based on Honeyd . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xuewu Liu, Lingyi Peng, and Chaoliang Li

78

83

93

Research of SIP DoS Defense Mechanism Based on Queue Theory . . . . . . Fuxiang Gao, Qiao Liu, and Hongdan Zhan

99

Research on the Use of Mobile Devices in Distance EFL Learning . . . . . . Fangyi Xia

105

Flood Risk Assessment Based on the Information Diffusion Method . . . . Li Qiong

111

Dielectric Characteristics of Chrome Contaminated Soil . . . . . . . . . . . . . . . Yakun Sun, Yuqiang Liu, Changxin Nai, and Lu Dong

118

Influences of Climate on Forest Fire during the Period from 2000 to 2009 in Hunan Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ZhiGang Han, DaLun Tian, and Gui Zhang

123

Numerical Simulation for Optimal Harvesting Strategies of Fish Stock in Fluctuating Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lulu Li, Wen Zhao, Lijuan Cao, and Hongyan Ao

131

The Graphic Data Conversion from AutoCAD to GeoDatabase . . . . . . . . Xiaosheng Liu and Feihui Hu

137

Research on Knowledge Transference Management of Knowledge Alliance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jibin Ma, Gai Wang, and Xueyan Wang

143

The Study of Print Quality Evaluation System Using the Back Propagation Neural Network with Applications to Sheet-Fed Offset . . . . . Taolin Ma, Yang Li, and Yansong Sun

149

Improved Design of GPRS Wireless Security System Based on AES . . . . TaoLin Ma, XiaoLan Sun, and LiangPei Zhang Design and Realization of FH-CDMA Scheme for Multiple-Access Communication Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abdul Baqi, Sajjad Ahmed Soomro, and Safeeullah Soomro

155

161

Table of Contents – Part I

XI

Design and Implement on Automated Pharmacy System . . . . . . . . . . . . . . HongLei Che, Chao Yun, and JiYuan Zang

167

Research on Digital Library Platform Based on Cloud Computing . . . . . . Lingling Han and Lijie Wang

176

Research on Nantong University of Radio and TV Websites Developing Based on ASP and Its Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shengqi Jing Analysis of Sustainable Development in Guilin by Using the Theory of Ecological Footprint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hao Wang, GuanWen Cheng, Shan Xu, ZiHan Xu, XiaoWei Song, WenYuan Wei, HongYuan Fu, and GuoDan Lu Analysis of Emergy and Sustainable Development on the Eco-economic System of Guilin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ZiHan Xu, GuanWen Cheng, Hao Wang, HongYuan Fu, GuoDan Lu, and Ping Qin Multiple Frequency Detection System Design . . . . . . . . . . . . . . . . . . . . . . . . Wen Liu, Jun da Hu, and Ji cui Shi

181

187

194

201

The Law and Economic Perspective of Protecting the Ecological Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Xiuping and Liang Xianyan

207

Research on the Management Measure for Livestock Pollution Prevention and Control in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yukun Ji, Kaijun Wang, and Mingxia Zheng

214

The Design of Supermarket Electronic Shopping Guide System Based on ZigBee Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yujie Zhang, Liang Han, and Yuanyuan Zhang

219

The Research of Flame Combustion Diagnosis System Based on Digital Image Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . YuJie Zhang, SaLe Hui, and YuanYuan Zhang

225

Design and Research of Virtual Instrument Development Board . . . . . . . . Lin Zhang, Taizhou Li, and Zhuo Chen

231

Substantial Development Strategy of Land Resource in Zhangjiakou . . . . Yuqiang Sun, Shengchen Wang, and Yanna Zhao

239

Computational Classification of Cloud Forests in Thailand Using Statistical Behaviors of Weather Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Peerasak Sangarun, Wittaya Pheera, Krisanadej Jaroensutasinee, and Mullica Jaroensutasinee

244

XII

Table of Contents – Part I

Research on Establishing the Early-Warning Index System of Energy Security in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yanna Zhao, Min Zhang, and Yuqiang Sun Artificial Enzyme Construction with Temperature Sensitivity . . . . . . . . . . Tingting Lin, Jun Lin, Xin Huang, and Junqiu Liu

251 257

An Efficient Message-Attached Password Authentication Protocol and Its Applications in the Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . An Wang, Zheng Li, and Xianwen Yang

263

Research on Simulation and Optimization Method for Tooth Movement in Virtual Orthodontics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhanli Li and Guang Yang

270

An Interval Fuzzy C-means Algorithm Based on Edge Gradient for Underwater Optical Image Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shilong Wang, Yuru Xu, and Lei Wan

276

A Generic Construction for Proxy Cryptography . . . . . . . . . . . . . . . . . . . . . Guoyan Zhang VCAN-Controller Area Network Based Human Vital Sign Data Transmission Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atiya Azmi, Nadia Ishaque, Ammar Abbas, and Safeeullah Soomro Study on the Some Labelings of Complete Bipartite Graphs . . . . . . . . . . . WuZhuang Li, GuangHai Li, and QianTai Yan

284

290 297

An Effective Adjustment on Improving the Process of Road Detection on Raster Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yang Li, Xiao-dong Zhang, and Yuan-lu Bao

302

Multi-objective Optimized PID Controller for Unstable First-Order Plus Delay Time Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gongquan Tan, Xiaohui Zeng, Shuchuan Gan, and Yonghui Chen

309

Water Quality Evaluation for the Main Inflow Rivers of Nansihu Lake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yang Liyuan, Shen Ji, Liu Enfeng, and Zhang Wei

316

Software Piracy: A Hard Nut to Crack—A Problem of Information Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bigang Hong

324

Study of Bedrock Weathering Zone Features in Suntuan Coal Mine . . . . . XiaoLong Li, DuoXi Yao, and JinXiang Yang

330

Mercury Pollution Characteristics in the Soil around Landfill . . . . . . . . . . JinXiang Yang, MingXu Zhang, and XiaoLong Li

336

Table of Contents – Part I

XIII

The Research on Method of Detection for Three-Dimensional Temperature of the Furnace Based on Support Vector Machine . . . . . . . . Yang Yu, Jinxing Chen, Guohua Zhang, and Zhiyong Tao

341

Study on Wave Filtering of Photoacoustic Spectrometry Detecting Signal Based on Mallat Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yang Yu, Shuo Wu, Guohua Zhang, and Peixin Sun

347

Ontology-Based Context-Aware Management for Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Keun-Wang Lee and Si-Ho Cha

353

An Extended Center-Symmetric Local Ternary Patterns for Image Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaosheng Wu and Junding Sun

359

Comparison of Photosynthetic Parameters and Some Physilogical Indices of 11 Fennel Varieties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mingyou Wang, Beilei Xiao, and Lixia Liu

365

Effect of Naturally Low Temperature Stress on Cold Resistance of Fennel Varieties Resource . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Beilei Xiao, Mingyou Wang, and Lixia Liu

370

Survey on the Continuing Physical Education in the Cities around the Taihu Lake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . JianQiang Guo

375

The Gas Seepage and Migration Law of Mine Fire Zone under the Positive Pressure Ventilation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HaiYan Wang, ZhenLong Zhang, DanDan Jiang, and FeiYin Wang

381

Study on Continued Industry’s Development Path of Resource-Based Cities in Heilongjiang Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ying Zhu and Jiehua Lv

390

Cable Length Measurement Systems Based on Time Domain Reflectometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianhui Song, Yang Yu, and Hongwei Gao

396

The Cable Crimp Levels Effect on TDR Cable Length Measurement System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianhui Song, Yang Yu, and Hongwei Gao

402

The Clustering Algorithm Based on the Most Similar Relation Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wei Hong Xu, Min Zhu, Ya Ruo Jiang, Yu Shan Bai, and Yan Yu

408

Study of Infrared Image Enhancement Algorithm in Front End . . . . . . . . Rongtian Zheng, Jingxin Hong, and Qingwei Liao

416

XIV

Table of Contents – Part I

Influence of Milling Conditions on the Surface Quality in High-Speed Milling of Titanium Alloy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaolong Shen, Laixi Zhang, and Chenggao Ren Molecular Dynamics Simulation Study on the Microscopic Structure and the Diffusion Behavior of Methanol in Confined Carbon Nanotubes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hua Liu, XiaoFeng Yang, Chunyan Li, and Jianchao Chen

423

430

Spoken Emotion Recognition Using Radial Basis Function Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shiqing Zhang, Xiaoming Zhao, and Bicheng Lei

437

Facial Expression Recognition Using Local Fisher Discriminant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shiqing Zhang, Xiaoming Zhao, and Bicheng Lei

443

Improving Tracking Performance of PLL Based on Wavelet Packet De-noising Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . YinYin Li, XiaoSu Xu, and Tao Zhang

449

Improved Algorithm of LED Display Image Based on Composed Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xi-jia Song, Xi-qiang Ma, Wei-ya Liu, and Xi-feng Zheng

457

The Development Process of Multimedia Courseware Using Authoware and Analysis of Common Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LiMei Fu

464

Design of Ship Main Engine Speed Controller Based on Expert Active Disturbance Rejection Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Weigang Pan, Guiyong Yang, Changshun Wang, and Yingbing Zhou

470

Design of Ship Course Controller Based on Genetic Algorithm Active Disturbance Rejection Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hairong Xiao, Weigang Pan, and Yaozhen Han

476

A CD-ROM Management Device with Free Storage, Automatic Disk Check Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Daohe Chen, Xiaohong Wang, and Wenze Li

482

An Efficient Multiparty Quantum Secret Sharing with Pure Entangled Two Photon States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Run-hua Shi and Hong Zhong

489

Problems and Countermeasures of Educational Informationization Construction in Colleges and Universities . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiaguo Luo and Jie Yu

496

Table of Contents – Part I

Synthesis and Characterization of Eco-friendly Composite: Poly(Ethylene Glycol)-Grafted Expanded Graphite/Polyaniline . . . . . . . . Mincong Zhu, Xin Qing, Kanzhu Li, Wei Qi, Ruijing Su, Jun Xiao, Qianqian Zhang, Dengxin Li, Yingchen Zhang, and Ailian Liu

XV

501

The Features of a Sort of Five-Variant Wavelet Packet Bases in Sobolev Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yujuan Hu, Qingjiang Chen, and Lang Zhao

507

The Features of Multiple Affine Fuzzy Quarternary Frames in Sobolev Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hongwei Gao

513

Characters of Orthogonal Nontensor Product Trivariate Wavelet Wraps in Three-Dimensional Besov Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiantang Zhao and Qingjiang Chen

519

Research on Computer Education and Education Reform Based on a Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianhong Sun, Qin Xu, Yingjiang Li, and JunSheng Li

525

The Existence and Uniqueness for a Class of Nonlinear Wave Equations With Damping Term . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bo Lu and Qingshan Zhang

530

Research on the Distributed Satellite Earth Measurement System Based on ICE Middleware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jun Zhou, Wenquan Feng, and Zebin Sun

534

The Analysis and Optimization of KNN Algorithm Space-Time Efficiency for Chinese Text Categorization . . . . . . . . . . . . . . . . . . . . . . . . . . Ying Cai and Xiaofei Wang

542

Research of Digital Character Recognition Technology Based on BP Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xianmin Wei

551

Image Segmentation Based on D-S Evidence Theory and C-means Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xianmin Wei

556

Time-Delay Estimation Based on Multilayer Correlation . . . . . . . . . . . . . . Hua Yan, Yang Zhang, and GuanNan Chen Applying HMAC to Enhance Information Security for Mobile Reader RFID System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fu-Tung Wang, Tzong-Dar Wu, and Yu-Chung Lu

562

568

XVI

Table of Contents – Part I

Analysis Based on Generalized Regression Neural Network to Oil Atomic Emission Spectrum Data of a Type Diesel Engine . . . . . . . . . . . . . ChunHui Zhang, HongXiang Tian, and Tao Liu

574

Robust Face Recognition Based on KFDA-LLE and SVM Techniques . . . GuoQiang Wang and ChunLing Gao

581

An Improved Double-Threshold Cooperative Spectrum Sensing . . . . . . . . DengYin Zhang and Hui Zhang

588

Handwritten Digit Recognition Based on Principal Component Analysis and Support Vector Machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rui Li and Shiqing Zhang

595

Research on System Stability with Extended Small Gain Theory Based on Transfer Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yuqiang Jin and Qiang Ma

600

Research on the Chattering Problem with VSC of Supersonic Missiles Based on Intelligent Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Junwei Lei, Jianhong Shi, Guorong Zhao, and Guoqiang Liang

606

Research on Backstepping Nussbaum Gain Control of Missile Overload System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianhong Shi, Guorong Zhao, Junwei Lei, and Guoqiang Liang

612

Adaptive Control of Supersonic Missiles with Unknown Input Coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jinhua Wu, Junwei Lei, Wenjin Gu, and Jianhong Shi

616

The Fault Diagnostic Model Based on MHMM-SVM and Its Aplication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FengBo Zhu, WenQuan Wu, ShanLin Zhu, and RenYang Liu

621

Analysis of a Novel Electromagnetic Bandgap Structure for Simultaneous Switching Noise Suppression . . . . . . . . . . . . . . . . . . . . . . . . . . Hua Yang, ShaoChang Chen, Qiang Zhang, and WenTing Zheng

628

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

635

Convergence of the Stochastic Age-Structured Population System with Diffusion Dongjuan Ma and Qimin Zhang* School of Mathematics and Computer Science, Ning Xia University 750021,Yinchuan, China [email protected], [email protected]

Abstract. In this paper, stochastic age-structure population system with jump are studied. It is proved that the semi-implicit Euler approximation solutions converge to the analytic solution for the stochastic age-structured population system with Poisson jump. The analysis use Itoˆ ′s formula, Burkholder-DavisGundy's inequality, Gronwall's lemma and some inequalities for our purposes. Keywords: Semi-implicit Euler method, Poisson jump, Numerical solution.

1 Introduction The theories of stochastic partial differential equations have been extensively many areas, such as economics, finance and several areas of science and engineering and so on. There have been mach researched in deterministic age-structured population with diffusion system and discussed the existence, uniqueness, stability regularity and localization of the solution of this system [1-3]. In recent years, it is more necessary to consider the random behavior of the birthdeath process and the effects of the stochastic environmental noise for Age-structured population systems. Most of papers are concerned about stochastic population system. The random element is considered, there have been many results from stochastic agestochastic age-structured population system. For instance, Zhang discussed the existence and uniqueness for a stochastic age-structured population system with diffusion [4]. When the diffusion of the population is not considered, Zhang studied the existence, uniqueness and exponential stability of a stochastic age-dependent population system ,and numerical analysis for stochastic age dependent population have been studied in [5-8]. Interest has been growing in the study of stochastic differential equations with jumps, which is extensively used to model many of the phenomena arising in the areas [9-10]. In general, most of stochastic age-structured population system with Poisson jump have not analytic solutions, thus numerical approximation schemes are invaluable tools for exploring their properties. In this paper, a numerical analysis for stochastic age-structured population system which is described by Eqs(1) will be developed. The first contribution is to study the Semi-implicit Euler approximation solutions converge to the analytic solution. The second contribution is to consider diffuse form div( P∇u ). In particular, our results extend those in [6-8]. *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 1–7, 2011. © Springer-Verlag Berlin Heidelberg 2011

2

D. Ma and Q. Zhang

2 Preliminaries and the Semi-implicit Euler Approximation Let:

O = ( 0, A) × T , and V ≡ {ϕ | ϕ ∈ L2 ( O ) ,

∂ϕ ∂ϕ ∈ L2 ( O ) , where are ∂xi ∂xi

generalized partial derivatives}. Then V ′ the dual space of V .we denote by ⋅ and

⋅

the norms in V and V ′ respectively; by 〈⋅, ⋅〉 the duality product between V , V ′ , and

(⋅, ⋅) the scalar product in H .Let ( Ω, F , P ) be a complete probability space with filtration {Ft }t≥ 0 satisfying the usual conditions (i.e., it is increasing and right

by a

F0 contains all P-null sets). In this paper, we consider the convergence of stochastic systems with diffusion kdiv ( P ∇ u ),

continuous while

⎧ ∂P ∂P ⎪ ∂t + ∂r = kdiv( P∇u ) − μ (r , t , x) P + ⎪ ⎪ f (r , t , x, P ) + g (r , t , x, P ) ∂Wt + h(r , t , x, P ) ∂N t , inQ = (0, A) × Q, A ⎪ ∂t ∂t ⎪⎪ (1) A in(0, T ) × Γ, ⎨ P (0, t , x ) = ∫ β (r , t , x ) P (r , t , x )dr , 0 ⎪ P r x P = ( , 0, ) in(0, A) × Γ, ⎪ 0 ( r , x ), ⎪ P (r , t , x) = 0, onΣ A = (0, A) × (0, T ) × ∂Γ, ⎪ A ⎪u (t , x ) = P (r , t , x)dr , inQ, ∫0 ⎪⎩

div be the divergence operator. Let W(t) be a Wiener process, hr ( ,t, x,P) poisson jump procession. For system (1), the discrete time semi-implicit Euler approximation on by the iterative scheme:

∂Nt is the ∂t

t is defined

∂Qn+1 ∂Q + kdiv(Qn+1∇u) − μ(r, t, x)Qn + f (r, t, x, Qn )]+t +α[− n+1 ∂r ∂r +kdiv(Qn+1∇u) − μ(r, t, x)Qn+1 + f (r, t, x,Qn+1)]+t + g(r, t, x, Qn )ΔWn + h(r, t, x, Qn )ΔNn ,

Qn+1 = Qn + (1−α)[−

Here

α ∈ [0,1], Qn

is the approximation to

P (tn , r , x) , for tn = nΔt , the time

increment is Δt = T  1 , and Brownian motion increment is N Possion process increment is +N n = N (t n +1 ) − N (t n ).

+Wn = W(tn+1) −W(tn ),

Convergence of the Stochastic Age-Structured Population System with Diffusion

3

For (1),we define the continuous-time approximation : t ∂Q Qt = P0 + ∫ (1 − α )[− s + kdiv(Qs∇u ) − μ (r , s, x) Z1 ( s ) + f (r , s, x, Z1 ( s ))]ds 0 ∂r t ∂Qs + ∫ α [− + kdiv(Qs ∇u ) − μ (r , s, x) Z 2 ( s) + f (r , s, x, Z 2 ( s))]ds 0 ∂r t

t

0

0

+ ∫ g (r , s, x, Z1 ( s )d W ( s ) + ∫ h(r , s, x, Z1 ( s )d N ( s ),

Z1 (t ) = Z1 (t, r, x) = ΣkN=−01Qk I[k Δt ,(k +1)Δt ] , Z2 (t ) = Z2 (t, r, x) = ΣkN=−01Qk +1I[kΔt ,(k +1)Δt ] , There I G is the indicator function for the set G and Z1(tk ) = Z2 (tk−1) = Qk = Q(tk , r, x). To establish the convergence theorem we shall use the following assumptions: (i)(Lipschitz condition ) here exists a positive constant K such that P1 , P2 ∈ C

| f (r , t , x, P1 ) − f (r , t , x, P2 ) | ∨ | g (r , t , x, P1 ) − g (r , t , x, P2 ) | ∨ | h(r , t , x, P1 ) − h(r , t , x, P2 ) |≤ K | P1 − P2 |, a.e.t ; (ii) μ ( r , t , x ) and

β (r , t , x) are continuous in Q such that

0 ≤ μ 0 ≤ μ ( r , t , x ) ≤ μ < ∞, 0 ≤ β ( r , t , x ) ≤ β < ∞, k 0 ≤ k ( r , t ) ≤ k ; t

∫ | |+u || < k ;

(iii) f ( r , t , x, 0) = 0, g ( r , t , x, 0) = 0,

2

3

0

3 The Main Results In this section, we will provide some theorem which are necessary for the proof of Qt convergence to the analytical Solution of this system Pt . (We only discuss the iterative scheme of the continuous-time, for iterative scheme of the discrete time, there is similar.) Theorem 3.1. Under assumptions (i)-(ii) E Proof. For (1), applying N (t ) = t

| Qt |2 =| Q0 |2 +2(1 − α ) ∫ 〈− 0

t

+2α ∫ 〈− 0

sup | Qt |2 ≤ C1T .

0 ≤t ≤T

N (t ) − λt , and Itoˆ′s formula to | Qt |2 ,

∂Qs + kdiv(Qs ∇u ) − μ ( r , s, x) Z1 ( s) + f ( r , s, x, Z1 ( s)), Qs 〉 ds ∂r

∂Qs + kdiv(Qs∇u) − μ ( r, s, x) Z 2 ( s) + f ( r, s, x, Z 2 ( s)), Qs 〉 ds ∂r

t

t

+2 ∫ d Ws + ∫ | | g (r , s, x, Z1 ) ||22 ds 0

0

t

t

0

0

+2 ∫ 〈Qs , h (r , s , x, Z1 )〉 d N s + ∫ |h ( r , s , x, Z1 ) |2 d N s

4

D. Ma and Q. Zhang

t

≤| Q0 |2 −2 ∫ 〈 0

t t ∂Qs , Qs 〉ds + 2 ∫ 〈 kdiv(Qs ∇u ), Qs 〉 ds − 2 μ0 ∫ ∫ ((1 0 0 O ∂r

−α ) Z1 ( s) + α Z 2 ( s))Qs drdxds + 2 ∫

t

∫

0 O

+ 2∫

t

∫

0 O

((1 − α ) f (r , s, x, Z1 ) + α f (r , s, x, Z 2 ))Qs drdxds

t

t

0

0 O

+ ∫ | | g (r , s, x, Z1 ) ||22 ds + 2 ∫ +2λ ∫

t

∫

g ( r , s, x, Z1 )Qs drdxd Ws

0 O

∫

h(r , s, x, Z1 )Qs drdxdN

h(r , s, x, Z1 )Qs drdxds

t t + ∫ |h(r , s, x, Z1 ) |2 dN + λ ∫ |h(r , s, x, Z1 ) |2 ds. 0

0

t

∫ 〈kdiv(Q ∇u ), Q 〉 ds ≤ k ∫ ∫ (∇Q ∇u + Q +u ) drdxds + k ∫ |Q | ds ≤ 2k ∫ | |+u || ds + 2k ∫ | | Q +u || ds + k ∫ |Q | ds ≤ 2k ∫ | |+u || ds + 2k ∫ |Q | ds ∫ | |+u || ds + k ∫ |Q

Since 2

s

0

s

t

t

2

s

0 O t

s

t

2

0

t

2

0

0

t

2

s

0

t

2

s

0

0

t

2

s

2

s

t

2

0

|2 ds.

s

0

By assumptions and the quality of operator, there exist k1 =(2k3 +1)k and k2 =2k3k such that 2

∫

t

0

t

〈 kdiv(Qs ∇u ), Qs 〉 ds ≤ k1 ∫ |Qs |2 ds + k2 . () 0

Applying (7) and −

∫

t

0

〈

t ∂Qs 1 , Qs 〉ds ≤ Aβ 2 ∫ |Qs |2 ds, we have 0 2 ∂r

t

t

0

0

t

t

0

0

| Qt |2 ≤| Q0 |2 + Aβ 2 ∫ |Qs |2 ds + k1 ∫ |Qs |2 ds + k2 + 2 μ0 ∫ |Z1 |2 ds + 2 μ0 ∫ |Z 2 |2 ds t

t

t

0 t

0

0

+2∫ | f (r, s, x, z1 (s)) |2 ds + 2∫ | f (r, s, x, z2 (s)) |2 ds + (1+ λ + μ0 )∫ |Qs |2 ds +2∫

∫

0 O t

t

t

g(r, s, x, Z1)QsdrdxdWs + ∫ || g(r, s, x, Z1)||22 ds + λ∫ |h(r, s, x, z1(s))|2 ds 0

0

 + |h(r, s, x, Z )|2 dN . +λ∫ |h(r, s, x, z1(s))|2 ds + 2∫ ∫ h(r, s, x, Z1)QdrdxdN 1 s ∫ 0

t

t

0 O

0

Hence, for any t1 ∈ [0, T ], t

E sup | Qt |2 ≤ E | Q0 |2 + k 2 + ( Aβ 2 + 1 + λ + μ 0 + k1 ) ∫ E sup | Qs |2 ds 0

0 ≤t1 ≤t

0 ≤t1 ≤t

t

t

0

0

+ (2μ0 + 3K 2 + 2 K 2λ ) ∫ |Z1 |2 ds + (2μ0 + 2 K 2 ) ∫ |Z 2 |2 ds

Convergence of the Stochastic Age-Structured Population System with Diffusion

+2E sup ∫

t

∫

0≤t1 ≤t 0 O

+2E sup ∫

t

5

g(r, s, x, Z1 )Qs drdxdWs t

∫ h(r, s, x, Z )Q drdxdN + E sup ∫ |h(r, s, x, Z ) | 1

0≤t1 ≤t 0 O

s

0≤t1 ≤t 0

2

1

dN .

By Burkholder-Davis-Gundy's inequality, there exist positive constants K1, K2 such that

E sup ∫

t

∫

t

0≤t1 ≤t 0 O

1 2

g (r, s, x, Z1 )Qs drdxd Ws ≤ 3E[sup | Qs | (∫ | | g (r, s, x, Z1 ) || ds) ] 2 2

0

0≤t1 ≤t

t t 1 1 ≤ E[sup | Qs |2 ] + K1 ∫ || g(r, s, x, Z1)||22 ds ≤ E[sup | Qs |2 ] + K2 K1 ∫ E | Z1 |2 ds, 0 0 8 0≤t1≤t 8 0≤t1≤t

In the same way, we obtain:

∫

O

E sup ∫

t

∫ h(r, s, x, Z )Q drdxdN 1

0≤t1t 0 O

s

t 1 ≤ E sup | Qs |2 + K 2 K 2 ∫ |Z1 |2 ds, byZ i ≤ sup | Qs |, i = 1, 2 0 8 0≤t1 ≤t 0≤ t1 ≤ t t 3 1 E sup | Qt |2 ≤ ( Aβ 2 + + 1λ + 5μ0 + (5 + 2 K1 + 2λ + 3K 2 ) K 2 ) ∫ E sup | Qs |2 ds + E | Q0 |2 +k2 . 0 2 8 0≤ t1 ≤ t 0 ≤t1t

At present, applying Gronwall's lemma, the proof complete. Theorem 3.2. under assumption, for each t ∈ [0, T ],

E[| Qt − Z1 (t ) |2 ] ≤ C2 +t , E[| Qt − Z 2 (t ) |2 ] ≤ C3 +t.

Proof. For arbitrary t∈[0,T], there exists k such that t ∈[k+t,(k +1)+t], so we have

| Qt − Z1(t) |2 ≤ 6+t

∫

t

k +t

|

t ∂Qs 2 | ds + 6k 2 +tk1 ∫ |Qs |2 ds + 6k 2 +tk2 k +t ∂r

t

t

+6μ2Δt ∫ |(1−α)Z1(s) +αZ2 (s)|2 ds +12λ2Δt ∫ |h(r, s, x, Z1(s))|2 ds k +t

t

k +t

t

+12Δt ∫ | f (r, s, x, Z1 (s)) | ds +12Δt ∫ | f (r, s, x, Z2 (s)) |2 ds 2

k +t

+6 | ∫

t

k +t

k +t t

 |2 . g (r , s, x, Z1 ( s))d Ws |2 +12 | ∫ h(r , s, x, Z1 ( s))dN k +t

By Burkholder-Davis-Gundy's inequality, there exist positive constants K3,K4such that

E sup | ∫ 0≤t1 ≤T

t

k +t

g (r , s, x, Z1 ( s ))d Ws |2 ≤ K 3 ∫

t

k +t

t

t

k +t

k +t

E sup | Z1 ( s ) |2 ds, 0≤t1 ≤T

E sup | ∫ h(r , s, x, Z1 ( s ))dN |2 ≤ K 4 ∫ E sup | Z1 ( s ) |2 ds, 0 ≤t1 ≤T

By

Zi ≤ sup | Qs | and assumption, have 0≤t1 ≤t

0 ≤t1 ≤T

6

D. Ma and Q. Zhang

E sup | Qt − Z1 (t ) |2 ≤ (6 K5 +t + 6k 2 +tk1 + 24μ 2 +t + 24+tK 2 + 6 K3 + 12 K 4 0 ≤t1 ≤T

+ 12λ 2 +tK 2 ) sup E | Qs |2 +6k 2 +tk2 . 0 ≤t1 ≤T

C2 = (6K5 + 6k k1 + 24μ + 24K + 6K3 +12K4 +12λ2 K2 )C1t + 6k 2 K2 , Such that 2

2

2

E[| Qt − Z1(t)|2] ≤ C2+t. (Similar method, we can obtain E[| Qt − Z 2 (t ) | ] ≤ C3 +t. ) 2

Theorem 3.3. Under assumption, for each t ∈ [0, T ], E[| P (t ) − Qt | ] ≤ C4 Δt. 2

N (t ) = N (t ) − λt and Itoˆ′s formula to | Qt |2 , t t ∂( P − Qs ) | P(t ) − Qt |2 = −2∫ 〈 Ps − Qs , s 〉ds + 2∫ 〈 Ps − Qs , kdiv(( Ps − Qs )∇u)〉 ds 0 0 ∂r

Proof. Applying

t

−2 ∫ 〈 Ps − Qs , μ (r , t , x)((1 − α )( Ps − Z1 ) + α ( Ps − Z 2 )〉 ds 0

t

+2∫ 〈Ps −Qs ,(1−α)( f (r, t, x, Ps ) − f (r, t, x, Z1)) +α( f (r, t, x, Ps ) − f (r, t, x, Z2 )〉ds 0

t

t

+∫ || g(r, t, x, Ps ) − g(r, t, x, Z1)||22 ds + 2∫ 〈Ps −Qs , g(r, t, x, Ps ) − g(r, t, x, Z1)〉dWt 0

0

t

t

+2∫ 〈Ps −Qs , h(r, t, x, Ps ) − h(r, t, x, Z1)〉d Nt + ∫ |h(r, t, x, Ps ) − h(r, t, x, Z1)|2 d Nt 0

0

t

t

0

0

t

t

0

0

≤ Aβ 2 ∫ |Ps −Qs |2 ds + k1∫ |Ps −Qs |2 ds + k2 + 2μ0 ∫ |Ps − Z1 |2 ds + 2μ0 ∫ |Ps − Z2 |2 ds t

t

+2∫ | f (r, s, x, Ps ) − f (r, s, x, z1(s)) | ds + 2∫ | f (r, s, x, Ps ) − f (r, s, x, z2 (s)) |2 ds 2

0

0

t

t

0

0 O

+(2 + λ + μ0 )∫ |Ps − Qs |2 ds + 2∫

∫ (P − Q )(g(r,t, x, P ) − g(r,t, x, Z ))drdxdW +∫ |g (r, t , x, P ) − g (r, s, x, z (s)) | ds + ∫ | | g (r, t, x, P ) − g (r, s, x, Z ) || ds +λ∫ |h(r, t, x, P ) − h(r, s, x, z (s))| ds + λ∫ |h(r, t, x, P ) − h(z (s))| ds +2∫ ∫ (h(r, t, x, P ) − h(r, s, x, Z ))(P −Q )drdxdN + ∫ |h(r, t, x, P ) − h(r, s, x, Z )| dN . t

s

s

0

t

0

t

2

2

t

1

s

s

2 2

1

s

0

t

0 O

1

s

0

1

s

s

t

2

1

s

1

s

s

2

1

s

0

Hence, for any t1 ∈ [0, T ], t

E sup | Ps − Qs |2 ≤ k 2 + ( Aβ 2 + 1 + λ + μ0 + k1 ) ∫ E sup | Ps − Qs |2 ds 0

0 ≤t1 ≤t

0 ≤t1 ≤t

t

t

0

0

+(2μ0 + 3K2 + 2K2λ)∫ |Ps − Z1 |2 ds + (2μ0 + 2K2 )∫ |Ps − Z2 |2 ds +2E sup ∫

t

∫ (P −Q )(g(r,t, x, P ) − g(r,t, x, Z ))drdxdW

0≤t1≤t 0 O

s

s

s

1

s

Convergence of the Stochastic Age-Structured Population System with Diffusion

+2E sup ∫

t

7

∫ (h(r, t, x, P ) − h(r, s, x, Z ))(P − Q )drdxdN s

0≤t1≤t 0 O

1

s

s

+E sup ∫ |h(r, t, x, Ps ) − h(r, s, x, Z1) |2 dN . t

0≤t1 ≤t 0

By Burkholder-Davis-Gundy's inequality, there exist positive constants K5, K6 such that

E sup ∫

t

∫

( Ps − Qs )( g ( r , t , x, Ps ) − g ( r , t , x, Z1 )) drdxd Ws

0 ≤t1 ≤t 0 O

t 1 ≤ E[sup | Ps − Qs |2 ] + K 2 K 5 ∫ E | ps − Z1 |2 ds, 0 8 0≤t1 ≤t

∫

O

E sup ∫ 0 ≤t1t

t

∫

0 O

( h(r , t , x, Ps ) − h( r , s, x, Z1 ))( Ps − Qs ) drdxdN

t 1 ≤ E sup | Ps − Qs |2 + K 6 K 2 ∫ E | Pt − Z1 |2 ds, 0 8 0≤t1 ≤t

Applying Theorem3.2, have E sup | Pt − Qt | ≤ C5 +t + C6 2

0≤t1 ≤t

t

∫ E sup | P − Q | 0

2

0≤t1 ≤t

t

t

dt ,

Where C5 = (4μ0 + 7 K + 4λ K + 4K5 K + 6K6 K )C2 + (4μ0 + 4K )C3 + k2 , 2

2

2

2

2

C6 = Aβ 2 + k1 + μ0 + 2 + λ + 12K 2 + 4λ K 2 + 4K5 K 2 + 6K6 K 2 . At present, applying Gronwall's lemma, the proof complete. So applying Theorem3.3, under the assumption condition, we obtain the semi-implicit Euler numerical solution Qt convergence to the analytical Solution Pt of this system.

References 1. Hernandez, G.E.: Age-density dependent population dispersal in RN. Mathematical Biosciences J. 149, 37–56 (1998) 2. Hernandez, G.E.: Existence of solutions in a population dynamic problem. J. Appl. Math. 509, 43–48 (1986) 3. Hernandez, G.E.: Localization of age-dependent ant-crowding populations. J. Q. Appl. Math. 53, 35 (1995) 4. Zhang, Q., Han, C.Z.: existence and uniqueness for a stochastic age-structured population system with diffusion. J. Science Direct 32, 2197–2206 (2008) 5. Zhang, Q., Liu, W., Nie, Z.: Existence, uniqueness and exponential stability of stochastic age-dependent population. J. Appl. Math. Comput. 154, 183–201 (2004) 6. Zhang, Q., Han, C.Z.: Convergence of numerical solutions to stochastic age-structured population system with diffusion. J. Applied Mathematics and Computation 07, 156 (2006) 7. Zhang, Q.: Exponential stability of numerical solutions to a stochastic age-structured population system with diffusion. Journal of Computational and Applied Mathematics 220, 22–33 (2008) 8. Zhang, Q., Han, C.Z.: Numerical analysis for stochastic age-dependent population equations. J. Appl. Math. Comput. 176, 210–223 (2005) 9. Gardon, A.: The Order of approximations for solutions of Ito-type stochastic differential equations with jumps. J. Stochastic Analysis and Applications 38, 753–769 (2004)

Parallel Computer Processing Systems Are Better Than Serial Computer Processing Systems Zvi Retchkiman Konigsberg Instituto Politecnico Nacional

Abstract. The main objective and contribution of this paper consists in using a formal and mathematical approach to prove that parallel computer processing systems are better than serial computer processing systems, better related to: saving time and/or money and being able to solve larger problems. This is achieved thanks to the theory of Lyapunov stability and max-plus algebra applied to discrete event systems modeled with time Petri nets. Keywords: Parallel and Serial Computer Processing Systems, Lyapunov Methods, Max-Plus Algebra, Timed Petri Nets.

1

Introduction

Serial computer processing systems are characterized by the fact of executing software using a single central processing unit (CPU) while parallel computer processing systems simultaneously use multiple CPU’s at the time. Some of the arguments which have been used to say why it is better parallel than serial are: save time and/or money and solve larger problems. Besides that there are limits to serial processing computer systems due to: transmission speeds, limits to miniaturization ans economic limitations. However we would like to be more precise and give a definitive and unquestionable formal proof to justify the claim that parallel computer processing systems are better than serial computer processing systems. The main objective and contribution of this paper consists in using a formal and mathematical approach to prove that parallel computer processing systems are better than serial computer processing systems (better related to: saving time and/or money and being able to solve larger problems). This is achieved thanks to the theory of Lyapunov stability and max-plus algebra applied to discrete event systems modeled with time Petri nets. The paper is organized as follows. Sections 2 and 3 provide the mathematical results utilized in the paper about Lyapunov theory for discrete event systems modeled with Petri nets and max-plus algebra in order to achieve its goal (for a detailed exposition see [1] and [2]). In section 4, the solution to the stability problem for discrete event systems modeled with timed Petri nets using a Lyapunov, maxplus algebra approach is given. Section 5, applies the theory presented in the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 8–14, 2011. c Springer-Verlag Berlin Heidelberg 2011 

Parallel Computer Processing vs. Serial Computer Processing

9

previous sections to formally prove that parallel computer processing systems are better than serial computer processing systems. Finally, the paper ends with some conclusions.

2

Lyapunov Stability and Stabilization of Discrete Event Systems Modeled with Petri Nets [1]

Proposition 1. Let P N be a Petri net. P N is uniform practical stable if there exists a Φ strictly positive m vector such that Δv = uT AΦ ≤ 0

(1)

Moreover, P N is uniform practical asymptotic stable if the following equation holds Δv = uT AΦ ≤ −c(e), for c ∈ K (2) Lemma 1. Let suppose that Proposition (1) holds then, Δv = uT AΦ ≤ 0 ⇔ AΦ ≤ 0

(3)

Remark 1. Notice that since the state space of a TPN (timed Petri net) is contained in the state space of the same now not timed PN, stability of PN implies stability of the TPN. Definition 1. Let P N be a Petri net. P N is said to be stabilizable if there exists a firing transition sequence with transition count vector u such that the reachable markings M´ remain bounded. Proposition 2. Let P N be a Petri net. P N is stabilizable if there exists a firing transition sequence with transition count vector u such that the following equation holds Δv = AT u ≤ 0

3

(4)

Max-plus Algebra [2,3]

Theorem 1. The max-plus algebra max = (Rmax , ⊕, ⊗, , e) has the algebraic structure of a commutative and idempotent semiring. n×n Theorem 2. The 5-tuple n×n max = (Rmax , ⊕, ⊗, E, E) has the algebraic structure of a noncommutative idempotent semiring.

Definition 2. Let A ∈ Rn×n max and k ∈ N then the k-th power of A denoted by A⊗k is defined by: A⊗k = A ⊗ A ⊗ · · · ⊗ A, where A⊗0 is set equal to E.    k−times

10

Z.R. Konigsberg

+ + Definition 3. Let A ∈ Rn×n ∈ Rn×n = max then define the matrix A max as: A ∞  ⊗k + A . Where the element [A ]ji gives the maximal weight of any path from j k=1

to i. If in addition one wants to add the possibility of staying at a node then one must include matrix E in the definition of matrix A+ giving rise to its Kleene star representation defined by: A∗ =

∞  A⊗k .

(5)

k=0

Lemma 2. Let A ∈ Rn×n max be such that any circuit in the communication graph G(A) has average circuit weight less than or equal to . Then it holds that: A∗ =

n−1 

A⊗k .

(6)

k=0 n Definition 4. Let A ∈ Rn×n max be a matrix. If μ ∈ Rmax is a scalar and v ∈ Rmax is a vector that contains at least one finite element such that:

A⊗v =μ⊗v

(7)

then, μ is called an eigenvalue and v an eigenvector. Theorem 3. If A ∈ Rn×n max is irreducible i.e., its communication graph G(A) is strongly connected, then there exists one and only one finite eigenvalue (with possible several eigenvectors). This eigenvalue is equal to the maximal average weight of circuits in G(A): λ(A) = max

p∈C(A)

|p|w |p|1

(8)

n Theorem 4. Let A ∈ Rn×n max and b ∈ Rmax . If the communication graph G(A) has maximal average circuit weight less than or equal to e, then x = A∗ ⊗ b solves the equation x = (A ⊗ x) ⊕ b. Moreover, if the circuit weights in G(a) are negative then, the solution is unique. n Definition 5. Let Am ∈ Rn×n max for 0 ≤ m ≤ M and x(m) ∈ Rmax for −M ≤ M  m ≤ −1; M ≥ 0. Then, the recurrence equation: x(k) = Am ⊗x(k −m); k ≥

0 is called an M th order recurrence equation.

m=0

Theorem 5. The M th order recurrence equation, given by equation x(k) = M  Am ⊗ x(k − m); k ≥ 0, can be transformed into a first order recurrence m=0

equation x(k + 1) = A ⊗ x(k); k ≥ 0 provided that A0 has circuit weights less than or equal to zero.

Parallel Computer Processing vs. Serial Computer Processing

11

With any timed event Petri net, matrices A0 , A1 , ..., AM ∈ Nn ×Nn can be defined by setting [Am ]jl = ajl , where ajl is the largest of the holding times with respect to all places between transitions tl and tj with m tokens, for m = 0, 1, ..., M , with M equal to the maximum number of tokens with respect to all places. Let xi (k) denote the kth time that transition ti fires, then the vector x(k) = (x1 (k), x2 (k), ...xm (k))T , called the state of the system, satisfies the M th order M  recurrence equation: x(k) = Am ⊗ x(k − m); k ≥ 0 Now, assuming that all m=0

the hypothesis of theorem (5) are satisfied, and setting x ˆ(k) = (xT (k), xT (k − M  1), ..., xT (k − M + 1))T , equation x(k) = Am ⊗ x(k − m); k ≥ 0 can be m=0

expressed as: x ˆ(k + 1) = Aˆ ⊗ x ˆ(k); k ≥ 0, which is known as the standard autonomous equation.

4

The Solution to the Stability Problem for Discrete Event Systems Modeled with Timed Petri Nets

Definition 6. A TPN is said to be stable if all the transitions fire with the same proportion i.e., if there exists q ∈ N such that xi (k) = q, ∀i = 1, ..., n k→∞ k lim

(9)

Lemma 3. Consider the recurrence relation x(k + 1) = A ⊗ x(k), k ≥ 0, x(0) = x0 ∈ Rn arbitrary. A an irreducible matrix and λ ∈ R its eigenvalue then, lim

k→∞

xi (k) = λ, ∀i = 1, ..., n k

(10)

Now starting with an unstable T P N , collecting the results given by: proposition (2), what has just been discussed about recurrence equations for T P N and the previous lemma (3) plus theorem (3), the solution to the problem is obtained.

5

Parallel vs. Serial Computer Processing Systems

In this section, the main objective of this manuscript which consists in giving a precise and definitive answer to the question why are parallel computer processing systems preferred to serial computer processing systems (better related to: saving time and/or money and being able to solve larger problems), is presented. 5.1

Serial Computer Processing System

Consider a serial computer processing system with T P N model as depicted in Fig 1. Where the events (transitions) that drive the system are: q: a problem of size Ca has to be solved, s: the problem starts being executed by the CPU,

12

Z.R. Konigsberg

Fig. 1.

d: the problem has been solved. The places (that represent the states of the serial computer processing system) are: A: problems loading, P: the problems are waiting for a solution, B: the problem is being solved, I: the CPU of capacity Cd is idle. The holding times associated to the places A and I are Ca and Cd respectively, (with Ca > Cd). Remark 2. Notice that Ca, the size of q, is the time it takes to a problem until is completely loaded in the computer in order to be solved, larger problems will have larger Ca’ s, while Cd, the capacity of the CPU, is the time it takes to the CPU to reset. ⎡ ⎤ 0 1 0 0 The incidence matrix that represents the P N model is A = ⎣ 0 −1 1 −1 ⎦ 0 0 −1 1 Therefore since there does not exists a Φ strictly positive m vector such that AΦ ≤ 0 the sufficient condition for stability is not satisfied. Moreover, the P N (T P N ) is unbounded since by the repeated firing of q, the marking in P grows indefinitely i.e., the amount of problems that require a solution accumulate. However, by taking u = [k, k, k]; k > 0 (but unknown), we get that AT u ≤ 0. Therefore, the P N is stabilizable which implies that the T P N is stable. Now, let us proceed to determine the ⎛ exact value ⎞ of k. From the T P N model we Ca ε ε |p| obtain that: Aˆ = A∗0 ⊗ A1 = ⎝ Ca ε Cd ⎠. Therefore, λ(A) = max |p|w = 1 p∈C(A) Ca ε Cd max{Ca, Cd} = Ca. This means that in order for the T P N to be stable and work properly the speed at which the serial computer processing system works has to be equal to Ca or being more precise, that all the transitions must fire at the same speed as the problems arrive i.e., they have to be solved as soon as they are loaded into the computer which is attained by setting k = Ca. In particular, transition s which is related to the execution time of the CPU has to be fired at a speed equal to Ca.

Parallel Computer Processing vs. Serial Computer Processing

13

Summary 6. The serial computer processing system works properly if transition s fires at a speed equal to Ca which implies that the execution frequency of the CPU has to be equal to Ca. Now, if Ca increases due to the fact that the problem to be solved becomes larger then, this will result in an increment on the CPU’s execution frequency. However, there is a limit to this increment due to economical and physical limitations. One possible solution is to break this large problem into several smaller problems but this will result in larger execution times. 5.2

Parallel Computer Processing System

Consider a parallel computer processing systems with two CPU’s with T P N model as depicted in Fig 2. Where the events (transitions) that drive the system are: q: a problem of size Ca has to be solved, s1, s2: the problem starts being executed by the CPU’s, d1,d2: the problem has been solved. The places (that represent the states of the parallel computer processing system) are: A: problems loading, P: the problems are waiting for a solution, B1, B2: the problem is being solved, I1, I2: the CPU’s of capacity Cd are idle. The holding times associated to the places A and I1, I2 are Ca and Cd respectively,⎡ (with Ca > Cd). The ⎤ 0 1 0 0 0 0 ⎢ 0 −1 1 −1 0 0 ⎥ ⎢ ⎥ ⎥ incidence matrix that represents the P N model is A = ⎢ ⎢ 0 −1 0 0 1 −1 ⎥ ⎣ 0 0 −1 1 0 0 ⎦ 0 0 0 0 −1 1 Therefore since there does not exists a Φ strictly positive m vector such that AΦ ≤ 0 the sufficient condition for stability is not satisfied. Moreover, the P N (T P N ) is unbounded since by the repeated firing of q, the marking in P grows indefinitely i.e., the amount of problems that require a solution accumulate. However, by taking u = [k, k/2, k/2, k/2, k/2]; k > 0 (but unknown) we get that AT u ≤ 0. Therefore, the P N is stabilizable which implies that the T P N is stable. Now, let us proceed to determine ⎛ the exact value ⎞ of k. From the T P N Ca ε ε ε ε ⎜ Ca ε ε Cd ε ⎟ ⎜ ⎟ ∗ ˆ ⎟ model we obtain that: A = A0 ⊗ A1 = ⎜ ⎜ Ca ε ε ε Cd ⎟ ⎝ Ca 0 ε Cd ε ⎠ Ca ε ε ε Cd Therefore, λ(A) = max

p∈C(A)

|p|w |p|1

= max{Ca, Cd} = Ca. This means that in order

for the T P N to be stable and work properly the speed at which the parallel computer processing system works has to be equal to Ca or being more precise, that all the transitions must fire at the same speed as the problems arrive i.e., they have to be solved as soon as they are loaded into the computer which is attained by setting k = Ca. In particular, transitions s1 and s2 which are related to the execution time of the CPU’s have to be fired at a speed equal to Ca/2.

14

Z.R. Konigsberg

Fig. 2.

Remark 3. The previous analysis is easily extended to the case with n CPU’s, obtaining that u = [Ca, Ca/n, Ca/n, ..., Ca/n] which translates into the condition that the transitions s1,s2,...,sn, have to be fired at a speed equal to Ca/n. Summary 7. The parallel computer processing system works properly if transitions s1,s2,...,sn, fire at a speed equal to Ca/n which implies that the execution frequency of the CPU’s has to be equal to Ca/n. 5.3

Comparison

As a result of summaries (6) and( 7) the following facts are deduced: 1. (Saving time) It is possible to solve a problem of size Ca with one CPU which takes time ”Ca”, or there is the option of solving a problem of size nCa (or n problems of size Ca each one) using n CPU’s which will take the same time as with one CPU. 2. (Saving Money) In order to execute a program, there is the option of purchasing one CPU that costs ”Ca” or n CPU’s that cost ”Ca/n”. This is significant for large Ca. 3. (Solving larger problems) If Ca increases due to the fact that the problem to be solved becomes larger then this will result in an increment on the CPU’s execution frequency. As a consequence the serial computer processing option becomes expensive and/or slow. This is also true for the parallel computer processing alternative however, by distributing Ca between the n CPU’s the economical and/or time impact results to be much lower.

References 1. Retchkiman, Z.: Stability theory for a class of dynamical systems modeled with Petri nets. International Journal of Hybrid Systems 4(1) (2005) 2. Heidergott, B., Olsder, G.J., van der Woude, J.: Max Plus at Work. Princeton University Press, Princeton (2006) 3. Baccelli, F., Cohen, G., Olsder, G.J., Quadrat, J.P.: Synchronization and Linearity, Web-edition (2001)

Smooth Path Algorithm Based on A* in Games Xiang Xu and Kun Zou Department of Computer Engineering, University of Electronic Science and Technology of China Zhongshan Institute, Zhongshan, P.R. China [email protected]

Abstract. Pathfinding is a core component of many games especially real-time strategy games. The paper proposed a smooth path generation strategy based on the A * algorithm. Firstly, adopted an admissible heuristics function, and a key-point optimization is applied to make the path to be connected by a series of key points. Secondly, the paper applied Catmull-Rom splines to the key points interpolation, through add several interpolation points between the key points, make the whole path look more smooth. Experimental results show that the proposed smooth path generation algorithm improves the path of smoothness, make the pathfinding more realistic, and more suitable for use in games. Keywords: pathfinding, A* algorithm, heuristic function, smooth path, Catmull-Rom splines.

1 Introduction In games, we often use a regular grid diagram to demonstrate game map, these grids in certain proportion or resolution divide game map into small pieces of cells, each cell called a node. Based on grid game map, pathfinding's main purpose is according to different terrain and obstacles, find a shortest and lowest cost path. Many games use A* algorithm as its pathfinding strategy, such as typical RTS games and RPG games. Due to the characteristics of game software itself, its pathfinding algorithm has more request, such as searching time should be short, path found should smooth and realistic, etc. Therefore, the standard A* algorithm need to do many improvement before used in games. Aiming at the special request of pathfinding in games, this paper analyses various improvement method, and proposes a smooth path generation algorithm.

2 The Basics of A* Algorithm A* algorithm is a typical kind of heuristic algorithm in artificial intelligence. In order to understand the A* algorithm, we must first understand the state space search and heuristic algorithm. State space search is a problem solving process to look for one path from the initial state to the end state [1]. The popular spot said, because there are so many problem solving methods, and so many solving path caused by many branches, uncertain and incomplete in solving process. All these paths constitute a diagram, and this diagram is called state space diagram. The solution is actually to find a path from S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 15–21, 2011. © Springer-Verlag Berlin Heidelberg 2011

16

X. Xu and K. Zou

the starting point to the goal in this diagram. This search process is called state space search. Common state space search methods have depth first search (DFS) and breadth first search (BFS), BFS first searches the initial state layer, and then next layer until find the goal so far. DFS is according to certain order first searches a branch, and then another branch until find the goal. Breadth and depth first search have a big flaw is that they are both in a given state space exhaustion, it can be adopted when the state space is small, but will not desirable when the state space is very big, and unpredictable circumstances. They will have much lower efficiency, and even not complete pathfinding, In this case we should use heuristic pathfinding. Heuristic pathfinding will estimate each search position in the state space, and get the lowest cost of position and from this position until target. This may omit many useless path searches, improve efficiency. In heuristic pathfinding, the estimate cost of position is very important, and use different heuristic function will get different effect [2]. The heuristic function’s general form is as follows: f(n)=g(n)+h(n)

(1)

Among them, g (n) is the actual cost from the starting point to node n, and h (n) is the estimate cost from node n to the goal. Because g(n) is known, it can be calculated by reverse tracking from node n to starting point in accordance with a pointer to the parent, then accumulate all the edge cost in the path. So, heuristic function f (n)’s heuristic information relies mainly on function h (n) [3]. According to a certain known conditions of state space, heuristic function will select the node with minimum cost to search, again from this node continue to search, until you reach the goal or failure, but not expanded nodes need not search. Design of function h (n) will direct impact on whether this heuristic algorithm can become A* algorithm [4].

3 Smooth Path Design Design a path in games is more than just the application of pathfinding algorithm. It also includes several techniques for achieving more realistic looking results from pathfinding. We can use the following three main methods to improve the pathfinding algorithm: make more straight-line movement and make more smoothly movement and make more directly movement, all these optimizations bring more joyful gaming experience for gamers. And these optimizations also directly affect the implement of A* algorithm. 3.1 The Selection of Heuristic Function Function h (n) in A* algorithm usually adopts the classic Manhattan heuristic function. Namely obtain the minus of abscissa from current node to the goal, and also the minus of ordinate from current node to the goal, again both absolute values adding together. Its primary drawback is that in an eight-way pathfinder, this method is inadmissible, so it is not guaranteed to find the shortest path. Also, because it is overweighted compared to G, it will overpower any small modifiers that you try to add to the calculation of G like, say, a turning penalty or an influence map modifier. So we need to find more suitable heuristic function. And when choosing heuristic function, we still need to

Smooth Path Algorithm Based on A* in Games

17

consider calculated amount. Therefore we should take the compromise in the precise function and its calculated amount. Here we adopted an improved heuristic function shown below: h(n)=max(fabs(dest.x-current.x),fabs(dest.y-current.y))

(2)

This heuristic function can satisfy the admissible condition and guarantee to give us the shortest path from starting point to the goal. In order to improve search efficiency, we preprocess those unreachable areas in the game map. These areas possibly are separated by a bar obstacle, for example river in addition one side, also possibly be surrounded by walls, etc. For such a terrain, A* algorithm will detect all neighbour nodes around this unreachable node until failed, waste a lot of time. Through put all unreachable nodes into the unreachable list beforehand, and check whether destination is in the unreachable list before pathfinding. And for the Open table, we adopted the binary heaps to enhance the efficiency of the algorithm. The specific algorithm flow chart shown below:

Fig. 1. A* algorithm flow chart, adopted the binary heaps for the Open table, and preprocess those unreachable areas in the game map before starting searching

18

X. Xu and K. Zou

3.2 Key-Point Optimization The path generated by A* algorithm is a set of discrete node {N1 N2, N3,..., , NP-1, NP}, if a game role move along these nodes, it will encounter many twists, the path is too long, and quite time-consuming, we can adopt key-point optimization strategy, namely select limited key points to represent the whole path node set. There are many methods to select the key points, we can select each direction change point as key point, and other nodes are all omitted. Also we can calculate the original path node set{N1 N2, N3,..., , NP-1, NP}, if in any two node central segment does not have any obstacles (assume the grid map is known), then all other nodes between this two nodes, can be omitted but only this two nodes are preserved. After such processing, the path generated by A* algorithm is constituted by limited key points, the path length reduced many, the track time reduced suddenly, and convenient for further smooth path design (The experimental results is shown below) [5].

Fig. 2. Left figure shows A* algorithm generated the node sequence, and right figure shows the key-point node sequence after optimization

3.3 The Generation of Smooth Path After finished the key-point optimization, we can apply Catmull-Rom splines to the key-point interpolation, through add several interpolation points between the key points, make the whole path look more smooth. Catmull-Rom splines are a family of cubic interpolating splines formulated such that the tangent at each point Pi is calculated using the previous and next point on the spline, (Pi+1 −Pi−1). The geometry matrix is given by

p ( s ) = [1 u

u2

⎡ 0 ⎢− τ u 3 ]⎢ ⎢ 2τ ⎢ ⎣− τ

1 0

0

τ τ − 3 3 − 2τ 2 −τ τ − 2

0 ⎤ ⎡ pi−2 ⎤ 0 ⎥⎥ ⎢⎢ p i −1 ⎥⎥ − τ ⎥ ⎢ pi ⎥ ⎥ ⎥⎢ τ ⎦ ⎣ p i +1 ⎦

(3)

Catmull-Rom splines have C1 continuity, local control, and interpolation, but do not lie within the convex hull of their control points.

Smooth Path Algorithm Based on A* in Games

19

Fig. 3. A Catmull-Rom spline

Fig. 4. The effect of τ

Note that the tangent at point p0 is not clearly defined; oftentimes we set this to τ (p1 − p0) although this is not necessary for the assignment (you can just assume the curve does not interpolate its endpoints). The parameterτis known as “tension” and it affects how sharply the curve bends at the (interpolated) control points (figure 4). It is often set to 0.5 but you can use any reasonable value for this assignment. Catmull-Rom formulas required four input point coordinates, the calculation results is the point for the second point to the third point between an approximate u% places. When τ= 0.5, computation formula is as follows [6]: p ( s ) = p i − 2 * ( − 0 .5 * u + u * u − 0 .5 * u * u * u ) + p i −1 * (1 − 2 . 5 * u * u + 1 . 5 * u * u * u ) + p i * ( 0 .5 * u + 2 * u * u − 1 .5 * u * u * u )

(4)

+ p i +1 * ( − 0 . 5 * u * u + 0 . 5 * u * u * u )

Note that if u=0, the result is Pi-1; u=100, results of Pi. Smooth processing also need time consume, in order to reduce the processing time, we should as less as possible insert intermediate points under the quite satisfactory processing effect premise, this paper chooses three insert points. Respectively the choice u=0.25, 0.5 and 0.75, and produce three equal-distance points. So, every n key points, after the interpolation increased 3*(n-1) points, after smooth processing the nodes number is original (4*n-3)/n times. Because Catmull-Rom splines can only generate interpolation points between the second and the third point, so aiming at the first two key points and the last two key points, we need separately using the key point sequence (1, 1, 2, 3) and (n-2, n-1, n, n), but the other key point sequence by simply use (s-1, s, s+1, s+2). This can obtain the uniform distribution of interpolation points, specific effects are shown below.

20

X. Xu and K. Zou

Fig. 5. Catmull-Rom smooth path production. Left figure shows the key points (marked as red circle), right figure shows the smooth path.

4 Other Problems to Be Considered There are many other problems need to consider in game pathfinding [7], For instance: (1) The terrain problems. The path from A to B has two choices: one path is Steep mountain road but the distance is near, second path is smooth road but the distance is far. Sometimes we will choose the latter, but A* algorithm can only select the former. General method to solve this kind of problem is to give different terrain with different influence factor, but in order to make the choice more randomness, we can set a tolerable difference value like C, when the differentials with the mountain and the smooth road cost does not exceed C, we can allow random selection of one of the paths. For example, when the mountain road is not very steep, we can also select this path. (2) The traffic problems. For instance in a relatively narrow terrain, there is a large group of game roles requires passed by, can produce traffic congestion. It's probably best to let later roles know this situation, and dynamic increase the terrain cost, so that they can change their route. (3) March algorithm. In a real-time strategy game, if we need simultaneously to move many game roles, we will call A* algorithm to calculate many times, the time-consuming unbearable. The solution has two kinds: a kind of simple method is to all the cells pressed into the queue, carries on the pathfinding in order. This can quickly get response, but each unit can not move together, some roles can first move, behind of slowly catch up with. Another common way is in the army, random select a role as a guide, just once pathfinding, other roles as long as the tailgate afterward can. (4) Other moving units. Due to the map still exists other moving units, their positions are not fixed, so it is very difficult to calculate one path that can avoid other units at the beginning. The most simple and feasible method is another collision detection, after the collision to search path or direct selection to the right or left movement. (5) The number of pathfinders. In many real-time strategy games, also exist such problems: need to allow multiple units to move together. In order to reduce pathfinding time, must reduce the number of pathfinders, namely a March unit's population upper limit.

Smooth Path Algorithm Based on A* in Games

21

5 Conclusion This paper analyzed the A* standard algorithm, and proposed one kind of improved strategy. The algorithm adopted an admissible heuristics function, and performed key-point optimization on the node sequence, in view of the key-point sequence, the paper realized a kind of smooth path generation based on the Catmull-Rom splines. Generated by the search path can be reflected in the game actual path effect, and embodies the certain intelligence and humanization. But in execution efficiency, take sacrifices the storage space and the CPU time as the price. Future game need more intelligences, more user-friendly game roles, therefore, hoped that can have better algorithms to solve problems in game pathfinding.

References 1. Tao, Z.H., Hang, C.Y.: Path Finding Using A* Algorithm. Micro Computer Information 23(17), 238–240 (2007) 2. Lester, P.: A* pathfinding for beginners (2005), http://www.policyalmanac.org/games/aStarTutoria.lhtm 3. Heping, C., Qianshao, Z.: Applicaion And Implementation of A*Agorithms in the Game Map Pathfinding. Computer Applications and Software 22(12), 118–120 (2005) 4. Lester, P.: Using Binary Heaps in A* Pathfinding (2003), http://www.policyalmanac.org/games/binaryHeaps.htm 5. Wei, S., Zhengda, M.: Smooth path design for mobile service robots based on improved A* algorithm. Journal of Southeast University (Natural Science Edition) 40sup(I) (September 2010) 6. Deloura, M.: Game Programming Gems. Charles River Media, Inc., London (2000) 7. Higgins Daniel, F.: Pathfinding Design Architecture. In: AI Game Programming Wisdom. Charles River Media, London (2002)

The Features of Biorthogonal Binary Poly-scale Wavelet Packs in Bidimensional Function Space Zhihao Tang* and Honglin Guo Department of Fundamentals, Henan Polytechnic Institute, Nanyang 473009, China [email protected]

Abstract. Wavelet analysis has become a developing branch of mathematics for over twenty years. In this paper, the notion of orthogonal nonseparable bivariate wavelet packs, which is the generalization of orthogonal univariate wavelet packs, is proposed by virtue of analogy method and iteration method. Their biorthogonality traits are researched by using time-frequency analysis approach and variable separation approach. Three orthogonality formulas regarding these wavelet wraps are obtained. Moreover, it is shown how to draw new orthonormal bases of space L2 ( R 2 ) from these wavelet wraps. A procedure for designing a class of orthogonal vector-valued finitely supported wavelet functions is proposed by virtue of filter bank theory and matrix theory. Keywords: Nonseparable, binary wavelet packs, wavelet frame, Bessel sequence, orthonormal bases, time-frequency analysis approach.

1 Introduction and Notations The main advantage of wavelet packs is their time-frequency localization property. Construction of wavelet bases is an important aspect of wavelet analysis, and multiresolution analysis method is one of importment ways of constructing various wavelet bases. There exist many kinds of scalar scaling functions and scalar wavelet functions. Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. Wavelet analysis [1] has been developed a new branch for over twenty years. Its applications involve in many areas in natural science and engineering technology. The main advantage of wavelets is their time-frequency localization property. Many signals in areas like music, speech, images, and video images can be efficiently represented by wavelets that are translations and dilations of a single function called mother wavelet with bandpass property. Wavelet packets, owing to their good properties, have attracted considerable attention. They can be widely applied in science and engineering [2,3]. Coifman R. R. and Meyer Y. firstly introduced the notion for orthogonal wavelet packets which were used to decompose wavelet components. Chui C K.and Li Chun L.[4] generalized the concept of orthogonal wavelet packets to the case of non-orthogonal wavelet packets so that wavelet packets can be employed in *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 22–28, 2011. © Springer-Verlag Berlin Heidelberg 2011

The Features of Biorthogonal Binary Poly-scale Wavelet Packs

23

the case of the spline wavelets and so on. Tensor product multivariate wavelet packs has been constructed by Coifman and Meyer. The introduction for the notion on nontensor product wavelet packs attributes to Shen Z [5]. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. But, there exist a lot of obvious defects in this method, such as, scarcity of designing freedom. Therefore, it is significant to investigate nonseparable multivariate wavelet theory. Nowadays, since there is little literature on biorthogonal wavelet wraps, it is neces-sary to investigate biorthogonal wavelet wraps . In the following, we introduce some notations. Z and Z + denote all integers and all nonnegative integers, respectively. R denotes all real numbers. R 2 denotes the 2dimentional Euclidean space. L2 ( R 2 ) denotes the square integrable function space. 2 ω − iω 2 Let x = ( x1 , x2 ) ∈ R , ω = (ω1 , ω2 ) ∈ R 2 , k = ( k , k ) ∈ Z , z = e , z2 = e 2 . The inner product for any functions ( x ) and ( x ) ( ( x ), ( x) ∈ L2 ( R 2 )) and the Fourier transform of ( x ) are defined, respectively, by −i

2

1

=∫

,

( x) ( x ) dx,

R2

2

2

1

(ω ) = ∫

R2

( x) e − iω ⋅ x dx,

where ω ⋅ x = ω1 x1 + ω2 x2 and ( x) denotes the complex conjugate of ( x ) . Let R and C be all real and all complex numbers, respectively. Z and N denote, respectively, all integers and all positive integers. Set Z + = {0} ∪ N , a, s ∈ N as well as a ≥ 2 By 2 algebra theory, it is obviously follows that there are a elements d 0 , d1 , , d a 2 −1 in 2 Z + = {( n1 , n2 ) : n1 , n2 ∈ Z + } such that Z 2 = ∪ d ∈Ω ( d + mZ 2 ) ; (d1 + mZ 2 ) ∩ (d2 + mZ 2 ) = φ , where Ω 0 = {d 0 , d1 , , d a 2 −1} denotes the aggregate of all the different representative elements in the quotient group Z 2 /(mZ 2 ) and order d 0 = {0} where {0} is the null element of Z and d1 , d 2 denote two arbitrary distinct elements in Ω0 .Let Ω = Ω 0 − {0} and Ω, Ω 0 to be two index sets. Define, By L2 ( R 2 , C s ) , we denote the set of all vector-valued functions L2 ( R 2 , C s ) := { ( x) , = (h1 ( x)), h2 ( x), , hu ( x))T : hl ( x) ∈ L2 ( R 2 ), l = 1, 2, , s} ,where T means the transpo2 2 s -se of a vector. For any ∈ L ( R , C ) its integration is defined as follows T ∫ R2 ( x)dx = (∫ R2 h1 ( x)dx, ∫ R2 h2 ( x)dx, , ∫ R2 hs ( x)dx) . 0

2

+

Definition 1. A sequence {

n

( y ) n∈Z 2 ⊂ L2 ( R 2 , C s )} is called an orthogonal set, if

〈

n

,

v

〉 = δ n ,v I s , n, v ∈ Z 2 ,

(1)

where I s stands for the s × s identity matrix and δ n , v , is generalized Kronecker symbol, i.e., δ n ,v = 1 as n = v and δ n ,v = 0 , otherwise.

2 The Bivariate Multiresolution Analysis 2

2

Firstly, we introduce multiresolution analysis of space L ( R ). Wavelets can be constructed by means of multiresolution analysis. In particular, the existence

24

Z. Tang and H. Guo

theorem[8] for higher-dimentional wavelets with arbitrary dilation matrice has been given. Let h( x) ∈ L ( R ) satisfy the following refinement equation: 2

2

f ( x) = m2 ⋅ ∑ k∈Z 2 bk f (mx − k )

(2)

where {b(n)}n∈Z 2 is real number sequence which has only finite terms.and f ( x) is called scaling function. Formula (1) is said to be two-scale refinement equation. The frequency form of formula (1) can be written as

f (ω ) = B ( z1 , z2 ) f (ω m),

(3)

where

B( z1 , z2 ) =

∑ b(n , n ) ⋅ z1n ⋅ z2 n . 1

1

( n1 , n2 )∈Z

Define a subspace

2

(4)

2

2

X j ⊂ L2 ( R 2 ) ( j ∈ Z ) by V j = closL2 ( R2 ) m j f ( m j x − k ) : k ∈ Z 2 .

(5)

Definition 2. We say that f ( x) in (2) generate a multiresolution analysis {V j } j∈Z of

L2 ( R 2 ) , if the sequence {V j } j∈Z defined in (4) satisfy the following properties: (i) V j ⊂ V j +1 , ∀ j ∈ Z ; (ii) ∩ V j = {0}; ∪ V j is dense in L2 ( R 2 ) ; (iii) ψ ( x) ∈ V j∈Z j∈Z ⇔ ψ (mx) ∈ Vk +1 , ∀ k ∈ Z (iv) the family { f (m j x − n) : n ∈ Z 2 } forms a Riesz basis for the spaces V j . Let

Yk (k ∈ Z ) denote the complementary subspace of V j in V j +1 , and ass-ume

that there exist a vector-valued function G ( x) = {g1 ( x), g 2 ( x), a Riesz basis for

, g m2 −1 ( x)} constitutes

Yk , i.e., Y j = closL2 ( R2 ) g λ: j , n : λ = 1, 2,

, m 2 − 1; n ∈ Z 2 ,

where j ∈ Z , and g λ : j , k ( x) = m j / 2 g λ ( m j x − k ), λ = 1, 2, dition (5), it is obvious that g1 ( x ), g 2 ( x ), (λ ) n

(6)

, m 2 − 1; k ∈ Z 2 . Form con-

, g m2 −1 ( x ) are in Y0 ⊂ X 1. Hence

there exist three real number sequences {q }(λ ∈ Δ = {1, 2,

, m 2 − 1}, n ∈ Z 2 ) such

that

gλ ( x) = m 2 ⋅ ∑ qk( λ ) f (mx − k ),

(7)

k∈Z 2

Formula (7) in frequency domain can be written as

gλ (ω ) = Q ( λ ) ( z1 , z2 ) f (ω a ), λ = 1, 2,

, m 2 − 1.

(8)

The Features of Biorthogonal Binary Poly-scale Wavelet Packs

where the signal of sequence {qk( λ ) }(λ = 1, 2,

∑

Q ( λ ) ( z1 , z2 ) =

25

, m 2 − 1, k ∈ Z 2 ) is

q((nλ ),n ) ⋅ z1 ⋅ z2 . n1

( n1 , n2 )∈Z

1

n2

(9)

2

2

A bivariate function f ( x ) ∈ L (R ) is called a semiorthogonal one, if 2

2

f (⋅), f (⋅ − k ) = δ 0, k , n ∈ Z 2 .

(10)

We say G ( x ) = {g1 ( x), g 2 ( x), , g m2 −1 ( x)} is anorthogonal bivariate vectorvalued wavelets associated with the scaling function f ( x ) , if they satisfy:

f (⋅), gν (⋅ − k ) = 0 , ν ∈ Δ, k ∈ Z 2 ,

(11)

g λ (⋅), gν (⋅ − n) = δ λ ,ν δ 0,n , λ , ν ∈ Δ, n ∈ Z 2

(12)

3 The Traits of Nonseparable Bivariate Wavelet Packs To construct wavelet packs, we introduce the following notation: a = 3, h0 ( x ) = f ( x), hν ( x ) = gν ( x), b( 0) (n) = b(n), b(ν ) (n) = q (ν ) (n), whereν ∈ Δ We are now in a position of introducing orthogonal bivariate nonseparable wavelet wraps. Definition 3. A family of functions { hmk +ν ( x) : n = 0,1, 2,

3, ⋅⋅⋅, ν ∈ Δ } is called a

nonseparable bivariate wavelet packs with respect to an orthogonal scaling function Λ 0 ( x) , where Λ mk +ν ( x) = ∑ n∈Z 2 b(ν ) (n) Λ k (mx − n),

(13)

whereν = 0,1, 2, 3. By taaking the Fourier transform for the both sides of (12), we have h nk +ν (ω ) = B (ν ) ( z1 , z2 ) ⋅ h k (ω 2 ) .

(14)

where B (ν ) ( z1 , z2 ) = B (ν ) (ω / 2 ) = Lemma 1. [6]. Let φ ( x ) ∈ L2 (R 2 ). Then

φ ( x)

∑ | φ ( ω + 2k π ) |

2

∑ bν

( )

k ∈Z

(k ) z1k1 z2k2

(15)

2

is an orthogonal one if and only if

=1 .

(16)

k∈Z2

Lemma 2. Assuming that f ( x ) is an semiorthogonal scaling function. B ( z1 , z2 ) is the symbol of the sequence {b( k )} defined in (3). Then we have

Π = B ( z1 , z 2 ) + B (− z1 , z 2 ) + B ( z1 , − z 2 ) + B ( − z1 , − z 2 ) 2

2

2

2

(17)

26

Z. Tang and H. Guo

∑

f ( x) is an orthogonal bivariate function, then

Proof. If

2

k∈Z

2

f (ω + 2kπ ) =1 .

Therefore, by Lemma 1 and formula (2), we obtain that

∑ | B (e

1=

− i (ω1 2+ k1π )

, e − i ( ω2

2 + k 2π )

) ⋅ f ((ω1 , ω2 ) 2 + (k1 , k2 )π ) |2

k∈Z 2

=| B( z1 , z2 ) ∑ k ∈Z 2 f (ω + 2kπ ) |2 + | B( − z1 , z2 ) ⋅ ∑ k ∈Z 2 f (ω + 2kπ + (1,0)π ) |2 + | B( z1 , − z2 ) ⋅ ∑ k ∈Z 2 f (ω + 2kπ + (0,1)π ) |2 + | B(− z1 , − z2 ) ⋅ ∑ k ∈Z 2 f (ω + 2kπ + (1,1)π ) |2

= B ( z1 , z2 ) + B ( − z1 , z2 ) + B ( z1 , − z2 ) + B ( − z1 , − z2 ) 2

2

2

2

This complete the proof of Lemma 2. Similarly, we can obtain Lemma 3 from (3), (8), (13). Lemma 3. If ψ ν ( x ) (ν

= 0,1, 2,3 ) are orthogonal wavelet functions associated with

h( x) . Then we have

∑

{ B (( −1) z1 , ( −1) z 2 ) B (( −1) z1 , ( −1) z 2 ) + B (λ )

1 j =0

j

(ν )

j

(ν )

⋅ B (( −1)

j +1

j

j

z1 , ( −1) z2 )}: = Ξ λ , μ j

(λ )

(( −1)

j +1

z1 , ( −1) z 2 ) j

= δ λ ,ν , λ ,ν ∈ {0,1, 2, 3}.

(18)

n ∈ Z + , expand it by

For an arbitrary positive integer

n = ∑ j =1ν j 4 j −1 , ν j ∈ Δ = {0,1, 2,3} . ∞

(19)

n ∈ Z + and n be expanded as (17). Then we have

Lemma 4. Let

∞

h n (ω ) = ∏ B j =1

(ν j )

(e −iω1 / 2 , e− iω12 / 2 )h 0 ( 0 ) . j

j

Lemma 4 can be inductively proved from formulas (14) and (18). Theorem 1. For

n ∈ Z + , k ∈ Z 3 , we have hn (⋅), hn (⋅ − k ) = δ 0,k .

(20)

Proof. Formula (20) follows from (10) as n=0. Assume formula (20) holds for the

0 ≤ n < 4r0 ( r0 is a positive integer). Consider the case of 4 r0 ≤ n < 4r0 +1 . For ν ∈ Δ , by induction assumption and Lemma 1, Lemma 3 and Lemma 4, we have case of

( 2π ) =

2

2

hn (⋅), hn (⋅ − k ) = ∫ 2 h n (ω ) ⋅ exp {ikω} dω R

4 π ( j1 +1) 4 π ( j2 +1)

∑ ∫ j∈Z

2

4π

= ∫0

∫

4π j1

∫

4π

0

B

B (ν ) ( z1 , z2 ) ⋅ h[ n / 8] (ω / 2) ⋅ eikω dω 2

4 π j2

(ν )

(z , z ) ∑| h 2

1

2

j ∈Z

2

[n / 8]

(

ω 2

+ 2π j ) | ⋅ e d ω 2

ik ω

The Features of Biorthogonal Binary Poly-scale Wavelet Packs

=

4π

∫ ∫ 0

4π 0

2

B (ν ) ( z1 , z 2 , z 3 ) ⋅ e ik ω d ω =

2π

∫ ∫ 0

2π

0

27

Π ⋅ e ik ω d ω = δ o , k

Thus, we complete the proof of theorem 1. Theorem 2. For every

k ∈ Z 2 and m, n ∈ Z + , we have

hm (⋅), hn (⋅ − k ) = δ m ,nδ 0,k .

(21)

，

m = n (20) follows from Theorem 1.As m ≠ n and m, n ∈ Ω0 , the result (20) can be established from Theorem 2, where Ω0 = {0,1, 2,3} . In what follows, assuming that m is not equal to n and at least one of {m, n} doesn’t belong to Ω0 , rewrite m , n as m = 4 m1 +λ1 , n = 4n1 + μ1 , where m1 , n1 ∈ Z + , and λ1 , μ1 ∈ Ω 0 . Proof. For the case of

Case 1. If

m1 = n1 , then λ1 ≠ μ1 . By (17), formulas (21) follows, since

(2π )2 hm (⋅), hn (⋅ − k ) = ∫ R2 h4 m1 + λ1 (ω )h 4 n1 + μ1 (ω ) ⋅ exp{ikω}d ω

= ∫ [0,4π ]2 B ( λ1 ) ( z1 , z2 )

1 = (2π )2

∫

[0,2π ]2

∑ hm (ω 1

s∈Z

2 + 2sπ ) ⋅ h m1 (ω 2 + 2sπ ) B ( μ1 ) ( z1 , z2 ) ⋅ eikω d ω

2

Ξ λ1 , μ1 ⋅ exp{ikω} dω = O.

Case 2. If m1 ≠ n1 we order m1 = 4m2 + λ2 , n1 = 4n2 + μ 2 , where m2 , n2 ∈ Z + , and λ2 , μ2 ∈ Ω 0 . If m2 = n2 , then λ2 ≠ μ 2 . Similar to Case 1, we have (21) follows. That is to say, the proposition follows in such case. As m2 ≠ n2 , we order m2 = 2m3 + λ3 , n2 = 2n3 + μ3 , once more, where m3 , n3 ∈ Z + , and λ3 , μ3 ∈ Ω0 . Thus, after taking finite steps (denoted by r ), we obtain mr , nr ∈ Ω0 , and λr , μ r ∈ Ω0 . If α r = β r , then λr ≠ μ r . Similar to Case 1, (21) holds. If α r ≠ β r , Similar to Lemma 1, we conclude that

1 ikω hm (⋅), hn (⋅ − k ) = dω 2 h 4 m1 + λ1 (ω ) h 4 n1 + μ1 (ω ) ⋅ e 2 r (2π ) ∫ R r 1 = { B ( λι ) (ω / 2ι )} ⋅ O ⋅{∏ B ( μι ) (ω / 2ι )} ⋅ eikω d ω = O. 2 ∫ [0,2r +1 π ]2 ∏ (2π ) ι =1 ι =1 Theorem 3. If {Gβ ( x), β ∈ Z +2 } and {Gβ ( x), β ∈ Z +2 } are vector-valued wavelet packs with respect to a pair of biorthogonal vector-valued scaling functions G0 ( x) and G0 ( x) , then for any α , σ ∈ Z +2 , we have

Gα (⋅), Gσ (⋅ − k ) = δα ,σ δ 0,k I s , k ∈ Z 2 .

(22)

28

Z. Tang and H. Guo

References 1. Telesca, L., et al.: Multiresolution wavelet analysis of earthquakes. Chaos, Solitons & Fractals 22(3), 741–748 (2004) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis: Nature of ε∞  Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Zhang, N., Wu, X.: Lossless Compression of Color Mosaic Images. IEEE Trans. Image Processing 15(16), 1379–1388 (2006) 4. Chen, Q., et al.: A study on compactly supported orthogonal vector-valued wavelets and wavelet packets. Chaos, Solitons & Fractals 31(4), 1024–1034 (2007) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal.~26(4), 1061--1074 (1995)

6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 8. Chen, Q., Huo, A.: The research of a class of biorthogonal compactly supported vectorvalued wavelets. Chaos, Solitons & Fractals 41(2), 951–961 (2009)

The Traits of Dual Multiple Ternary Fuzzy Frames of Translates with Ternary Scaling Functions* ShuKe Zhou1,** and Qingjiang Chen2 1

Dept. of Math. & Physics, Henan University of Urban Construction, Pingdingshan 467036 2 School of Science, Xi'an University of Architecture & Technology, Xi’an 710055, P.R. China [email protected]

Abstract. The rise of frame theory in appled mathematics is due to the flexibility and redundancy of frames. Structured frames are much easier to construct than Structured orthonormal bases. In this work, the notion of the ternary generalized multiresolution structure (TGMS) of subspace L2 ( R 3 ) is proposed, which is the generalization of the ternary frame multiresolution analysis. The biorthogonality character is characterized by virtue of iteration method and variable separation approach. The biorthogonality formulas concerning these wavelet packages are established.The construction of a TGMS of Paley-Wiener subspace of L2 ( R 3 ) is studied. The pyramid decomposition scheme is obtained based on such a TGMS and a sufficient condition for its existence is provided. A procedure for designing a class of orthogonal vector-valued finitely supported wavelet functions is proposed by virtue of multiresolution analysis method. Keywords: Dual pseudoframes, trivariate wavelet transform, Haar wavelet, Bessel sequence, dual ternary fuzzy frames, time-frequency representation.

1 Introduction Every frame(or Bessel sequence) determines an synthesis operator, the range of which is important for a lumber of applications. The main advantage of wavelet function is their time-frequency localization property. Construction of wavelet functions is an important aspect of wavelet analysis, and mul-tiresolution analysis approach is one of importment ways of designing all sorts of wavelet functions. There exist a great many kinds of scalar scaling functions and scalar wavelet functions. Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. The frame theory has been one of powerful tools for researching into wavelets. Duffin and Schaeffer introduced the notion of frames *

**

Foundation item: The research is supported by Natural Scientific Foundation of Sh-aanxi Province (Grant No:2009J M1002), and by the Science Research Foundation of Education Department of Shaanxi Provincial Government (Grant No:11JK0468). Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 29–35, 2011. © Springer-Verlag Berlin Heidelberg 2011

30

S. Zhou and Q. Chen

for a separable Hilbert space in 1952. Later, Daubechies, Grossmann, Meyer, Benedetto, and Ron revived the study of frames in[1,2], and since then, frames have become the focus of active research, both in theory and in applications, such as signal processing, image processing and sampling theory. The rise of frame theory in applied mathematics is due to the flexibility and redundancy of is due to the flexibility and redundancy of frames, where robust-ness, error tolerance and noise suppression play a vital role [3,4]. The concept of frame multiresolution analysis (FMRA) as described in [2] generalizes the notion of MRA by allowing non-exact affine frames. Inspired by [2] and [5], we introduce the notion of a trivariate generalized multiresolution structure(TGMS) of L2 ( R 3 ) , which has a pyramid decomposition scheme. It also lead to new constructions of affine frames of L2 ( R 3 ) . Sampling theorems play a basic role in digital signal processing. They ensure that continuous signals can be represented and processed by their discrete samples. The classical Shannon Sampling Theorem asserts that band-limited signals can beexactly represented by their uniform samples as long as the sampling rate is not less than the Nyquist rate. Wavelet wraps, owing to their good properties, have attracted considerable attention. They can be widely applied in science and engineering. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. But, there exist a lot of obvious defects in this method, such as, scarcity of designing freedom. Therefore, it is significant to study nonseparable multivariate wavelet theory. Nowadays, since there is little literature on biorthogonal wavelet wraps, it is necessary to research biorthogonal wavelet wraps.

2 Notations and the Dual Ternary Pseudoframes of Translate We start from some notations. Z and Z + denote all integers and all nonnegative integers, respectively. R denotes all real numbers. R3 denotes the 3-dimentional Euclidean space. Let L2 ( R 3 ) be the square integrable function space on R 3 . Set and Z 3 = {( z1 , z2 , z3 ) : zr ∈ Z , r = 1, 2,3}, Z +3 = {{( z1 , z2 , z3 ) : : zr ∈ z+ , r = 1, 2,3}. Let U be a separable Hilbert space and Ω is an index set. We say that a sequence {λν }v∈Ω ⊆ U is a frame for U if there exist positive real constrants L1 , L2 such that

∀

∈ U , L1

2

≤ ∑ v∈Ω |

, λv | ≤ L2 2

2

,

(1)

A family {λν }v∈Ω ⊆ U is a Bessel sequence if (only) the upper inequality of (1) holds. If only for all ∈ Γ ⊂ U , the upper inequality of (1) follows, the sequence {λν }v∈Ω ⊆ U is a Bessel sequence with respect to (w.r.t.) Γ . If a family {λv } ⊂ U is * a frame for U , there exists a dual frame {λv } such that

∀ β ∈U

， β = ∑ β,λ v∈Ω

v

λv* = ∑ β , λv* λv . v∈Ω

(2)

The Traits of Dual Multiple Ternary Fuzzy Frames of Translates

31

For a sequence c = {c(v)} ∈ 2 ( Z ) , we define its discrete-time Fourier transform as the function in space L2 (0,1)3 as follows Fc ( γ ) = C ( γ ) = ∑ u∈Z 3 c ( u )e −2π iuγ

，

(3)

Note that the discrete-time Fourier transform is 1-periodic. Let τ v g ( x ) stand for integer translates of a function g ( x) ∈ L2 ( R 3 ) , i.e., (τ va g )( x) = g ( x − va) , and g n ,va

= 2 n g (2n x − va ) , where a is a positive real constant number. Let ϕ ( x) ∈ L ( R 2

3

)

and let V0 = span{Tv : v ∈ Z } denote a closed subspace of L ( R ) . Assume that 2

2

∧

3

Φ (γ ) := ∑ v∈Z 3 | ϕ ( γ + v ) |2 ∈ L∞ [ 0,1] . In [ 3] , the sequence {τ vϕ ( x )}v is a frame for 3

and only if there exist positive constants

L1 ≤ Φ (ω ) ≤ L2

V0 if

L1 and L2 such that

，a.e., ω ∈ [0,1] \ N = {ω ∈ [0,1] : Η(ω ) = 0} . 3

3

(4)

We begin with introducing the concept of pseudoframes of translates. Definition 1. Let {τ saφ , s ∈ Z 3 } and {τ sa φ , s ∈ Z } be two sequences in L2 ( R 3 ) . Let Y be a closed subspace of L2 ( R 3 ) . We say {τ vaφ , v ∈ Z 3 } forms an affine pseudoframe for Y with respect to {τ va φ , v ∈ Z 3 } if 3

∀ h( x) ∈ Y , h( x) = ∑ v∈Z h,τ va φ τ vaφ ( x ) 3

Define an operator K : Y →

2

( Z 3 ) by

∀ h( x) ∈ Y , and define another operator

S:

(5)

2

Kh = { h,τ vaφ } ,

(6)

( Z 2 ) → Y such that

∀ c = {c(u )} ∈ 2 ( Z 3 ) , Sc = ∑ u∈Z c(u ) τ ua φ. 3

(7)

Theorem 1. Let {τ vaφ }v∈Z 3 ⊂ L2 ( R 3 ) be a Bessel sequence with respect to the subspace Y ⊂ L2 ( R 3 ) , and {τ va φ}v∈Z 3 is a Bessel sequence in L2 ( R 3 ) . Assume that K be defined by (7), and S be defined by (8). Assume P is a projection from L2 ( R 3 ) onto Y . Then {τ vaφ }v∈Z 3 is pseudoframes of translates for the subspace Y with re-spect to {τ va φ}v∈Z 3 if and only if

KSP = P .

(8)

Proof. The convergence of all summations of (7) and (8) follows from the assumptions that the family {τ vaφ}v∈Z 3 is a Bessel sequence with respect to the subspace Y , and he family {τ va φ}v∈Z 3 is a Bessel sequence in L2 ( R 3 ) with which the proof of the theorem is direct forward.

32

S. Zhou and Q. Chen

We say that a trivariate generalized multiresolution structure (TGMS){Vn , f ( x), f ( x)} of L2 ( R 3 ) is a sequence of closed linear subspaces {Vn }n∈Z of L2 ( R 3 ) and two

Vn ⊂ Vn +1 , n ∈ Z ; (ii) ∩ V = {0} ; ∪ V is dense in L ( R ) ; (iii) g ( x) ∈ Vn if and only if g (2 x) ∈ Vn+1 ∀n ∈ Z . (iv) ϕ ( x ) ∈ V0 implies τ vaϕ ( x ) ∈ V0 , for v ∈ Z ; (v) {τ vaφ }v∈Z forms pseud-oframes of elements f ( x) , f ( x) ∈ L2 ( R 3 ) such that (i) 2

n∈ Z

n∈ Z

n

3

n

3

translates for with respect to {τ va φ}v∈Z 3 .

Proposition 1[3]. Let f ( x) ∈ L2 ( R 3 ) satisfy | f | a.e. on a connected neighbourhood of 0 in [− 12 , 21 )3 , and | f | = 0 a.e. otherwise. Define Λ ≡ {ω ∈ R 2 : | f (ω ) | ≥ C > 0}, and ∧ V0 = PWΛ = {φ ∈ L2 ( R 3 ) : supp(φ ) ⊆ Λ} . Then for arbitraryfun. f ( x) ∈ L2 ( R 3 ) , {τ v f : v ∈ Z 3 } is pseudoframes of trananslates for V0 with respect to {τ v f : v ∈ Z 3 } if and only if ∧

∧

f (ω ) f (ω ) χ Λ ( ω ) = χ Λ (ω ) a. e. ,

(9)

where χ Λ is the characteristic function on Λ . Moreover, if f (ω ) is the above conditions then {τ v f : v ∈ Z 3 } and {τ v f : v ∈ Z 3 } are a pair of commutative pseudoframes of translates for V0 , i. .e.

，

h ( x ) = ∑ k ∈ Z 3 h , τ k f τ k f ( x ) = ∑ k ∈Z 2 h , τ k f τ k f ( x ) .

∀ h( x) ∈ V0 ,

Proposition 2[3]. Let {τ va f }v∈Z 3 be pseudoframes of translates for

{τ va f }v∈Z 3 . Define

Vn by Vn ≡ {h( x) ∈ L2 ( R 3 ) : h( x / 2n ) ∈ V }

Then { f n , va }v∈Z 3 is an affine pseudoframe for

(10)

V0 with respect to

，n∈Z ,

(11)

Vn with respect to { f n ,va }v∈Z . 3

The filter functions associated with a TGMS are presented as follows. Define filter functions

D0 (ω )

B 0 (ω ) = ∑ s∈Z 3 b0 ( s ) e

and −2π isω

D 0 (ω )

by

D0 (ω ) = ∑ s∈Z 3 d 0 ( s ) e −2π isω

and

of the sequences d 0 = {d 0 ( s)} and d 0 = {d 0 ( s )} , resp-

ectively, wherever the sum is defined. Let

{b0 (v)} be such that D0 (0) = 2 and

B0 (ω ) ≠ 0 in a neighborhoood of 0. Assume also that D0 (ω ) ≤ 2 . Then there exists f ( x) ∈ L2 ( R 2 ) (see ref.[3]) such that f ( x) = 2 ∑ s∈Z 3 d0 ( s ) f (2 x − sa ) .

(12)

There exists a scaling relationship for f ( x) under the same conditions as that of for a sequence d 0 , i.e.,

f ( x) = 2 ∑ s∈Z 3 d 0 ( s) f (2 x − sa) .

d0

(13)

The Traits of Dual Multiple Ternary Fuzzy Frames of Translates

33

3 The Traits of Nonseparable Trivariate Wavelet Packages Denoting by G0 ( x) = F ( x ), Gμ ( x ) = Ψ μ ( x ), G0 ( x ) = F ( x ), Gμ ( x) = Ψ μ ( x), Qk(0) = Ω k , (μ) (μ) (μ ) (μ) 3 3 Qk = Bk , Qk(0) = Ω k , Qk = Bk , μ ∈ Γ, k ∈ Z , M = 4 I v . For any α ∈ Z + and the given vector-valued biorthogonal scaling functions G0 ( x) and G0 ( x) , iteratitively define, respectively,

Gα ( x) = G2σ + μ ( x) = Gα ( x) = G2σ + μ ( x) =

∑ Q μ Gσ (2 x − k ),

μ ∈ Γ0 ,

(14)

∑ Q μ Gσ (2 x − k ),

μ ∈ Γ0 .

(15)

( ) k

k ∈Z

3

( ) k

k ∈Z

3

where σ ∈ Z +3 is the unique element such that α = 4σ + μ , μ ∈ Γ 0 follows. Lemma 1[4]. Let F ( x), F ( x) ∈ L2 ( R 3 , C v ). Then they are biorthogonal if and only if

∑ Fˆ (γ + 2kπ ) Fˆ (γ + 2kπ )

k∈Z

*

= Iv .

(16)

3

Definition 2. We say that two families of vector-valued functions {G2σ + μ ( x ), σ ∈ Z +3 , μ ∈ Γ 0 } and {G2σ + μ ( x), σ ∈ Z +3 , μ ∈ Γ 0 } are vector-valued wavelet packets with respect to a pair of biorthogonal vector-valued scaling functions G0 ( x) and G0 ( x) , resp., where G2σ + μ ( x) and G2σ + μ ( x) are given by (14) and (15), respectively. Applying the Fourier transform for the both sides of (14) and (15) yields, resp.,

Gˆ 2σ + μ (2γ ) = Q ( μ ) (γ )Gˆσ (γ ), μ ∈ Γ 0 , ˆ ˆ G2σ + μ (2γ ) = Q ( μ ) (γ )Gσ (γ ),

μ ∈ Γ0 ,

(17) (18)

Lemma 2[6]. Assume that Gμ ( x), Gμ ( x) ∈ L ( R , C ), μ ∈ Γ are pairs of biorthogonal vector-valued wavelets associated with a pair of biorthogonal scaling functions G0 ( x) and G0 ( x) . Then, for μ ,ν ∈ Γ 0 , we have 2

Q μ ((γ + 2 ρπ ) / 2)Q ν ∑ ρ ( )

∈Γ0

( )

3

v

((γ + 2 ρπ ) / 2)* = δ μ ,ν I v .

(19)

Theorem 2[8]. Assume that {Gβ ( x), β ∈ Z +3 } and {Gβ ( x), β ∈ Z +3 } are vectorvalued wavelet packets with respect to a pair ofbiorthogonal vector-valued functions G0 ( x) and G0 ( x) , respectively. Then, for β ∈ Z +3 , μ , v ∈ Γ 0 , we have

[Gα (⋅), Gα (⋅ − k )] = δ 0, k I v , k ∈ Z 3 . [G2 β + μ (⋅), G2 β +v (⋅ − k )] = δ 0, k δ μ ,ν I v , k ∈ Z 3 .

(20) (21)

34

S. Zhou and Q. Chen

Theorem 3. If {Gβ ( x), β ∈ Z +3 } and {Gβ ( x), β ∈ Z +3 } are vector-valued wavelet wraps with respect to a pair of biorthogonal vector scaling functions G0 ( x) and G0 ( x) , then for any α ,σ ∈ Z +3 , we have

[Gα (⋅), Gσ (⋅ − k )] = δα ,σ δ 0, k I v , k ∈ Z 3 .

(22)

Proof. When α = σ , (22) follows by Theorem 2. as α ≠ σ and α , σ ∈ Γ 0 , it follows from Theorem 1 that ((22)) holds, too. Assuming that α is not equal to β , as well as at least one of {α ,σ } doesn’t belong to Γ 0 , we rewrite α , σ as α = 2α1 + ρ1 , σ = 2σ 1 + μ1 , where ρ1 , μ1 ∈ Γ 0 . Case 1. If α1 = σ 1 , then ρ1 ≠ μ1 . (22) follows by virtue of (17), (18) as well as Lemma 1 and Lemma 2, i.e.,

ˆ (2π )3 [Gα (⋅), Gσ (⋅ − k )] = ∫ 3 Gˆ 2α1 + ρ1 (γ )G2σ1 + μ1 (γ )* ⋅ exp{ik ⋅ γ }d γ R

=∫

[0,2 π ]3

δ ρ , μ I v ⋅ exp{ik ⋅ γ }d γ = O. 1

1

Case 2. If α1 ≠ σ 1 , order α1 = 2α 2 + ρ 2 , σ 1 = 2σ 2 + μ 2 , where α 2 , σ 2 ∈ Z +3 , and

ρ 2 , μ2 ∈ Γ0 . If α 2 = σ 2 , then ρ 2 ≠ μ2 . Similar to Case 1, (22) follows. As α 2 ≠ σ 2 , order α 2 = 2α 3 + ρ3 , σ 2 = 2σ 3 + μ3 , where α 3 , σ 3 ∈ Z +3 , ρ3 , μ3 ∈ Γ 0 . Thus, taking finite steps (denoted by κ ), we obtain α κ ∈ Γ 0 , and ρκ , μκ ∈ Γ 0 . ˆ 8π 3 [Gα (⋅), Gσ (⋅ − k )] = ∫ Gˆα (γ )Gσ (γ )* ⋅ eik ⋅γ d γ R3

=∫

R

=∫

ˆ Gˆ 2α1 + λ1 (γ )G2 β1 + μ1 (γ )* ⋅ exp{ik ⋅ γ }d γ 3 κ

κ

([0,2⋅2 π ]

3

{∏Q ( ρl ) (γ / 2l )} ⋅ O ⋅ {∏ l =1Q ( μl ) (γ / 2l )}* ⋅ exp{−ik ⋅ γ }d γ = O. κ

l =1

Therefore, for any α , σ ∈ Z +3 , result (22) is established.

4 Conclusion The construction of a TGMS of Paley-Wiener subspace of L2 ( R 3 ) is studied. The pyramid decomposition scheme is obtained based on such a TGMS. The biorthogonality formulas concerning these wa-velet packages are established.

References 1. Telesca, L., et al.: Multiresolution wavelet analysis of earthquakes. Chaos, Solitons & Fractals 22(3), 741–748 (2004) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis: Nature of ε ∞  Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007)

The Traits of Dual Multiple Ternary Fuzzy Frames of Translates

35

3. Li, S., et al.: A theory of generalized multiresolution structure and pseudoframes of translates. Fourier Anal. Appl. 7(1), 23–40 (2001) 4. Chen, Q., et al.: A study on compactly supported orthogonal vector-valued wavelets and wavelet packets. Chaos, Solitons & Fractals 31(4), 1024–1034 (2007) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal. 26(4), 1061–1074 (1995) 6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Wei, Z.: The characteristics of orthogonal trivariate wavelet packets. Information Technology Journal 8(8), 1275–1280 (2009) 8. Chen, Q., Shi, Z.: Biorthogonal multiple vector-valued multivari-ate wavelet packets associa-ted with a dilation matrix. Chaos, Solitons & Fractals 35(3), 323–332 (2008)

The Characteristics of Multiple Affine Oblique Binary Frames of Translates with Binary Filter Banks YongGan Li* Office of Financial affairs, Henan Quality Polytechnic, Pingdingshan 467000, P.R. China [email protected]

Abstract. Frame theory has been the focus of active research for twenty years, both in theory and applications. In this paper, the notion of the bivariate generalized multiresolution structure (BGMS) of subspace L2 ( R 2 ) , which is the generalization of frame multiresolution analysis, is proposed. The biorthogonanality traits on wavelet wraps are researched by using time-frequency analysis approach and variable separation approach. The construction of a BGMS of Paley-Wiener subspace of L2 ( R 2 ) is studied. The pyramid decomposition scheme is obtained based on such a GMS and a sufficient condition for its existence is provided. A procedure for designing a class of orthogonal vectorvalued finitely supported wavelet functions is proposed by virtue of filter bank theory and matrix theory. Keywords: Affine pseudoframes, bivariate wavelet wraps, wavelet frame, Bessel sequence, orthonormal bases, time-frequency analysis approach.

1 Introduction and Notations The main advantage of wavelet function is their time-frequency localization property. Construction of wavelet functions is an important aspect of wavelet analysis, and multiresolution analysis approach is one of importment ways of designing all sorts of wavelet functions. There exist a great many kinds of scalar scaling functions and scalar wavelet functions. Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. The frame theory has been one of powerful tools for researching into wavelets. Duffin and Schaeffer introduced the notion of frames for a separable Hilbert space in 1952. Later, Daubechies, Grossmann, Meyer, Benedetto, Ron revived the study of frames in[1,2],and since then, frames have become the focus of active research, both in theory and in applications, such as signal processing, image processing and sampling theory. The rise of frame theory in applied mathematics is due to the flexibility and redundancy of is due to the flexibility and redundancy of frames, where robustness, error toleranceand noise suppression play a vital role [3,4]. The concept of frame *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 36–41, 2011. © Springer-Verlag Berlin Heidelberg 2011

The Characteristics of Multiple Affine Oblique Binary Frames

37

multiresolution analysis (FMRA) as described in [2] generalizes the notion of MRA by allowing non-exact affine frames. However, subspaces at different resolutions in a FMRA are still generated by a frame formed by translates and dilates of a single function. This paper is motivated from the observation that standard methods in sampling theory provide examples of multiresolution structure which are not FMRAs. Inspired by [2] and [5], we introduce the notion of a bivariate generalized multiresolution structure(BGMS) of L2 ( R 2 ) , which has a pyramid decomposition scheme. It also lead to new constructions of affine frames of L2 ( R 2 ) . Wavelet wraps, owing to their good properties, have attracted considerable attention. They can be widely applied in science and engineering. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. But, there exist a lot of obvious defects in this method, such as, scarcity of designing freedom. Therefore, it is significant to investigate nonseparable multivariate wavelet theory. Nowadays, since there is little literature on biorthogonal wavelet wraps, it is necessary to investigate biorthogonal wavelet wraps . In the following, we introduce some notations. Z and Z + denote all integers and all nonnegative integers, respectively. R denotes all real numbers. R 2 denotes the 2dimentional Euclidean space. L2 ( R 2 ) denotes the square integrable function space. 2 − iω 2 Let x = ( x1 , x2 ) ∈ R , ω = (ω1 , ω2 ) ∈ R 2 , k = ( k1 , k 2 ) ∈ Z 2 , z1 = e − iω 2 , z2 = e 2 . The inner product for any functions ( x ) and ( x ) ( ( x ), ( x) ∈ L2 ( R 2 )) and the Fourier transform of ( x ) are defined, respectively, by

,

=∫

R2

( x) ( x ) dx,

(ω ) = ∫

R2

( x) e −2π iω ⋅ x dx,

where ω ⋅ x = ω1 x1 + ω2 x2 and ( x) denotes the complex conjugate of ( x) . Let R and C be all real and all complex numbers, respectively. Z and N denote, respectively, all integers and all positive integers. Set Z + = {0} ∪ N , m, s ∈ N as well as m ≥ 2 By 2 algebra theory, it is obviously follows that there are m elements λ0 , λ1 , , λm2 −1 in 2 2 Z +2 = {(n1 , n2 ) : n1 , n2 ∈ Z + } such that Z = ∪ d ∈Ω (λ + mZ ) ; 2 2 (λ1 + mZ ) ∩ (λ2 + mZ ) = φ , where Λ 0 = {λ0 , λ1 , , λm2 −1} denotes the aggregate of all the different representative elements in the quotient group Z 2 /(mZ 2 ) and order λ = {0} where {0} is the null element of Z and λ1 , λ2 denote two arbitrary distinct elements in Λ 0 .Let Λ = Λ 0 − {0} and Λ, Λ 0 to be two index aggregates. By L2 ( R 2 , C s ) , we denote the set of vector-valued functions L2 ( R 2 , C s ) := { ( x) = (h1 ( x), h2 ( x), , hu ( x))T : hl ( x) ∈ L2 ( R 2 ), l = 1, 2, , s} ,where T means the transpose of a vector. 0

2

+

0

Definition 1. A sequence {

n

( x) n∈Z 2 ⊂ L2 ( R 2 , C s )} is called an orthogonal set, if

〈

n

,

v

〉 = δ n ,v I s , n, v ∈ Z 2 ,

(1)

where I s stands for the s × s identity matrix and δ n ,v , is generalized Kronecker symbol, i.e., δ n ,v = 1 as n = v and δ n ,v = 0 , otherwise.

38

Y. Li

Let W be a separable Hilbert space and Λ is an index set. We recall that a sequence {ξ v : v ∈ Z } ⊆ W is a frame for H if there exist positive real numbers C , D such that ∀ η ∈W , C η

2

≤ ∑ v∈Λ | η , ξv | ≤ D η 2

2

,

(2)

A sequence {ξ v : v ∈ Z } ⊆ W is a Bessel sequence if (only) the upper inequality of (2) holds. If only for all ∈ Γ ⊂ W , the upper inequality of (2) holds, the sequence {ξ v } ⊆ W is a Bessel sequence with respect to (w.r.t.) Γ . If { f v } is a frame, there * exists a dual frame { f v } such that

∀ ϒ ∈W

， ϒ = ∑ ϒ, f v∈Λ

For a sequence c = {c(v)} ∈

2

v

f v* = ∑ ϒ, f v* f v .

(3)

v∈Λ

( Z ) , we define its discrete-time Fourier transform as

the function in L2 (0,1) 2 by Fc (ω ) = C (ω ) = ∑ v∈Z 2 c ( v )e −2π ixω dx

，

Note that the discrete-time Fourier transform is 1-periodic. Let

(4)

Tvφ ( x ) stand for

φn,va

integer translates of a function φ ( x) ∈ L ( R ) , i.e., (Tvaφ )( x) = φ ( x − va) , and 2

2

= 4 φ (4 x − va ) , where a is a positive real constant number. Let ( x) ∈ L ( R 2 ) n

n

2

and let V0 = span{Tv : v ∈ Z 2 } be a closed subspace of L2 ( R 2 ) . Assume that ∧

(ω + v ) | ∈ L [0,1] . In [5] , the sequence {Tv ( x)}v is a frame for V0 if and only if there exist positive constants L1 and L2 such that Η (ω ) := ∑ v |

2

L1 ≤ Η (ω ) ≤ L2

∞

2

，a.e., ω ∈ [0,1] \ N = {ω ∈[0,1] : Η(ω) = 0} . 2

2

(5)

2 The Bivariate Affine Pseudoframes of Translate We begin with introducing the concept of pseudoframes of translates. Definition 1. Let {Tva ϒ, v ∈ Z 2 } and {Tva ϒ, v ∈ Z 2 } be two sequences in L2 ( R 2 ) . Let U be a closed subspace of L2 ( R 2 ) . We say {Tva ϒ, v ∈ Z 2 } forms an affine pseudoframe for U with respect to {Tva ϒ, v ∈ Z 2 } if

∀ f ( x) ∈ U , f ( x) = ∑ v∈Z f , Tva ϒ Tva ϒ( x ) 2

Define an operator K : U →

2

( Z 2 ) by

∀ f ( x) ∈U , and define another operator

S:

(6)

2

Kf = { f , Tva ϒ } ,

( Z 2 ) → W such that

(7)

The Characteristics of Multiple Affine Oblique Binary Frames

39

∀ c = {c(k )} ∈ 2 ( Z 2 ) , Sc = ∑ v∈Z c(v) Tva ϒ.

(8)

2

Theorem 1. Let {Tva ϒ}v∈Z 2 ⊂ L2 ( R 2 ) be a Bessel sequence with respect to the subspace U ⊂ L2 ( R 2 ) , and {Tva ϒ}v∈Z 2 is a Bessel sequence in L2 ( R 2 ) . Assume that K be defined by (7), and S be defined by(8). Assume P is a projection from L2 ( R 2 ) onto U . Then {Tva ϒ}v∈Z 2 is pseudoframes of translates for U with respect to {Tva ϒ}v∈Z 2 if and only if

KSP = P .

(9)

Proof. The convergence of all summations of (7) and (8) follows from the assumptions that the family {Tva ϒ}v∈Z 2 is a Bessel sequence with respect to the subspace Ω , and he family {Tva ϒ}v∈Z 2 is a Bessel sequence in L2 ( R 2 ) with which the proof of the theorem is direct forward.

We say that a bivariate generalized multiresolution structure (BGMS) {Vn , f ( x),

f ( x)} of L2 ( R 2 ) is a sequence of closed linear subspaces {Vn }n∈Z of L2 ( R 2 ) and two

Vn ⊂ Vn +1 , n ∈ Z ; (ii) ∩ V = {0} ; ∪ V is dense in L ( R ) ; (iii) h ( x ) ∈Vn if and only if h ( 4 x ) ∈Vn +1 ∀n ∈ Z . (iv) g ( x) ∈ V0 implies Tva g ( x) ∈ V0 , for v ∈ Z ; (v) {Tva f }v∈Z forms pseudoframes of elements f ( x) , f ( x) ∈ L2 ( R 2 ) such that (i) 2

n∈ Z

n∈ Z

n

2

n

2

translates for with respect to {Tva f , v ∈ Z } . 2

( )

Proposition 1[6]. Let f ∈ L R satisfy | f | a.e. on a connected neighbourhood of 0 in [− 12 , 12 )2 , and | f | = 0 a.e. otherwise. Define ∧ 2 2 Λ ≡ {ω ∈ R 2 : | f (ω ) | ≥ C > 0}, and V0 = PWΛ = {φ ∈ L ( R ) : supp(φ ) ⊆ Λ} . 2

Then for

2

f ∈ L2 ( R 2 ) , {Tv f : v ∈ Z 2 } is pseudoframes of trananslates for V0 with

respect to {Tv f : v ∈ Z 2 } if and only if ∧

∧

h (ω ) f ( ω ) χ Λ ( ω ) = χ Λ ( ω ) a. e. , where

χΛ

is the characteristic function on

(11)

Λ . Moreover, if f (ω ) is the above

conditions then {Tv f : v ∈ Z 2 } and {Tv f : v ∈ Z 2 } are a pair of commutative pseudo-

，

frames of translates for V0 , i. .e.

∀ Γ( x) ∈ V0 ,

Γ( x) = ∑ k∈Z 2 Γ, Tk f Tk f ( x) = ∑ k∈Z 2 Γ, Tk f Tk f ( x) .

Proposition 2[5]. Let {Tva f }v∈Z 2 be pseudoframes of translates for

{Tva f }v∈Z 2 . Define

Vn by Vn ≡ {ϒ( x) ∈ L2 ( R 2 ) : ϒ( x / 4 n ) ∈ V }

，n∈Z ,

(12)

V0 with respect to (13)

40

Y. Li

Then, { f n , va }v∈Z 2 is an affine pseudoframe for

Vn with respect to { f n ,va }v∈Z . 2

The filter functions associated with a BGMS are presented as follows. Define filter functions

D0 (ω )

and

B 0 (ω ) = ∑ s∈Z 2 b0 ( s) e

−2π iω

D0 (ω ) = ∑ s∈Z 2 d 0 ( s ) e−2π iω

D 0 (ω ) by

and

of the sequences d 0 = {d 0 ( s )} and d 0 = {d 0 ( s )} , res-

pectively, wherever the sum is defined. Let

{b0 (v)} be such that D0 (0) = 2 and

B0 (ω ) ≠ 0 in a neighborhoood of 0. Assume also that D0 (ω ) ≤ 2 . Then there exists f ( x) ∈ L2 ( R 2 ) (see ref.[3]) such that f ( x) = 2∑ s∈Z 2 d 0 ( s ) f (4 x − sa ) .

(14)

f ( x) under the same conditions as that of

There exists a scaling relationship for d0 for a seq. d 0 , i.e.,

f ( x) = 2∑ s∈Z 2 d0 (v) f (4 x − sa) .

(15)

3 The Traits of Nonseparable Bivariate Wavelet Packs To construct wavelet packs, we introduce the following notation: a = 3, h0 ( x ) = f ( x),

hν ( x ) = gν ( x), b( 0) (n) = b(n), b(ν ) (n) = q (ν ) (n), whereν ∈ Δ We are now in a position of introducing orthogonal bivariate nonseparable wavelet wraps. Definition 3. A family of functions { hmk +ν ( x ) : n = 0,1, 2,

3, ⋅⋅⋅, ν ∈ Δ } is called a

nonseparable bivariate wavelet packs with respect to an orthogonal scaling function

Λ 0 ( x) , where Λ mk +ν ( x ) = ∑ n∈Z 2 b(ν ) (n) Λ k (mx − n), whereν

(16)

= 0,1, 2, 3. By taaking the Fourier transform for the both sides of (12), we have h nk +ν (ω ) = B (ν ) ( z1 ,2 z ) ⋅ h k (ω B

( z1 , z2 ) = B (ω / 2 ) = ∑ b

(ν )

(ν )

2). (ν )

(17) k1 1

(k ) z z

k2 2

(18)

k ∈Z 2

Lemma 1[6]. Let φ ( x) ∈ L2 (R 2 ). Then

φ ( x)

∑ | φ ( ω + 2k π ) |

2

k∈Z

is an orthogonal one if and only if

=1 .

(19)

2

Lemma 2[6]. Assuming that f ( x) is an semiorthogonal scaling function. B ( z1 , z2 ) is the symbol of the sequence {b(k )} defined in (3). Then we have

Π = B ( z1 , z 2 ) + B (− z1 , z 2 ) + B ( z1 , − z 2 ) + B ( − z1 , − z 2 ) 2

2

2

2

(20)

The Characteristics of Multiple Affine Oblique Binary Frames

ψν ( x) ( ν = 0,1, 2,3 )

Lemma 3[8].

If

associated with

h( x ) . Then we have

∑

1 j =0

are orthogonal binary wavelet functions

{ B (( −1) z1 , ( −1) z 2 ) B (( −1) z1 , ( −1) z 2 ) + B (λ )

j

(ν )

⋅ B (( −1) Lemma 4[6]. Let

(ν )

j

j +1

j

j

z1 , ( −1) z 2 )}: = Ξ λ , μ j

41

(λ )

(( −1)

j +1

z1 , ( −1) z 2 ) j

= δ λ ,ν , λ ,ν ∈ {0,1, 2, 3}.

(21)

n ∈ Z + and n be expanded as (17). Then we have ∞

h n (ω ) = ∏ B j =1

(ν j )

(e −iω1 / 2 , e − iω12 / 2 )h 0 ( 0 ) . j

j

Lemma 4 can be inductively proved from formulas (14) and (18). 3 Theorem 1[6]. For n ∈ Z + , k ∈ Z , we have

hn (⋅), hn (⋅ − k ) = δ 0,k . Theorem 2[7]. For every

(22)

k ∈ Z 2 and m, n ∈ Z + , we have

hm (⋅), hn (⋅ − k ) = δ m, nδ 0, k .

(23)

References 1. Telesca, L., et al.: Multiresolution wavelet analysis of earthquakes. Chaos, Solitons & Fractals 22(3), 741–748 (2004) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis: Nature of ε ∞  Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Li, S., et al.: A theory of generalized multiresolution structure and pseudoframes of translates. Fourier Anal. Appl. 7(1), 23–40 (2001) 4. Chen, Q., et al.: A study on compactly supported orthogonal vector-valued wavelets and wavelet packets. Chaos, Solitons & Fractals 31(4), 1024–1034 (2007) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal. 26(4), 1061–1074 (1995) 6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Wei, Z.: The characteristics of orthogonal trivariate wavelet packets. Information Technology Journal 8(8), 1275–1280 (2009) 8. Yang, S., Cheng, Z., Wang, H.: Construction of biorthogonal multiwavelets. J. Math. Anal. Appl. 276(1), 1–12 (2002)

Generation and Characteristics of Vector-Valued Quarternary Wavelets with Poly-scale Dilation Factor* Ping Luo1,** and Shiheng Wang2 1

2

Department of Fundamentals, Henan Polytechnic Institute, Nanyang 473009, China Department of Computer Science, Nanyang Agricultural College, Nanyang 473003, China [email protected]

Abstract. Wavelet analysis has become a developing branch of mathematics for over twenty years. In this paper, the notion of orthogonal nonseparable bivariate wavelet packs, which is the generalization of orthogonal univariate wavelet packs, is proposed by virtue of analogy method and iteration method. Their biorthogonality traits are researched by using time-frequency analysis approach and variable separation approach. Three orthogonality formulas regarding these wavelet wraps are obtained. Moreover, it is shown how to draw new orthonormal bases of space L2 ( R 4 ) from these wavelet wraps. A procedure for designing a class of orthogonal vector-valued finitely supported wavelet functions is proposed by virtue of filter bank theory and matrix theory. Keywords: Nonseparable, quarternary wavelet packs, frames of transform, Bessel sequence, Gabor frames, time-frequency analysis approach.

1 Introduction and Notations There is a large diversity of research fields where Gabor systems and frames play a role. The main advantage of wavelet packs is their time-frequency localization property. Construction of wavelet bases is an important aspect of wavelet analysis, and multiresolution analysis method is one of importment ways of constructing various wavelet bases. There exist many kinds of scalar scaling functions and scalar wavelet functions. Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. Wavelet analysis [1] has been developed a new branch for over twenty years. Its applications involve in many areas in natural science and engineering technology. The main advantage of wavelets is their time-frequency localization property. Many signals in areas like music, speech, images, and video images can be efficiently represented by wavelets that are translations and dilations of a single function called mother wavelet with bandpass property. They can be widely applied in science and engineering [2,3]. * Foundation item: The research is supported by Natural Scientific Foundation of Shaanxi Province (Grant No:2009J M1002), and by the Science Research Foundation of Education Department of Shaanxi Provincial Government (Grant No:11JK0468). ** Corresponding author. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 42–48, 2011. © Springer-Verlag Berlin Heidelberg 2011

Generation and Characteristics of Vector-Valued Quarternary Wavelets

43

Coifman R. R. and Meyer Y. firstly introduced the notion for orthogonal wavelet packets which were used to decompose wavelet components. Chui C K.and Li Chun L.[4] generalized the concept of orthogonal wavelet packets to the case of nonorthogonal wavelet packets so that wavelet packets can be employed in the case of the spline wavelets and so on. Tensor product multivariate wavelet packs has been constructed by Coifman and Meyer. The introduction for the notion on nontensor product wavelet packs attributes to Shen Z [5]. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. Therefore, it is significant to investigate nonseparable multivariate wavelet theory. In the following, we introduce some notations. Z and Z + denote all integers and all nonnegative integers, respectively. R denotes all real numbers. R 2 denotes the 4dimentional Euclidean space. L2 ( R 4 ) denotes the square integrable function space. 4 x = ( x1 , x2 , x3 , x4 ) ∈ R , ω = (ω1 , ω2 , ω3 , ω4 ) ∈ R 4 , k = (k , k , k , k ) ∈ Z , Let ωl z =e , i = 1, 2, 3, 4 . The inner product for any functions ψ ( x ) and ( x ) and the Fourier transform of ψ ( x ) are defined, respectively, by 4

1

−i

2

3

4

2

l

ψ,

= ∫ 4 ψ ( x) ( x ) dx, ψ (ω ) = ∫ 4 ψ ( x) e − iω ⋅ x dx, R

R

where ω ⋅ x = ω1 x1 + ω2 x2 + ω3 x3 + ω4 x4 and ( x) denotes the complex conjugate of ( x) . Set Z + = {0} ∪ N , m, s ∈ N as well as m ≥ 2 By algebra theory, it is obviously 4 follows that there are m elements d 0 , d1 , , d m4 in Z +4 = {(n1 , n2 , n3 , n4 ) : nl ∈ Z + } nl ∈ Z + } such that Z = ∪ (d + mZ ) ; (d1 + mZ 4 ) ∩ (d 2 + mZ 4 ) = φ , where Ω 0 = {d 0 , d1 , , d m4 −1} denotes the aggregate of all the different representative elements in the quotient group Z 4 /(mZ 4 ) and order d 0 = {0} where {0} is the null element of Z and d1 , d 2 denote two arbitrary distinct elements in Ω0 .Let Ω = Ω 0 − {0} and Ω, Ω 0 to be two index sets. Define, By L2 ( R 4 , C s ) , we denote the set of all vector-valued functions L2 ( R 4 , C s ) := { ( x) , = (h1 ( x)), h2 ( x), , hu ( x))T : hl ( x ) ∈ L2 ( R 2 ), l = 1, 2, , s} ,where T means the transpose of a vector. For any ∈ L2 ( R 4 , C s ) its integration is defined as follows 4

4

d ∈Ω 0

4

+

∫

R4

( x)dx = ( ∫ R4 h1 ( x)dx, ∫ R4 h2 ( x)dx,

, ∫ R4 hs ( x)dx )T .

Definition 1. A sequence {

n

( y ) n∈Z 4 ⊂ L2 ( R 4 , C s )} is called an orthogonal set, if

〈

n

,

v

〉 = δ n ,v I s , n, v ∈ Z 4 ,

(1)

2 The Bivariate Multiresolution Analysis 2

4

Firstly, we introduce multiresolution analysis of space L ( R ) . Wavelets can be constructed by means of multiresolution analysis. In particular, the existence

44

P. Luo and S. Wang

theorem[8] for higher-dimentional wavelets with arbitrary dilation matrice has been given. Let ϕ ( x ) ∈ L2 ( R 4 ) satisfy the following refinement equation:

ϕ ( x) = m 4 ⋅ ∑ k∈Z bkϕ (mx − k ) ,

(2)

4

where {b(n)}n∈Z 4 is real number sequence which has only finite terms.and ϕ ( x ) ∈ L2 ( R 4 ) is called scaling function. Formula (1) is said to be two-scale refinement equation. The frequency form of formula (1) can be written as

ϕ (ω ) = B( z1 , z2 , z3 , z4 ) ϕ (ω m), B( z1 , z2 , z3 , z4 ) = ∑ b( n) ⋅ z1n ⋅ z2 n ⋅ z3n ⋅ z4 n 1

n∈Z

3

2

4

(3) .

(4)

2

Define a subspace V j ⊂ L ( R ) ( j ∈ Z ) by 2

4

V j = closL2 ( R4 ) m 2ϕ ( m j x − k ) : k ∈ Z 4 .

(5)

Definition 2. We say that ϕ ( x) in (2) generate a multiresolution analysis {V j } j∈Z of

L2 ( R 4 ) , if the sequence {V j } j∈Z defined in (4) satisfy the following properties: 2 4 (i) V j ⊂ V j +1 , ∀ j ∈ Z ; (ii) ∩ V j = {0}; ∪ V j is dense in L ( R ) ; (iii) h( x) ∈ Vk j∈Z j∈Z j ⇔ h( mx) ∈ Vk +1 , ∀ k ∈ Z (iv) the family {ϕ (m x − n) : n ∈ Z 4 } forms a Riesz basis for the spaces V j .

Let U k (k ∈ Z ) denote the complementary subspace of V j in V j +1 , and assume

that there exist a vector-valued function Φ ( x) = {ϕ1 ( x), ϕ 2 ( x),

, ϕ m4 −1 ( x)} constitutes

a Riesz basis for U k , i.e., U j = closL2 ( R4 ) ϒ λ : j , n : λ = 1, 2,

, m4 − 1; n ∈ Z 4 ,

where j ∈ Z , and ϕ λ : j , k ( x ) = m j / 2ϕ λ ( m j x − k ), λ = 1, 2,

dition (5), it is obvious that ϕ1 ( x ), ϕ 2 ( x),

(6)

, m 4 − 1; k ∈ Z 4 . Form con-

, ϕ m4 −1 ( x) are in U 0 ⊂ X 1. Hence there

(λ ) n

exist three real number sequences {q }(λ ∈ Δ = {1, 2,

, m 4 − 1}, n ∈ Z 4 ) such that

ϒλ ( x) = m 4 ⋅ ∑ qk( λ )ϕ (mx − k ),

(7)

k∈Z 4

Formula (7) in frequency domain can be written as

ϒ λ (ω ) = Q ( λ ) ( z1 , z2 , z3 , z4 ) f (ω m), λ = 1, 2, (λ ) k

where the signal of sequence {q (λ )

, m 4 − 1.

}(λ = 1, 2,

, m − 1, k ∈ Z ) is

∑q

⋅ z1n ⋅ z2 n ⋅ z3n ⋅ z4 n .

Q ( z1 , z2 , z3 , z4 ) =

n∈Z

4

(λ ) n

4

1

(8)

4

2

3

4

(9)

Generation and Characteristics of Vector-Valued Quarternary Wavelets

45

A bivariate function ϕ ( x ) ∈ L (R ) is called a semiorthogonal one, if 2

4

ϕ (⋅), ϕ (⋅ − k ) = δ 0, k , n ∈ Z 4 .

(10)

We say G ( x) = {ϒ1 ( x), ϒ 2 ( x), , ϒ m4 −1 ( x)} is an orthogonal binary vector-valued wavelets according to the scaling function ϕ ( x) ∈ L2 (R 4 ) ,if they satisfy:

ϕ (⋅), ϒν (⋅ − k ) = 0 , ν ∈ Δ, k ∈ Z 4 ,

(11)

ϒ λ (⋅), ϒν (⋅ − n) = δ λ ,ν δ 0, n , λ , ν ∈ Δ, n ∈ Z 4

(12)

3 The Traits of Nonseparable Bivariate Wavelet Packs Denoting by H 0 ( x) = F ( x), H μ ( x) = Ψ μ ( x), H 0 ( x) = F ( x), (0) k

Q

(μ ) k

= Pk , Q

(μ ) k

=B

(0) k

, Q

= Pk Q

(μ ) k

H μ ( x) = Ψ μ ( x),

= B , μ ∈ Γ, k ∈ Z . Let us order S = 4 I v . (μ) k

4

For any α ∈ Z and the given vector-valued biorthogonal scaling functions G0 ( x) 4 +

and G0 ( x ) , iteratively define, respectively,

H α ( x) = H 4σ + μ ( x) = H α ( x) = H 4σ + μ ( x) =

∑ Q μ Hσ (4 x − k ),

(13)

∑Qμ

(14)

( ) k

k∈Z 4

( ) k

H σ (4 x − k ).

k∈Z 4

where μ ∈ Γ 0 , σ ∈ Z +4 is the unique element such that α = 4σ + μ , μ ∈ Γ0 holds. Lemma 1[4]. Let F ( x ), F ( x ) ∈ L2 ( R 4 , C v ). Then they are biorthogonal ones if and only if

∑ Fˆ (γ + 2kπ ) Fˆ (γ + 2kπ )

*

= Iv .

(15)

k∈Z 4

Definition 4. We say that two families of vector functions {H 4σ + μ ( x ), σ ∈ Z +4 , μ ∈ Γ 0 }

and {H 4σ + μ ( x), σ ∈ Z +4 , μ ∈ Γ 0 } are vector wavelet packets with respect to a pair of biorthogonal vector scaling functions H 0 ( x) and H 0 ( x) , respectively, where

H 4σ + μ ( x) and H 4σ + μ ( x) are given by (13) and (14), respectively. Taking the Fourier transform for the both sides of (13) and (14) yields, resp.,

H 4σ + μ (γ ) = Q ( μ ) (γ / 4) H σ (γ / 4), μ ∈ Γ 0 , H 4σ + μ (4γ ) = Q ( μ ) (γ ) H σ (γ ), μ ∈ Γ 0 , 1 Q ( μ ) (γ ) = 4 ∑ Qk( μ ) ⋅ exp{−ik ⋅ γ }, μ ∈ Γ 0 4 k∈Z 4

(16) (17) (18)

46

P. Luo and S. Wang

Q ( μ ) (γ ) =

1 44

∑Qμ

( ) k

k∈Z

⋅ exp{−ik ⋅ γ }, μ ∈ Γ 0 .

(19)

4

Lemma 2[7]. Assume that H μ ( x), H μ ( x) ∈ L ( R ) , μ ∈ Γ are pairs of biorthogonal vector-valued wavelets associated with a pair of biorthogonal scaling functions H 0 ( x) and H 0 ( x) . Then, for μ , λ ∈ Γ 0 , we have 4 n

2

∑ρ

∈Γ0

Q ( μ ) ((γ + 2 ρπ ) / 4)Q ( λ ) ((γ + 2 ρπ ) / 4)* = δ μ ,λ I v

(20)

Theorem 1. Assume that {H β ( x), β ∈ Z +4 } and {H β ( x), β ∈ Z +4 } are vector-

valued wavelet packets with respect to a pair of biorthogonal vector-valued functions

H 0 ( x) and H 0 ( x) , respectively. Then, for β ∈ Z +4 , μ , v ∈ Γ 0 , we have [ H 4 β + μ (⋅), H 4 β +v (⋅ − k )] = δ 0,k δ μ ,ν I v , k ∈ Z 4 .

(21)

Proof. Since the space R 4 has the following partition: R 4 = ∪ u∈Z ([0, 2π ]4 + 2uπ ) , and 4

([0, 2π ]4 + 2π u1 ) ∩ ([0, 2π ]4 + 2π u2 ) = Ø, where u1 ≠ u2 , u1 , u2 ∈ Z 4 ,then 1 [ H 4 β + μ (⋅), H 4 β +ν (⋅ − k )] = H 4 β + μ (γ ) H 4 β +ν (γ )* ⋅ exp{ik ⋅ γ }d γ 4 ∫R 4 (2π )

=

1 (2π )

4

∫

Rs

Q ( μ ) (γ / 4) H β (γ / 4) H β (γ / 4)*Q (ν ) (γ / 4)* eik ⋅γ d γ

2

= ( ) 4 ∑ ∫[0,2π ] + 2 kπ Q ( μ ) (γ ) H β (γ ) H β (γ )* ⋅ Q (ν ) (γ )* ei 4 k ⋅γ d γ π k ∈Z 4

4

=

1 (2π )

4

∫

[0,8π ]4

Q ( μ ) (γ / 4)Q (ν ) (γ / 4)* eik ⋅γ d γ =

1 (2π )4

∫

[0,2π ]4

δ μ ,v I u ei 4⋅γ d γ = δ 0, k δ μ , v I v .

This completes the proof of Lemma 1. Theorem 2. If {H β ( x), β ∈ Z + } and {H β ( x), β ∈ Z + } are vector wavelet packets 4

4

with respect to a pair of biorthogonal vector-valued scaling functions H 0 ( x) and

H 0 ( x) , then for any α ,σ ∈ Z +4 , we have [ Hα (⋅), H σ (⋅ − k )] = δα ,σ δ 0, k I v , k ∈ Z 4 .

(28)

Proof. When α = σ ,(28) follows by Lemma 3. as α ≠ σ and α , σ ∈ Γ 0 , it follows from Lemma 4 that (28) holds, too. Assuming that α is not equal to β , as well as at least one of {α ,σ } doesn’t belong to Γ0 , we rewrite α , σ as α = 4α1 + ρ1 , σ = 4σ 1 + μ1 , where ρ1 , μ1 ∈ Γ 0 . Case 1. If α1 = σ 1 , then ρ1 ≠ μ1 . (28) follows by virtue of (24), (25) as well as Lemma 1 and Lemma 2,i.e.,

Generation and Characteristics of Vector-Valued Quarternary Wavelets

(2π ) 4 [ H α (⋅), H σ (⋅ − k )] =

=∫

∫

R4

H 4α1 + ρ1 (γ ) H 4σ1 + μ1 (γ )* ⋅ exp{ik ⋅ γ }d γ

Q ( ρ ) (γ / 4){ ∑ H α (γ / 4 + 2uπ ) ⋅ H α (γ / 4 + 2uπ )* }Q ( μ ) (γ / 4)* ⋅ e ik ⋅γ d γ 1

[0,8 π ]

4

47

1

1

u∈ Z

=∫

[0,2π ]4

1

s

δ ρ , μ I v ⋅ exp{ik ⋅ γ }d γ = O. 1

1

Case 2. If α1 ≠ σ 1 , order α1 = 4α 2 + ρ 2 , σ 1 = 4σ 2 + μ 2 , where α 2 , σ 2 ∈ Z +s , and ρ 2 , μ2 ∈ Γ0 . Provided that α 2 = σ 2 , then ρ 2 ≠ μ2 . Similar to Case 1, (28) can be established. When α 2 ≠ σ 2 ,we order α 2 = 4α 3 + ρ3 , σ 2 = 4σ 3 + μ3 , where α 3 ,σ 3 ∈ Z +4 , ρ3 , μ3 ∈ Γ 0 . Thus, after taking finite steps (denoted by κ ), we obtain α κ ∈ Γ0 , and ρκ , μκ ∈ Γ0 . If α κ = σ κ , then ρκ ≠ μκ . Similar to the Case 1, (28) follows. If α κ ≠ σ κ , then it gets from (12)-(15) that

16π 4 [ H α (⋅), H σ (⋅ − k )] = ∫ 4 H α (γ ) H σ1 (γ )* ⋅ eik ⋅γ d γ R

= ∫ 4 H 4α1 + λ1 (γ ) H 4 β1 + μ1 (γ )* ⋅ exp{ik ⋅ γ }d γ = R κ κ γ γ γ γ = ∫ κ {∏Q ( ρ ) ( l )}{ ∑ H ακ ( l + 2uπ ) H σ κ ( l + 2uπ )*}{∏Q ( μ ) ( l )}* ⋅ eik ⋅γ d γ l

[0,2⋅4 ]4

l

4

l =1

u∈Z 4

4

4

l =1

4

γ κ γ )} ⋅ O ⋅{∏ l =1Q ( μ ) ( l )}* ⋅ exp{−ik ⋅ γ }d γ = O. l 4 4 l =1 4 Therefore, for any α , σ ∈ Z + , result (28) is established. =∫

κ

κ

([0,2⋅ 4 π ]

4

{∏Q ( ρl ) (

l

4 Conclusion The concept of biorthogonal vector four-dimensional wavelet packets was introduced. Three biorthogonality formulas with respect to these wavelet packets are obtained. The direct decomposition of space L2 ( R 4 ) n is proposed by constructing a series of subspaces of the wavelet wraps.

References 1. Telesca, L., et al.: Multiresolution wavelet analysis of earthquakes. Chaos, Solitons & Fractals 22(3), 741–748 (2004) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis: Nature of ε∞ Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Zhang, N., Wu, X.: Lossless Compression of Color Mosaic Images. IEEE Trans. Image Processing 15(16), 1379–1388 (2006) 4. Chen, Q., et al.: A study on compactly supported orthogonal vector-valued wavelets and wavelet packets. Chaos, Solitons & Fractals 31(4), 1024–1034 (2007) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal. 26(4), 1061–1074 (1995)

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6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Wei, Z.: The characteristics of orthogonal trivariate wavelet packets. Information Technology Journal 8(8), 1275–1280 (2009) 8. Chen, Q., Huo, A.: The research of a class of biorthogonal compactly supported vectorvalued wavelets. Chaos, Solitons & Fractals 41(2), 951–961 (2009)

A Kind of New Strengthening Buffer Operators and Their Applications Ran Han* and Zheng-peng Wu College of Science, Communication University of China, Beijing 100024, China [email protected], [email protected] Abstract. Under the axiomatic system of buffer operator in grey system theory, two new strengthening buffer operators are established, which have been based on strictly monotone function. Meanwhile, the characters and the inherent relation among them are studied. The problem that there are some contradictions between quantitative analysis and qualitative analysis in pretreatment for vibration data sequences is resolved effectively. A practical example shows theirs validity and practicability. Keywords: Grey system, Monotone increasing function, Buffer operator, Strengthening buffer operator, Fixed point.

1 Basic Concept Definition 1. Assume that the sequence of data representing a system’s behavior is given, X=(x(1),x(2),…,x(n)) then (1)X is called a monotonously increasing sequence if ∀k = 1,2, " , n − 1 ,

x(k ) < x(k + 1) . (2) X is called a monotonously decreasing sequence, if ∀k = 1,2, " , n − 1 ,

x(k ) > x(k + 1) .

(3) X is called a vibration sequence if k , k ′ ∈{1,2, " , n − 1} , x(k ) < x(k + 1) and

x(k ) > x(k + 1) . And M= max x ( k ) , m= min x (k ) , then M-m is called the amplitude of X. 1≤ k ≤ n

1≤ k ≤ n

Definition 2. Assume that X is a sequence of raw data, D is an operator worked on X, and the sequence, obtained by having D worked on X, is denoted as X=(x(1)d,x(2) d,…,x(n) d). Then D is called a sequence operator, and XD is the first order sequence worked on by the operator D. Sequence is referred to as operator. A sequence operator can be applied as many times as needed. It can obtain a second order sequence, even order sequence, they can be denoted as XD , " , XD . 2

r

Axiom 1. Axiom of Fixed Points. Assume that X is a sequence of raw data and D is a sequence operator, then D must satisfy x(n) d= x(n). *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 49–54, 2011. © Springer-Verlag Berlin Heidelberg 2011

50

R. Han and Z.-p. Wu

In the effect of the Axiom of Fixed Points which limit the sequence operator, x(n) in the raw data is never changed. Axiom 2. Axiom on Sufficient Usage of Information. When a sequence operator is applied, all the information contained in each datum x(k), (k=1,2,…,n)of the sequence X of the raw data should be sufficiently applied, and any effect of each entry x(k), (k=1,2,…,n) should also be directly reflected in the sequence worked on by the operator. The Axiom 2 limits any sequence operator which should be defined without the sequence of raw data and based on the information in the sequence we have kept. Axiom 3. Axiom of Analytic Representations. For any x(k)d, (k=1,2,…,n) can be described with a uniform and elementary analytic representation in x(1),x(2),…,x(n). The Axiom 3 requires procedures which the operator is applied to the raw data clearly, standardized, and as simple as possible, in order to calculate and makes calculation easier on the computer. Definition 3 All sequence operators, satisfying these three axioms, are called buffer operators, XD is called buffer sequence. Definition 4 Assume X is a sequence of raw data, D is an operator worked on X, when X is a monotonously increasing sequence, a monotonously decreasing sequence or a vibration sequence, if the buffer sequence XD increases or decreases more rapidly or vibrate with a bigger amplitude than the original sequence X, the buffer operator D is termed as a strengthening operator. Theorem 1 (1) When X is a monotonously increasing sequence, XD is a buffer sequence, then D is a strengthening operator ⇔ x( k ) d ≤ x ( k ) ( k = 1, 2,3,..., n ) ; (2)When X is a monotonously decreasing sequence, XD is a buffer sequence, then D is a strengthening operator ⇔ x( k ) d ≥ x( k ) ( k = 1,2,3,..., n) ; (3)When X is a monotonously vibration sequence and D is a strengthening operator, XD is a buffer sequence ,then

max x(k ) ≥ max x( k )d , min x(k ) ≤ min x( k )d . 1≤ k ≤ n

1≤ k ≤ n

1≤ k ≤ n

1≤ k ≤ n

That is, the data in a monotonously increasing sequence shrink when a strengthening operator is applied and data in a monotonously decreasing sequence expand when a strengthening operator is applied[1].

2 Study on a Kind of New Strengthening Buffer Operators Theorem 2. Assume X=(x(1),x(2),…,x(n)) is a sequence of raw data, x(k)>0, (k=1,2,…,n), fi is a strictly monotonic function and fi>0,i=1,2,…,n, gi is its inverse function, and XD1=(x(1)d1,x(2) d2,…,x(n) dn),

⎡ ⎛ f (x (k )) ⎞ n − k +1 ⎤ k = 1, " , n , ⎥, ⎟ x(k ) d 1 = g i ⎢ f i ( x(k ))⎜⎜ i f i (x (n )) ⎟⎠ ⎢ ⎥ ⎝ ⎣ ⎦ 1

when X is a monotonously increasing sequence, a monotonously decreasing sequence or a vibration sequence, D1 is a strengthening buffer operator.

A Kind of New Strengthening Buffer Operators and Their Applications

51

Proof: It is easily proved that D1 satisfies the three axioms of buffer operator, so D1 is a buffer operator. We prove that D1 is strengthening buffer operator. (1) When X is a monotonously increasing sequence, because 0≤x(k)≤…≤x(n) and fi is a strictly monotonic increasing function and fi>0,i=1,2,…,n, 0≤fi (x(k))≤…≤fi (x(n)) ,

[ (( (( )))) ] fi x k fi x n

1 n − k +1

[ (( (( )))) ]

≤ 1 , f i ( x(k ))

1 n − k +1

fi x k fi x n

≤ f i ( x(k )) .

And because gi is inverse function of fi,

[ (( (( )))) ]

x(k )d1 = g i ⎧⎨ f i ( x(k )) ⎩

1 n − k +1

fi x k fi x n

⎫ ≤ g [ f x(k )] = x(k ) . ⎬ i i ⎭

According to theorem 1, D1 is a strengthening buffer operator. (2)When X is a monotonously decreasing sequence, because x(k)≥…≥x(n)>0, fi is a strictly monotonic increasing function and fi>0,i=1,2,…,n,, fi (x(k))

≥…≥fi (x(n))>0,

[ (( (( )))) ]

1 n −k +1

fi x k fi x n

[ (( (( )))) ]

≥ 1 , f i ( x(k ))

fi x k fi x n

1 n − k +1

≥ f i ( x(k )) ,

and gi is inverse function of fi ,so

[ (( (( )))) ]

x(k )d1 = g i ⎧⎨ f i ( x(k )) ⎩

fi x k fi x n

1 n − k +1

⎫ ≥ g [ f x(k )] = x(k ) . ⎬ i i ⎭

According to theorem 1, D1 is a strengthening buffer operator. (2) When X is a vibration sequence, let x( k ) = max x(i ), x( h) 1≤i ≤ n

= min x (i ), 1≤ i ≤ n

∈{1,2, … (k)≥ (1),…, ( ) (h)≤ (1),…, ( ) (k)≥ ( ), (h)≤ ( ),

for i , n},we have x x x n ; x x x n ,because x x n x x n fi is a strictly monotonic increasing function, f i > 0 , f i ( x(k )) ≥ f i ( x(n )), f i ( x(h )) ≤ f i ( x (n )) ,

[ (( (( )))) ] ≥ 1, [ (( (( )))) ] ≤ 1 , f (x(k ))[ (( (( )))) ] ≥ f (x(k )) f (x (h ))[ (( (( )))) ] ≤ f ( x(h )) , and g is inverse function of f , therefore x(k )d = g ⎧⎨ f ( x(k ))[ (( (( )))) ] ⎫⎬ ≥ g [ f x(k )] = x(k ) , ⎩ ⎭ x(h )d = g ⎧⎨ f ( x(h ))[ (( (( )))) ] ⎫⎬ ≤ g [ f x(h )] = x(h ) ⎩ ⎭ 1 n − k +1

fi x k fi x n

fi x h fi x n

fi x k fi x n

i

1 n − k +1

i

,

1 n − k +1

fi x h fi x n

i

1 n − k +1

i

i

1

i

i

fi x k fi x n

1

i

i

fi x h fi x n

i

1 n − k +1

i

i

i

i

1 n − k +1

max{x(k )d 1 } ≥ max{x(k )} 1≤ k ≤ n

and

1≤ k ≤ n

min{x(k )d 1 } ≤ min{x(k )} .According to theorem 1, D1 is a strengthening

1≤ k ≤ n

1≤ k ≤ n

buffer operator.

X = ( x(1), x(2), " , x(n)) is a sequence of raw data, x(k ) > 0, k = 1,2," , n , f i is a strictly increasing monotonic function and f i > 0, i = 1,2, ", n , g i is its

Theorem 3. Assume

inverse function, and XD 2 = ( x(1)d 2 , x(2) d 2 , " , x( n)d 2 ) is its buffer sequence,

52

R. Han and Z.-p. Wu

⎡ f ( x (k )) n ⎛ f ( x(i )) ⎞ n − i +1 ⎤ ⎜⎜ i ⎟⎟ ⎥, k = 1, " , n , x( k )d 2 = g i ⎢ i ∑ n − k + 1 ⎢ ⎥ i = k ⎝ f i ( x (n )) ⎠ ⎣ ⎦ 1

when X is a monotonously increasing sequence or a monotonously decreasing sequence, D2 is a strengthening buffer operator.

D2 satisfies the three axioms of buffer operator, so D2 is a buffer operator. We prove that D2 is strengthening buffer operator. Proof: It is easily proved that

(1)When X is a monotonously increasing sequence, because 0≤x(k)≤…≤x(n)and fi is a strictly increasing monotonic function and

[ (( (( )))) ] ≤ 1 , f ( x(k )) 1 ( ( )) ( ( )) [ [ ≤ 1, ≤ f ( x (k )) , and ∑ ∑ ( ( )) ] ( ( )) ] n − k +1 n − k +1

f i > 0, i = 1,2," , n , 0 ≤ f i ( x(k )) ≤ " ≤ f i ( x(n )) , n

i =k

fi x i fi x n

n

1 n − i +1

i

i=k

fi x i fi x n

fi x k fi x n

1 n −k +1

1 n − i +1

i

because g i is inverse function of fi,

⎧ f ( x(k )) n f i ( x (i )) n −1i +1 ⎫ x(k )d 2 = g i ⎨ i ∑ fi ( x(n )) ⎬⎭ ≤ g i [ f i x(k )] = x(k ) . ⎩ n − k + 1 i =k According to theorem 1, D2 is a strengthening buffer operator.

[

]

We can follow the example of the proof of theorem 2, when X is a monotonously decreasing sequence, D2 is a strengthening buffer operator.

3 Case Study We take Per capita power consumption (Unit :kwh) for example to prove the effect of strengthening buffer operator in this paper on GM(1,1) prediction model. Per capita power consumption of China from 2000 to 2006 is chosen as a sequence of raw data (Table1). Table 1. Per capita power consumption(Unit: kwh)

Year Percapita power consumpti on

2000

2001

2002

2003

2004

2005

2006

132.4

144.6

156.3

173.7

190.2

216.7

249.4

At present, China is on economic development of the process of industrialization and more dependent on electric power. From 2000 to nowadays, China overcame the effects of Asian financial crisis, the government adopted a proactive fiscal policy and

A Kind of New Strengthening Buffer Operators and Their Applications

53

prudent monetary policy for economic growth, injecting vigor, cause the power demand increased sharply. Therefore, this article takes China's per capita power consumption of raw data sequence from 2000 to 2005 as modeling data, the data in 2006 as a model test data. Calculating per capita consumption growth power is as follows: 9.215%, 8.091%, 11.132%, 9.499, 13.933%, 15.090%, an annual average increase rate of 9.468%. We test the primary data sequence for quasi-smooth, when t ≥ 2003 , its smooth ratio is 0.401,0.313, 0.272, 0.246 which is in (0,0.5).Its smooth ratio is decreasing and satisfies quasi-smooth. Therefore a accumulation of the primary data sequence has quasi-exponential law. But it is clear that the former has a little slow growth rate, the latter has fast growth rate. Therefore, it is best to smooth the original data sequence to weaken the impact of the shock disturbance and highlight the laws of the data. Take

f i ( x ) = x 2 , g i ( x ) = x 0.5 , i = 1,2," , n to construct the buffer operator,

and apply the second order buffer operator which in this article to strengthen the raw data. Then we build the prediction model and compare with the raw data sequence (Table 2). The GM(1,1) model directly built by the raw data sequence without buffer operator is

xˆ (2000 + t ) = 1317.848e0.102t − 1185.448 . The GM(1,1) model built by the strengthening buffer operator sequence XD1 is

xˆ ( k + 1) = 654.7787e 0.1549 k − 544.7797 . The GM(1,1) model built by the strengthening buffer operator sequence XD2 is

xˆ ( k + 1) = 801.78e 0.139 k − 686.784 . Table 2. Case 3 GM(1,1) model

Sequence

X

Predictive value 236.831

Predictive relative error(%) 5.040

XD12

238.2672

4.53

XD22

241.23

3.28

From the table 2, all the predictive relative error of the strengthening buffer sequences which are applied by the second order buffer operator D1 and D2 are smaller than the predictive relative error of the raw data sequences in the model. The predictive relative error applied with D2 is smaller, and its predictor is 241.23 and closer to the observation 249.4. Its one step predictive error is only 3.28%, namely the predictive accuracy is the highest.

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4 Conclusion Based on the recent literature, two new strengthening buffer operators are established, which have been based on strictly monotone function. The example shows that the predictive accuracy increases by the strengthening buffer sequences which are applied by the second order buffer operator D1 and D2 .

References 1. Liu, S.-f., Dang, Y.-g., Fang, Z.-g.: Grey system theory and its application. Science Press, Beijing (2004) 2. Liu, S.-f.: The three axioms of buffer operator and their applications. The Journal of Grey System 3(1), 39–48 (1991) 3. Liu, S.-f.: Buffer operator and its application. Theories and Practices of Grey System 2(1), 45–50 (1992) 4. Liu, S.-f.: The trap in the prediction of a shock disturbed system and the buffer operator. Journal of Huazhong University of Science and Technology 25(1), 25–27 (1997) 5. Dang, Y.-g., Liu, S.-f., Liu, B., et al.: Study on the strengthening buffer operators. Chinese Journal of Management Science 12(2), 108–111 (2004)

Infrared Target Detection Based on Spatially Related Fuzzy ART Neural Network BingWen Chen1, WenWei Wang1, and QianQing Qin2 1

College of Electronic Information, Wuhan University, 430079 Wuhan, China 2 State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, China [email protected]

Abstract. In order to solve the ghosts, the halo effect as well as the lower signal-to-noise ratio problems more effectively, this paper presents a spatially related fuzzy ART neural network. We introduce a laterally-inspirited learning mode into the background modeling stage. At first, we combine the regionbased feature with the intensity-based feature to train the spatially related fuzzy ART neural network by the laterally-inspirited learning mode. Then two spatially related fuzzy ART neural networks are configured as master-slave pattern to build the background models and detect the infrared targets alternately. Experiments have been carried out and the results demonstrate that the proposed approach is robust to noise, and can eliminate the ghosts and the halo effect effectively. It can detect the targets effectively without much more post-process. Keywords: infrared target detection, laterally-inspirited learning mode, spatially related fuzzy ART neural network, master-slave pattern.

1 Introduction Visual surveillance is a hot topic in computer vision. In recent years, thanks to the improvement of infrared technology and the drop of its cost, the thermal imagery has been widely used in the surveillance field. In comparison with visible imagery, adopting the thermal imagery has many benefits, such as all-day working ability, robust to light change, no shadow, etc. However, the thermal imagery has its own difficulties, such as a lower signal-to-noise ratio, a lower resolution, an uncalibrated white-black polarity change as well as the “halo effect” which appears around the very hot or cold objects [1]. The comparison between visible and thermal imagery can be learned from Lin’s review [2]. Many detection approaches have been proposed for thermal imagery. Some approaches base on the target’s appearance [3-5]; some approaches base on the target’s motion [1, 6]. A fuzzy ART neural network approach is proposed to detect the targets in our previous works [7]. It is capable of learning the total number of categories adaptively and stable, but it has some shortages. It does not take advantage of the strong spatial correlation of thermal imagery. It only exploits the time domain information, and S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 55–61, 2011. © Springer-Verlag Berlin Heidelberg 2011

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utilizes only one simple feature to build the background models; moreover its background model updating strategy is not comprehensive. In this paper, we exploit and combine the spatial information with the temporal information, and propose a novel infrared target detection approach based on spatially related fuzzy ART neural network. The remainder of this paper is described as follows: Sec. 2 introduce the laterally-inspirited learning mode and the master-slave working pattern, and present the detection approach comprehensively. The experimental evaluation of our approach is described in Sec. 3. Finally Sec. 4 includes conclusions and further research directions.

2 The Spatially Related Fuzzy ART Neural Network The infrared target detection approach using spatially related fuzzy neural network can be divided into two stages: background modeling stage; target detection and model updating stage. The whole detection schema is the same for each location of infrared image. To facilitate the interpretation, we present the approach for one location pixel in the following. 2.1 Background Modeling Stage Several frames ahead (Ft, t=0…N) are allocated to build the background model, so we can obtain the sample data like formula 1. [ f 0 ( i , j ), ..., f t ( i , j ), ..., f N ( i , j )] .

(1)

The background modeling stage includes two sub-stages: initial background model sub-stage and build background model sub-stage. Initial Background Model Sub-stage. This stage is focused on the fuzzy ART neural network initialization and sample data filter out. A fuzzy ART neural network is initialized and trained with the sample data. Taking advantage of the strong spatial correlation of infrared image, we combine the regionbased feature that the median of pixel’s neighbor with the intensity-based feature that the pixel’s own intensity to train the fuzzy ART neural network (like formula 3). Pt (i, j ) = [ f t (i, j ); Median{ f t (i ± k , j ± k ) | k = 0,1,..., ( M − 1) / 2}] .

(2)

P ( i , j ) = [ P0 (i , j ),..., Pt ( i , j ),..., PN ( i , j )] .

(3)

Where, M denotes the size of pixel’s neighbor, P (i,j) denotes the input feature vector. After training, we can obtain each category’s information, such as category’s appearing frequency and each sample data’s category, and then filter each category out according to its properties. If a category belongs to the background, then its appearing frequency must be bigger than others or a threshold value, so we set a threshold θ, if the category’s frequency larger than θ, then this category belongs to background, or else, this category belongs to non-background and must be deleted. In the same way, the sample data are filtered out according to its category. By means of

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filtering, the proposed approach can suit for the real situation that the foreground objects appear during the background modeling period. Build Background Model Sub-stage. This stage is focused on the fuzzy ART neural network retrained and background model refined. Owing to the thermal imagery mechanism, the thermal image has a strong spatial correlation in a local region, so the background models should also reflect this property. In order to exploit and fuse the spatial and temporal correlation effectively, we introduce the laterally-inspirited learning mode as follow: According to the category of Pt(i,j), for each location, its initialized fuzzy ART neural network and those initialized fuzzy ART neural networks in its neighbor are retrained, like formula 4.

⎧ {FART(i ± k, j ± k) | k = 0,1,...,(R −1) / 2} are retrained with P (i, j), ⎨ ⎩nothing, t

if Pt (i, j) belongs to background if Pt (i, j) belongs to foreground.

(4)

Where, R denotes the size of laterally-inspirited region, FART (i,j) denotes the fuzzy ART neural network of location (i,j). The fuzzy ART neural network is retrained by the laterally-inspirited learning mode can associate the background models with the spatial information. Furthermore, it combines with the region-based feature can exploit the spatial correlation information effectively, and make the detection more stable and robust to noise. We name this type of neural network as spatially related fuzzy ART neural network. 2.2 Target Detection and Model Updating Stage The approach in reference [7] only updates the background model when the current pixel belongs to the background model, but do not consider the updating method when the current pixel belongs to the non-background model. Therefore, when this approach works for a long time, the background model may be not fit the actual situation, and the false objects, often referred to as ghosts [8] will be turn out. For example, the still background objects start moving, or the moving foreground objects stop for a long time. These may be lead to ghost appearance, and the performance may also worsen. In order to solve this problem, two spatially related fuzzy ART neural networks are configured as master-slave pattern to detect the infrared targets alternately. Here, we suppose that: A, B denote the two spatially related fuzzy ART neural networks; T denotes the alternation time interval; Wj denotes the weights of category j; β denotes the learning rate parameter. Then the target detection and model updating strategy as follow: 1) In the background modeling stage, A is established as the master network and trained with the sample data follow the strategy in background modeling stage; 2) In target detection stage, A is utilized to detect the targets. If the new input pixel can find the matched category and the resonance happen, then the corresponding category’s weights are updated like formula 5. At the same time, B is established as the slave network and trained with current data follow the strategy in background modeling stage.

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W jt+ 1 = β ( P t ( i , j ) ^ W jt ) + ( 1 -β ) W jt .

(5)

3) When the alternation time interval T passes, the slave network B turn to be master network and begin to detect the targets, and the master network A is reset and established as slave network. When each alternation time interval T passes, the master network and the slave network swap.

3 Experimental Results To evaluate the performance of the proposed approach, we tested the approach with the OTCBVS Benchmark Dataset Collection [9]. Some example images of five original thermal sequences are shown in the first row of Fig. 1. We can see from these images that the thermal images have a lower resolution; the “halo effect” appears around objects; the target’s temperature is not always higher than environment’s. In our experimental evaluation, all detection results obtained by any approach are the raw detection results without the post-processing. In order to quantitatively measure the performance of the detection results, we manually segment the person regions and take it as the ground truth to compare with the automatic detection results. Some silhouettes segmented are shown in the second row of Fig. 1. We compare the spatially related fuzzy ART neural network (SRFART) with three other approaches: the single weighted Gaussian approach (SWG) [1]; the codebook approach (CB) [10] and the fuzzy ART neural network (FART) [7]. The single weighted Gaussian approach is an improved version of single Gaussian model. The codebook approach is one of prominent detection approaches. About parameter setting, for single weighted Gaussian approach, we set the stand deviation σˆ = 5 , the detection threshold T=8; for codebook approach, we set the light control parameters α=0.7, β=1.3; for FART approach and the proposed approach, we set the choice parameter α=0, the learning rate parameter β=1, the vigilance parameter ρ=0.85 for seq.1, 2, 5, ρ=0.75 for seq.3, 4; for the proposed approach, we set the alternation time interval T=10s, the size of pixel’s neighbor M=3, the size of laterallyinspirited region R=3. We show the silhouette results obtained by each detection approaches on representative images (from the five sequences) in Fig. 1. From the third row, we can see that the detection results obtained by codebook approach have much noise, and even exist the ghosts like the seq. 4, 5. From the fourth row, we can see that the detection results obtained by single weighted Gaussian approach also have much noise, and the halo effect is very clear which severely impairs the detection results like the sequences 3, 4. From the fifth row, we can see that the detection results obtained by fuzzy ART neural network approach have some noise, like seq. 1, and cannot detect the targets effectively when the contrast between target and environment is low, like seq. 5. In contrast, from the last row, we can see that the detection results obtained by the proposed approach have less noise and do not exist the ghosts; the proposed approach is able to detect most portions of people’s bodies even when the contrast between target and environment is low; the proposed approach can eliminate most of halo and extract the people effectively.

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Fig. 1. Visual comparisons of detection results of the four approaches across different images

Fig. 2. Visual comparison of detection results between whether to utilize the master-slave pattern

Fig. 2 shows the visual comparison of detection results between whether to utilize the master-slave pattern. Image (a) in Fig. 2 is one example image of the background sample frames. We can see that there is a person standing in front of door and the door is open. After a while, the person goes into the house and the door is closed, and we can see it from the image (b). Image (c) shows the ground truth detection result for image (b). From the image (d) we can see that: when we do not utilize the masterslave pattern, the detection result has two ghosts (false object) obviously. In contrast,

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when we do utilize the master-slave pattern, the background model can reflect the real situation as accurately as possible, and can eliminate the ghosts effectively. In order to evaluate the detection results objectively and quantitatively, the F1 metric [8] is adopted. The F1 metric, also known as Figure of Merit or F-measure, is the weighted harmonic mean of precision and recall, as defined in formula 6. Recall, also known as detection rate, gives the percentage of detected true positives as compared to the total number of true positives in the ground truth; Precision, also known as positive prediction rate, gives the percentage of detected true positives as compared to the total number of detected items. Higher value of F1 means a better detection performance. F1=

2 * R e c a ll* P r e c is io n R e c a ll+ P r e c is i o n

(6)

The F1 measurements of each approach for five sequences in the Fig. 1 are shown in table 1. Comparing the measurements in table 1, we can see that: Due to the presence of halo and ghosts, the F1 values of single weighted Gaussian and codebook are poor, and due to the lower contrast between target and environment, the F1 values of the fuzzy ART neural network is low, like seq. 5. In contrast, the spatially related fuzzy ART neural network approach performs well all the same even when the halo and ghosts exist. Table 1. The F1 measurements of four approaches for five sequences Detection approach SWG CB FART SRFART

Seq.1 0.709 0.678 0.702 0.772

Seq.2 0.668 0.600 0.815 0.858

Seq.3 0.593 0.655 0.829 0.834

Seq.4 0.528 0.536 0.833 0.881

Seq.5 0.626 0.343 0.566 0.756

Generally speaking, the proposed approach is robust to noise and can reflect the real situation as accurately as possible. It can eliminate the halo and the ghosts effectively and detect the targets effectively without much more post-process.

4 Conclusions We presented a novel infrared target detection approach based on spatially related fuzzy ART neural network. It associates the background models with the spatial information by the laterally-inspirited learning mode, and it reflects the real situation as accurately as possible by adopting the master-slave working pattern. The approach can detect targets more stable and robust to noise. It can eliminate the halo and ghosts effectively and detect the targets effectively without much more post-process. In the implementation of the proposed approach, we do not take account of the processing speed. In the end, the detection speed of the proposed approach is only 2 fps. So we are going to study how to speed the model up in the future.

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Acknowledgments. This research was supported in part by the Natural Science Foundation of Hubei Province of China No. 2009CDA141.

References 1. Davis, J.W., Sharma, V.: Background subtraction in thermal imagery using contour saliency. International Journal of Computer Vision 71, 161–181 (2007) 2. Lin, S.-S.: Review: Extending visible band computer vision techniques to infrared band images. Technical Report, University of Pennsylvania (2001) 3. Li, Z., Bo, W., Ram, N.: Pedestrian detection in infrared imaged based on local shape features. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, Minneapolis (2007) 4. Kai, J., Michael, A.: Feature based person detection beyond the visible spectrum. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 30–33. IEEE Press, Miami (2009) 5. Stephen, O.H., Ambe, F.: Detecting People in IR Border Surveillance Video Using Scale invariant image moments. In: Proceedings of SPIE, pp. 73400L-1–6. SPIE, Orlando (2009) 6. Fida, E.B., Thierry, B., Bertrand, V.: Fuzzy Foreground Detection for Infrared Videos. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1–6. IEEE Press, Anchorage (2008) 7. Chen, B., Wang, W., Qin, Q.: Infrared target detection based on Fuzzy ART neutral network. In: The Second International Conference on Computational Intelligence and Natural Computing, pp. 240–243. IEEE Press, Wuhan (2010) 8. Lucia, M., Alfredo, P.: A self-organizing approach to background subtraction for visual surveillance applications. IEEE Transactions on Image Processing 17, 1168–1177 (2008) 9. Object Tracking and Classification in and Beyond the Visible Spectrum, http://www.cse.ohio-state.edu/otcbvs-bench/ 10. Kyunqnam, K., Chalidabhonqse, T.H., David, H., et al.: Real-time foreground-background segmentation using codebook model. Image Segmentation 11, 172–185 (2005)

A Novel Method for Quantifying the Demethylation Potential of Environmental Chemical Pollutants Yan Jiang1,2,3 and Xianliang Wang2,* 1

College of Oceanography and Environmental Science, Xiamen University, Xiamen, Fujian 361005, People’s Republic of China 2 State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, People’s Republic of China Tel.: +86-10-84916422; Fax: +86-10-84916422 [email protected] 3 College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875, People’s Republic of China Abstract. We developed a novel method to quantify the demethylation epigenetic toxicity of pollutants. A hyper-methylated pEGFP-C3 plasmid eukaryotic expression vector was constructed and used to evaluate the epigenetic toxicity of aquatic pollutants samples from polluted coastal waters of Tianjin, China. The methylated pEGFP-C3 plasmid was transfected into HepG2 cells and incubated with 5-aza-2-deoxycytidine at various concentrations. The HepG-2 cell line reporter gene vector was used to assess the epigenetic toxicity of heavy metal extracts from polluted marine waters, and shellfish samples. Results indicated that the demethylation ability of 5-aza-dC at doses between 0.0008 and 0.1 µM could be quantitatively detected. Nine of the 19 aquatic samples showed strong demethylation ability at values between 0.0064 and 0.0387 µM 5-AZA equivalents. A GFP reporter gene vector with a hypermethylated CMV promoter was constructed, and a relatively sensitive response relationship between GFP gene expression and 5-AZA dose was observed, providing a novel method for quantifying the demethylation ability of pollutants. Keywords: Demethylation, Epigenetic toxicity, Cellular test system, Enhanced green fluorescent protein, Aquaculture.

1 Introduction Before chemical compounds can be used, evaluation of their safety is essential. Currently, assessment of contamination of genetic material, such as DNA mutation, focuses mainly on detecting direct damage. However, many pollutants that may be deemed safe by existing safety evaluation protocols can have indirect effects. For example, pollutants may cause DNA methylation and activate other epigenetic mechanisms that can lead to slight changes in long-term biological traits but may not cause genetic mutations, chromosomal aberrations, and other genetic damage [1; 2] *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 62–71, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Low-dose pollutant exposure can cause DNA methylation changes, and long-term, mild, recurring methylation changes can begin the process of damaging health. Thus, developing a tool to assess indirect damage is essential. [3; 4] Currently, research of the epigenetic toxicity of environmental pollutants is in its infancy. [5] Some researchers have proposed the use of serum biochemical analysis, histopathological evaluation, and analysis of the DNA methylation status in healthy animals treated with chronic and/or sub-chronic pollutant exposure in vivo. [6; 7] However, such a detection system has not been developed, and there is an urgent need to establish a stable and practical detection method to evaluate the epigenetic toxicity of pollutants. [8; 9] Our approach to quickly evaluate epigenetic toxicity of pollutants was to use the non-toxic enhanced green fluorescent protein (EGFP) to build a screening system, which we call quantifying the demethylation potential (QDMP) . The basic principles of the system are as follows: DNA methylase Mss.I was used to artificially modify commercial green fluorescent protein plasmid (EGFP) in vitro so that the EGFP gene promoter was highly methylated. [10] The methylated EGFP plasmid was transfected into the human hepatoma cell line HepG-2, and successfully transfected HepG-2 cells were selected through several rounds of screening of plate cultures. [11] The selected HepG-2 cells that contained the methylated EGFP plasmid were used as the target and confirm the demethylation matter arsenate, hydralazine as a positive control. Next, the heavy metals Cd and Ni, atmospheric particulate matter extracts, and contaminated shellfish samples extracts in a gradient of doses were tested using the screening system. [12; 13; 14] For each pollutant type, gene promoter methylation, cell expression of EGFP mRNA, and green fluorescence intensity of EGFP in cells were measured to establish a linear relationship between these parameters and pollutant dose. In this way, the level of EGFP gene promoter methylation was linked to the level of cell green fluorescence intensity, so that the former could be calculated from the latter. Thus, the lower the level of methylation of the EGFP gene promoter of cultured cells, the stronger the green fluorescence. [15] When pollutants and HepG-2 cells transfected with hypermethylated pEGFP-C3 were co-cultured, those with a strong DNA demethylation function exhibited significantly enhanced green fluorescence; such pollutants were considered to have low-methylation epigenetic toxicity. [16] In contrast, the lack of a significant increase in green fluorescence was indicative of weak DNA demethylation potential, and such compounds were deemed to have low-methylation epigenetic toxicity (Fig. 1).

Fig. 1. Chemical contaminants demethylation principles of epigenetic toxicity. A: Positive test substance, B: control.

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2 Materials and Methods 2.1 Preparation of the Methylated C3 Plasmid DNA (500 ng) digested with the restriction enzymes MspΙ and HpaΙΙ was treated with sodium bisulfite as previously reported (Gonzalgo, 2002; Xianliang, 2006). [17] 2.2 Cell Culture and C3 Plasmid Transfection The human liver cancer cell line HepG-2 was purchased from the China Type Culture Collection (Chinese Academy of Medical Sciences, Beijing, China) and grown in DMEM supplemented with 10% fetal bovine serum (FBS; JRH Bioscience, San Antonio, TX, USA) and 1% NEAA (Chinese Academy of Medical Sciences). A 599 kb CMV promoter of the pEGFP-C3 plasmid was transfected into HepG-2 cells using the FuGENE HD transfection reagent (F. Hoffmann-La Roche Ltd, Basel, Switzerland). This reagent (3, 4, 5, 6, or 7 μl) was directly pipetted into the medium containing the diluted pEGFP-C3 DNA (0.02 μg/μl) without allowing contact with the walls of the plastic tubes. The transfection reagent:DNA complex was incubated for 15 min at room temperature, and then the transfection complex was added to the cells in a drop-wise manner. The wells were swirled to ensure distribution over the entire plate surface. Cell growth was best and the fluorescence was brightest when 7 μl of the transfection reagent were used. 2.3 Treatment with 5-aza-dC Cells were seeded at a density of 3×105 cells/10 cm dish on day 0. On day 1, the medium was changed to one containing 5-aza-dC (Amresco Co Ltd, Amresco, ,USA), which was freshly dissolved in PBS and filtered through a 0.2μm filter. On day 4, cells were harvested and genomic DNA was obtained by serial extraction with phenol/chloroform and ethanol precipitation. Total RNA was extracted by ISOGEN kit (QIAGEN Co Ltd, Germany) HepG-2 cells, into which the hypermethylation EGFP-C3 plasmid gene had been introduced by homologous recombination, were exposed to heat at 37 °C for 6 h on days 2, 3, and 4 because this treatment effectively induced higher expression of hypermethylated EGFP-C3 mRNA. 2.4 Quantification of Methylation of the CMV Promoter In the next step, competent bacteria were prepared using E. coli strain DH5α. After the PCR product was purified, it was linked with the pGEM2T vector, transformed into the competent bacteria, and screened via blue-white screening. The product was separated by 1.5% agarose gel electrophoresis and photographed using a gel imaging system camera. Positive clones were screened by PCR amplification, and bacteria were cultured with shaking at 37 °C, and confirmed using universal primer T7 and SP6 sequencing by the Beijing Genomics Institute of Bacteria Biotechnology Company.

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2.5 Relative Quantification of CMV Promoter by Real-Time PCR To determine the quantitative PCR amplification efficiency, a PCR standard curve was generated. Samples of extracted cDNA were used to create a series of solutions representing 1/8, 1/4, 1/2, 1, and 1.5 times the cDNA content of β1, β2, and β actin cDNA, and these samples were analyzed using TaKaRa's sybrr premix Ex Taq™ quantitative , (TaKaRa' Ltd, Tokyo,Japan) PCR kit. In a 12.5 μl reaction system, in which the first three times higher than the concentration of cDNA diluted liquid samples, the following components (1 μl) were added. Components are composed of 1.5 times the liquid content (1.5 μl) is added, adding sybr quantitative PCR and reagent mixture (6.25 μl), the upstream and downstream primer mix solution (0.25 μl), the final complement to 12.5 μl with additional ultrapure water of sterilization. The PCR reaction conditions were as follows: predenaturation at 94°C for 10 s; denaturation at 94 °C for 45 s; annealing at 57 °C for 45 s; extension at 72 °C for 45 s; 95 °C for 1 min post-production thermal melting point curve to determine the amplification product specificity. Real-time PCR analysis was performed using a Stratagene MX3100 (USA). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used to normalize the mRNA expression levels. Primer sequences were as follows: EGFP-C3, 5'TAATGGGAGTTTGTTTTGGTATT-3' (sense), 5'-TTA TAC TCC AAC TTA TAC CCC AAA A-3' (antisense); and GAPDH, 3'-AGGTGAAGGTCGGAGTCAACG-3' (sense), 5' -AGGGGTCATTGATGGCAACA-3' (antisense). For both genes, PCR was performed for 40 cycles with annealing at 60 °C. Primer sequences and PCR conditions for other genes have been reported. 2.6 Detection of EGFP Protein by Fluorescent Imaging and Flow Cytometry Prior to flow cytometry and fluorescent imaging analysis, cells were washed with PBS and fixed with 4% paraformaldehyde. Cells were assayed using a Beckman Coulter Altra flow cytometer. Cells were placed into 24-well. After cells digestion, adding 1 ml PBS puff uniform each sample was placed into a 1.5 ml tube and centrifuged at 2000 g to remove the supernatant. Next, 1 ml PBS was added, followed by washing and centrifugation. 1 ml PBS re-suspended cell pellet, gently puff uniform, through 300 mesh filter to the stream-specific tube, into flow cytometry and to detect positive EGFP fluorescent percentage. 2.7 Analysis of Environmental Samples Using the QDMP Fish and shellfish samples were collected from the coast of Tianjin and washed, dried, and digested as previously reported (C. Brunori 2006) [18] Laid in Tianjin coastal sampling sites from north to south, a total of eleven sampling points, including two breeding base for seawater samples, seven samples for the marine capture fishing port, two sampling points for the seafood wholesale market, are important local sea Product supply base. Representative to collect the local residents like to eat fish, shellfish, eight varieties, a total of forty samples of the same species in each location, as close to the size of individual samples collected. For each sample type, the digestion solution was transferred carefully to a 1.5 ml polypropylene centrifuge tube. The sample was adjusted to a concentration of 1 g/L, and the test liquid was assayed for HepG-2 cell EGFP green fluorescence using the QDMP.

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3 Results and Discussion 3.1 Preparation of Methylated C3 Plasmid Unmethylated plasmids that were digested with HpaΙΙ and MspΙ and methylated plasmids digested with MspI exhibited the "smearing" phenomenon on gels, whereas methylated plasmids digested with HpaΙΙ showed a single band, suggesting the plasmid that treatment by methylation in the methylation status. 3.2 Exposure Optimization To establish a sensitive detection system, we first searched for an endogenous methylated CMV promoter in HepG2 cells that would show a sensitive response to 5AZA-dC. The CMV promoter of pEGFP-C3 was found to be methylated in HepG2 cells, and no mRNA expression was detected by RT-PCR before the addition of 5AZA-dC. By treating cells with very low doses (0.02–0.1 μM) of 5-aza-dC for 30 h, expression of pEGFP-C3 was restored. Next, expression levels were quantitatively analyzed by quantitative real-time RT-PCR, and CMV of pEGFP-C3 was found to be sensitively and abundantly expressed. 3.3 The Demethylation Potential of 5-aza-dC and Its Effect on EGFP Expression Methylation of the CMV promoter. The sequencing results were compared with the sequence of the C3 plasmid EGFP gene CpG island DNA from the GenBank database. Our sequence showed no mutation and the CpG cytosines were not modified by sodium bisulfite; these results indicated that the HepG2 cell lineC3 plasmid EGFP gene sub-CpG islands were methylated. Figure 2 shows

Fig. 2. Representative treated with sodium bisulfite sequencing group and the untreated group. Note: the picture in the sequence of the nine target sites in the CG, the figure shows the sites of which three from the methylation sites, six loci from the non-methylated sites; the chart below shows nine loci in the methylation status of all.

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are presentative sequence diagram and pattern of methylation, which showed that methylation of plasmid construction management is better, the plasmid EGFP gene promoter methylation after treatment with 90.4% of CG sites was methylated, and hypermethylation status of the EGFP gene promoter was quantitatively expressed. Relative quantification of EGFP expression. Quantitative real-time PCR detection results map: real-time fluorescence detection of fluorescence were displayed all sorts of quality control within the 22 cycles are significantly enhanced, showing all sorts of quality control have been good amplification. The fluorescence signal was stable, and a moderate elevation gradient was observed (Fig. 3). Real-time quantitative PCR results showed that the EGFP expression vector and the relative amount of 5-aza-dC exhibited a good dose-response relationship: y = 37.022x + 0.3087; R2 = 0.9821.

Fig. 3. Real-time quantitative PCR detection of cell sample results and dissolution curves of PCR products

Fluorescence of the EGFP protein. An obvious fluorescence gradient was detected in samples cultured with different doses of 5-aza-dC for 30 h; as the 5-aza-dC dose increased, the fluorescence intensity also increased. Flow cytometry results revealed a

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good linear relationship between the 5-aza-dC dose gradient and the mean fluorescence intensity :y = 10.402x + 6.0334; R2 = 0.829. This result shows that eukaryotic cells containing the green fluorescent protein gene vector exhibit a methylation-sensitive response relationship. The intensity of cellular green fluorescence can be used as an indicator of the presence of certain pollutants. [18] 3.4 Performance of the QDMP The sensitivity of the assay system was tested by adding various doses of 5-aza-dC to it. Demethylation of the promoter CMV of pEGFP-C3 was clearly observed at doses of 0.1μM or higher. Furthermore, fluorescence intensity was induced in a dose-dependent manner. We also examined the appearance of green fluorescence before and after the addition of 5-aza-dC. Under a fluorescence microscope, significant fluorescence was observed in the cytoplasm after the addition of 0.0008 μM of 5-aza-dC.

Fig. 4. Green fluorescent flow cytometry results

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3.5 The Application of QDMP for Aquatic Sampling To aquatic mixture for detection, according to the above method based on fluorescence flow cytometry to the relationship between methylation capacity equation, there are eight positive, obtained demethylation potential of the port of Tianjin Tanggu is strongest, equally 8 times the minimum concentration of 5-aza-dC dose toxicity. The epigenetic toxicity of polluted marine samples collected from the coast of Tianjin was evaluated based on the HepG-2 cell line reporter gene vector (i.e., the QDMP). The heavy metal extracts from aquatic samples were prepared and then cocultured with the test system. The demethylation potential of the samples was quantified relative to the corresponding equivalent of 5-aza-dC. EGFP fluorescence was quantified using microscopy. Demethylation by 5-aza-dC could be successfully detected in a quantitative manner at doses between 0.0008 and 0.1µM. Nine of the 19 aquatic samples had a relatively strong demethylation ability, with values ranging from 0.0064 to 0.0387µM 5-aza-dC equivalents. (Fig. 4)

4 Conclusions A system to assay for demethylating agents was established using the promoter CMV of the plasmid pEGFP-C3. To our knowledge, this is the first assay system that uses an endogenous CMV promoter. Methylation stability is high for endogenous sequences , and CGIs(CpG islands)in promoter regions have higher fidelity than those outside [19]. Mechanisms involved in the maintenance and monitoring of the methylated status of CGIs are expected to function well for the promoter CMV of the plasmid pEGFP-C3. Therefore, accurate estimation of epimutagens should be possible with this system. To establish a sensitive detection system, it was necessary to use a methylated promoter CMV that responds to low doses of demethylating agents (i.e., 5-aza-dC). In this study, we used the CMV promoter of the plasmid pEGFP-C3 because our recent studies [20] identified it as one that met the requirements. The CMV was demethylated by 5-AZA-dC at doses as low as 0.01 μM in parental HepG2 cells. This represents high sensitivity, considering that laboratory use of 5-aza-dC is between 0.1 and 10 μM. Demethylation of the CMV and expression of the introduced EGFP were observed after addition of 5-aza-dC at doses of 0.1 μM or higher. Fluorescence of the EGFP product was detected by fluorescence microscopy after addition of 1 μM 5AZA-dC. In summary, we established a detection system for demethylating agents using an endogenous promoter CMV; this system is expected to allow accurate detection of epimutagens. Acknowledgements. This work was supported by the National Nature Science Foundation of China(No. 20907047) and National Nonprofit Institute Research Grant of CRAES (No. 2008KYYW05).

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References 1. Eriksen, T.A., Kadziola, A., Larsen, S.: Binding of cations in Bacillus subtilis 2.

3. 4. 5. 6. 7. 8.

9. 10. 11. 12. 13. 14. 15. 16. 17.

18.

phosphoribosyldiphosphate synthetase and their role in catalysis. Protein Sci. 11, 271–279 (2002) Zoref, E., Vries, A.D., Sperling, O.: Mutant feedback-resistant phosphoribosylpyrophosphate synthetase associated with purine overproduction and gout. Phosphoribosylpyrophosphate and purine metabolism in cultured fibroblasts. J. Clin. Invest. 56, 1093–1099 (1975) Becker, M.A., Smith, P.R., Taylor, W., Mustafi, R., Switzer, R.L.: The genetic and functional basis of purine nucleotide feedback-resistant phosphoribo sylpyro phosphate synthetase superactivity. J. Clin. Invest. 96, 2133–2141 (1995) Reichard, J.F., Schnekenburger, M., Puga, A.: Long term low-dose arsenic exposure induces loss of DNA methylation. Biochem. Biophys. Res. Commun. 352, 188–192 (2007) Olaharski, A.J., Rine, J., Marshall, B.L., et al.: The flavoring agent dihydrocoumarin reverses epigenetic silencing and inhibits sirtuin deacetylases. PLoS Genet. 1(6), e77 (2005) Birnbaum, L.S., Fenton, S.E.: Cancer and developmental exposure to endocrine disruptors. Environ. Health Perspect. 111, 389–394 (2003) Salnikow, K., Zhitkovich, A.: Genetic and epigenetic mechanisms in metal carcinogenesis and cocarcinogenesis: nickel, arsenic, and chromium. Chem. Res. Toxicol. 21, 28–44 (2008) Tang, W.Y., Newbold, R., Mardilovich, K., et al.: Persistent hypomethylation in the promoter of nucleosomal binding protein 1 (Nsbp1) correlates with overexpression of Nsbp1 in mouse uteri neonatally exposed to diethylstilbestrol or genistein. Endocrinology 149, 5922–5931 (2008) Reik, W., Dean, W., Walter, J.: Epigenetic reprogramming in mammalian development. Science 293, 1089–1093 (2001) Bombail, V., Moggs, J.G., Orphanides, G.: Perturbation of epigenetic status by toxicants. Toxicol. Lett. 149, 51–58 (2004) Feil, R.: Environmental and nutritional effects on the epigenetic regulation of genes. Mutat. Res. 600, 46–57 (2006) Wu, C., Morris, J.R.: Genes, genetics, and epigenetics: a correspondence. Science 293, 1103–1105 (2001) Feinberg, A.P., Ohlsson, R., Henikoff, S.: The epigenetic progenitor origin of human cancer. Nat. Rev. Genet. 7, 21–33 (2006) Suzuki, M.M., Bird, A.: DNA methylation landscapes: provocative insights from epigenomics. Nat. Rev. Genet. 9, 465–476 (2008) Barreto, G., Schaefer, A., Marhold, J., et al.: Gadd45α promotes epigenetic gene activation by repair-mediated DNA demethylation. Nature 445, 671–675 (2007) Wade, P.A., Archer, T.K.: Epigenetics: environmental instructions for the genome. Environ. Health Perspect. 114, A140–A141 (2006) Schmelz, K., Sattler, N., Wagner, M., et al.: Induction of gene expression by 5-aza-2’deoxycytidine in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) but not epithelial cells by DNA-methylation-dependent and -independent mechanisms. Leukemia 19, 103–111 (2005) Olaharski, A.J., Rine, J., Marshall, B.L., et al.: The flavoring agent dihydrocoumarin reverses epigenetic silencing and inhibits sirtuin deacetylases. PLoS Genet. 1, e77 (2005)

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19. Appanah, R., Dickerson, D.R., Goyal, P., et al.: An unmethylated 3’ promoter-proximal region is required for efficient transcription initiation. PLoS Genet. 3, e27 (2007)

20. Okochi-Takada, E., Ichimura, S., Kaneda, A., et al.: Establishment of a detection system 21. 22. 23. 24.

for demethylating agents using an endogenous promoter CpG island. Mutat. Res. 568, 187–194 (2004) Wang, X., et al.: High-throughput assay of DNA methylation based on methylationspecific primer and SAGE. Biochem. Biophys. Res. Commun. 341, 749–754 (2006) Brunori, C., Ipolyi, I., Massanisso, P., Morabito, R.: New Trends in Sample Preparation Methods for the Determination of Organotin Compounds in Marine Matrices. Handbook Environment Chemistry, Part O(5), 51–70 (2006) Barreto, G., Schaefer, A., Marhold, J., et al.: Gadd45α promotes epigenetic gene activation by repair-mediated DNA demethylation. Nature 445, 671–675 (2007) Cheetham, S., Tang, M.J., Mesak, F., et al.: SPARC promoter hypermethylation in colorectal cancers can be reversed by 5-aza-2’deoxycytidine to increase SPARC expression and improve therapy response. Br. J. Cancer 98, 1810–1819 (2008)

Study of Quantitative Evaluation of the Effect of Prestack Noise Attenuation on Angle Gather Junhua Zhang, Jing Wang, Xiaoteng Liang, Shaomei Zhang, and Shengtao Zang College of Geo-Resource and Information, China University of Petroleum, Qingdao, 266555

Abstract. With the increasing refinement of exploration activity, the information of different angles has to be used in the extraction of prestack attributes and prestack inversion. For large angle gather, denoising methods should be different from conventional prestack noise attenuation methods used in CSP and CMP gathers. We established specific theoretical model and quantitatively study the effect of prestack noise attenuation on angle gather. Through the research, we draw the following conclusions: 1) The antinoise ability of angle gather stacking is much better than that of CMP stacking. 2) The larger the apparent velocity of coherent noise is, the more seriously the effect of it on angle gather. Otherwise it is opposite. 3) Surface wave has strong energy and low frequency and a small amount of residues will affect the angle gather largely. After suppressing surface wave, there will be energy loss in near angle gather, which should be compensated. Keywords: angle gather, random noise, coherent noise, surface wave, quantitative evaluation of noise attenuation.

1 Introduction Seismic data preserved-amplitude processing is crucial to achieve reliable prestack characteristic and prestack inversion results. Although the importance of AVO forward and inversion technique has been shown by Jonathan E et al. (2006) [1] and Heidi Anderson Kuzma et al. (2005) [2], there will be false abnormal responses in AVO analysis because of disadvantages of prestack noise attenuation and energy compensation methods which easily lead to energy inconsistencies of near and far offset. Then the following inversion and attribute analysis processing will appears multi-solutions, making inversion results not able to truly reflect subsurface lithology and physical property changes, which is not conducive to lithologic inversion, reservoir prediction and fluid discrimination, as for example in Gary Mavko et al.(1998) [3], Yinbin Liu et al.(2003) [4] and Fatti J L et al.(1994) [5]. The information of different angles has to be used in the extraction of prestack attributes and prestack inversion. For big angle gather, because of the characteristics of angle gather and the impact of oil/gas AVO and random noise and coherent noise, the denoising methods may be different from conventional methods used in CSP and CMP gathers. As the real data is complex and direct quantitative evaluation is not S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 72–77, 2011. © Springer-Verlag Berlin Heidelberg 2011

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easy to achieve, it has both necessity of theoretical study and feasibility of achieving that we establish specific theoretical model and quantitatively study the effect of prestack noise attenuation on angle gather. Now we will carry out quantitative evaluation for random noise, coherent noise and surface wave always occurring in real data.

2 Quantitative Evaluation of the Effect of Random Noise Attenuation on Angle Gathers We established the horizontal layer model (Figure 1). Figure 1, left shows velocity model and right shows the shot gather. The model has 7 layers and the fourth layer is used for quantitative evaluation. The number of total traces is 241, sampling points is 3001, sampling interval is 2ms and trace offset is 50m. While establishing model, we applied time-varying wavelet and the frequency from the first layer to the seventh layer becomes smaller. Based on this model, we added random noise of signal to noise ratio(S/N) of 3, 2, 1 and 0.5, then we made quantitative evaluation of the effect of random noise attenuation. By experiment, we found that adding random noise with S/N of 3 and 2 is similar to that of 1. In the paper, for the limitation of space, we discuss the S/N 1 directly.

Fig. 1. Horizontal layer model. Left) Velocity model. Right) Shot gather.

Figure 2, left, shows CMP gather before and after NMO and the angle gather without random noise and with noise of signal to noise ratio of 1 and 0.5. While S/N is 1, random noise affects event slightly and AVO phenomenon can be obviously observed. After attenuating noise, a small amount of residual random noise has a little effect on events. While S/N is 0.5, random noise affects event very largely and we can’t observe AVO phenomenon. After attenuating noise, a great amount of residual random noise affects angle gather to a large extent. In order to see more obvious changes in angle gather, we selectively stacked 1º13º, 13º-26º and 27º-39º of the angle gather into one trace and repeated it five times (Figure 3). When S/N is 1, AVO phenomenon of small reflection efficient has been difficult to distinguish visually, the middle angle information in the deeper formation has been largely polluted and far angle information has been also greatly affected. After attenuating noise, the middle angle gather in the deeper formation has been

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clearly improved, but the distortion of the contaminated weak signal slightly increased. When S/N is 0.5, only strong reflection information can be distinguished. Far angle, middle angle and near angle gather are all greatly polluted. After attenuating noise, the angle gather section has been greatly improved entirely, but the contaminated events of far angle, middle angle and near angle gather have not.

Fig. 2. Stacking angle gather. From left to right: without random noise; before attenuating random noise (S/N=1), after attenuating random noise(S/N=1), before attenuating random noise(S/N=0.5) and after attenuating random noise(S/N=0.5).

Fig. 3. Stacking angle gather. From left to right: without random noise; before attenuating random noise (S/N=1), after attenuating random noise, before attenuating random noise(S/N=0.5) and after attenuating random noise.

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Fig. 4. Comparison of AVA curve of the fourth layer. Left) S/N=1. Right) S/N=0.5.

Figure 4 shows comparison of AVA curve of the fourth layer when S/N is 1 and 0.5. We can find that as signal to noise ratio decreases, the jitter phenomenon is more and more serious and the reflection coefficient occurred a very significant jump.

3 Quantitative Evaluation of the Effect of Coherent Noise Attenuation on Angle Gathers Based on the horizontal layer model (Figure 1), we adding coherent noise to carry out quantitative evaluation (Figure 5). Figure 5, left, shows coherent noise has a certain degree of cross with effective wave, and the apparent velocity changes a little on angle gather section. Right shows coherent noise has almost been eliminated, only a small amount of which is remained because of edge effect. Figure 5 right shows that inphase property of coherent noise has almost disappeared, but some glitches occur on stacking angle gather section. After attenuating coherent noise there is little effect of coherent noise on angle gather section, but there are residual locally, especially in big angle traces.

Fig. 5. From left to right: CMP gather after NMO and angle gather before and after attenuating coherent noise, stacking angle gather before and after attenuating coherent noise

Fig. 6. Comparison of AVA curve of the fourth layer

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Figure 6 shows comparison of AVA curve of the fourth layer before and after attenuating coherent noise. We can clearly observe the main interference point of coherent noise, and the reflection coefficient has a very significant jump.

4 Quantitative Evaluation of the Effect of Surface Wave Attenuation on Angle Gathers We carry out finite difference surface wave simulation through programming. A free surface boundary condition for numerical simulation of Rayleigh wave is built by using 2×10 order high precision staggered grids finite difference when the source is at the free surface. PML absorbing boundary condition is applied to eliminate boundary reflections, as shown in Xu Yixian et al. (2007) [6] and Saenger E H et al. (2004) [7]. Then we add surface wave into the horizontal layer model (Figure 1) and get the results shown in Figure7. From Figure 7 we can see that surface wave has almost been eliminated, only a small amount of which is remained. Figure 7 right shows that surface wave largely affects angle gather because of strong energy. The events in near angle gather can hardly be distinguished, but middle angle and far angle gather are less affected. After attenuating surface wave, there is little effect of surface wave on angle gather section. However, because surface wave has strong energy and low frequency, a small amount of residue affects the angle gather largely, especially affects the near offset. Figure 8 shows the comparison of AVA curve of the fourth layer. We find that the effect of surface wave mainly occurs in near offset and reflection coefficient has a slight jump after attenuating it.

Fig. 7. From left to right: CMP gather after NMO and angle gather before and after attenuating surface wave, stacking angle gather before and after attenuating surface wave

Fig. 8. Comparison of AVA curve of the fourth layer

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5 Conclusions Through the analysis, we draw the following conclusions: 1) Through adding random noise of different signal to noise ratio and attenuating it, we find that the anti-noise ability of angle gather stacking is much better than that of stacking CMP gather. For original angle gather, the threshold of signal to noise ratio is 1. For angle gather stacking, the minimum signal to noise ratio can be up to 0.5. 2) Through adding random noise of different signal to noise ratio and attenuating it, we find that the effect of coherent noise on angle gather is smaller than that on CMP gather. After attenuating coherent noise, stacking angle gather became better and only a small amount of high frequency glitches are remained. The larger the apparent velocity of coherent noise is, the more seriously the effect of it on angle gather. 3) Based on attenuating surface wave, we find that surface wave has strong energy and low frequency and a small amount of residue will affect the angle gather largely. As surface wave mainly occurs in near offset, the effect of it on near offset than that on far offset. After suppressing surface wave, there will be energy loss in near angle gather, which should be compensated.

References 1. Downton, J.E., Ursenbach, C.: Linearized amplitude variation with offset (AVO) inversion with supercritical angles. Geophysics 71(5), E49–E55 (2006) 2. Kuzma, H.A., Rector, J.W.: The zoeppritz equations, information theory and support vector machines. In: SEG/Houston 2005 Annual Meeting, pp. 1701–1705 (2005) 3. Mavko, G., Mukerji, T.: A rock physics strategy for quantifying uncertainty in common hydrocarbon indicators. Geophysics 63(6), 1997–2008 (1998) 4. Liu, Y., Schmitt, D.R.: Amplitude and AVO responses of a single thin bed. Geophysics 68(4), 1161–1168 (2003) 5. Fatti, J.L., Vail, P.J., Smith, G.C., et al.: Detection of gas in sandstone reservoirs using AVO analysis: A case seismic case history using the Geostack technique. Geophysics 59(5), 1362–1376 (1994) 6. Xu, Y., Xia, J., Miller, R.D.: Numerical investigation of implementation of air-earth boundary by acoustic-elastic boundary approach. Geophysics 72(5), 147–153 (2007) 7. Saenger, E.H., Bohlen, T.: Finite difference modeling of viscoelastic and anisotropic wave propagation using the rotated staggered grid. Geophysics 69, 583–591 (2004)

A User Model for Recommendation Based on Facial Expression Recognition Quan Lu1, Dezhao Chen2, and Jiayin Huang2 1

Center for Studies of Information Resources, Wuhan University, Wuhan, China 2 Research Center for China Science Evaluation, Wuhan University, Wuhan, China [email protected], [email protected], [email protected]

Abstract. User modeling is crucial in recommendation system. By analyzing users’ behavior, gathering users’ interest information, the user model can well express the users’ need. While users’ emotion is also good expression of users’ needs. A user model based on facial expression recognition is built. The user model is on the base of traditional user model, affective function α is provided to reflect user’s emotion. As well as the user model updating times t is also discussed in the model. And then a discussion of the updating strategy and application in recommendation is had. Keywords: user model, recommendation, facial expression recognition, emotion recognition.

1 Introduction User modeling is crucial in personalized services such as recommendation system. Personalized service provides the necessary information to the user who needs it, and the user model expresses the user’s need. User modeling firstly needs getting user’s characteristics, such as user’s profile, user’s behavior when browsing and clicking. Some researchers have researched in user modeling and provided some methods. Topic method uses some topics to express user’s interest and this method has applied to My Yahoo system[1]. Bookmark and keywords are also used to express user’s interest, some systems such as SiteSeer[2], WebWatcher[3] use the method to recommend users interesting information. To reflect user’s semantic information, ontology technology has adopted to the user model. Researchers build domain ontology to mine user’s interesting information, and track user’s interest shifting[4]. User’s interest shifts as the environment changes. User model should reflect the dynamic interest. Document[5] founds three hierarchical user model and uses weight function to update user’s interesting information. Users’ emotion may also express users’ interest, while user models at present don’t contain the emotion. A user model based on facial expression recognition is built in this paper. This model avoids the fault that a user clicked some information while he isn’t interested in them. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 78–82, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Section 1 makes an introduction to this paper, Section 2 provides the user model and section 3 gives the method to build the user model, including t and α value. Section 4 introduces updating mechanism of this model. Section 5 makes a summary of this paper.

2 User Modeling Based on Facial Expression Recognition When a user browses one topic of information, a reaction may be made to it, then he may click it, restore it, and his expression may also reflect his interest. In the user model, emotion is important to obtain user’s interest. User’s emotion can be recognized and expressed, document [6] has researched in the affective visualization, document [7] has built affective model for emotion. The user model built in this paper is combined with affective model, and user’s emotion is added to the model. This user model can be described as:

U = {T , C , W , t , α }

(1)

Ti = {(C , W ), t i , α i }

(2)

(C ,W ) = {(C1 ,W1 ), (C 2 , W2 ),.....(C n ,Wn )}

(3)

Formula (1) describes the elements of the model. In this model, T are the topics which the user is interested in. C represents the characteristic of the topic. W represents the weight related to the characteristic, t represents the times user model changes. α is an affective function reflecting the user emotion by facial expression recognition, α is emotional sign of interest degree. Every topic Ti has a series of (C, W) and ti, α i. Very active

Very negative

Very possitive

Very passive Fig. 1. Continuous emotion space

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The result affective function α computes is based on coordinate which decides the emotion of expression. User’s emotion is continuous and can be classified by two dimensions[8] , as it shows in firgure1. User’s emotion may be mapped in this space. In this model, it needn’t recognize the emotion, but the degree of the emotion, such as positive or negative. Because in recommendation system, t just knows whether user is interested in the topic or not, and to what degree. So it should map the emotion to the emotion dimension, then it may use 0 to express very negative emotion, and 1 very positive emotion, the value 0.5 just represents neutral.

3 User Model Building Building the user model, topics are from the information user browsed, such as the web page user clicked. Every topic has some characteristics and related weight, as it shows in Formula (2) and (3). Ci represents the characteristic of each topic and is decided by the statistics. Wi represents the weight of the characteristic and reflects the importance of the Ci. Ci is also expressed by ontology. Wi is decided by TF/IDF formula, TFIDF(ti) = TF(ti)*log(n/DF(ti))

(4)

TF(ti) represent times item ti occurs in the document, and DF(ti) represents the amount of documents. t represents the times topic T updates, it reflects the frequency user’s interest updates. If t is increasing, it may infer that the user is paying more attention to the topic. At the same time the t should include the time t value changes. The times user model updates and the time it updates will be referred when the model eliminates topics. To decide the topics, it should also gather user’s facial expression which is used to analyze user’s emotion. Affective function α computes user’s emotion, which is a sign of user’s interest. Affective function α computes user’s emotional value between 0 and 1, and the value represents different emotion in different degree. Affection computing depends on the facial expression recognition, and decides the emotion by analyzing the facial characteristics such as structure of face, shape and so on[9]. And then the function will compute the emotion, the result is presented as potential value. It is decided by expression potential formula.

K (e, Ex) =

1 1 + a || e − Exc || 2

(5)

||●||2 represents the distance norm of expression, a is a constant, controls the fading speed of basic expression Ex’s potential. Exc represents the center of expression. Expression potential can be used to classify expression, and then the expression should be mapped to the emotion value, its value is between 0 and 1. Affective function α can express user’s real emotion, avoiding the problem of traditional model that user clicks a web page or browses one topic information while he isn’t interested in it.

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4 User Model Updating and Shifting Mechanism After building the user model, it will update in the following learning. It includes two aspects: one is to update the model, such as to adjust the value Ci, Wi, α , t , and to add new topic. Another is to eliminate some topics when the storage is not so large. When a topic is in the user model, the user model will compute similarity based on SVM theory. And then the user model will be updated including the Ci, Wi, α , t. Every time the topic updates, the t related to the topic will be added: t = t+1

(6)

When a new topic is found, it will be added to the model, if the storage can store the topic, or some topics will be eliminated. Elimination strategy includes α , and t. If the emotion value according to α is low, it indicates that user’s interest is not so strong. So the topic will have priority of elimination. If the t is low, it may indicate that this topic is not updated constantly and user doesn’t browse this topic information. This topic may be context information and user does not pay attention to this topic after a period of time. From the point view of information lifecycle management theory, the topic has no value or low value[10]. So the topic is chosen to eliminate. If t is high but the time model updates is long, it means the model doesn’t update for a long time, so the topic may be out of date, and the topic can be chosen. The long time is relative. When deciding which topic to be eliminated, the user model should consider t and α , and adjust the user model to reflect user’s interest.

5 Summary This paper makes an introduction to our user model, and details the processing and application of the user model. In the personalized service, users’ emotion is also important, while the user model doesn’t express it. So the model takes advantage of the facial expression recognition and builds a user model which contains users’ emotion. This model utilizes affective function α , as a sign of users’ interest. At the same time, this model provides t to reflect the frequency of the topic changes. t is also used to decide whether the user pays attention to the topic or not. t and α values are important in updating the model and recommending information to users. As users require more accurate information and affective computing develops, user model will adopt the emotion factor and applied to the recommendation system. Acknowledgement. This research is supported by National Natural Science Foundation of China (No: 70833005), the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (No: 2009JJD870002) and Education Ministry's Humanities & Social Sciences Program (No: 09YJC870020).

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References 1. Ying, X.: The Research on User Modeling for Internet Personalized Services. National University of Defence Technology (2003) 2. Rucker, J., Polanco, M.J.: Siteseer: Personalized Navigation for the Web. Communications of the ACM 40(3), 73–75 (1997) 3. Joachims, T., Freitag, D., Mitchell, T.: WebWatcher:A tour guide for the world wide web. In: Artificial Intelligence, Japan (August 1998) 4. Yan, D., Liu, M., Xu, Y.: Toward Fine-rained User Preference Modeling Based on Domain Ontology. Journal of the China Society for Scientific and Technical Information 29(3), 442–443 (2010) 5. Li, S.: The Representation and Update for User Profile in Personalized Service. Journal of the China Society for Scientific and Technical Information 29(1), 67–71 (2010) 6. Zhang, S., Huang, Q.: Affective Visualization and Retrieval for Music Video. IEEE Transactions on Multimedia 12(6) (2010) 7. Qin, Y., Zhang, X.: A HMM-Based Fuzzy Affective Model For Emotional Speech Synthesis. In: 2nd International Conference on Signal Processing Systems (2010) 8. Li, J.: Study on Mapping Method of Image Features and Emotional Semantics. Taiyuan University of Technology (2008) 9. Skelley, J.P.: Experiments in Expression Recognition. Master’s thesis, Massachusetts Institute of Technology, EECS (2005) 10. Rief, T.: Information lifecycle management. Computer Technology Review 23(8), 38–39 (2003)

An Improved Sub-Pixel Location Method for Image Measurement Hu Zhou, Zhihui Liu, and Jianguo Yang College of Mechanics Engineering, Donghua University, Shanghai, China {tigerzhou,liuzhihui,jgyangm}@dhu.edu.cn Abstract. Sub-pixel edge location is an effective way to improve measurement accuracy. For the deficiency of traditional gaussian interpolation algorithm for sub-pixel location, this paper presents an improved algorithm: After obtaining pixel-accuracy edge of object to be measured by LoG operator, use Hough transform to get the curve slope of the boundary line and the normal of the corresponding point on the edge; Weighing Lagrange interpolation in the normal direction is performed to obtain the gray values in the direction of the gradient under new coordinate system; finally, perform sub-pixel relocation in the gradient direction based on the gaussian interpolation algorithm. Experimental results show that the improved method can get much better precision than the traditional algorithm. Keywords: Sub-Pixel Edge Detection, Precision Measurement, Machine Vision, Lagrange Interpolation.

1 Introduction Machine vision based measurement is one of the key technologies in manufacturing. It can perform shape and dimensional inspection to ensure that they lie within the required tolerances [1]. In order to improve the precision of image measurement, many scholars have put forth some effective sub-pixel location algorithm [2-6]. As the actual measurement system should meet the requirements of precision, efficiency and reliability, it should not be too complicated. Interpolation based sub-pixel edge detection method has been widely used in practice for its fast calculation speed. It uses the interpolation function to restore onedimensional continuous light intensity approximately. However, for the discrete distribution of pixel points in the digital image, the traditional gaussian interpolation algorithms are only available in horizontal, vertical and diagonal direction (± 45 °, ± 135 °). Certain errors will be generated inevitably for the location of arbitrary edge direction. Consequently, it is necessary to improve the algorithm to improve the sub-pixel location precision.

2 Principle and Problem 2.1 Sub-Pixel Location Algorithm Based on Gaussian Interpolation The distribution of gray values on the object edges for general image is shown in Fig. 1(a), and the distribution of the gray value difference is shown in Fig.1(b). S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 83–92, 2011. © Springer-Verlag Berlin Heidelberg 2011

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(b)

(a)

Fig. 1. Distribution of gray values and difference

The position on the maximum of the gray value difference is the boundary to discriminate the background and the object. Because the integration effects and optical diffraction effects of optical components, as well as the aberrations of the optical system, the change of the gray values become gradient style in the image, which should be drastic changes in reality. Classic edge extraction principle considers that the maximum difference presents the edges of image objects. According to Square aperture sampling theorems, optical components always perform the integration of the light intensity which projected onto the photosensitive surface with a fixed size area at fixed interval, the output results are the gray values in an image. As integral time and integral area is fixed, so the outputs depend only on the light intensity distribution on the surface. A pixel gray values output can be expressed as:

f (i , j ) = ∫

j +1 2 j −1 2

∫

i +1 2

i −1 2

g ( x, y )dxdy

(1)

Here, f (i, j ) is pixel gray values, g ( x, y ) is the light intensity distribution of the continuous images. Theoretically, variations of edge gray values should be a gaussian distribution, which is shown in Fig.2, the vertex position of the curve is the precise location of the edge point. Expression of the Gaussian curve is: y=

1 −( x − μ ) 2 exp( ) 2σ 2 2πσ

(2)

μ is a mean value; σ is a standard deviation. Because it is difficult to fit directly, and the purpose here is just to find the vertex position. Therefore perform logarithmic operation on both sides to transform the equation: ln y = −

( x − μ )2 1 + ln 2σ 2 2πσ

(3)

Obviously, the equation is conic style. To simplify the calculation, we can use the values after logarithmic operation to fit a parabola to obtain vertex coordinate. So, we use conic instead of Gaussian curve to improve the efficiency.

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Mm W2

W1

P1

P

Pmax

P2

Fig. 2. Variations of edge gray values

Surpose the conic form is y = Ax2 + Bx + C , the gray value output for each pixel is:

y (n) = ∫

n +1 2

n −1 2

( Ax 2 + Bx + C ) dx

(4)

Let the number of the maximum point of grayscale value difference be 0, and its value be represented as f0. This position can be calculated by classic operator mentioned above. The number of the two points which is nearby the maximum point are represented as -1 and 1, and their values are represented as f-1and f1 , We can get the gray values as follow: −1

1 ⎡1 ⎤ 2 13 ( Ax 2 + Bx + C )dx = ⎢ Ax3 + Bx 2 + Cx ⎥ = A − B + C −3 2 2 ⎣3 ⎦ − 32 12

f −1 = ∫

−1 2

1 A+C 12

(6)

13 A+ B +C 12

(7)

f0 =

f1 =

(5)

Combine the equations from (5) to (7), we can obtain the expression of A, B, C as follows: A=

1 ( f 1 + f −1 − 2 f 0 ) 2

B=

1 ( f 1 − f −1 ) 2

C=

13 1 1 f0 − f −1 − f 12 24 24

(8)

Thus, the abscissa value of the parabola’s vertex is: x=−

f1 − f −1 B = 2 A 2(2 f 0 − f1 − f −1 )

(9)

This solution is the result after taking logarithms in the Gaussian curve and the pixel gray values difference in (9) should be substituted by logarithms, so we get: x=

ln f1 − ln f −1 2(2 ln f 0 − ln f1 − ln f −1 )

(10)

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2.2 The Deficiency of Traditional Gaussian Interpolation Algorithm

For the discrete distribution of digital image’s pixel points, the traditional gaussian interpolation algorithms can only be performed in horizontal, vertical and diagonal direction (± 45 °, ± 135 °). In most cases, edges are in arbitrary direction, so the accuracy of location will be decreased inevitably. Fig.3 shows an object edge of the original image. Fig.4(a) shows the trend curve of gray value change in arbitrary horizontal direction, and Fig.4(b) in gradient direction. As can be seen from the figures, the gray values in normal direction change more drastically than in the other direction, which means that edge location in normal direction will be more accurate.

Fig. 3. Variations of edge gray values

(a)

(b)

Fig. 4. Gray values change chart in horizontal and normal direction

3 Algorithm Optimization 3.1 Interpolation in the Gradient Direction

After obtained the edge location of object using LoG operator, we use Hough transform to get the curve slope of the boundary tangent line, and thus the corresponding normal could be obtained. Suppose the angle of edge normal to horizontal axis is θ, as shown in Fig.5. Take a certain edge point after pixel-precise location as center, rotate the coordinate system to make the normal line be the x-axis, then the edge direction become the y-axis. Do gaussian curve fitting in gradient direction to get the sub-pixel location more accurately.

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Fig. 5. Interpolation in edge normal direction

(a) Input image

(b) Output image

Fig. 6. The interpolation if image gray values

The algorithm is possible to achieve a high precision theoretically. However, there is a critical problem that must be resolved: because the discrete distribution of digital image pixels, the original pixel point f-1 and f1 in the new rotated coordinate system '

'

'

'

( f −1 and f1 ) may not be integers. The gray values of f −1 and f1 after coordinate rotation must be determined. To solve this problem, reintroduce gray value interpolation method, as shown in Fig. 6. Suppose the existing pixel gray values as f(u1,v1) f u2 v2 … f un vn , the new pixel gray values in the new coordinate system can be expressed as:

、 （ ， ）， ， （ ， )

n

f (u 0 , v0 ) = ∑ f(u i ,vi )h(u i − u0 , vi − v0 )

(11)

i =1

h(·,·) is interpolation kernel function,

f(ui ,vi )(i = 1,2,0..., n )

is weight coefficient.

3.2 The Chosen of Interpolation Kernel Function

The precision and calculation of interpolation algorithm depend on the interpolation kernel function, and the design of kernel function is the core of algorithm. The paper presents a weighing Lagrange interpolation algorithm to keep a balance between precision and complexity. From mathematical analysis we found that if any function f(x) has n+1 derivative at point x0, then the function can be expanded as a Taylor series in that neighborhood:

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f ( x ) = f ( x 0 ) + f' ( x 0 )( x − x 0 ) +

f (n ) (x 0 ) 1 (x − x 0 ) + R n (x ) f " ( x 0 )( x − x 0 ) 2 + " + n! 2!

f (n +1) (ξ )

(12)

n +1

In the formula, R n ( x ) = (n + 1)! (x − x 0 ) , which is Lagrange remainder. In General, second order Taylor series is sufficient to approach the original function and this paper try to use Taylor series to the interpolation function. As shown in Fig.7, a single pixel is surrounded by 4 pixels and we can choose any 3 points 3

( C 4 ) to do Lagrange interpolation. Finally, we take the average as the output gray value for the pixel. (0,0)

(0,1) (x,y)

(1,0)

(1,1)

Fig. 7. Interpolation of pixels

Suppose the gray value for points (0, 0), (0, 1) (1, 0), (1, 1) is y0, y1, y2 and y3 respectively. Do second order Lagrange interpolation for point (0, 0), (0, 1) and (1, 0) to get f0(x, y): f 0( x, y) = y 0

( x − x 0 )( x − x 2 ) ( x − x 0 )( x − x 1 ) ( x − x1 )( x − x 2 ) + y1 + y2 ( x 0 − x1 )( x 0 − x 2 ) ( x1 − x 0 )( x1 − x 2 ) ( x 2 − x1 )( x 2 − x 0 )

(13)

Similarly, Lagrange interpolation for points (0, 0), (0, 1) and (1, 1), we get f1(x,y): f 1(x, y) = y0

(x − x1 )(x − x 3 ) ( x − x 0 )(x − x 3 ) ( x − x 0 )(x − x1 ) + y1 + y3 ( x 0 − x1 )(x 0 − x 3 ) ( x1 − x 0 )(x1 − x 3 ) ( x 3 − x1 )(x 3 − x 0 )

(14)

Lagrange interpolation for points (0, 1), (1, 0) and (1, 1), we get f2(x, y): f 2( x , y) = y1

( x − x 2 )( x − x 3 ) ( x − x 1 )( x − x 3 ) ( x − x 2 )( x − x 1 ) + y2 + y3 ( x 1 − x 2 )( x 1 − x 3 ) ( x 2 − x 1 )( x 2 − x 3 ) ( x 3 − x 1 )( x 3 − x 2 )

(15)

Lagrange interpolation for points (0, 0), (1, 0) and (1, 0), we get f3(x, y): f 3( x , y) = y 0

( x − x 2 )( x − x 3 ) ( x − x 0 )(x − x 3 ) ( x − x 2 )(x − x 0 ) + y2 + y3 ( x 0 − x 2 )( x 0 − x 3 ) ( x 2 − x 0 )(x 2 − x 3 ) ( x 3 − x 0 )(x 3 − x 2 )

(16)

Finally, Calculated the pixel gray value f(x, y) for point (x,y): f ( x, y) =

1 (f 0 ( x, y) + f1 ( x, y) + f 2 (x, y) + f 3 ( x, y)) 4

(17)

After obtaining the gray values for the interpolation points in the gradient direction under the new coordinates system, we can relocate the edge points for sub-pixel precision in the gradient direction based on the Gaussian interpolation algorithm.

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4 Experiment Results In order to verify the algorithm, we adopted the standard Gauge which has a high quality of straight edges for sub-pixel location experiment. Fig.8(a) illustrate a standard Gauge with 20mm of working length (the long side is the working face) and Fig.8(b) shows the gray value data of gradual partial edge.

(a)

(b)

Fig. 8. Original image of Gauge and gray values of partial edge Table 1. The list of edge point coordinates by different edge extraction methods

No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Pixel precision (437,444) (437,445) (437,446) (438,447) (438,448) (438,449) (439,450) (439,451) (439,452) (440,453) (440,454) (440,455) (441,456) (441,457) (441,458) (442,459) (442,460) (442,461) (442,462) (443,463) (443,464) (443,465)

Traditional Interpolation (436.7507, 444.1063 ) (437.1611,444.7419 ) (437.3867,446.5000) (437.7011,446.7521) (438.2676,448.4210) (438.4088,448.5000) (438.5354,449.8514) (439.1241, 451.3852) (439.3931,452.0611) (439.5411, 453.4563) (440.1897,454.4351) (440.3845,454.7162) (440.6585,455.8461) (441.0398, 456.6891) (441.2947,458.0000) (441.6210,458.6502) (441.7600,460.4556) (442.2098, 461.4322) (442.3906,461.6704) (442.8143,463.4500) (443.0912,464.6721) (443.3627,465.2967)

Improved algorithm (436.9439,444.0181) (437.1932,444.9377) (437.3832,445.8765) (437.9123,447.0282) (438.2705,447.9128) (438.4052,448.8693) (438.7990,450.0648) (439.1645,450.9470) (439.3851,451.8758) (439.7986,453.0649) (440.2177,453.9298) (440.3815,454.8770) (440.8256,456.0562) (441.1015,456.9673) (441.2945,457.9050) (441.3920,459.1961) (441.9337,460.0214) (442.2306,460.9253) (442.3854,461.8757) (442.9165,463.0269) (443.1451,463.9532) (443.3624,464.8831)

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Execute the LoG edge extraction (σ=1, thresh=70) and we can get the edge binary image. Do Hough transform for the left side edge we get the line equation as y=3.0994x-909.3564. To precisely locate the edge point, rotate the coordinate system about the LoG zero crossing point to make the edge be y-axis and the normal direction become x-axis. Conduct sub-pixel location according to the algorithm mentioned above. Notice that the operation is only carried out for the zero crossing point along the normal direction. Table 1 lists the edge point coordinates for pixel precision, sub-pixel precision by traditional Gaussian Interpolation and the sub-pixel precision by improved algorithm. Fig.9 shows the 2D curve drawn by positions of each sub-pixel points. We can find that the curve made by pixel level precision shapes like a zigzag, traditional gaussian interpolation method remedy such errors to some extent. However, because it was not carried on the edge’s normal, so it inevitably has some errors compared with the real edge. The improved algorithm executes second sampling in edge’s normal and uses 470 pixel accuracy edge traditional sub-pixel edge improved sub-pixel edge

465

y coordinate

460

455

450

445

440 436

437

438

439

440 x coordinate

441

442

443

444

Fig. 9. Comparison of edge point curve made from different algorithms

Fig. 10. Ring gauge of Ф 20

Fig. 11. Comparison of edge point curve

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second-order Lagrange interpolation algorithm to restore the gray values in the gradient direction. Consequently, this method can improve the accuracy of edge location to some extent. As shown in the figure, line connected by sub-pixel points obtained by executing improved algorithm, get even closer to the real straight line. Fig.10 is a ring gauge of Ф20. Similarly, We obtained the edge point coordinate by pixel precision, sub-pixel precision by tradition Gaussian interpolation, sub-pixel precision by improved algorithm. Fig.11 is the comparison of the edge curve derived from different methods. Fig.12 shows the error data curve between the improved arc sub-pixel location method and pixel-level location method. 

ẃᑺᮍ৥ᅮԡ䇃Ꮒ





Error values 





                      







Pixel point পḋ⚍ᑣ߫

Fig. 12. Error data curve

Because standard gauge boasts high-quality straight lines and curve edges, we can figure out the sub-pixel location precision by checking the shape errors of the object edges from the image. The shape errors of gauge are shown in Table 2 and we can find that the new algorithm improved the precision of sub-pixel location obviously. Table 2. Shape Errors of gauge image

Algorithm

Pixel-level Location

Straightness Radian

0.849 0.868

Traditional Location 0.318 0.403

Sub-pixel Improved Location 0.223 0.238

Sub-pixel

5 Summary Edge detection and sub-pixel precision location for edge points are the basis for image measurement. Classical Gaussian interpolation location can achieve high speed but low precision. As for arbitrary oriented edges, gaussian interpolation on the edge gradient can improve the location precision. To restore the gray values on the gradient direction, perform second order Lagrange interpolation and then the gaussian interpolation of sub-pixel relocation. Experiment proves that improved sub-pixel interpolation algorithm get much better precision than traditional algorithm. Acknowledgment. Supported by Chinese Universities Scientific Fund.

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References 1. Steger, C., Ulrich, M., Wiedemann, C.: Machine Vision Algorithms and Applications, pp. 1–2. Tsinghua University Press, Beijing (2008) 2. Qu, Y.D.: A fast subpixel edge detection method using Sobel-Zernike moment operator. Image and Vision Computing 23, 11–17 (2005) 3. Tabatabai, A.J., Mitchell, O.R.: Edge location to sub-pixel values in digital imagery. IEEE Trans. Pattern Anal. Machine Intell. PAMI-6(2), 188–201 (1984) 4. van Assen, H.C., Egmont-Petersen, M., Reiber, J.H.C.: Accurate object localization in gray level images using the center of gravity measure:accuracy versus precison. IEEE Transactions on Image Processing 11(12), 1379–1384 (2002) 5. Malamas, E.N., Petrakis, E.G.M., Zervakis, M., et al.: A survey on industrial vision systems, applications and tools. Image and Vision Computing 21, 171–188 (2003) 6. Li, Y., Pang, J.-x.: Sub-pixel edge detection based on spline interpolation of D2 and LoG operator. Journal of Huazhong University of Science and Technology 28(3), 77–79 (2000)

The Dynamic Honeypot Design and Implementation Based on Honeyd Xuewu Liu1, Lingyi Peng2, and Chaoliang Li3 1

Hunan University of Commerce Beijin College 2 Hunan First Normal University 3 School of Computer Hunan University of Commerce, Changsha, China {12870595,494680234,522396825}@qq.com

Abstract. Along with the rapid development of Internet technology, Network security has become a very serious problem. At present the main security technologies include firewall technology, intrusion detection technology, access control technology, data encryption technology and so on. These safety technologies are based on the passive defence, so they are always in a passive position when thay are face to the up-to-date attack means. So,we put forward a kind of active defense network security technology -Honeypot technology and research detailedly the dynamic honeypot design and implementation based on Honeypot. Keywords: Network security, Honeyd, Dynamic honeypot, Virtual honeypot.

1 Preface Along with the the rapid development of Internet technology, Network information safety has to be face to a serious threat. The current network security technologies mainly use the passive defense methods, but these methods are very tough to deal with complex and changeable attacks from hacker. Since passive defense modes are difficult to deal with the complex and changeable attacks, we must solve the problem of defensive measure which is from the passive into active.This is also our research new topic. In this context , We put forward a kind of active defense network security technology—Honeypot. The Honeypot system elaborate network resources for hackers, which is a strict monitoring network deception system.The system aims at attracting hacker attacks through offerring real or analog networks and services ,,collecting the information and analyzing its attack behavior and process during the hacker attacks.In this way,we can hold the hackers’ motivations and goals, repair security holes The system attacked before , which can avoid the attacks occurred.

2 Honeyd Analysis and Research The Honeyd is designed by the Niels Prowvos from the Michigan university.It’s a application-oriented honeypot with low interactive. The Honeyd’s software frame S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 93–98, 2011. © Springer-Verlag Berlin Heidelberg 2011

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includes configuration database, central bag dispensers, agreement processor, personality engines and an optional routing component several parts. The structure is shown in figure 1:

Fig. 1. Logical frame of honeyd

After Honeyd receives packets, The central bag splitter will check IP packet length and confirm bag checksum. Honeyd main response three Internet protocols which are ICMP, TCP and UDP , Other protocols are discarded after credited into log .Before Packets are processed, The central bag splitter will search the honeypot configuration corresponding with the packet destination address. If they can't find the corresponding configuration, the System uses a default configuration..After the configuration is given, Packet and corresponding configuration will be assigned to specific protocol processor.

3 The Dynamic Honeypot Design Based on Honeyd 3.1 The Design of Dynamic Honeypot Environment Obtain The main purpose obtaining the environment around is to learn about the Internet environment. It’s the necessary conditions to solve the honeypot system configuration , That is, to solve allocation problems must know surrounding network environment first. 1) Active detection technology In order to get the network operating system and server types, We can use tools Nmap in detecting the entire network, After that ,we can get the feedback of target system that help us to determine its operating systems and services provided by it. But if active detection by excessive used can also cause faults, Namely excessive active detection will consume extra bandwidth,,which may cause the system shutdown. 2) Passive fingerprint identification technology Passive fingerprint identification technology is based on the principles which each operating system IP protocol has its own characteristic, maintains a fingerprinting

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database, Records data packets characteristic of different kinds of operating system . After it catches data packets in the network ,it will compare with the record of the database ,thereby it can judge the operating system categories. 3) Design of the active detection combining with the passive fingerprint According to the above active detections and passive fingerprint designs, we will be able to determine approximately the kind of operating system and obtain the basic situation of the environment. Its design is shown in figure 2:

Fig. 2. Design of the active detection combining with the passive fingerprint

3.2 The Architecture Design of the Dynamic Honeypot System Dynamic honeypot technology is first proposed as a kind of design method by the honeynet organization. For the challenge existing in the honeypot configuration and maintenance, we have to analyze it with dynamic honeypot technology. The system mainly uses active detection technology, passive fingerprint identification technology and Honeyd technology. The overall structure design which is made for the above content is in the following figure 3:

Fig. 3. The dynamic honeypot overall design based on Honeyd

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4 The Dynamic Honeypot Realization Based on Honeyd 4.1 Set Virtual Machine We can use installing Linux operating system hosts to do the honeypot host, Linux is main operating system in the machine honeypot mainframe, And let the system with bridge function, Another installation Vmware virtual machine, Used to support multiple guest operating system. Also installed the virtual machine to support guest operating system. In this honeypot system, We adopt Settings gateway for 2 Bridges mode, Through the use of two-layer gateway, Honeypot system with real system in a network environment, So in tracking and understand the external network attack, Can understand the internal network security problems. In addition, we through the source code to realize system support bridge mode. 4.2 Establish Honeyd Configuration Files The system through the Honeyd to simulate the virtual honeypot. Through creating Honeyd.config files to configure the template. The system created a default host templates, Used to store those not in other templates defined in packets, In addition, also created a Windows operating system template and a XP operating system template and router template. 4.3 Data Control Honeyd usually has two layers of data control, Respectively is a firewall data control and router data control, Firewall data control mainly through a firewall to control the honeypot out connection, Firewall adopt "wide into severe out" strategy, In fire prevention wall of honeypot machine from outside sends the number of connections set a rational threshold, Generally allow outside sends number of connections Settings for 5 to 10 more appropriate, Won't cause invaders doubt, Also avoid honeypot system become the invaders against other systems and tools. Routing control by routers completed, Basically is to use routers to go out the access control function of the packet filtering, Lest honeypot is used to attack other parts of a network. Mainly used to prevent Dos attack, IP deception or some other deceptive attack. In this system, we adopt gateway to replace, The advantage of using gateway is: Gateway no network address, Control operation will more latent, Hackers perceive is not easy. We adopt Honeynet development of rc. Firewal scripts to the configurations and realization, And using IPTables to restrict. IPTables is Linux self-contained open source firewall, According to the need to Forsake a bag, In a given period allowed only a certain number of new connection, Possibly through discard all packages to completely isolate the honeypot system. Every time the connection initialization out the connection, Firewall count, When the total limit is reached then, IPTables will block any Honeypot launched from any connection. Then IPTable reset itself, Allow each time period allowed out connection number. In this script installed per hour allow TCP and UDP, ICMP or other arbitrary IP packet out number of connections, When an intruder outside sends a packet to specified value, Automatically cut off all foreign connections, To reduce the network risk.

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4.4 Data Capture Data capture is the key of the honeypot system, We need to use data capture information to determine the invaders behavior and motivation, In order to determine the invaders gain access after had done, We need to capture data can provide invaders keystroke records and attack effect. 1) Realize data capture by snort Snort is a lightweight intrusion detection system, It has three working mode: Sniffer, packet recorder, network intrusion detection system. We mainly use Snort intrusion detection model. Above configuration files is Snort collected data output to local called Snortdb Mysql database, The user name is Snortoper, Verification code is Password. At the same time will be recorded in Tcpdump format packets Snort.log file. 2) Realize data capture by sebek Sebek is a based on the kernel's data capture tools, It can be used to capture the honeypot concealed all activities. Sebek caught in the packet encryption has great advantage, Because no matter what kind of encrypted data to the destination host to have after action, Will be decrypted to call system calls. Hackers who get packets, Use its own agreement will the packet on the Internet, Thus obtained by the Sebek Server. Sebek Client are through some hidden technology makes the invaders feel oneself be monitored, Convenient for us to capture the real data. Sebek Client capture the data package into UDP packets, Through the nic driver sent to the Internet, Avoid being invaders may install the sniffer to detect. Sebek consists of two parts: The client and the server. The client from the honeypot capture data and the output to network lets server-side collection. The server have two ways to collect data: The first kind is directly from the network activity packet capture, The second from Tcpdump format preservation packets files. When data collected can upload the relational database, Also can instantly display keystroke records. 4.5 Log Record log record is mainly to the honeypot host capture data recorded, Its main function is to collect and record hackers behavior, For the future analysis hackers the tools used, strategies and their attack purposes or take lawsuit hackers crime to provide evidence. In order to ensure that capture hacker attacks data security, We design a log oportunidades programme to the backup data in the system. The honeypot host is running with Linux ep-red Hat 9.0 operating system of real host,the Syslog of Linux Red Hat 9.0 function is powerful, Syslog can send recording system kernel and tools generated information. We can configure their Syslog. Conf files, To realize the virtual honeypot collected log message transferred to log server. By modifying Syslog. Conf, Realized the local log information transfer to remote log server for backup. Finally, we began to capture the hacker information for analysis, Thus learning hackers means and

、

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methods, In view of its attack means to take corresponding defensive measures, To this, the Honeyd based on dynamic honeypot is realized basically.

5 Summary Dynamic honeypot although is based on virtual honeypot, But it is a low interaction of honeypot, With the interaction between the attacker is very limited, Capture data also is very limited, Improve the honeypot interactivity can gain more attack information, To study the attacker to attack has very great help. We can interact with high virtual honeypot honeypot combined, To capture more attacks, information. Dynamic virtual honeypot on network security role is mainly indirectly, Namely recognition threat, divert attacks flow. Thus the honeypot with other security technology, Such as firewall technology and intrusion detection system combining but also the future of a very important developing direction. Along with the development of honeypot technology, Some problems will be solved step by step, Some new techniques and applications will further development, Make honeypot technology better for network security provided protection.

References 1. Fu, X., Yu, W., Cheng, D., et al.: On Recognizing Virtual Honeypots and Countermeasures. In: The 2nd IEEE Interational Symposium on Dependable, Autonomic and Secure Computing, vol. 9, pp. 220–230 (2006) 2. Leita, C., Mermoud, K., Daeier, M.: SeriptGen:all automated script generation tool for honeyd. In: 21st Annual Computer Security Applications Conference, vol. 9, pp. 125–135 (2008) 3. Zhang, F., Zhou, S., Qin, Z., et al.: Honeypot:a supplemented active defense system for network security. In: Proceedings of the Fourth International Conference, PDCAT 2009, vol. 8, pp. 231–235 (2003) 4. Kreibich, C., Crowcroft, J.: Honeycomb-Creating intrusion Detection Signatures Using Honeypots (EB/PDF), http://www.sigcomm.org/I-IotNets-II/papershaoneycomb.pal.2010 5. Domscif, M., Holz, T., Mathes, J., Weisemoller, I.: Measuring Security Threats with Honeypot Technology, 21–29 (2009) 6. Kwong, L., Yah: Virtual honeynet srevisited.SMC Information Assurance Workshop. In: Proceedings from the Sixth Annual IEEE, vol. 9, pp. 230–240 (2010)

Research of SIP DoS Defense Mechanism Based on Queue Theory Fuxiang Gao, Qiao Liu, and Hongdan Zhan College of Information Science and Engineering, Northeastern University, Shenyang 110819, China [email protected], {dongqin4060432,hongdanzhan}@163.com

Abstract. The SIP is becoming the core of multimedia communication network through the IP, based on which the 3G network has been operated in our country. The easy implementation, high destruction and hard tracking against attacking source which are the characters of DoS attack cause the great security threat to SIP. Focusing on the research on defense mechanisms of DoS attacks in SIP protocol, this paper proposes a model based on queue theory to approximately analyze the DoS attack, and then presents a DoS attack defense method. Simulation was taken to analyze the performance of the defense mechanism. Keywords: SIP, DoS attack, queue model, defense mechanism.

1 Introduction SIP was proposed in 1999 by IETF as a signaling protocol that based on IP network environment. And it has been widely used in NGN at present. SIP is vulnerable to DoS attack because it runs on IP network environment and has openness. For example, attackers can create false messages which have false source addresses and via field. And the SIP proxy server which was attacked is set as request initiator, then these messages are sent to large numbers of SIP users. Hence the spoofed users will send many DoS attack messages to the attacked server. Therefore, research on DoS detection defense system of SIP has become a hot point at present and also has been a problem that urgently needed to be solved in NGN deployment. According to the definition of VolPSA, DoS attack problems of SIP system can be divided into five categories: request flooding, malformed requests and messages, QoS abuse, spoofed messages, call hijacking [1]. This paper mainly researches on the flooding problems of SIP, and combining with the M/M/1/K mathematical model it proposes a SIP DoS attack defensive scheme that based on the queue theory. At last, this paper simulates and analyzes the performance of the scheme.

2 Analytical Model of SIP DoS Attack 2.1 Related Assumptions We assume that the arrival time of SIP request messages obeys exponential distribution and the average arrival rate is λ / s. We also assume that the consuming S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 99–104, 2011. © Springer-Verlag Berlin Heidelberg 2011

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time that the server processes the unit message is Q seconds, the size of messages obeys exponential distribution whose average is L, the average service rate of SIP system is µ and the average service time is S, thus: S=1/μ=LQ

(1)

For convenient analysis, we assume that the service time and the interarrival time still obey exponential distribution during the system under DoS attacking [2]. We also assume that the whole system has only a core processing unit and the size of the cache is K, namely there are a maximum of K request messages wait to be processed, the rest of the arrival messages will be discarded [3]. So we can analyze the whole system using the M/M/1/K model. 2.2 The Establishment of the Analytical Model For the M/M/1/K system, we write ρ as ρ= λ / μ, thus we can obtain the rate (p0) when the queue’s length of the system is 0:

⎛ k ⎞ p0 = ⎜ ∑ ρ i ⎟ ⎝ i =1 ⎠

−1

(2)

The rate of messages being discarded when the system statistical balance is: П=pk=ρkp0

(3)

The average waiting time of messages when there are no messages are lost is: ρ0 1 ⎧ 1 P (1 − k ρ k −1 + ( k − 1) ρ k ) ( ρ ≠ 1) 2 ⎪1 − Π − (1 − ρ ) μ ⎪ W =⎨ ⎪ 1 ρ 1 ( k − 1) k ⎪1 − Π 0 μ 2 ⎩

(4)

The average delay of the messages equals the waiting time of the messages in the queue plus the average service time, thus the average response time of the system is: R = W ( λ , L, K ) + S ( L )

(5)

We can see that the response time of system is related with three parameters: the arrival rate of the request messages λ, the average size of the messages L and the size of the system cache K. Normally, the value of K is sure, so the response time of system depends on λ and L.

3 The Design of SIP DoS Attack Defensive Scheme According to the M/M/1/K model above, the new coming message will be discarded when the number of the received messages larger than k. That means that other legal users will not be able to accept normal services if the server is suffering a DoS attack and causing its own buffer space exhausted.

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For example, if the illegal INVITE message blocks up the header of the queue, the legal INVITE message behind it will not be able to obtain the service so that the call can not be established according to the normal process, which will lead to sessions is failed because of the timeout at last. Even if the illegal INVITE message does not block up the header of the queue, a large number of illegal messages block at the head of the queue, that may cause the new coming session response message cannot be accepted or be discarded, the call of legal users will also be timeout because of not accepting any response [4], what is shown in Fig.1. 180 Running The normal INVITE message

The illegal INVITE message

The normal INVITE message

200 OK Programming

Incoming message Programming

The illegal INVITE message

Fig. 1. The blocked queue of INVTE message. The former is the situation of blocking the header of the queue and the later is blocking the queue. Others

Others

SIP message

INVITE

INVITE Programming

Others Programming

Programming

INVITE Programming

Fig. 2. The Sketch maps of single queue and priority queue. The former is the situation of the signal queue and the later is the priority queue.

In order to reduce the influence that the INVITE flooding has on the proxy server, we consider the scheme in which the priority queue is introduced. SIP server generally uses FIFO queue when it processes the message queue. When there is a DoS attack, it will produce the problem above. If we adopt the priority queue, the INVITE messages will be assigned with low priority and be put into low priority queue, others that are not INVITE messages will get high priority and be put into high priority queue. The two queues respectively follow FIFO principle, but only when the higher priority queue is empty, they will process the messages of lower priority, what is shown in Fig.2. Thus, we can assign the original cache sources of server to two queues, and the way of assigning the sources according to the actual conditions. For convenient analysis, this paper assign the cache sources to two queues averagely, namely two M/M/1/K/ queues [5]. The priority queue adopts the non-preemptive priority rules, a message which is accepting services is allowed to finish this service without interference, even if there is a higher priority message arrives. Every priority message has an independent queue. When the server can be used, the first message of the non-preemptive priority queue that has the highest priority will be the first to accept the service. It will give the corresponding average delay equations for every priority category. For the M/M/1/ (K/2) system which has multiple priority levels, firstly, we define various parameters as followed: qwi is the average length of queue whose priority is i; Wi is the average waiting time whose priority is i; p0i is the rate when the length of the message

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queue is 0 whose priority is i; ρi= λi / μi is the utilization rate of the message whose priority is i on the system; TR is the average residual service time. Assuming that the whole utilization rate of the system is lesser than 1, namely: ρ1+ρ2+…+ρn<1.

(6)

If it cannot meet this assumption, the average delay time of the messages whose priority is not larger than k will be equal to infinity, while that of the messages whose priority is larger than k will be limited values. We can get the average length of the message queues whose priority is i: ⎧ ρi 2 ⎛ k k2 −1 ⎛ k ⎞ k2 ⎞ 1 − ρi + ⎜ − 1 ⎟ ρi ⎟ p0i ( ρi ≠ 1) ⎪ 2 ⎜ ⎝2 ⎠ ⎠ ⎪⎪ (1 − ρ ) ⎝ 2 qwi = ⎨ k⎛k ⎞ ⎪ ⎜ − 1⎟ ⎪ 2 ⎝ 2 ⎠ p ( ρ = 0) i 0i ⎪⎩ 2

(7)

This paper will only discuss the situation of having two priority levels, we can easily get the average delay time of the messages that having high priority is: 1

W1 = TR +

μ1

qwi

(8)

For the messages of low priority, the expression of average detention is generally similared with the expression of high priority expect that there is still a message waiting in the queue when a message of high priority arrives at the server. At this time, the expression is: W2 = TR +

1

μ1

qwi +

1

μ2

qwi + ρ1W2

(9)

According to P-K equation, we can deduce the average residual service time is: TR =

1 n ∑ λi X i 2 2 i =1

(10)

For the message whose priority is i, the response time is: Ri =

1

μi

+ Wi

(11)

For the system which has two priority levels, its average response time is: R=

λ1 R1 + λ2 R2 λ1 + λ2

(12)

4 The Simulation and Comparison of Performance The node model consists of a group of node module, the internal of every node module need to process domain modeling. This paper just gives the domain modeling of the crucial ARS node module, what is shown in Fig.3.

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Fig. 3. The domain modeling of the crucial ARS node

Fig. 4. The performance comparison between three priority queues and two priority queues

The parameters of simulation are set as followed: the average arrival rate of messages, namely, the attacking factor λ obtains its value between 0 msg/s and 10 msg/s. The average service rate of SIP transaction process µ is 10 msg/s. We can obtain the result through running the simulation program. We can observe dramatically that with the growth of λ, the average response time of messages obeys exponential distribution. So the attracting factor has a huge affect on the response time of the system. When the value of attracting factor is larger than 8, the response time of message of the target node will increased greatly, even causing the target node cannot response to any message, the system will collapse. In order to accurately compare the superiority of three levels queue and two levels queue, we obtain the curve of the two queues under the same parameters, what is shown in Fig.4. We can obviously find that the response time of three levels queue is far better than that of two levels queue from the comparative curve.

5 Conclusion Although the M/M/1/K model that was established in this paper just aims at the INVITE flooding attack, it summarizes the advantages of the detecting defense

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mechanisms in a certain extent and realizes easily. All kinds of the existing SIP DoS attack defense mechanism has its own advantages and disadvantages, the key factors to analyze the performance of the scheme is to establish an effectively mathematical analysis model. This paper verified the effective of the DoS attack defense scheme that is mentioned through emulating the ARS model based on queuing theory. In the future research, it will obtain better effect if it couples with certain discarding INVITE message algorithms.

References 1. Rosenberg, J., Schulzrinne, H., Handley, M., et al.: SIP: Session Initiation Protocol. RFC 3261 (2002) 2. Yin, Q.: The reserch on SIP DoS attack defense mechianism. The Journal of Chongqing University of Posts and Telecommunications 20(4), 471–474 (2008) 3. Zhang, G., Fischer-Hübner, S., Ehlert, S.: Blocking attacks on SIP VoIP proxies caused by external processing. Telecommunication Systems 45(1), 61–76 (2009) 4. Ormazabal, G., Nagpal, S., Yardeni, E., Schulzrinne, H.: Secure SIP: A Scalable Prevention Mechanism for DoS Attacks on SIP Based VoIP Systems. In: Schulzrinne, H., State, R., Niccolini, S. (eds.) IPTComm 2008. LNCS, vol. 5310, pp. 107–132. Springer, Heidelberg (2008) 5. El-moussa, F., Mudhar, P., Jones, A.: Overview of SIP Attacks and Countermeasures. In: Weerasinghe, D. (ed.) ISDF 2009. LNICST, vol. 41, pp. 82–91. Springer, Heidelberg (2010)

Research on the Use of Mobile Devices in Distance EFL Learning Fangyi Xia School of Foreign Languages, Tianjin Radio & TV University, 300191 Tianjin, P.R. China [email protected]

Abstract. This research focuses on exploring the possible use of mobile devices in distance learning of English as a Foreign Language. Firstly, it studies mobile devices’ application in language teaching. Secondly, it analyzes the current problems of distance EFL learners in China. Then, it makes suggestions on how to use mobile devices in distance EFL learning in China. Finally, it finds that mobile learning could partly address some of the current problems of distance EFL learners, such as lack of constant exposure to learning contents and lack of big chunk of time for study and revision etc. Some effective ways are to represent learning contents on mobile devices, create an online submission system for oral and written assignment and design a mobile interactive quiz system. Keywords: mobile devices, mobile learning, EFL, distance learning.

1 Introduction With the rapid development of wireless mobile technology, mobile, portable and handheld devices, such as mobile phones, personal digital assistants (PDAs), MP3 and MP4, etc. have become very popular in people’s daily life. And some have powerful functions as personal computers do. They are now regarded as ideal tools for students with little time because they can access increasingly sophisticated content no matter where they are, or when they have time to study. Research in the field of mobile learning is on the rise in recent years. A lot of studies and projects have been conducted to explore the possibilities of mobile phones for educational use. As Mohamed Ally believes, mobile learning is transforming the delivery of education and training. This study finds that mobile learning has growing significance in distance education. The slogan of COL’s (Commonwealth of Learning) Lifelong Learning for Farmers initiative says “Mobile phones: not just a tool for talking, but also a tool for learning.” However, in China, with the world’s greatest number of cell phones, most people still use mobile phones just as a tool for talking or recreation but not a tool for learning. Mobile learning enables learning anywhere at anytime, which matches the mission of Radio & TV Universities (RTVU), the largest provider of open and distance learning (ODL) in China. Nevertheless, mobile learning has not found widespread use at RTVUs except for a few researches focusing on model exploration. This research will explore the use of S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 105–110, 2011. © Springer-Verlag Berlin Heidelberg 2011

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mobile devices in distance learning of English as a Foreign Language (EFL) and commits itself to fitting mobile learning into learners’ daily life.

2 An Overview of Mobile Devices’ Application in Language Teaching The use of mobile phones in language teaching and learning has increased in the last decade. One of the first projects was developed by the Stanford Learning Lab to support Spanish study utilizing both voice and email with mobile phones. These programs offered vocabulary practice, quizzes, word and phrase translations, and access to live talking tutors. Thornton and Houser studied the use of mobile phones in Japan to teach English as a Foreign Language (EFL). They introduced two types of materials for studying EFL on mobile devices. The first, Learning on the Move (LOTM), emailed lessons to students’ mobile phones at timed intervals. The results of pre- and post-tests indicated that the Mobile E-mail students learned about twice the number of vocabulary words as the Web students and the Paper students. The second, Vidioms, display short, Webbased videos and 3D animations and to give visual explanations of English idioms The two projects show that mobile devices such as phones and PDAs can be effective tools for delivering foreign language learning materials to students. Levy and Kennedy created a similar program for Italian learners in Australia in 2005. It sent, in a spaced and scheduled pattern, words and idioms, definitions, and example sentences to students’ cell phones via SMS and requested feedback in the form of quizzes and follow-up questions. In 2007, Cavus and Ibrahim carried out an experimental study to support English vocabulary learning at Near East University by using SMS. They developed a Window-based program on a PC, called the Mobile Learning Tool (MOLT). The mobile phone attached to the PC via Bluetooth interface received SMS text messages and phone numbers from the PC and then sent these messages to the recipient students’ mobile phones at the times requested by the PC. The messages sent are English words with brief descriptions of their meanings. The literature review generally presents a positive and favorable picture of mobile phones in language teaching. While these researches and projects are focused on vocabulary learning and practicing, this research will shift its focus to review, practice and examination preparation.

3 Current State of Distance EFL Learning in China The Ministry of Education requests all colleges to include English in their compulsory curriculum. At regular universities, non-English majors who don't pass the College English Test—Band Four (CET-4) — can't get a degree, while at Radio & TV universities, students who don’t pass a national online examination in English (College English A for English majors and College English B for non-English majors) can’t get a diploma. Government’s emphasis and teachers’ hard work have not produced desired effect in trying to improve students’ proficiency in English. At

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present, most of the distance learners of EFL in China are in-service adults and parttime students, so they are encountering more difficulties than those full-time students at regular universities. 3.1 Lack of English Language Environment In China, English, as a foreign language, is not a language for daily communication, so most students only learn English in classrooms but not use the language in their daily life. Even in classrooms, for most of the time, they are not learning English, instead, they are learning about English. Although the communicative approach places an emphasis on communicative skills rather than grammatical rules and sentence structures, due to a lack of authentic English-speaking situations, many students haven’t developed very good oral communicative skills. It’ true that more students are braver than before and have the nerve to speak in front of people, but there’s not obvious improvement in their listening and speaking skills. When made to speak English, a lot of students are just talking or uttering some English words but not communicating because they can’t form logically complete sentences. That’s because they haven’t developed the concept of English sentence structures, which are very different from those of Chinese. Without a basic concept of English sentence structures, their English writing skills are generally poorer than those of the students taught in traditional approaches such as translation-grammar method etc. Owing to a lack of English language environment as well as imbalanced and hard-to-handle English teaching methodology, English learners often get half the result with twice the effort. This problem is more typical of distance English learners because they are at a distance and self-guided for most of the time. 3.2 Lack of Big Chunk of Time Most of the students at Radio & TV universities in China are working adults and have many roles in one with many conflictive tasks to deal with. They have to take care of their work, family, study etc., so they are always pressed for time. They can’t manage to always give top priority to study and sit down to learn English for even one whole hour without interruption. They only have sporadic and bits of time every day that could be used for study. But many of them even do not know how to make full use of such bits of time, so they don’t have time left for study, which constitutes great impediment to language learning. 3.3 Lack of Constant Exposure to the Learning Contents Radio & TV universities have a hybrid delivery mode, partly online and partly in classroom. In the limited hours of classroom teaching, tutors bombard students with huge amount of information and contents which students can not digest for the present. It needs repeated exposure to the learning materials to digest and internalize what they have learned in the classroom. But the learning materials are in textbooks or online. The working adult students are often on the move, traveling from home to workplace, from workplace to their children’s schools, from this city to that city on business etc. It’s almost impossible for them to carry those thick and heavy books

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about with them and access to a computer and Internet is not always available for every one of them anywhere. Without constant exposure to the learning contents, what they have learned in classroom slips out of their memory quickly. As a result, a lot of the students are constantly in the agony of learning-then-forgetting, learningthen-forgetting. 3.4 Poorly Motivated A large part of the students are poorly motivated. They don’t want to work hard to acquire knowledge so as to work better and live better, or to give themselves a sense of achievement or satisfaction. Their only purpose of getting registered with the university is to get a diploma, which could be helpful to their promotion or anything else. Thus, they don’t care about what they can learn in the process, but focus their attention on examinations. They like exam-oriented teaching very much. All these problems should be blamed for the fact that distance EFL learning is not as effective as desired. Something has to be done to solve some of the problems so as to enhance the delivery of distance English language courses.

4 The Promise of Mobile Device Application in Distance Learning of EFL Since the absolute majority of these distance learners carry mobile devices (especially mobile phones) about with them — almost 24 hours a day and 7 days a week — ,mobile learning could be utilized to solve some of the above problems and improve the situation. As Brown’s Stanford Learning Lab project indicates, mobile phones’ tiny screen sizes are deemed unsuitable for learning new content but effective for review, practice and quiz delivery if delivered in small chunks. Based on the characteristics of distance language learning, this research finds that distance educators should focus their efforts on the following aspects to enable mobile distance language learning. 4.1 Learning Content Representation on Mobile Devices for Review Reading materials such as the passages and articles from the textbook should be redesigned in the format that could be read on mobile devices, such as textfile (.txt). Listening materials should be represented in mp3 or other formats so that they could be retrieved and played on mobile devices. Focal language points, such as words, phrases, collocations, sentence structures could be made in small chunks so that students could make bits of time to review and recite them. In this way, students can store these learning materials in their phones and they can access these materials anywhere at anytime. Since the mobile devices are together with their users almost round-the-clock, this will increase distance learners’ exposure to the learning materials, thus enhancing their language sensitivity, which is of great help to language learning.

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4.2 An Online Submission System for Oral and Written Assignment An assignment submission system should be designed for students to submit their oral and written assignment online. This system should be very easy to use, similar to an email system. Students can read the assignment requirements online, do the assignment and submit it to the system, all of which could be done either on their computers or on mobile phones, whichever is handy for them. As for oral assignment, students can record their own voice responses to the oral tasks and send them back to the teacher for marking, evaluation and feedback. Tutors could retrieve and download students’ submitted assignment through a computer or a mobile phone, mark them and submit their feedback to the system. 4.3 A Mobile Interactive Quiz System An interactive quiz system should be designed for a range of interactive exercises and diagnostic quizzes to help examination preparation. The quizzes should be delivered in small chunks and students could get immediate feedback after submitting their answers. The system should be able to record the students’ points. It would be more appealing for students if it were game-like. Students could earn bonus points toward their continuous assessment by answering the quiz questions. Students can make full use of their bits of time to review what they have learned from the text book as well as tutorials and test themselves even when they just have 5 minutes. Next time when the learner accesses the quiz system, it will start where it stopped last time.

5 Conclusion China has the greatest number of mobile phone users in the world, but mobile phones’ features and capabilities are not fully explored and utilized. This leads to a great waste of mobile resources. While many countries are researching into the use of mobile devices in education, the largest providers of ODL in China, Radio & TV universities should take the initiative to research, explore and develop mobile learning technology for use in its delivery distance courses. Only by doing so could they live up to their promise to allow for learning anywhere at anytime. While a lot of previous researches and projects are focused on vocabulary learning and practicing, this research shifts its focus to review and examination preparation. It finds that the portability of mobile devices could be utilized to address some of the current problems of distance EFL learners, such as lack of constant exposure to learning contents and lack of big chunk of time etc. Mobile learning could become a daily reality for distance EFL learners through learning content representation on mobile devices, an online submission system for oral and written assignment as well as a mobile interactive quiz system. Mobile learning enables students to review what they have learned and prepare for the exams in a more leisurely, relaxed and effective way. It is expected that students would be better prepared for, more confident and achieve better results in the exams than otherwise.

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References 1. Ally, M. (ed.): Mobile Learning Transforming the Delivery of Education and Training (2009) 2. Brown, E. (ed.): Mobile Learning Explorations at the Stanford Learning Lab. Speaking of Computers, vol. 55. Board of Trustees of the Leland Stanford Junior University, Stanford (2001) 3. Cavus, N., Ibrahim, D.: m-Learning: An Experiment in Using SMS to Support Learning New English Language Words. British Journal of Educational Technology 40(1), 78–91 (2009) 4. Cui, G., Wang, S.: Adopting Cell Phones in EFL Teaching and Learning. Journal of Educational Technology Development and Exchange 1(1), 69–80 (2008) 5. Levy, M., Kennedy, C.: Learning Italian via Mobile SMS. In: Kukulska-Hulme, A., Traxler, J. (eds.) Mobile Learning: A Handbook for Educators and Trainers. Taylor and Francis, London (2005) 6. Prensky, M.: What Can You Learn From A Cell Phone? – Almost Anything (2005), Information on http://innovateonline.info/pdf/vol_issue5/ What_Can_You_Learn_from_a_Cell_PhoneAlmostAnything.pdf 7. Thornton, P., Houser, C.: Using Mobile Phones in English Education in Japan. Journal of Computer Assisted Learning 21, 217–228 (2005)

Flood Risk Assessment Based on the Information Diffusion Method Li Qiong School of Mathematics and Physics, Huangshi Institute of Technology, Huangshi, Hubei, China

Abstract. According to the fact that the traditional mathematical statistical model can hardly analyze flood risk issues when the sample size is small, this paper puts forward a model based on information diffusion method. Taking Henan province for example, the risks of different flood grades are obtained. Results show that by using this risk analysis method we can avoid the problem of inaccuracy faults by small sample size, the estimations obtained by this risk method conform with the actual disasters and the method is satisfactory. Keywords: information diffusion, flood, risk assessment.

1 Introduction Flood disasters are more and more frequent in our country, in ordinary flood risk assessment, probability statistics method is the main tools which is used to estimate hydrological variables’ exceedance probability. This method has the advantage that its theory is mature and its application is easy. But when it comes to solving practical problems, problems exist in the feasibility and reliability without considering fuzzy uncertainty. Once encountering small sample problem, results based on the classical statistical methods are very unreliable sometimes. In fact it is rather difficult to collect long sequence of extremum data and the sample is often small. So we can use fuzzy mathematical method for comprehensively disaster risk evaluation. This paper uses information diffusion-a fuzzy mathematics method to establish flood risk assessment model with small sample and then applies it to the flood risk analysis in henan province successfully.

2 Information Diffusion Information diffusion is a fuzzy mathematic set-value method for samples, considering optimizing the use of fuzzy information of samples in order to offset the information deficiency([1],[2],[3],[4]). The method can turn an observed sample into a fuzzy set, that is, turn a single point sample into a set-value sample. The simplest model of information diffusion is normal diffusion model. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 111–117, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Information diffusion: Let X be a set of samples, and V be a subset of the universe,

μ : X × V → [0,1] is a mapping from X × V kind of information diffusion of

to [0,1]. ∀( x, v) ∈ X × V is called a

X on V .

If the random variables’ domain is discrete, suppose it is

∑ μ ( x, u ) = 1 ， ∀x ∈ X . m

conservation condition is

U = {u1 , u2 ," , um } , the

j

j =1

X = {x1 , x2 ," , xn } be a sample, and U = {u1 , u2 ," , um } be the discrete universe of X. xi and u j are called a sample point and a monitoring point, respectively. ∀xi ∈ X ∀u j ∈ U we diffuse the information carried by xi to u j at gain fi (u j ) by using the normal information diffusion shown in Eq. (1). Let

，

，

⎡ ( x − u )2 ⎤ fi (u j ) = exp ⎢ − i 2 j ⎥ 2h ⎢⎣ ⎥⎦

， u ∈U j

(1)

where h is called normal diffusion coefficient, calculated by Eq. (2). n = 5; ⎧ 0.8146(b − a), ⎪ 0.5690(b − a), n = 6; ⎪ ⎪ 0.4560(b − a), n = 7; ⎪ h = ⎨ 0.3860(b − a), n = 8; ⎪ 0.3362(b − a), n = 9; ⎪ n = 10; ⎪ 0.2986(b − a), ⎪ ⎩0.6851(b − a) / (n − 1), n ≥ 11

where

（2)

b = max{xi }; a = min{xi } 1≤i ≤ n

1≤i ≤ n

m

Ci = ∑ f i (u j ) j =1

（3)

Let We obtain a normalized information distribution on U determined by xi , shown in Eq. (4).

μ x (u j ) = i

f i (u j ) Ci

（4)

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113

For each monitoring point u j , summing all normalized information, we obtain the information gain at u j , which came from the given sample X. The information gain is shown in Eq. (5).

（5)

n

q(u j ) = ∑ μ xi (u j ) i =1

q(u j ) means that, with the information diffusion technique we infer that there are q(u j ) (generally is not an integer) sample points in terms of statistic averaging at the monitoring point

u j .Obviously q(u j ) is not usually a positive integer, but is certainly m

a number not less than zero. And assumption the sample size of all

Q = ∑ q(u j ) j =1

, (6) where Q is the sum of

q(u j ) , theoretically, there will be Q = n, but due to the numerical

calculation error, there is a slight difference between Q and n. Therefore, we can employ Eq. (7) to estimate the frequency value of a sample falling at

p(u j ) =

uj .

（7)

q(u j ) Q

The frequency value can be taken as the estimation value of its probability. Apparently, the probability value of transcending

u j should be

m

P (u j ) = ∑ p (u j )

(8)

k= j

P (u j ) is the required risk estimation value.

3 Application Example 3.1 Flood Disaster Index According to the 41 years’ practical series material from 1950 to 1990 in henna province, we take disaster area and direct economic loss as the disaster degree’s index and by frequency analysis the floods are classified into four grades as seen in table 1, and the four flood grades are small, medium, large and extreme flood.

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Table 1. Henan flood disaster rating standard Inundated area˄hm2˅ Direct economic losses (Billion

Disaster level

Grade

yuan)

number

small flood

0~46.7

0~9.5

1

medium

46.7~136.7

9.5~31.0

2

large flood

136.7~283.3

31.0~85.0

3

extreme

283.3~

85.0~

4

flood

flood

Table 2. Disaster index based on the projection pursuit model number

Inundated

Direct

Degree

area

economic

value

˄hm2˅

losses

number

Inundated

Direct

Degree

area

economic

value

˄hm2˅

losses(Billion

(Billion

yuan)

yuan) i

X(1,i)

X(2,i)

i

X(1,i)

X(2,i)

1

38.70

7.900

1.369

17

157.30

38.600

2.486

2

38.50

7.800

1.366

18

283.30

85.000

3.498

3

32.10

6.500

1.315

19

556.90

67.100

3.967

4

24.20

4.900

1.256

20

649.50

194.900

3.987

5

36.40

7.400

1.350

21

602.30

180.700

3.979

6

46.70

9.500

1.432

22

446.50

134.000

3.897

7

97.60

21.700

1.895

23

694.90

208.500

3.992

8

60.40

12.800

1.552

24

72.92

9.900

1.574

9

112.60

25.200

2.033

25

148.13

20.656

2.156

10

56.20

11.800

1.515

26

203.92

27.521

2.559

11

80.60

17.600

1.736

27

179.10

24.858

2.389

12

136.70

31.000

2.258

28

375.46

94.927

3.726

13

259.10

76.100

3.363

29

301.24

47.836

3.233

14

200.10

54.400

2.915

30

141.97

116.439

3.368

15

280.10

83.800

3.481

31

279.84

121.127

3.699

16

236.10

67.600

3.209

32

172.06

51.619

2.750

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115

To raise the grade resolution of flood disaster loss, a new model—projection pursuit (PP) model ([5]) is used for evaluating the grade of flood disaster and the flood degree values are calculated as in table 2. 3.2 Flood Risk Evaluation Based on Information Diffusion Based on the disaster degree values of the 32 samples (see Table 2), that is the sample points set

X = {x1 , x2 ," , x32 } .The universe discourse of the disaster degree values

namely the monitoring points set is taken as U = {u1 , u2 ," , u41} = {0, 0.1, 0.2," 4.0} . The normalized information distribution of each xi ,that is, μ x (u j ) ,can be obtained i according to equation (1)(2)(3)and(4)

， then based on equation (5),(6),(7)and(8),

disaster risk estimate namely probability risk value in Henan province is calculated out. The relationship between the recurrence interval

N and probability p can be

expressed as N = 1 p , then the exceedance probability curve of flood to disaster degree value are shown as Figure 1.

Fig. 1. The exceedance probability curves of flood to disaster degree value based on information diffusion and frequency analysis

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Due to the standard of four grades, so we have Chen (2009) ([6]): (a) If 1.0 ≤ H ≤ 1.5,then desertification degree belongs to small (1 grade). (b) If 1.5 < H ≤ 2.5,then it belongs to medium (2 grade). (c) If 2.5 < H ≤ 3.5, then it belongs to large (3 grade). (d) If 3.5 < H ≤ 4, then it belongs to extreme (4 grade) The result in Figure 1 illustrates the risk estimation i.e. the probability of exceeding the disaster degree value. From Figure 1 we know the risk estimation is 0.2745 when the disaster index is 3.5, in other wods, in Henan Prvince, floods exceeding 3.5 degree value (extreme floods) occur every 3.64 years. Similarly, the probability of floods exceeding 2.5 degree(large floods) is 0.5273, namely Henan Province suffers the floods exceeding that intensity every 1.90 years. This indicate the serious situation of floods in Henan Province whether on the aspect of frequency or intensity . In Figure 1 the curve so estimated is compared to the frequency analysis based on the results of Jin et al.([5]). Figure 1 shows that our results are consistent with those of frequency analysis. It also means that normal information diffusion is useful to analyze probability risk of flood disaster. Because the flood disaster belong to the fuzzy events with incomplete data, therefore, the method proposed is better than frequency method to analyze the risk of the flood disaster.

4 Conclusion Floods occur frequently in China and cause great property losses and casualties. In order to implement a compensation and disaster reduction plan, the losses caused by flood disasters are among critically important information to flood disaster managers. This study develops a method of flood risk assessment disasters based on information diffusion method, and it can be easily extended to other natural disasters. It has been tested that the method is reliable and the results are consistent with the real values.

References 1. Huang, C.F.: Integration degree of risk in terms of scene and application. Stochastic Environmental Research and Risk Assessment 23(4), 473–484 (2009) 2. Huang, C.F.: Information diffusion techniques and small-sample problem. Internat. J. Information Technol. Decision Making 1(2), 229–249 (2002) 3. Huang, C.F.: Risk Assessment of Natural Disaster: Theory & Practice, pp. 86–98. Science Press, Beijing (2005) 4. Huang, C.F., Shi, Y.: Towards Efficient Fuzzy Information Processing-Using the Principle of Information Diffusion. Physica-Verlag (Springer), Heidelberg, Germany (2002) 5. Jin, J.L., Zhang, X.L., Ding, J.: Projection Pursuit Model for Evaluating Grade of Flood Disaster Loss. Systems Engineering-theory & Practice 22(2), 140–144 (2002) 6. Chen, S.Y.: Theory and model of variable fuzzy sets and its application. Dalian University of Technology Press, Dalian (2009)

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7. Chen, S.Y.: Fuzzy recognition theory and application for complex water resources system optimization. Jilin University Press, Changchun (2002) 8. Chen, S.Y.: Theory and model of engineering variable fuzzy sets - mathematical basis for fuzzy hydrology and water resources. Journal of Dalian University of Technology 45(2), 308–312 (2005) 9. Jin, J.L., Jin, B.M., Yang, X.H., Ding, J.: A practical scheme for establishing grade model of flood disaster loss. Journal of Catastrophology 15(2), 1–6 (2000)

Dielectric Characteristics of Chrome Contaminated Soil Yakun Sun, Yuqiang Liu, Changxin Nai, and Lu Dong Research Institute of Solid Waste Management, Chinese Research Academy of Environmental Sciences, No.8 Dayangfang BeiYuan Road, Beijing, 100012, China [email protected]

Abstract. In order to research the feasibility of monitoring chromium contaminated field using complex dielectric constant method, we designed an experiment to compare the soil complex dielectric constants in conditions of different chromium pollution concentration, soil water content and void ratio. The result shows that, the complex dielectric constant of contaminated soil decreases obviously with the increasing frequency. And, when the frequency is lower than 50MHz, a significant change of the real and imaginary parts of soil complex dielectric constant can be observed. Moreover, with the increasing chromium pollutants concentration, water content and void ratio, both of the real and imaginary parts of soil complex dielectric constant increase as well. With the analysis of the relationship among soil dielectric constant, moisture content, and chromium pollution concentration, we built two soil dielectric constant models on the real quantity and imaginary quantity. Therefore, through the comparison of the real and imaginary quantity of the complex dielectric constant, we could evaluate and monitor the chrome pollutions. Keywords: chrome contaminated soil, complex dielectric constant, dielectric dispersion, electrical monitoring method.

1 Introduction Recently, nearly all the chromium contaminated soil is due to chromium residue, and chromium residue is a kind of hazardous waste containing Cr6+, which is caused in the proceeding of chromium salt production. Now the unsettled chromium residue is still up to 400 million tons, crossing more than 20 provinces of the whole country[1]. Some chromium salt enterprises closed down after the chromium production, and the chromium waste residue is placed directly on the open air without any windproof, waterproof and leakproof facilities, so most of the domestic chromium contaminated sites formed. Some contaminated sites are near the surface water, and the leaching Cr6+ caused serious groundwater, surface water and soil pollution[1-3]. The former work of contaminated sites restoration is to monitor the pollution accurately. Currently to monitor the contaminated soil and groundwater, the basic way is to collect samples for the physical and chemical analysis, however, this traditional S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 118–122, 2011. © Springer-Verlag Berlin Heidelberg 2011

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method may consume much time and high cost [4-6]. There are obvious shortcomings: the samples is limited, and it is difficult to achieve a thorough understanding of the pollution conditions; geological drilling could destroy the original pollutants distribution and concentration in the ground, and easily make the pollutants migrate to the deeper layer of the ground; monitoring period is very long, not suitable for long-term monitoring. Because of the above problems, a rapid and effective monitoring method needs to be developed in the chromium contaminated sites. Geophysical studies show that as a very important parameter, the dielectric properties are rapid and non-destructive in the measurement[7], so dielectric properties of the contaminated soil may evaluate the underground pollution conditions[8]. Dielectric constant, also known as the permittivity, dimensionless, is a factor that shows insulation material properties; it is to measure the degree of charge polarization in external electric field. In the previous study of dielectric properties of soil, relationship between dielectric properties and water content, soil contaminants is researched [9-11]. There is no report about the complex dielectric constant of chromium contaminated soil. This study will search for the relationship between complex dielectric constant and physicochemical property (such as water content, pollutant concentration and void ratio) of chromium contaminated soil at the different frequency.

②

③

2 Materials and Methods 2.1 Soil Sampling and Pretreatment Use random distribution methods in soil sampling. The main pollutants in the contaminated sites are Na2CrO4 and Na2Cr2O4. As the need for simulation with the contaminated soil in the sites, adding the Na2CrO4 into the unpolluted soil to make the soil sample. Each soil sample is about 100g after quartation. Table 1 shows the physical properties of soil samples, and table 2 shows the leachate concentration of the soil samples. Table 1. Physical properties of soil sample ²/

w/% pH

7.61

sand

slit

clay

˄g/cm3˅

23.0

63.3

13.7

2.62

CEC/(cmol/kg)

TOC/%

T/ć

7.61

8.42

20

（mg/kg）

Table 2. Leachate concentration of soil sample Na+

K+

Mg2+

Ca2+

Ba2+

SO42-

Cl-

CO32-

3.24

0.78

1.23

5.68

1.02

2.56

6.01

1.43

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2.2 Experimental Analysis The pollutant concentration, water content and frequency are the main factors of the complex dielectric constant. And prepare a series of soil samples with different concentrations of chromium contamination (50, 100, 150, 200, 500, 1000mg/kg), different water content (8, 15, 25%). In the range of 10MHz to 200MHz frequency, the real and imaginary parts of soil samples are measured by Agilent E5061A microwave network analyzer.

3 Experimental Results 3.1 Water Content Figure 1 shows the soil samples complex dielectric constant with different water contents. Both the real and imaginary parts of samples decrease when the frequency increases. When the frequency is less than 50MHz, the real and imaginary part sharply decline; when higher than 50MHz, the downward trend is smooth. The imaginary part is largely affected by water content, and the real part is not affected by water content significantly.

Fig. 1. Dielectric dispersion characteristics of 1000mg/kg chrome contaminated soil

3.2 Concentration of Chromium Pollutants Figure 2 shows the constant properties of samples with different pollutants concentration. Overall, as the frequency increases, complex dielectric constant is gradually decreased. In the low frequency range (below 100MHz), the real part has a slight rise with the increasing pollutants concentration; when above 100MHz, the decreasing trend is small; the real part stay stable with 200MHz. Water and air co-exist in the soil pores, and the charge polarization on the gas-solid interface of the soil pores makes the real part increase. The imaginary part rises with the pollutants increase when the frequency is below 50MHz.

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Fig. 2. Dielectric dispersion characteristics of different chrome pollution

3.3 Dielectric Model of Soil Based on the above analysis, considering the water content, void ratio and other factors impact on the soil constant, the real part could be represented by extending Topps formula[9]

θ v = mε + nε 2 + pε 3 + kρ b Where and

ρb

ε

is real part of dielectric constant.

θv

(1)

is volumetric water content of soil,

is volume weight of soil. According to the experimental data, the formula is

given as

θ v = 9.548 × 10−4 ε − 7.605 × 10−5 ε 2 + 1.951×10 −6 ε 3 + 8.694 ×10 −2 ρb

(2)

The relationship between pollution concentration and imaginary part could be represented by empirical formula as[12]

ε ′ = K1θ vα w β + K 2 Where

ε′

is imaginary part.

θv

is volumetric water content of soil, and

(3)

w is

pollution concentration. According to the experimental data, this equation is given as

ε ′ = 4.312θ v 0.669 w 0.546 + 10.586

(4)

Therefore, taking into account real part and imaginary part, dielectric method could be used in the evaluation of chromium polluted soil.

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4 Conclusions In the conditions of different water content and pollution concentration, both the real part and imaginary part of soil samples dielectric constant have a significant dispersion. The complex dielectric constant has a dramatic change when the frequency is below 50MHz, therefore, 10-50MHz is the suitable frequency range for the dielectric constant measurement. As the real part is largely affected by the water content, the imaginary part is necessary for the evaluation of the chromium pollution in the soil. And the complex dielectric method could be used in the chromium pollution monitoring. Acknowledgement. This research was financed by the Chinese central commonweal research institute basic scientific research special project (2009KYYW04), and by the National High-tech Research and Development (863) Program (2007AA061303).

References 1. Gu, C., Shan, Z., Wang, R.: Investigation on pollution of chromic slag to local soil. Mining Safety & Environmental Protection 32, 18–20 (2005) (in Chinese) 2. Li, J., Zhu, J., Xie, M.: Chromium and health. Trace Elements Science 4, 8–10 (1997) (in Chinese) 3. Zhang, H., Wang, X., Chen, C.: Study on the polluting property of chrome residue contaminated sites in plateau section. Chinese Journal of Environmental Engineering 4, 915–918 (2010) (in Chinese) 4. Cheng, Y., Yang, J., Zhao, Z.: Status and development of environmental geophysics. Progress in Geophysics 22, 1364–1369 (2007) (in Chinese) 5. Li, Z., Nai, C., Nian, N.: Application and prospect of physical exploring technology for solid waste. Environmental Science & Technology 29, 93–95 (2006) (in Chinese) 6. Kaya, A., Fang, H.Y.: Identification of contaminated soils by dielectric constant and electrical conductivity. Journal of Environmental Engineering 123, 169–177 (1997) 7. Campbell, J.E.: Dielectric properties and influence of conductivity in soils at one to fifty megahertz. Soil Science Society of America 54, 332–341 (1990) 8. Thevenayagam, S.: Environmental soil characterization using electric dispersion. In: Proceedings of the ASCE. Special Conference of the Geoenvironment 2000, pp. 137–150. ASCE, New York (2000) 9. Topp, G.C., Davis, J.L., Annan, P.: Soil water content: measurements in coaxial transmission lines. Water Resource 16, 574–582 (1980) 10. Dobson, M.C., Ulaby, F., Hallikainen, T., et al.: Microwave dielectric behavior of wet soil. Part II. Dielectric mixing models. IEEE Transactions on Geoscience and Remote Sensing 23, 35–46 (1985) 11. Arulanandan, K.: Electrical dispersion in relation to soil structure. Journal of the Soil Mechanics and Foundations Division 99, 1113–1133 (1973) 12. Francesco, S., Giancarlo, P., Raffaele, P.: A strategy for the determination of the dielectric permittivity of a lossy soil exploiting GPR surface measurements and a cooperative target. Journal of Applied Geophysics 67, 288–295 (2009)

Influences of Climate on Forest Fire during the Period from 2000 to 2009 in Hunan Province ZhiGang Han1,2, DaLun Tian1,2, and Gui Zhang1 1

Central-South University of Forestry and Technology, 498 Shaoshan South Road, Changsha, 410004, China 2 National Engineering Laboratory of Southern Forestry Ecological Applied Technology, 498 Shaoshan South Road, Changsha, 410004, China [email protected], [email protected], [email protected]

Abstract. Climate change affects the dynamic changes of forest fire. This paper aims to analyze the influence of climate on forest fire in Hunan province by using multiple linear regression and correlation analysis. The results showed that the average affected area of forest and forest loss caused by forest fire showed a significant linear relationship with climate and could be expressed by multiple regression equation. According to the meteorological factors, we can forecast the trend of forest fire development in most areas of Hunan. The formation of a large number of fuel was caused by ice crystal pressure off forests during special freezing climate, which led to remarkably increasing occurrence of forest fire. The correlation coefficient between the thickness of ice during freezing disaster and the frequency of forest fire in March after disaster reached 0.798 with significant correlation. Keywords: Hunan, forest fire, climate, multivariate regression analysis, correlation analysis, freezing.

1 Introduction Climate is an important factor in dynamic change of forest fire. The dynamic change can lead to climate change of forest fire in frequency occurrence, fire area, fire cycle can change the structure and function of forest landscape[1~3]. With the population increasing, the influence of human activities on forest fire is growing, but climate is still the dominant factor of forest fire dynamic change[4,5]. Since the early 1900s, the global average surface temperature has increased by 0.74 , the average temperature increase rate over the past 50 years is almost twice over the past 100 years[6]. As the global gets warming, the extreme weather events such as El Niño, droughts, floods, thunderstorms, hail, storms, high temperatures and sandstorms occur frequently both in their frequency and intensity. Under the extreme weather conditions, the condition of forest fire is key to the research of relationship between the climate and forest fire. In various countries, the scientists have studied the relationship between abnormal climate and forest fire, the results show that: Along with the global warming, the accelerating

℃

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frequency of the extreme weather affected the changes in forest fire danger and increased the possibility of forest fire and extra serious forest fire in the extreme weather areas[7~12]. The study of relationship between the climate change and forest fire has a great practical significance in forestry production, which is the important basis in national and local formulated long-term forest management strategy[13]. Hunan province has abundant forest resources and frequent forest fire. In recent years, the annual temperature has rised, the rainfall has declined gradually and the rare freezing weather has occurred in Hunan. Those factors result in the increase of the forest fire and the decrease of the industrial and agricultural production, a serious threat to people's life and property security. This paper has set Hunan province as the research area, studied and quantified various meteorological factors and forest factor relations, explored the occurrence and development in different counties and cities of Hunan under the climatic conditions’ influence, which has a great significance to the proper management of forest fire.

2 Data Sources and Methods 2.1 Research Areas Review Hunan province is located in the east between 108°47'~114°15' and north between 24°38'~30°08', which is subtropical monsoon climate, with the features of the mild climate, concentrated rainfall and rich sunlight resources. The yearly mean temperature is around 16 ~18.5 , the annual average duration of sunshine is 1250~1850 hours, the yearly precipitation is 1200~1700mm. Hunan covers a total area of 211875 square kilometers and is characteristic of abundant mountains and hills. It is an important agricultural province in the south of China. Hunan is troubled with frequent forest fire, 18782 fires during 2000~2009. Due to the huge agricultural population, productive fire is the main cause for forest fire which accounts for 62% of the total number, unproductive fire 31%, thunders and other natural fire less, which occur only 20 times during 2000~2009. Winter and spring are seasons of forest fire. Fires take place the most from February to April.

℃

℃

2.2 Data Sources Wildfires data is from the statistical data of Hunan forest public security bureau and Hunan forest fire prevention headquarters, which includes forest fire records of 101 counties from 2000 to 2009. Because of the missing data of forest fire affected area, trees loss and economic loss, this paper has analyzed the mean from various parameters of statistical data at hand. The meteorological data comes from the weather data from 2000 to 2009 of the 46 meteorological stations distributed evenly in Hunan. This paper calculated the missing data by interpolation, and finally got the climate factors of temperature, precipitation, humidity, sunshine and wind speed’s yearly and monthly average values.

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2.3 Analysis Method As multiple meteorological factors and forest fire factors are related, namely multiple meteorological factors have much influence on forest fire occurrence. Therefore, multiple linear regression analysis method is used in analyzing their mutual relationship, with each forest factors variables as the dependent variable, each meteorological factors variables as the independent variables. The dependent variable and independent variables respectively are:

⎡Y1 ⎤ ⎢Y ⎥ Y =⎢ 2⎥ ⎢# ⎥ ⎢ ⎥ ⎣YP ⎦

，

⎡ x1 ⎤ ⎢x ⎥ 2 X =⎢ ⎥ ⎢# ⎥ ⎢ ⎥ ⎣ xm ⎦

，

⎡ σ 12 σ 12 ⎢ σ 21 σ 22 Σ=⎢ ⎢ # # ⎢ σ σ p2 ⎣⎢ p1

" σ1p ⎤ ⎥ " σ 2p ⎥ # # ⎥ ⎥ " σ p2 ⎦⎥

(1)

Among them, Y ~ N p (μY , ΣY ), μ y = (μY , μY ,", μY )T , X is normal vector or general 1 2 P vector, and set that Y with X exist linear regression relationship, namely at the point of X , the Y expectations (average) are:

⎧ y1 = β 01 + β 11 x1 + β 21 x 2 + " + β m1 x m , ⎪ ⎪ y 2 = β 02 + β12 x1 + β 22 x 2 + " + β m 2 x m , ⎨ # ⎪ ⎪ y p = β 0 p + β1 p x1 + β 2 p x 2 + " + β mp x m . ⎩

(2)

The formula is called Y linear regression equation about X [13]. 101 counties of Hunan Province as a unit, select a total of four indicators including the frequency of forest fire, the average area of affected forest (hm2/time), the average forest tree loss (m3/time), the average economic loss (ten thousand RMB /time) as dependent variables, and 7 indicators of the annual average temperature, annual precipitation, annual relative humidity, annual average wind speed, annual sunshine hours, stumpage stock and regional altitude as independent variables. The paper extracted 280 sets of data from the statistical data, made multiple linear regression analysis, regression effect test and prediction error test. There are some exceptions in the statistical data, such as the incidental data (forest fire increase sharply) during the special freezing climate period and the data of much less fire areas (average annual number of forest fire is 0 to 3 times) including Hengyang, Changsha, Xiangyin, Yuanjiang, Anxiang, Huarong. As these data can not reflect the inherent relationship between meteorological factors and forest fire factors in normal climatic conditions, and thus affect the accuracy of the model, so they should be removed beforehand. In early 2008, Hunan affected a freezing disaster, the number of forest fire increased dramatically after the disaster. The climate data such as the temperature, relative humidity, ice thickness during the disaster and the regional forest fire data in February and March were collected and studied. The correlation and comparative analysis of the forest fire data in February, March and the meteorological data during the disaster had been done respectively.

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3 Results and Analysis 3.1 Multiple Regression Analysis of Forest Fire and Climate The frequency of forest fire, the average fire forest area, average fire forest loss and average economic loss are expressed by Y1, Y2, Y3 and Y4 respectively, x1, x2, x3, x4, x5. x6 and x7 separately stand for annual average temperature, annual precipitation, annual sunshine hours, annual average relative humidity, annual average wind speed, altitude and stumpage. The relationship calculated by multiple linear regression analysis between forest fire factors and meteorological, environmental factors is respectively showed as follow: (1) Regression equation of forest fire number and meteorological factors: Y1 = −42.6291+ 5.433x1 − 0.0075x2 − 0.008x3 + 0.2502x4 − 4.9669x5 − 0.0046x6

(3)

R =0.149281, F = 1.0371, p=0.4014. (2) Regression equation of average affected forest area and meteorological factors: Y2 = −8.0579 + 0.2625x1 − 0.0013x2 + 0.004x3 + 0.0946x4 − 0.4996x5 + 0.0011x 6

(4)

R =0.815992, F =90.6637, p=0.001. (3) Regression equation of average tree loss and meteorological factors: Y3 = −1.3983 + 1.1236x1 − 0.0138x2 + 0.0203x3 + 0.4686x4 − 0.0624x5 + 0.0035x6

(5)

R =0.832049, F =102.3741, p=0.001. (4) Regression equation of average economic loss and meteorological factors: Y4 = 3.5646 − 0.1853x1 + 0.003 x2 + 0.001x3 − 0.0046 x 4 + 0.1456 x5 + 0.0002 x6

(6)

R =0.092729, F =0.3946, p=0.8822. In the equation above, the all estimated coefficients (x7) of stumpage volume are zero, indicating that the stumpage volume united by county and the forest fire factors has no linear corresponding relationship. Four regression models results are: the number of forest fire (Y1), economic losses of forest fire (Y4) and the regression coefficient R and F values of meteorological factors are too small, p is not at the significant level (p>0.05). Therefore, the regression relationship is not obvious. The reason is that the forest fire source in Hunan is mainly from productive and non- productive fire, the forest fire caused by human activities account for more than 93% of the total forest fire number, there is no significant linear relationship between the fire occurrence number and meteorological factors each year in different counties and cities. Meanwhile, fire economic loss statistics are mainly based on the fire suppression expenditures and other losses (the estimated value of other losses), which also have no significant correlation between meteorological factors. The regression coefficient R between the average area of affected forest (Y2), average forest loss (Y3) and the meteorological factors gets over 0.8, F is large, there is significant difference (p <0.05). We get 20 groups random sample from the statistics (not including modeling data) for further testing of the two regression equations, the results can be seen in Tab.1 and

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Tab.2: the average difference of the predictive and the actual sampling data between the average area of affected forest and meteorological factors model is 0.183. The mean difference of the predictive and the actual sampling data between average forest loss and meteorological factors model is 7.5242. The results show that the predicting and actual values are close to each other and the regression model (4) and (5) can accurately predict the average affected forest area and the average forest loss. Table 1. Validation of regression equation for average area of forest damage and meteorological data The average area of affected forest (hm2 / time)

Mean

Maximum

Minimum

Actual value

3.205

4.1

1.4

Predictive value

3.388

4.0379

2.4282

Difference

0.183

-0.23592

2.0582

Table 2. Validation of regression equation for average forest lost and meteorological data The average forest loss (m3 / time)

Mean

Maximum

Minimum

Actual value

59.01947

69.5924

49.5288

Predictive value

66.7947

60.17163

48.9252

Difference

7.5242

-9.8265

-1.13448

3.2 Special Freezing Climate Influence on Forest Fire In recent years, under the influence of global climate change, the frequency of special climate is increasing in Hunan, which has a significant impact on forest fire. Especially in early 2008 (from 13th January to 3rd February), there was low temperature freezing weather in a large area of Hunan, causing the probability of forest fire increasing (Fig.1). As the result of the correlative analysis between the fire frequency of affected area and temperature of the ice disaster on February and March in 2008, the correlation coefficient between every region’s fire and the temperature is 0.095 in February, 0.352 in March. At the same time, the history data shows Changsha area minimum temperatures reached -9.5℃ on 31st January, 1969 and -11.3℃ on 9th February, 1972. And the minimum temperature of Chenzhou reached -9℃ on 11th January, 1955[14]. According to the historical record, it was said that the temperature of each district was below this temperature of the weather at the same period, but neither such ice freezing phenomenon on a large-scale appeared, nor the increasing frequency of forest fire caused by large-scale affected forest occurred. These indicate that the temperature is not the key element to trees loss caused by the wildfires after the ice disaster.

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2500

se2000 ri f1500 ts er1000 oF 500

s2000 e r i1500 f t s1000 e r o F 500 0

0 1 2 3 4 5 6 7 8 9 10 11 12

month

a) forest fire in previous years

1 2 3 4 5 6 7 8 9 10 11 12

month

b) forest fire in 2008

Fig. 1. The number of forest fire in previous years (average monthly) and in 2008 ( each month)

The results of the correlative analysis between the fire frequency of affected area and the relative humidity on February and March in 2008 show that the correlation coefficient between every region’s fire and the relative humidity is 0.171 in February, 0.268 in March. The correlation is not significant, too. The sharp rise of the frequency of forest fire after freezing disaster is attributed to the ice crystals which are formed and accumulated under the special climate conditions in freeze disaster. And these make the branches and trunks mechanically wrecked, lots of combustible fuel formed. While ice crystals are created under the specific climate condition of nearly saturated relative humidity cooperated with moderate low temperature in a long time. Therefore, we can study the influence of climate on forest fire during the freeze disaster by analyzing the relationship among ice crystals, climate and forest fire. As the result of the correlative analysis between the ice thickness of each area and climate conditions, the correlative coefficient between the ice thickness and the days (relative humidity≥85%) is 0.59, the correlative coefficient between the ice thickness and the days (relative humidity≥85% and temperature below 0 ℃ ) is 0.648, the correlative coefficient between the ice thickness and the days (relative humidity≥85% and -1~0℃) is 0.75. The number of forest fire in February and March of 2008 and the thickness of ice during the freezing disaster are used to analyze their correlation respectively(Tab.3). The results show that: in February, the correlation coefficient between the number of forest fire and the ice thickness during the freezing disaster is 0.596, while the correlation coefficient in March is 0.798, the correlation is significant. The above analyses indicate that the freezing disaster on forest fire mainly makes an effect on the formation of ice crystals in an appropriate climatic condition (air relative humidity≥85% and the temperature is kept at -1~0℃). Under this condition, the climate period gets longer, the ice gets thicker. Ice accumulation causes trees impairment, makes combustible fuel formed, and then the probability of forest fire increases correspondingly, the ice thickness and the number of forest fire after disaster is positive correlation.

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Table 3. Thickness of ice accumulated around electric wires and the number of forest fire during ice disaster 2008 Site

Chenzhou

Yongzhou

Changsha

Loudi

Yiyang

Changde

thickness of ice（mm）

341

335

250

174

148

34

number of forest fire in February

70

65

36

55

48

59

number of forest fire in March

376

167

232

190

102

46

After the freezing disaster, the number of forest fire in February in Hunan is 1030 times, it sharply rises to 2744 times until March. As to the correlation analysis between the ice thickness and forest fire number in February and March, the impact of freezing disaster on forest fire number is delayed. According to the number of forest fire each time in February and March (10 days as a period), from Feb.1 to Feb.10, the number of forest fire is 85, from Feb.11 to Feb.20 and Feb.21 to Feb.29, 472 and 473 respectively. From March 1 to March 10, the number of forest fire is up to 2300, 84% of forest fire in March. It can be concluded that March 1~10 is the hot time of forest fire affected by the freezing disaster, and the lag effect is about one month. After the freezing disaster, climate gets warming, human activities gradually resume, coupled with the formation of lots of combustible fuel during the freezing disaster period, a large number of forest fire occur finally. Fitting the ice thickness with the number of forest fire in March of affected areas during the ice storm, we set y as the number of fire, x as the ice thickness, then the fitting curve is y = 2.9674x0.7672 , the confidence level is 95%, R2 is 0.8241.

4 Conclusion As more than 93% fires in Hunan are man-made fires, there is no significant linear relationship between the climate and the forest fire number. However, the average forest fire affected area and average forest fire loss have a linear relationship with meteorological factors, it can be expressed by multiple regression equation. According to the meteorological factors, we can forecast the trend of forest fire development under the general climatic conditions in most areas of Hunan. But the model does not apply to so few forest fire and frozen areas. The special freezing climate largely affects the forest fire by making the ice crystals formed under the appropriate climate condition. And ice accumulation causes trees impairment, makes combustible fuel formed, and then the probability of forest fire increases correspondingly, the number of forest fire finally surged greatly in February and March after the freezing disaster. The correlation coefficient between the thickness of ice during the freezing disaster and the number of forest fire in March is at 0.798.

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The impact of the freezing disaster on forest fire is delayed, the delay period is about one month. Therefore, the use of the delay time to reinforce the combustible fuel removing and standardize the forestry activities after the disaster is important and effective to the forest fire management. Acknowledgment. This work was carried out at the Natural Science Foundation program of Hunan Province of “Studies on the Influences of Global Climate Change on the Spatial -temporal Pattern of Forest Fire in Hunan”.

References 1. Florent, M., Serge, R., Richard, J.: Simulating climate change impacts on fire frequency and vegetation dynamics in a Mediterranean-type ecosystem. Global Change Biology 8(5), 423–437 (2002) 2. Donald, M., Gedalof, Z., David, L., Peterson,, Philip, M.: Climatic change, Wildfire, and Conservation. Conservation Biology 18(4), 890–902 (2004) 3. Tian, X., Shu, L., Wang, Y.: Forest fire and climatic change review. World Forestry Research 19(5), 38–42 (2006) 4. Mollicone, D., Eva, H.D., Achard, F.: Ecology: human role in Russian wild fires. Nature 440, 436–437 (2006) 5. Shu, L., Tian, X.: The forest fire conditions in recent 10 years. World Forestry Research 11(6), 31–36 (1998) 6. WMO. Press Release No.805, http://www.wmo.int/pages/index_zh.html 7. Williams, A.A.J., Karoly, D.J.: Extreme fire weather in Australia and the impact of the El Nino Southern Oscillation. Australian Meteorological Magazine 48, 15–22 (1999) 8. Wang, S.: The Study of the causes regularity of forest fire on big time scale and the prediction theory in medium-term. Technology Metallurgica (2), 47–50 (1994) 9. Zhao, F., Shu, L., Tian, X.: The forest combustible fuel dry conditions changes of Daxinanling forest region in Inner Mongolia under the climate warming. Ecological Journal 29(4), 1914–1920 (2009) 10. Ding, Y., Ren, G., Shi, G.: National Climate Change Assessment Report (I).Chinese Climate Change History and Future Trends. Climate Change Review 2(1), 3–8 (2006) 11. Zhang, T.: The Impact Analysis and Suggestion of Guangdong Freeze Disaster on Forest fire. Forestry Survey Planning 33(5), 79–84 (2008) 12. Zhao, F., Shu, L.: The Study of climatic abnormal’s impact on forest fire. Forest Fire Prevention (1), 21–22 (2007) 13. Yuan, Z., Song, S.: Multiple Statistical Analysis. Science Press, Beijing (2009) 14. Liu, X., Tan, Z., Yuan, Y.: The Cause of Hunan Freezing Disaster Weather Damage to Forest. Forestry Science 44(11), 134–140 (2008)

Numerical Simulation for Optimal Harvesting Strategies of Fish Stock in Fluctuating Environment Lulu Li1, Wen Zhao1, Lijuan Cao2, and Hongyan Ao1 1

College of Life Science and Biotechnology, Dalian Ocean University, Dalian, China, 116024 2 Institute of Mechanical Engineering, Dalian Ocean University, Dalian, China, 116024 {zhaowen,clj}@dlou.edu.cn

Abstract. The population size of fish stock is affected by the variability of its environment, both biologic and economic. The classical logistic growth equation is applied to simulate fish population dynamics. Environmental variation was included in the optimization of harvest to obtain a relation in which the maximum sustainable yield and biomass varied as the environment varied. The fluctuating environment is characterized by the variation of the intrinsic growth rate and environmental carrying capacity. The stochastic properties of environment variables are simplified as normal distribution. The influence of stochastic properties of environment variables to population size of fish stock is discussed. The investigation results relation can be applied for management of fisheries at the optimum levels in a fluctuating environment. Keywords: fish stock, fluctuating environment, optimal harvesting strategies, normal distribution.

1 Introduction Fish growth is a major process of fish biology and is part of the information necessary to estimate stock size and fishing mortality in stock assessments models. Modeling growth of fishes, crustaceans and mollusks has received considerable attention in studies of population dynamics and management of wild and cultivated species[1]. Knowledge of the size of a fish population is fundamentally important in the management of fisheries. The measurement of these populations is difficult and fishery scientists have developed a large body of both theory and practical experience that bears on the problem[2]. Bousquet investigated the biological reference points, such as the maximum sustainable yield (MSY), in a common Schaefer (logistic) surplus production model in the presence of a multiplicative environmental noise. This type of model is used in fisheries stock assessment as a firsthand tool for biomass modeling[3]. Die reviewed some methods to propose to calculate maximum sustainable yield[4]. Wang used the Novikov theorem and the projection operator method, and obtained the analytic expressions of the stationary probability distribution, the relaxation time, and the normalized correlation function of this system[5]. Bio-economic fisheries models, depicting the economic and biological conditions of the fishery, are widely used for the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 131–136, 2011. © Springer-Verlag Berlin Heidelberg 2011

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identification of Pareto improvement fisheries policies. Sustainable development may be characterized by three dimensions: the ecological, social, and economic dimension. The main objective of this paper is to show that the fluctuating environment can affect the population size of fish stock, maximum sustainable yield and optimal harvesting strategies.

2 Estimation of Sustainable Yield from Biomass Data In order to model growth of biological systems numerous models have been introduced. These variously address population dynamics, either modelled discretely or, for large populations, mostly continuously. Others model actual physical growth of some property of interest for an organism or organisms. The rate of change of fish stock dx/dt is determined by natural reproductive dynamics and harvesting. Functional relationship commonly used to represent the natural growth rate of fish stock is the logistic model. The simplest realistic model of population dynamics is the one with exponential growth [6].

dx x = rx(1 − ). dt K

(1)

Where r is the intrinsic growth rate, K is the environmental carrying capacity, and x is the population biomass associated with the intrinsic growth rate. Eq. (1) has solution

x(t ) =

Kx0 . ( K − x0 ) exp(− rt ) + x0

(2)

Where x0 is the population size at time t=0. The main features of the logistic model are characterized as follows: 1) The optimal size of fish population, in which the population size has a maximum intrinsic growth rate.

x

opt

=

K . 2

(3)

Where xopt represents optimal size of fish population. 2) The maximum growth rate, which is also called as maximum sustainable yield(MSY)

(dx / dt ) max =

rK . 4

(4)

3) The relative growth rate declines with increasing population, and it will equal zero when population size reaches its maximum.

dx x / x = r (1 − ). dt K

(5)

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Relative growth rate

1 0.8

r=0.3 r=0.5 r=0.7

0.6 0.4 0.2 0 0

0.2

0.4

0.6

0.8

1

Relative population size

Fig. 1. Variation of relative growth rate versus relative population size(x/K)

3 Optimal Fish Stock Harvesting Strategies The rate of change of fish stock dx/dt is determined by natural reproductive dynamics and harvesting [7]

x = f ( x, t ) − h(e, x, t ).

(6)

Where f(x,t) is the natural growth rate of fish stock which is dependent on the current size of the population x. The quantity harvested per unit of time is represented by h(e,x,t). The net growth rate dx/dt is obtained by subtracting the rate of harvest h(e,x,t) from the rate of natural growth f(x,t). The rate of harvest h(e,x,t) is assumed proportional to aggregate standardized fishing effort (e) and the biomass of the stock x; that is [8]

h(e, x, t ) = β e(t ) × x(t ).

(7)

Where β is the catchability coefficient. Once average fishing power has been calculated, the standardized fishing effort is computed as [9]

e(t ) = Pτ n.

(8)

Where e is the standardized fishing effort ; P represents average relative fishing power ; τ is the average fishing days at time t; and n denotes the number of vessels at time t. Fishing cost is evaluated by

C (e, x, t ) = ce(t ).

(9)

Where C(e,x,t) is the total cost function. It would be an economically optimal long-term strategy for commercial fisheries, if each factory tries to maximize the present value profit[10]

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∞

max Π = ∫ [ p × h − C]exp(−α × t )dt 0

(10)

∞

= ∫ [ p β e(t ) x(t ) − ce(t )]e

( −α × t )

dt.

0

In this formulation, Π is the ultimate performance measure of the fishery. P is output price of fisheries. T is starting catching time. xopt is optimal size of fish population. hopt is optimal rate of harvest. The optimal rate of harvest is expressed as follows:

hopt = β × eopt × xopt = xopt r (1 −

xopt K

)=

rK . 4

(11)

Where hopt represents optimal rate of harvest, and is also called as maximum sustainable yield (MSY). The MSY is achieved when fishing effort is adjusted to the optimum, which is half the biotic potential. The biotic potential is the instantaneous per capita growth of a population when it is not limited by food or other environmental constraints. The optimal fishing effort is deduced as follows

eopt = r (1 −

xopt K

)/ β =

r . 2β

(12)

From about analysis we can find that the fish stock has a maximum growth rate when population size of fish stock equal to half of the environmental carrying capacity. Maximum sustainable yield has been postulated by Shaefer for a fishery on an isolated population of fish which is growing according to the logistic law. When a fished population is found to be below half of the pristine population (i.e. the population prior to fishing), the population is termed overfished. When a population is overfished, the catch per unit effort (CPUE) decreases as the fishing effort increases.

4 Influence of Stochastic Properties of Environment Variables to Population Size of Fish Stock The logistic equation changes when the system is affected by some external factors such temperature, drugs, radiotherapy. Under equilibrium conditions in a deterministic environment the relationship between yield and biomass is a parabola and there is one maximum sustainable yield located as the top of parabola where h=rK/4 and e=r/(2β ). In a fluctuating environment, as the environment changes it will affect both the carrying capacity and the rate of increase and there is a family of parabolas relating yield and biomass[11].

probability density

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15 12 9 6 3 0

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SDr=0.05 SDr=0.025

0.5

0.6

0.7

0.8

0.9

1

r

Fig. 2. Stochastic distribution properties of intrinsic growth rate

probability density

0.02 SDk=20 SDk=40

0.01

0 900 930 960 990 1020 1050 1080 k

Fig. 3. Stochastic distribution properties of environmental carrying capacity 1200 Population size

1000 800 600 400 SDk=60,SDr=0.075 SDk=40,SDr=0.050

200 0 0

2 4

6 8 10 12 14 16 18 20 T ime

Fig. 4. Variation of population size versus time in fluctuating environment (Ka=1000, ra=0.75, x0=200)

Suppose that the intrinsic growth rate and environmental carrying capacity are subject to normal distribution. Fig. 2 shows stochastic distribution properties of intrinsic growth rate. Fig. 3 shows stochastic distribution properties of environmental carrying capacity. Fig. 4 shows the variation of population size versus time in fluctuating environment.

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From Fig. 4, we can conclude that the variation of population size versus time in fluctuating environment is stochastic changeable.

5 Conclusion Fishery systems have very complex interactions between resource stocks and the factors such as labor, fluctuating environment and capital used to harvest fish stocks. Stochastic simulation technique is used to describe the influence of the highly variable marine environment. The complexity of the fisheries management stems from the dynamic nature of the marine environment and numerous interest groups with different objective. The undermining properties of marine environment affect the variation of the intrinsic growth rate, environmental carrying capacity and optimal harvest strategies.

References 1. Hernandez-Llamas, A., David, A.: Estimation of the von Bertalanffy, Logistic, Gompertz and Richards Curves and a New Growth Model. Marine Ecology Progress Series 282, 237–244 (2004) 2. Swierzbinski, J.: Statistical Methods Applicable to Selected Problems in Fisheries Biology and Economics. Marine Resource Economics 1, 209–234 (1985) 3. Bousquet, N., Duchesne, T., Rivest, L.-P.: Redefining the Maximum Sustainable Yield for the Schaefer Population Model Including Multiplicative Environmental Noise. Journal of Theoretical Biology 254, 65–75 (2008) 4. Die, D.J., Caddy, J.F.: Sustainable Yield Indicators From Biomass: are there appropriate reference points for use in tropical fisheries? Fisheries Research 32, 69–79 (1997) 5. Wang, C.-Y., Gao, Y., Wang, X.-W.: Dynamical Properties of a Logistic Growth Model with Cross-correlated Noises. Physica A 390, 1–7 (2011) 6. Tsoularis, A., Wallace, J.: Analysis of logistic growth models. Mathematical Biosciences 179, 21–55 (2002) 7. Jensen, A.L.: Maximum Harvest of a Fish Population that Has the Smallest Impact on Population Biomass. Fisheries Research 57, 89–91 (2002) 8. Eisennack, K., Kropp, J.: Assessment of Management Options in Marine Fisheries by Qualitative Modeling Techniques. Marine Pollution Bulletin 43, 215–224 (2001) 9. Arnason, R.: Endogenous Optimization Fisheries Models. Annals of Operations Research 94, 219–230 (2000) 10. Sun, L., Xiao, H., Li, S.: Forecasting Fish Stock Recruitment and Planning Optimal harvesting strategies by Using Neural Network. Journal of Computers 4, 1075–1082 (2009) 11. Jensen, A.L.: Harvest in a Fluctuating Environment and Conservative Harvest for the Fox Surplus Production Model. Ecological Modelling 182, 1–9 (2005)

The Graphic Data Conversion from AutoCAD to GeoDatabase Xiaosheng Liu and Feihui Hu School of Architectural and Surveying Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China [email protected]

Abstract. According to the research of problem of data conversion from AutoCAD to GIS, this paper analyzes the characteristics of AutoCAD data and GIS data, and finds out the comparison relationship of graphic data conversion from AutoCAD to GIS. With the aid of the component libraries of ArcEngine and ObjectARX, the research implements the graphic data conversion using c # language in .NET environment, including point, line, polygon, etc. The implementation promotes the application of GIS technology. Keywords: ArcEngine, ObjectARX, CAD, GeoDatabase, Data conversion.

1 Introduction As AutoCAD software has powerful functions of graphics drawing and graphics editing, most companies use it to draw digital topographic map, so most of the vector data are CAD format [1]. However, to a large extent, these CAD data are also important source of GIS data, and now many related companies have established their own fundamental geographic information system. In order to satisfy the GIS application requirements and reduce the cost of buying GIS data [2], they hope their CAD data can be applied to fundamental geographic information system. To achieve the goal of applying CAD data to GIS system, we must complete the conversion form CAD data to GIS data. The conversion process includes two parts: one is Graphical data conversion, and the other is attribute data conversion. And graphics data conversion is the more complex and important part, so in order to solve the problem of graphics data conversion, we use ArcEngine components and ObjectARX components provided by ESRI to develop a data conversion tool from CAD to GeoDatabase in the .NET environment.

2 ArcEngine and ObjectARX Provided by ESRI, ArcEngine is component development kits which can help GIS developer develop independent GIS application [3]. By the component development kit of ArcEngine, we can create and draw graphic features, including points, lines, surfaces and other geometric entities, create GeoDatabase spatial database and edit spatial features, create spatial modeling and analysis, etc [4]. ObjectARX is a S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 137–142, 2011. © Springer-Verlag Berlin Heidelberg 2011

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component development kit of CAD secondary development which is offered by AutoDesk Company. It is the most powerful customized development tool of AutoCAD [5]. By ObjectARX components, we can develop CAD applications more rapid, efficient and concise. It can help CAD developers to access AutoCAD graphical systems and database structure, and can expand AutoCAD functions.

3 The Characteristics of CAD Data and GIS Data 3.1 CAD Data Characteristics AutoCAD software has powerful drawing function which can draw many different geometries, such as the points, lines, polygon, circle, arc, ellipse and ellipse arc, etc [6]. The position of every CAD graphic element in the coordinates is determined by one or more groups (x, y, z) coordinates. Meanwhile, the graphic element also includes some attribute information, such as color, linetype, line width, etc. In order to identify different graphic elements, every graphic element contains a unique Object ID [7, 8]. 3.2 GIS Data Characteristics In ArcGIS, the geometric type of graphic elements is mainly determined by Geometry Object which includes point, multipoint, polyline, polygon, multipatch and so on. Each graphic element contains spatial information and attribute information [9, 10]. At the some time, according to different geometric shape, the graphic elements are stored in point, polyline and polygon feature class of GeoDatabase [11]. 3.3 The Comparison Table of Graphic Data Conversion To achieve graphic data conversion from CAD to GIS, we must find one-to-one relationship of their graphic elements. Only in this way can we achieve the graphic elements conversion of these two format data, the Comparison Table of Graphic Data Conversion such as shown in table 1. Table 1. The Comparison Table of Graphic Data Conversion CAD Graphic Data

GIS Graphic Data

DBPoint, Simple BlockReference

Point MultiPoint Polyline

Line, Polyline(not closed), Circle, Arc, Ellipse, elliptical arc

、

Complex BlockReference

MultiPolyline

Polyline(closed)

Polygon

4 The Realization of Graphic Data Conversion from CAD to GIS 4.1 Graphic Data Conversion Process Because of the converted graphic data is stored in the GeoDatabase. Therefore, first by the programming create new GeoDatabase, feature dataset and feature class in

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139

Fig. 1. The Conversion Interface of Graphic Data from CAD to GeoDatabase

the.NET environment; Then read the point, straight line, polyline and other graphic elements of DWG files using ObjectARX development kit in the.net environment, and acquire the conversion data; Finally, based on the conversion data obtained which are in the relevant feature class of the GeoDatabase, program to realize creating feature. This is the conversion process of graphic data. The conversion interface is shown in figure 1. 4.2 The Detailed Process of AutoCAD Graphics Data Conversion 4.2.1 The Conversion of Point Graphic Elements The conversion of point graphic elements mainly included converting from CAD point to GIS point and CAD simple block to GIS point. Basically, their implementation processes are the same. However, the difference is that the conversion data what the point want to obtain is the coordinate of point, and the conversion data what the simple block want to obtain is the coordinate of insertion point. 4.2.2 The Conversion of Line Graphic Elements The conversion of line graphic elements included converting from the straight line, polyline, arc, circle, ellipse and elliptical arc in CAD to GIS polyline features. Due to a variety characteristics of graphical elements, thus their realization methods and the conversion data what we need to obtain are different. The conversion of straight line: you only need to obtain the coordinates of start point and end point of straight line for conversion. Conversion of not closed polyline: you need to obtain each node coordinates of polyline, and then according to the point coordinates to create polyline features of GeoDatabase. The conversion of circle and arc: The conversion data of circle and arc which you need to obtain are mainly starting angle, central angle, coordinates of centre point and

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radius. Actually, the circle is a peculiar arc whose central angle equals 360, so their conversion method is the same. The conversion of ellipse and elliptical arc: you should gain the conversion data which mainly included coordinates of centre point, starting angle, central angle, rotation angle, semi-major axis and elliptic axial ratio. Besides rotation angle, other conversion data can be obtained from graphic elements of ellipse and elliptical arc by ObjectARX. So you must calculate the rotation angle by writing an independent algorithm. Because the ellipse is a peculiar elliptical arc whose starting angle equals zero, they used the same conversion method. 4.2.3 The Conversion of Polygon Graphic Elements The conversion of polygon graphic elements includes closed polyline, rectangle and positive polygon in CAD convert to GIS polygon features. Because that the types of polyline, rectangle and polygon in CAD are polyline, and what we want to obtain are polygon’s each vertex coordinates, so their conversion method is the same. We need to be solving two problems when CAD polygon graphic elements converted: A) Judging whether polyline is closed or not Judging whether the beginning point coordinates and the destination point coordinates are equal or not, we solve the problem. If they are equal, the polyline is closed, and converted to GIS polygon features; otherwise, it is not closed, and then converted to GIS line features. B) Judging whether CAD polygon graphic elements are clockwise or not If the vertex point sequence of CAD polygon graphic elements is counterclockwise, the area of GIS polygon what we converted to is negative; And If the vertex point sequence of CAD polygon graphic elements is clockwise, the area of GIS polygon what we converted to is positive. Therefore, when the CAD polygon graphic elements convert to GIS features, we must first judge that if the vertex point sequence of CAD polygon graphic elements is clockwise. The paper mainly adopts vector product method to solve the problem. The specific process is: using the neighboring three vertexes of polygon constitute two vectors, then find out its value [12]. If the value of vector product obtained is negative, the vertex point sequence of polygon is clockwise; Otherwise, the vertex point sequence of polygon is counterclockwise, then we need to reversely obtain vertex coordinates of CAD polygon graphic elements. 4.3 The Display of Conversion Effect Through above the conversion job, then we can see the effect that AutoCAD graphic data are converted to GeoDatabase. Obviously, the AutoCAD graphic data and the GIS graphic data which is converted to GeoDatabase maintain a high degree of consensus. Thus, we achieve the lossless conversion of AutoCAD graphic data. The effect is shown in figure 2 and figure 3.

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Fig. 2. AutoCAD Graphic Data

Fig. 3. GIS Graphic Data

5 Conclusion This paper mainly introduced how to use ArcEngine components and ObjectARX components to realize graphic data conversion from AutoCAD to GIS in the .NET environment. And solved some problems which existed in the graphic data conversion, such as geometry distortion of graphic elements, coordinate location dislocation, area of polygon appeared negative value, etc. Finally, we achieve the consistency and integrity of graphic data before and after conversion, and accomplish graphic data lossless conversion from AutoCAD to GIS. Thus, these will promote the application of GIS technology.

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References 1. Weiler, K.J.: Boundary Graph Operators for Nonmanifold Geometric Modeling Topology Representations. In: Geometric Modeling for CAD Applications. Elsevier Science, Amsterdam (1988) 2. Li, S.: Research Based On the Conversion of Topographic Map and GeoDatabase. Geographic Space Information (2), 26–28 (2010) 3. Erden, T., Coskun, M.Z.: Analyzing Shortest and Fastest Paths with GIS and Determining Algorithm Running Time. Visual Information and Information System, 269–278 4. Yao, J., Tawfik, H., Fernando, T.: A GIS Based Virtual Urban Simulation Environment. In: Computational Science, ICCS 2006, pp. 60–68 (2006) 5. Qin, H., Cui, H., Sun, J.: The development training course of Autodesk. Chemical Industry Press, Beijing (2008) 6. Rebecca, Tse, O.C., Gold, C.: TIN Meets CAD – Extending the TIN Concept in GIS. In: Computational Science, ICCS 2002, pp. 135–144 (2002) 7. Liu, R., Liu, N., Su, G.: Combination and Application of Graphic Data and Relational database. Acta Geodaetica et Cartographica Sinica 29(4), 229–333 (2000) 8. Sun, X.: DWG Data Format and Information Transmission of Graphical File. Journal of XI’AN University of Science and Technology (4), 372–374 (2001) 9. Ebadi, H., Ahmadi, F.F.: On-line Integration of Photogrammetry and GIS to Generate Fully Structured Data for GIS. Innovations in 3D Geo Information System Part 2, 85–93 (2006) 10. Bordogna, G., Pagani, M., Psaila, G.: Spatial SQL with Customizable Soft Selection Conditions. STUDFUZZ, vol. 203, pp. 323–346 (2006) 11. Song, Z., Zhou, S., Wan, B., Wei, L., Li, G.: Research for CAD Data Integrated In GIS. Bulletin of Surveying and Mapping, Beijing (2008) 12. Frischknecht, S., Kanani, E.: Automatic interpretation of scanned topographic maps: A raster-based approach. In: Chhabra, A.K., Tombre, K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 207–220. Springer, Heidelberg (1998)

Research on Knowledge Transference Management of Knowledge Alliance Jibin Ma, Gai Wang, and Xueyan Wang Hebei University of Engineering 056038 Hebei, China [email protected]

Abstract. Knowledge alliance is the necessary for new era businesses, and knowledge transference has largely affected the Alliance's decision-making and behaviors. Based on the two companies form of alliance the paper makes the game analysis of knowledge transference, and then through the analysis shows how the knowledge alliances to manage knowledge transference and make management decisions. This paper researches on how to manage knowledge alliance well. Research finding, for guiding enterprises through the effective use of external knowledge of business alliances to enhance the competitiveness, for guiding the Alliance to effectively manage knowledge transfer in order to promote enterprise development, has important application value. Keywords: knowledge alliance, knowledge transference, management.

1 Introduction According to the transferability of knowledge, knowledge can be divided into explicit knowledge and tacit knowledge. Explicit knowledge can be used by formal language, including procedures, mathematical expression, plans, manuals, etc, recording these to transfer and share. Companies in advantages of explicit knowledge are more easily imitated by others, and then relatively weakened. Of course, companies can also learn explicit knowledge they need from other companies, which can be integrated with existing knowledge into new knowledge. Tacit knowledge refers to not be clearly expressed by a system or dominant language, which can be called only not words but meanings. In business, experience, skills and mental models are important asset of enterprises, also the most core ability of companies. Because of this knowledge is often implicit, it cannot easily be imitated. It is the most lasting competitiveness of enterprises. Knowledge alliance, a risk-sharing network, with other enterprises, universities and research institutions through a variety of contract or equity shares complementary advantages and risks, during the process of achieving the strategic objectives, in order to share knowledge resources and promote knowledge flowing and create new knowledge. The purpose is to learn and create knowledge. Alliance partners can not only get the experience, ability and other tacit knowledge market transactions cannot do, also, by the complementary knowledge, they can also create new knowledge a single enterprise cannot, so that alliance partners benefit. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 143–148, 2011. © Springer-Verlag Berlin Heidelberg 2011

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The concept of knowledge transference was first proposed in 1977 by Teece, U.S. technology and innovation management theorists. He believes that the international transference of knowledge can help companies accumulate valuable knowledge and promote technology diffusion, thereby reducing the technology gap between regions.

2 Analysis of Knowledge Transference Using Game Theory In the internal knowledge alliance, alliance members continue to carry out the transfer of knowledge, because of the different total knowledge leading to the potential difference. It can not only improve total knowledge of union members, also do well to the increase of total union knowledge. From the view of economic, knowledge transference can occur or not, depending on expected benefits from the main body of knowledge. The introduction of knowledge is often accompanied by the consumption of resources, which means knowledge transfer requires to paying price. Knowledge transfer can take place only knowledge transference obtained an expected return greater than the process of knowledge transference cost paid. In addition, the main body’s subjective consciousness and objective state of knowledge transference will have a major impact on knowledge transference. In order to analyze conveniently, this paper analyses knowledge transference between two main body’s behaviors, game of several main bodys can be done so on. Assuming the two companies for A and B, the total knowledge of the two companies were UA and UB. In the process of knowledge transference, the absorption capacity of A is a, and B is b, 0 a 1, 0 b 1. Knowledge transference is U generated by alliance, and condition of U is integration knowledge of two companies, that is three possibilities: A obtained knowledge from B; B obtained knowledge from A; A and B companies jointly acquired knowledge. A occupies knowledge exclusively in the case of , and B occupies knowledge exclusively in the case of , and A, B share knowledge in the case of . Suppose A transferred knowledge, but B did not, so that the income of B is UB+b(UA+U). B received additional revenue but no knowledge transference, and A transferred knowledge but no receive additional revenue, thus this situation is some loss for A, though this loss is psychology. Suppose the loss is k, so the revenue for A is UA-K. Similarly, if B transferred knowledge ,but A not, so the revenue for A and B is: UA+a(UB+U),UB-K. If A and B selected transference both, then the revenue for A and B is: UA+a(UB+U), UB+b(UA+U). On the contrary, if A and B did not select transference, then the revenue is UA, UB. Game payoff matrix of knowledge transference for A and B show table 1. If A selected knowledge transference, then the choice of transference or not was same for B--UB+b(UA+U). If A selected non-transference, then the revenue UB of B selecting non-transference was greater than the revenue UB-K of transference, so the non-transference is B’s strategy. If B selected knowledge transference, then A had the same revenue UA+a(UB+U), no matter of transference or not. If B selected nontransference, then the revenue UA of A selecting non-transference was greater than

③

① ①

＜＜ ＜＜ ③

②

②

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Table 1. Game payoff matrix of knowledge transference A transference non-transference

B transference UA+a(UB+U), UB+b(UA+U) UA+a(UB+U), UB-K

non-transference UA-K, UB+b(UA+U) UA, UB

the revenue UA-K of transference. Thus, (transference, transference) and (nontransference, non- transference) constitute the static Nash equilibrium. From the result of Nash equilibrium, if one selected transference, the second one had to selected nontransference. And if one selected non-transference, the both would not transfer. But from the view of revenue, the two sides built knowledge alliance once, they would transfer inevitably. Because transference choices of both have greater revenue than the revenue of only one, also than the revenue of neither. So, in this state, both have to transfer knowledge, which is the ideal state of building alliance knowledge transference. Further, the choice of (non- transference, non- transference) is a typical prisoner's dilemma game. Since our argument is the knowledge transfer of knowledge alliance, knowledge alliance’s focus is long-term cooperation, even permanent cooperation, rather than a one-time cooperation. In this way, the game becomes unlimited number of repeated games, and (transference, transference) becomes subgame perfect Nash equilibrium. But there is also another case: the existence time of the knowledge alliance may be limited, so that knowledge alliance may be going to be dissolved when one party of alliance can ensure constant revenue itself, who would make speculation strategy but no knowledge transference. Because the forthcoming dissolution of the alliance, even if they do not transfer leading to alliance’s revenge, the potential losses are limited. The following part the author will analyze the alliance strategies of dynamic game of all parties. Knowledge transference in the knowledge alliance is a dynamic complete information game, if one’s strategy were not to transfer knowledge, he would have been "eye for an eye" revenge by the other one, but the other one would choose not to transfer. Game time is assumed for the n, n = 0, 1, 2, , because the future value needs to be discounted to present value to be compared, we assume the discount factor for the u, 0
…

≥

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≥

uk [UA+a(UB+U)] (n-k)UA 1− u

(1)

Particularly, when n = 2, k = 1, (1) can be simplified as: u≥

UA 2U A +a(U B + U )

(2)

Inequality (2) is the condition of A carrying out knowledge transference. That establishment condition of (2) is the equation left is large enough, or the equation right is small enough. Inequality (2)’s left part is large enough, which means both game sides pay greater attention to future revenue, so, both sides choose knowledge transference more possibility. Inequality (2)’s right is small enough, which requires analysis of situation of UA, a, UB, U: UA’s impact on knowledge transference. The inequality (2) divided by the UA we 1 have the result: a(U B + U ) 2+ UA It can be seen, UA is larger, then the smaller the denominator, the greater the formula. This indicates that the total knowledge value of A is greater, A will more likely not to transfer knowledge congenially. It is true that the closer dissolution of the alliance, the strong side generally less likely continue to choose knowledge transference. U’s impact on knowledge transference. From the inequality (2), UB is larger, (2)’s right part is smaller. This shows that the greater total amount of knowledge of the other one, companies have less likely not to choose transfer knowledge. This is not difficult to understand, the greater the amount of knowledge of one alliance side, means who will get greater revenue through knowledge transference, and companies are less reluctant to carry out knowledge transfer. a’s impact on knowledge transference. From the inequality (2), a is larger, (2)’s right part is smaller. This indicates that, A has greater knowledge absorption capacity, who will have the greater choice likelihood of knowledge transference. This situation is also consistent with the intuitive case, greater visual absorption capacity means greater revenue obtained from knowledge transference, the greater likelihood of knowledge transference. U’s impact on knowledge transference. From the inequality (2)‘s right part we can see, U bigger, (2)’s right part is smaller. This suggests that greater value of new knowledge through knowledge transference, less likely the alliance party choose not to transfer congenially.

①

② ③ ④

3 Knowledge Transference Management The author early introduced knowledge concepts simply, then analyses the enterprise knowledge transference process from the perspective of game. The above results of game shows that: the greater the discount factor, the more amount of the alliance

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knowledge transference; more amount knowledge of alliance’s counterpart, more amount knowledge transference the other one will carry out; the greater amount of knowledge one side owns, who will transfer knowledge less; the stronger absorption knowledge capacity of one side, the more who will transfer knowledge. For this result, the author proposes the following corporate management strategies of knowledge transference: (A) To establish knowledge-sharing basis. The basis of knowledge sharing can be achieved through the following channels: mechanisms of information technology and organization, business process to be re-combined, promoting tacit knowledge to explicit knowledge transforming process, reducing the cost of the knowledge- sharing at the same time of expanding the scope of its share; in order to protect strategic value knowledge it must be graded authorization and protection; to encourage knowledge transference. When only transferor and recipient side promote knowledge transferring, we must take appropriate incentives for organizations and guiding behavior of other members, to make them fully aware of significance of improving the enterprises competitiveness by knowledge transference. (B) To integrate allied enterprises knowledge transference mechanisms. A common feature of both is also very important to relationship between the unions. If the common feature is far away, narrow, then the understanding of knowledge transference between then will be deviation, and the knowledge is difficult to avoid damage. Through the strategic integration to make two sides a better understanding of cooperation and innovation strategic planning, reducing the gap between each other. (C) To promote trust cooperation and to enhance knowledge transference will of member enterprises. The degree of confidence between both is the first most important condition to impact of the knowledge transference. To enhance the transferor’s will of knowledge, the cooperator should try to establish transparent cooperation relations, and to promote mutual trust, in particular of tacit knowledge transference, learning, absorbing, depending on the openness and transparency in mechanism design. (D) All parties should strive to build learning organizations. The total amount of knowledge between both is the critical to influence knowledge transference, and the most effective accumulation knowledge organization is learning organization. In the process of pursuing the goal of creating a learning organization, we can obtain development from information systems, intellectual capital management, organizational learning, and several other aspects. Thus balancing total amount of knowledge of the parties, it can form a coalition situation to conduct knowledge transference. (E)To integrate transfer channels and organizational structure knowledge transference required. Different companies have different learning culture and atmosphere. Cultivation and integration of learning culture is an effective way to enhance knowledge base and enhance absorptive capacity. Enterprises should establish a long-term vision of knowledge, provide effective knowledge management platform. Also note that the culture compatibility between partners, accelerate the pace of knowledge integration, reduce damage knowledge as much as possible, enhance the efficiency of knowledge transference, and promote cooperation and innovation performance. This can increase the absorption capacity of the two sides to further facilitate the knowledge transference.

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References 1. Hu, Y., Liu, X.: Game analysis of knowledge sharing in knowledge alliance. Science & Technology Progress and Policy, 143–145 (April 2009) 2. Wang, Y.: Research on knowledge alliance’s cooperation innovation based on game theory. Dalian University of Technology Master thesis, pp. 26–27 (2009) 3. Wang, Z., Li, J.: Introduction to Game Theory. China Renmin University Press, Beijing (2004)

The Study of Print Quality Evaluation System Using the Back Propagation Neural Network with Applications to Sheet-Fed Offset Taolin Ma, Yang Li, and Yansong Sun School of Printing and Packaging, Wuhan University, Wuhan, China [email protected]

Abstract. With the continuous development of the printing industry, print quality has significantly improved and enhanced. The evaluation of the print quality is mainly based on the objective and supplemented subjective methods, and it has changed from the traditional empirical judgments to science of quantitative analysis. So it improves the quality of management, scientific, standardized and rationality. This paper is to solve the color print quality problems by establishing the evaluation of index system, identifying the standard data and combining with BP neural network theory. Index Terms: Neural network, offset, print quality evaluation.

1 Introduction Subjective evaluation, objective evaluation and comprehensive evaluation are the three methods for color print quality evaluation. And the comprehensive evaluation is widely used, which is based on data obtained by objective evaluation and partly subjective evaluation with a variety of factors. The approach of combining psychological impression of subjective and objective data analysis makes the evaluation criteria more scientific. So the print quality evaluation system using the Back Propagation neural network is more efficient.

2 Overview of Back Propagation (BP) Neural Network BP neural network is an algorithm based on BP artificial neural network model. BP neural network is the most commonly used, which is the essence part of the artificial neural network. BP neural network is also known as multi-layer feed forward neural network. It is made of several layers neurons. They are input layer, hidden layer and output layer. By adjusting the connection weights and the size of the network, BP neural network can achieve non-linear classification problems, and also can approximate any nonlinear function with arbitrary precision. After determining the structure of BP network, we use the sample set training the BP network. The trained BP network can also give the right output when the sample do not input at the same time. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 149–154, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Although the BP network is the most widely used network model, but there are two shortcomings: first, the convergence rate of study is not so fast. Second, it will be trapped in local minima. Therefore, the improved BP algorithm is divided into two categories: The first category refers to the BP heuristic algorithms that use the information technology; the other is to join the BP algorithm for numerical optimization techniques.

3 The Construction of the Color Print Quality Evaluation Model Based on BP Neural Network This article attempts to introduce BP neural network to the print evaluation [1], establishing the color print quality evaluation model based on BP neural network, hoping to study for the evaluation of printed materials a new way of thinking. We confirmed the standards of each index printing witch have 34 targets in this paper. It comes from our having the print quality level as the four levels: excellent, good, fair, and poor. In accordance with People's Republic of industry standards - offset print quality requirements, and others authority standard. 3.1 The Steps of General Evaluating BP Neural Network (1) Determine assessment index system [2]. Index number of the BP network is the number of input nodes. (2) Determine number of layers BP network. The model used has a three-tier network structure with one input layer, one hidden layer and one output layer. (3) Determine the evaluation target. The node of output layer is 1.The evaluation target level is the corresponding each print value of quality. (4) Treat the samples and evaluation of target value positively and standardized. (5)Initialize the weights of the network nodes and network threshold with a random number (usually a number between 0 and 1). (6)Put samples and target of evaluation in the network after the standardization, and give the corresponding desired output. (7) Forward-propagation. Calculate the output layers nodes. (8) Calculate errors of the layers nodes. (9) Back-propagation. Correct weights. (10) Check that all samples of the input is completed or not. (11) Calculate errors. When the total error is less than the error limit, the network is end of the training. Otherwise the process goes to step (6), and continue to train. (12) Trained network can be used for formal evaluation. 3.2 Generating Samples Selection of learning samples is very important, and it is the final factor of generalization ability to neural network mapping. We randomly generated 300 samples

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in the MATLAB software for each grades, and generated a total of 1200 samples (also more). For using the method of the early termination to improve the network generalization ability, the random sample was divided into three parts: training sample, test samples and test samples. MATLAB neural network toolbox dividevec function is used in this paper. dividevec function call format: [trainV,valV,testV] =dividevec(p,t,valPercent,testPercent) Here, trainV is training samples; valV is the test samples; testV is the samples for testing; p is input vector; t is the output vector; valPercent represent samples to test the percentage of the total sample; testPercent is total sample for the percentage of test samples. 3.3 The Choice to Each Kind of Parameter Setting the model parameter is the important work of the evaluation system [3]. We will introduce the parameter involved and reason of choosing them. (1) Number of network layer: because the BP neural network can achieve any nonlinear mapping and its network characteristics, this model adopted an three-tier network including input layer, a hidden layer and an output layer. (2) Activation function: because the nonlinear approximation ability of BP network is reflected by the activation function, the activation function of S-type is usually used in hidden layer and the output layer activation function can be linear or S-type. We use the S-type activation function in the both hidden layer and output layer in this paper. (3) Input layer: we selected 34 evaluation indexes, namely the dimension of input vector is 34. So the input layer nodes are 34. (4) Output layer: In this paper, we determined that the corresponding print quality scale superior, good, qualified and the bad network model value of output is 0.2,0.4, 0.6, 0.8 respectively. (5) The choice of initial weight: In order to make the learning process convergence, we initialized the weight random (-1, 1). (6) The choice of learning algorithm: Selecting the learning algorithm, we must consider the performance of the algorithm itself and think about the complexity of the problem, the size of sample set, network error target and the type of problems to be solved. Through taking the experiments and analysis, this study used the method of an early termination method and SCG algorithm. (7) Number of training steps: After extensive testing, we found that combining the early termination method and the SCG algorithm method to train the network is very fast. So we selected 1000 as the training steps. When the network parameters have been identified, we can write programs in MATLAB to carry out training and simulation.

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4 Experiment 4.1 Experimental Condition 1. Evaluation sample request The sample to evaluate should have control strip, color batch, stepped scale and other elements that equipment can be used for quantitative measurement and control to facilitate the objective evaluation [4]. 2. The condition of subjective evaluation observe The technology measurement for color, control, and visual evaluation should have a uniform standard of lighting conditions. In this system, the qualitative indicators on the evaluation of color printing should be under the standard. (1) Illumination to print and observation condition a) The light source to print observed: standard illuminator D65 b) The light source of related color temperature: 6504K. c) Color rendering index: the general color rendering index Ra is not less than 90, the special color rendering index Ri should be not less than 80. d) Illumination of observed surface: it produce the uniform diffuse lighting on the observed surface, illumination rang from 500lx to 1500lx. e) The uniformity of illumination: the surface of observed surface have to be as uniform as possible, and differences between the surface center and the surrounding illumination can not be greater than 20%. f) The color of surround lighting: the surround of the observed surface should be the neutral gray. To avoid the color contrast, the background and the substrate of observed sample should be gray. a) Observation method: we use the illumination and observation of 0°/45°or 45°/0° which CIE recommended. (2) The influence and control of environmental factor In actual production, the environment is the biggest factor to standard lighting and observed condition. So observers should try to eliminate the influence of the environment. a) Avoid the additional light source or light beam to influence the correct color. b) Avoid the strong color in the observed field or the environmental surface. c) Temperature and humidity control: room temperature is 23±2 centigrade, and relative humidity is 50%±5%. d) For the subjective impression play an important role in evaluation to sample. So we should have the eye relax for a while before observation. (3) Introduction of objective measuring instruments a) Spectrophotometer. We use the spectrophotometer SpectroEye and control strip to measure the print density of the field, dot gain, relative contrast, trapping rate, color gray, color cast and so on. b) Loupe with a scale 40 times.

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4.2 Experimental Results and Conclusions To test the applicability and accuracy of the color print quality evaluation in BP network, this paper selected four color samples to evaluate. Each target [5] of the sample all comply with the above conditions and requirements. We can get the value of the sample by putting the data into the program. We use a variety of instruments to measure the related data of following requirements and put these data into the program we made to get the output value of the BP network model. Table 1. The sample and output of model

Sample Output of model

Ⅰ

0.5104

Ⅱ

0.3566

Ⅲ

0.4558

Ⅳ

0.7645

We can see in Table 1. The output value of the first sample is 0.5104. So its level of quality is qualified. The model output of sample II and III is in [0.2975, 0.4935], so the level of them is good. The output value of the forth sample is 0.7645. It is greater than 0.7039, so the quality level is disqualification. Though the sample II and III are all good, the output value of sample II is smaller. So we can get the quality of sample II is better than the sample III, which reflects the advantage of the BP network evaluation. In this paper, we use the subjective evaluation method for comparison. Under the standard lighting conditions, several experts with extensive experience have the four samples subjective evaluate. The mainly items are represented as following. Check the sheets clean or not; check the of high, medium, dark tone with a magnifying glass; check the replication for color with signal bar or color control strip; check clarity of dot with a magnifying glass; check the replication of text. After these series of progress, we can get the sample I is qualified, the sample II is excellent, and sample III is good. The forth sample is failed. Compared with the result of BP network evaluation, we can see the BP neural network model is effective.

5 Conclusions In this paper we proposed a sheet-fed offset print quality evaluation model based on BP neural network and achieve it though using MATLAB neural network toolbox. The applicability and accuracy of the evaluation model is confirmed through measurement, evaluation and comparison with the subjective evaluation to practical samples. As future works we have to supplement more targets to the evaluation index system for its comprehensive, and enable the parameters of BP neural network we established to be better. The following study can try to establish an independent evaluation of visual system to make it convenient without MATLAB which this paper used.

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References [1] Ma, T.: Study of the Method of Evaluating Color Digital Image. In: International Conference on Computer Science and Software Engineering, ICGC 2008, pp. 225–228 (December 2008) [2] Otaki, N.: Colour image evaluation system. OKI Technical Review 7.0(194), 68–73 (2003) [3] Guan, L., Lin, J., Chen, G., Chen, M.: Study for the Offset Printing Quality Control Expert System Based on Case Reasoning. IEEE, Los Alamitos [4] Bohner, M., Sties, M., Bers, K.H.: An automatic measurement device for the evaluation of the print quality of printed characters. Pattern Recognition 9, 11–19 (1997) [5] Guan, L., Lin, J., Chen, G., Chen, M.: Study for the Offset Printing Quality Control Expert System Based on Case Reasoning. IEEE, Los Alamitos

Improved Design of GPRS Wireless Security System Based on AES TaoLin Ma1, XiaoLan Sun1, and LiangPei Zhang2 2

1 School of Printing and Packaging, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Whuhan University, Wuhan, 430079, China [email protected]

Abstract. This paper mainly studied how to improve security system by analyzing the current situation and defects of existing encryption security systems. Based on existing studies, optimized GPRS wireless security system (GPRS-based WSS) based on AES was designed by using principles of designing a security system and basic theories in Cryptography. This new system can increase its query efficiency, accuracy and security. Keywords: GPRS-based WSS, Encryption Algorithm, AES, S-boxes.

1 Introduction With the development of network technology, the dangerous factors are increasing in the transmitting process of digital information. In China, to solve those issues, much attention was paid to form encryption systems combining with theories in Cryptography. The creation of those systems increased its query efficiency and accuracy, blew to criminals and protected the consumers and producers. In [1] RFID security system was studied. It’s useful by signing a digital signature for product’s ID via SHA-1 algorithm. However, how to prevent the deception of false data from illegal readers is an issue to be solved. In addition, literature [2] designed a GPRS-based WSS, which combining networks and encryption technology was used in products’ security system. But an obvious issue is that the selection of encryption algorithm.

2 GPRS-Based Wireless Security System The composition and work of GPRS-based WSS [2] was shown in Fig. 1. Although the performance of this system is good, it is difficult to guarantee the system’s security with the rapid development of computer technology. Therefore, it’s necessary to set up multi-level security for the system’s key parts. In [2], readers acquire security codes through specific agreements. But there is no difference between security code and ordinary code if agreements can’t ensure safety. It’s necessary to adopt multi-level measurements. In addition, readers with encrypted data can’t S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 155–160, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Fig. 1. Composition of GPRS-based WSS

communicate with serves until ID authentication. If digital signature technology was applied in data transmission, what servers need to do is verify senders’ ID. This kind of certification is more convenient and has higher accuracy. Based on above analysis, the system will have two kinds of constitution programs. First, the method between readers and security codes is double security, and the communication of readers and servers was designed according to the way in [2]. Second, setting up double security for the communication between readers and servers, the security method of readers and servers kept the same with that in [2]. The safety coefficient of the methods above is higher than that in the single security system. In this paper, we will improve the GPRS-based WSS based on the first program.

3 Introduction of Several Commonly Used Algorithms 3.1 Advantages and Disadvantages of Encryption Algorithms Block cipher encryption, as an important encryption means, has been deeply studied. In block cipher encryption, the representative algorithms are DES, IDEA and AES. DES. The key size of DES is 56-bit, which is too short. With the emerging of new attacks, DES faced an actual threat and will gradually be eliminated. IDEA. IDEA was developed based on the DES. With the calculation speed increasing, it is possible to be attacked by exhaustive search 128-bit key space of IDEA. AES. AES combines security, performance, efficiency, ease of implementation and flexibility [3]. But the key size of AES totally depends on the choice of S-boxes [4]. It is easy to be an attack breakthrough if its S-boxes were inappropriately designed.

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3.2 The Necessity of Optimizing AES Many cryptographists have discovered that existing S-boxes have some fatal weaknesses. They have properties of short periods and bad distribution [5]. In terms of AES-192 (12 rounds iteration), the number of rounds which can be successfully attacked is at least 6, and the highest record is 9 in 2005 [3]. Considering above analysis and the actual application requirements, we will select AES as the basic algorithm in this paper. However, we must use the optimized AES algorithm to decrease the possibility of being successfully attacked and ensure operation security of the system.

4 Theory of AES Algorithm and Algorithm Optimization 4.1 Theory of AES Algorithm The basic principle of AES can be described as following: plaintext block is treated as a matrix array of bytes in AES structure. The matrix array is encrypted by several rounds of iteration, and becomes cipher text finally. Key in every round is extended by the main key. Each round iteration operation covers SubBytes, ShiftRows, MixColumns and AddRoundKey. Because we will optimize the S-box, so we only introduce the SubBytes transformation. SuBbytes Transformation is a non-linear operation. It replaces the bytes in state by S-box. S-box operation is compounded by two transformations. One of them is affine transformation. The formula (1) shows the method of affine transformation. We use (B5, D3) to do affine transformation [6].

(1)

4.2 Algorithm Optimization In this paper, we selected optimizing S-box to better AES. Because SubBytes transformation is the only nonlinear operation in AES, so it is efficient to optimize AES by optimizing S-box. Increasing the Security Bytes. In 8 × 8 matrix of (1), the elements in line i +1 are generated by those in line i. Only if we don’t change the inverse feature of this matrix, we can change it as we want to improve S-box. In my opinion, the given matrix can be split into two 4×8 matrixes. In this case, we use (B5, D3) and (8F, D3) to do affine transformation. The formula was shown in (2). In (2), Hex B5 and D3 are shifted by Binary 10110101 and 10001111 respectively, then the first rows of two 4×8 matrixes

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are 10110101 and 10001111. This change can destroy the regularity of matrix and increase the difficulty of attack through increasing the number of private bytes.

(2)

Change of the matrix has broken regularity of the original data. Although the operation complexity in calculation programs didn’t change heavily, it has largely increased attack difficulty. Thus, the security factor of this system has been increased overall. Designing S-box with Better Nonlinearity. Many literatures show it is an efficient way to increase security of S-box by improving the nonlinearity of given S-box [7]. We can improve its nonlinearity by swapping two output vectors in its truth table [8]. To find a new S-box by this method, we need to define some sets of (ω ,θ ) pairs for which (ω ,θ ) is maximum and near-maximum. Definition 1. Let b(x)=y be a bijective n×n S-box with Walsh-Hadamard transformation Bθ (ω ) . (a)Let WHmax denote the maximum absolute value in the B matrix. Let us define the following sets (See 3):

W

+ 1

{

}

−

{

= (ω ,θ ) : B (ω ,θ ) = WH max ,W 1 = (ω ,θ ) : B (ω ,θ ) = −WH

max

}.

(3)

(b)Defining sets of (ω ,θ ) for which the WHT magnitude is close to the maximum (See 4).

W = {(ω,θ ) : B(ω,θ ) = WH W = {(ω,θ ) : B(ω,θ ) = WH + 2

+ 2

Further, defining

W

+ 2, 3

+

+

−

} { − 4},W = {(ω,θ ) : B(ω,θ ) = −WH −

max

−

max

} + 4}

− 2 ,W 2 = (ω,θ ) : B(ω,θ ) = −WH max + 2 2

−

−

= W 2 ∪W 23 ,W 2,3 = W 2 ∪W 23

max

(4)

.

Theorem 2. Theory for incremental improvement of a bijective S-box. Let b(x) =y be a bijective S-box. Further, let x1 and x2 be distinct input vectors with corresponding outputs y1=b(x1) and y2=b(x2). Let b’(x1) be a S-box the same as b(x) except that b’(x1)=y2, b’(x2)= y1. Then we can get S-boxes whose nonlinearity is better than that of b(x) if the following conditions are satisfied:

Improved Design of GPRS Wireless Security System Based on AES

(a) L ( x ) ≠ L ( x ), (θ , ω) ∈W + ∪W − ; ω ω 1 2 1 1 (b) ( y ) ≠ ( ), (θ , ω ) ∈ + , ( y ) ≠

Lθ

(c)

1

Lω x

W Lθ

2

1

2

159

Lω ( x ), (θ , ω ) ∈W ; +

1

1

Lθ ( y ) = Lω ( x ), (θ , ω) ∈W , Lθ ( y ) = Lω ( x ), (θ , ω) ∈W ; −

2

1

(d) For all (ω ,θ ) ∈

−

1

1

2

1

W , not all of the following are true: +

2 ,3

Lθ ( y ) = Lω ( x ), Lθ ( y ) = Lω ( x ), Lθ ( y ) ≠ Lω ( x ), Lθ ( y ) ≠ Lω ( x ) ; (e)For all (ω , θ ) ∈ W , not all of the following are true: Lθ ( y ) ≠ Lω ( x ), Lθ ( y ) ≠ Lω ( x ), Lθ ( y ) = Lω ( x ), Lθ ( y ) = Lω ( x ) . 1

2

1

2

1

2

1

1

2

2

−

2,3

2

1

1

1

2

2

We can acquire S-boxes with better nonlinearity based on the above method and satisfied those five conditions. AES algorithm can be optimized if S-box has successfully optimized. 4.3 Evaluation of the Optimized Results In the encryption procedure of AES, S-box in SubBytes can be existing S-box, new S-box respectively. Inputting the same plaintext into AES structure with different S-boxes, we can get different cipher texts through N rounds transformation. Comparing cipher texts generating by the same plaintext and through related calculating, we can draw a conclusion: cipher text encrypted via optimized AES has stronger anti-attack characteristic.

5 Optimized GPRS-Based Wireless Security System In given GPRS-based WSS, if we use optimized AES to encrypt product’s serial number, and store this security code in e-label. In addition, the communication between security readers and servers need be encrypted by optimized AES. Via encrypting a common system’s key parts, we can get a new system called optimized GPRS-based WSS. At present, it is still a newer technology that applying GPRS wireless network to security system. This technology isn’t very mature. However, if this technology turns stronger and combines with Cryptography theory, it will play an important role in anti-counterfeiting field in the future.

6 Conclusions In our work, we have analyzed the current situation and insecurity of current security systems. Otherwise, we selected AES which is much safer as the basic algorithm in the basis of existing GPRS-based WSS. In addition, S-box has been properly adjusted so as to get optimized AES, which has been applied to GPRS-based WSS to form a more reliable and safer security system. It will perform the product authenticity enquiry service more exactly and protect the benefits of firms and consumers more effectively.

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This work mainly stated some possible methods on how to optimize S-box of AES. To improve S-box, we analyzed the theory of AES. In our paper, improved S-boxes have been proposed. They are extremely practical in theory, what we should do is to program procedures and implement it. Now that we have built a useful theory, putting it into practice is our future work.

References 1. Ni, W., et al.: Design and Implementation of RFID-based Multi-level Product Security System. Computer Engineering & Design 15(30) (2009) 2. Jia, Y.: Research and Implementation of GPRS-based Wireless Security System. Dalian Technology University, Liaoning (2006) (in Chinese) 3. Liu, N., Guo, D.: AES Algorithm Implemented for PDA Secure Communication with Java (2007) (in Chinese) 4. Zheng, D., Li, X.: Cryptography–encryption algorithm and agreement. Electronic Industry Press, Beijing (2009) (in Chinese) 5. Wang, Y.B.: Analysis of Structure of AES and Its S-box. PLA Univ. Sci. Tech. 3(3), 13–17 (2002) 6. Chen, L.: Modern Cryptography. Science Press, Beijing (2002) (in Chinese) 7. Millan, W.: How to Improve the Nonlinearity of Bijective S-boxes. In: Boyd, C., Dawson, E. (eds.) ACISP 1998. LNCS, vol. 1438, pp. 181–192. Springer, Heidelberg (1998) 8. Millan, W.: Smart Hill Climbing Finds Better Boolean Functions. In: Workshop on Selected Areas in Cryptology 1997, Workshop Record, pp. 50–63 (1997)

Design and Realization of FH-CDMA Scheme for Multiple-Access Communication Systems Abdul Baqi, Sajjad Ahmed Soomro, and Safeeullah Soomro Department of Computer Science and Engineering, Yanbu University College, Yanbu Al-Sinaiyah, Kingdom of Saudi Arabia {abdul.baqi,sajjad.soomro,safeeullah.soomro)@yuc.edu.sa

Abstract. In this paper we proposed the Frequency Hopping Code Division Multiple Access (FH/CDMA) Scheme. In order to improve the spreading process of the spread spectrum modulation system, the conventional pseudorandom code has been replaced by chaotic signal owing to its dynamical behaviour. The spreading code generator has been implemented using discrete integrated circuits and components in which output is controlled by a conventional PN code. The proposed circuit has been tested using real time voice signal and has been transmitted as frequency hopping signal with different hopping patterns. A FH/CDMA Transmitter and Receiver based on proposed chaotic signal generator has been experimentally verified. The results of experimental investigation have been presented in the paper. The waveforms obtained at various check nodes have also been presented.

1 Introduction This Spread Spectrum is a type of modulation that spreads the modulated signal across available frequency band, in excess of minimum bandwidth required to transmit the modulating signal [1] and [5]. Spreading makes signal resistant to noise, interference and eavesdropping. Spread Spectrum is commonly used in personal communication systems including mobile radio communication and data transmission over LANs. Spread Spectrum has many unique properties that cannot be found in other techniques of modulation. These include the ability to eliminate multi-path interference, privacy of message security, multi-user handling capacity and low power spectral density since signal is spread over a large frequency band [2] and [6]. There are two commonly used techniques to achieve spread spectrum. Viz, Direct Sequence Spread Spectrum (DSSS) and Frequency Hopping Spread Spectrum (FH-SS).A DS-SS transmitter converts an incoming data (bit) stream into a symbol stream. Using a digital modulation technique like Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK), a transmitter multiplies the message symbols with a pseudo random (PN) code. This multiplication operation increases the modulated signal bandwidth based on length of chip sequence. A Code Division Multiple Access (CDMA) system is implemented via these coding. Each user over a CDMA system is assigned a unique PN code sequence. Hence, more than one signal can be transmitted at the same time on same frequency. In this paper Frequency Hopping (FH-SS) Spread Spectrum S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 161–166, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Fig. 1. Voice to voltage Converter

modulation technique has been used with a new spreading code in which conventional PN code controls a typical chaos oscillator. The resultant chaotic signal has a wide frequency range from few KHz to few MHz (12.34 kHz to 9.313 MHz). The motivation to use chaotic signal in place of conventional PN code has been because, chaotic systems are nonlinear dynamical systems with certain distinct characteristics. These systems can generate highly complex waveforms even though the number of interacting variables is minimal [3]. For an iterated map a dynamical system with single variable can result in chaotic behaviour while for a continuous system, three coupled differential equations can result in a complicated dynamics. Time series generated from chaotic dynamics have the following three interesting properties: (i) wide-band spectrum, (ii) noise-like appearance, and (iii) high complexity. In a chaotic system, trajectories starting from slightly different initial conditions diverge exponentially in time which is known as sensitive dependence on the initial conditions. Because of these distinctive properties, chaotic systems are widely being studied for secure communication and multiple user communication applications [4]. In this paper we are presenting the methodology in section and in section 3 we are presenting the results which came through our technique and finally we make conclusion.

2 Frequency Hoping Spread Spectrum (FH-SS) Frequency hopping is a radio transmission technique where the signal is divided into multiple parts and then sent across the air in random pattern of jumping or hopping, frequencies. When transmitting data, these multiple parts are data packets. The hopping pattern can be from several times per second to several thousand times per

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Fig. 2. Circuit Description of Receiver of Proposed Scheme

second. Frequency hopping is the easiest spread spectrum modulation to use. Any radio with a digitally controlled frequency synthesizer can, theoretically, be converted to a frequency hopping radio. This conversion requires the Addition of a pseudo noise (PN) code generator to select the frequencies for transmission or reception. Most hopping systems use uniform frequency hopping over a band of frequencies. This is not absolutely necessary, if both the transmitter and receiver of the system know in advance what frequencies are to be skipped. Thus a frequency hopper in two meters could be made that skipped over commonly used repeater frequency pairs. A frequency hopped system can use analogue or digital carrier modulation and can be designed using conventional narrow band radio techniques. De-hopping in the receiver is done by a synchronized pseudo noise code generator that drives the receiver’s local oscillator frequency synthesizer. FH-SS splits the available frequency band into a series of small sub channels. As transmitter hops from sub channel to sub channel, transmitting short bursts of data on each channel for predefined period, referred to as dwell time (the amount of time spent on each hop). The hopping sequence is obviously synchronized between transmitter and receiver to enable communications to occur. FCC regulations define the size of the frequency band, the number of channels that can be used, and the dwell time and power level of the transmitter. In the frequency hopping spread spectrum a narrowband signal mover hops from one frequency to another using a pseudorandom sequence to control hopping. This result in a signal’s lingering at a predefined frequency for a short period of time, which limits the possibility of interference from another signal source generating radiated power at a specific hop frequency.

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2.1 Types of Frequency Hopping Spread Spectrum Frequency Hopping Spread Spectrum Systems are categorized into following sections which are written below:2.2 Slow Frequency Hopping (SFH) In an SFH spread system the hop rate (fh chip rate) is less than the base band message bit rate fb. Thus two or more (in several implementations, more than 1000) base band bits are transmitted at the same frequency before hopping to the next RF frequency. The hop duration, TH is related to the bit duration Tb by: TH = KTb for K = 1, 2, 3... And fc = fH = 1/TC. 2.3 Fast Frequency Hopping Spread Spectrum (FFH) In an FFH spread spectrum the chipping rate, fc, (chipping rate is same as hopping rate) is greater than the base band data rate fb. In this case one message bit Tb is transmitted by two or more frequency hopped RF signals. The hop duration or chip duration (TH = TC), is defined by: TC = TH = 1/KTb for k = 1, 2, 3... And fc = fh = 1/TC 2.4 Advantages of Frequency Hopping Spread Spectrum (FH-SS) Some of the advantages of Frequency Hopping Spread Spectrum Modulation are as under:1. Frequency Hopping Spread Spectrum has an ability to provide diversity in fixed wireless access applications or slowly moving systems. 2. Frequency hopping system has a relatively short acquisition time than that of Direct Sequence system. 3. It can achieve greatest amount of spreading. 4. It can be programmed to avoid unwanted portions of spectrum. The second input to Modulo-Two adder has been generated by the frequency synthesizer driven by chaos oscillator. As such, this signal changes in a pseudorandom manner. The Chaotic signal generator is the heart of the proposed FHCDMA system. The chaotic signal generator is designed around a Wein bridge oscillator in which digitally controlled variable resistance technique using Linear Feedback Shift Register (LFSR), Decoders and array of transistors have been use to select randomly the resistor values and is given in Figure 2 and 1. The output of the oscillator thus produces the sustained analogue signal with varying frequency and amplitude. This FH-SS signal is thus regenerated at the receiver by means of the chaos oscillator in association with a locally generated PN sequence in a similar fashion as that used at the transmitter for Proper synchronization between transmitter and receiver. The FH- S generated at the receiver is modulo-2-added with the received

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Fig. 3. Waveform of output of FH-CDMA Receiver Transmitted Voice signal

modulated signal. The output of the Modulo-2-Adder is converted into Parallel form by using serial-to-parallel converter (Demultiplexer). The Demultiplexer output drives a digital to analogue converter. The resultant analogue signal is amplified and after low passes filtering to deliver the transmitted information signal at the receiver. The circuit diagram representation of the proposed scheme is outlined in Figure 2. The resultant FH-SS signal at the receiving end is shown in figure 3. The output of the receiver after de-spreading with the locally generated spreading code has been in the figure. It can be seen that the received signal which is similar to that of the transmitted signal shown in Figure 2.

3 Experimental Verification and Results The proposed Frequency Hopping Code Division Multiple Access (FH-CDMA) has been experimentally tested for its performance by transmitting and receiving a speech signal over the FH- CDMA system. Various waveforms obtained while transmitting and receiving the speech signal have been recorded for technical observation by using readily available non-linear and linear IC’s. The waveforms obtained at various check points have been found satisfactory and are in conformity with the theoretical observations. The waveforms obtained at various check points are shown in figure 3 as under:-

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4 Conclusion Spread Spectrum based Code Division Multiple Access (CDMA) are increasingly becoming more popular for multi-user communication systems. In most of such multi-user systems, the given bandwidth (in a given area) is to be divided and allocated to various communication channels. However, in order to share the same bandwidth by many users in a given service area, an equal number of unique pseudorandom codes with good correlation and statistical properties are required. Chaotic signal generators are generally used for generating pseudorandom codes with good correlation properties. In this paper hardware based chaotic signal generator has been proposed which can be easily programmed to generate a large number of unique random codes best suited for a multiuser CDMA system. The proposed programmable chaotic signal generator has been used to implement an FH-CDMA communication system and subsequently tested for the transmission and reception of a voice signal. The results of experimental verifications have been presented in the paper and are in conformity with theoretical observation. The proposed scheme will find a range of applications in Spread Spectrum modulation, CDMA, Global Positioning Systems (GPS) etc. Further, the proposed scheme guarantees adequate security with low system complexity.

References 1. Goodman, D.J., Henry, P.S., Prabhu, V.K.: Frequency -Hopping multilevel FSK for mobile radio. Bell Syst.-Tech., J. 59(7), 1257–1275 (1980) 2. Einarssen, G.: Address assignment for a Time-Frequency coded Spread Spectrum. Bell Syst. Tech. J. (7), 1241–1255 (1980) 3. Jiang: A note on Chaotic Secure Communication System. IEEE Trans. Circuits Systems, Fundamental Theory Applications 49, 92–96 (2002) 4. Bhat, G.M., Sheikh, J.A., Parah, S.A.: On the Design and Realization of Chaotic Spread Spectrum Modulation Technique for Secure Data Transmission, vol. (14-16), pp. 241–244. IEEE Xplore (2009) 5. Linnartz, J.P.M.G.: Performance Analysis of Synchronous MC-CDMA in mobile Rayleigh channels with both Delay and Doppler spreads. IEEE VT 50(6), 1375–1387 (2001) 6. Win, M.Z.: A unified spectral analysis of generalized time-hopping spread-spectrum signals in the presence of timing jitter. IEEE J. Sel. Areas in Communication 20(9), 1664– 1676 (2002)

Design and Implement on Automated Pharmacy System HongLei Che*, Chao Yun, and JiYuan Zang School of Mechanical Engineering and Automation, Beihang University, NO. 37 Xueyuan Road, Haidian District, Beijing, 100191, P.R. China [email protected], [email protected], [email protected]

Abstract. This paper introduces that the research design of the automated pharmacy system which is aim at accessing the packed drugs, which shows that the system should have three main functions and implementations of three main functions. Introducing the detailed structural design of the automatic medicineinput system, dense medicine-store system and medicine-output system; and researching on control methods of each executing agency in the system. In the end, it is to design the function of system software. The system has been developed and applied in Hospital outpatient pharmacy and it is in good working condition. Keywords: Packed Drugs, Automated pharmacy, Automatic medicine-input system, Dense medicine-store system, Medicine-output system, Controlling system.

1 Introduction The pharmacy is the pivotal issue of hospital. At present, the method of medicinestore mainly is fixed shelves in domestic hospital pharmacy, but this accessing mode has its unavoidable disadvantages: 1) drug storage is scattered and space utilization rate is very low; 2) pharmacist has high labor intensity and low working efficiency; 3) manual medicine-output makes mistakes easily, and cause drug accidents. Therefore, the hospital pharmacy automation is the new trend of development of pharmacy, and it is also an important sign of the service and working concept innovation [3]. This paper introduces the automated pharmacy system which mainly consists of automatic medicine-input system, dense medicine-store system and medicine-output system and database management system. The system can implement three basic functions which are medicine-input, dense medicine-store and medicine-output.

2 Automated Pharmacy System Ontology Structure Automated pharmacy system ontology structure, is shown in Fig. 1 as follows, including automatic medicine-input system, dense medicine-store system and medicine-output system. *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 167–175, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Fig. 1. Automated Pharmacy

2.1 Automatic Medicine-Input System Automatic medicine-input system mainly consists of medicine-input test system, medicine-input transmission system and medicine-input manipulator. Medicine-input detection system consists of operating platform, 3 laser rangefinding sensors and a PISO813 data acquisition card, as shown in Fig. 2. Data acquisition card collect real-time the kit length, width and height dimensions that are needed to add to dense storage system through three laser range-finding sensors, if the size of the collection is same as the size of kit in the data base, then it is transmitted to medicine-input manipulator, or generating error message.

Fig. 2. Detection of Medicine-input System

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Medicine-input transmission system consists of horizontal linear motion unit, vertical linear motion unit and synchronous transmission mechanism, as Fig. 3 shows.

Fig. 3. Transmission of Medicine-input System

Medicine-input manipulator consists of pedestal body, stepping motor, lifting board, transmission system, and rotating electromagnet, as shown in Fig. 4.

Fig. 4. Manipulator

The manipulators accept drugs that are tested, medicine-input transmission system will locate the medicine-input manipulator in the storage number of dense storage system, and stepping motor turned a certain Angle according to height of the kit, the lifting board lifts up the corresponding height driven by the synchronous belt. When kits rise to higher than the frame former board, because of the gravity, drugs will slide into

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the slot of the frame former board, and then slide into the slot of medicine storage in the dense storage system. Step motor repeats the above movements, until the lifting board hands out the last kit. In the process, if drugs decline due to friction, then rotate electromagnet work, drive the dial the piece to click, and make drugs slide successfully. 2.2 Dense Storage Systems Dense storage system consists of roller type slope store pharmacy and roller store medicine slot, as shown in Fig. 5. Roller type slope store pharmacy mainly consists of frame body, support beam, and roller medicine-store slot, frame body is 3540mm x built 1440mm x 2450mm cube structure which is composed by section aluminum; Support beam is constructed by aluminum extrusion, it and frame body are assembly constituted the installation matrix of roller store medicine slot.

Fig. 5. Dense Storage System

Roller medicine-store slot consists of roller, rolling shaft, parting strip, border and beams, as shown in figure 6. Beams and border compose the installation matrix of the roller medicine-store slot, the roller that is 10mm diameter is set into rolling shaft, the rolling shaft uniformly distributed with 20mm of separation distance. Because widths of pharmacy packed drugs are different, the bar is set into the rolling shaft; the space between adjacent parting strips constructs the minimum storage unit of packed drugs, because the parting strip is set into the rolling shaft, to enhance the overall rigidity of the roller medicine-store slot. Design idea is based on gravity blanking principle; the roller medicine-store slot is installed in store pharmacy with 15 ° angle, then drugs are affected by its own gravity after getting into store, and automatic slide into the opening of medicine-out of the dense storage system, wait for medicine-out.

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Fig. 6. Roller Medicine-store Slot

2.3 Automatic Medicine-Out System Automatic medicine-out system consists of the medicine-out driver and elevators. The packed drugs in the dense storage system is placed at the tilt roller medicine-store slot, each medicine-store slot keeps the same type of drugs, and form matrix arrangement as a whole. When there is no medicine-out action, the packed drugs is reliably located by fixed block shaft that is installed in the flanges of both ends. Medicine-out driver consists of electromagnet and flap, as shown in Fig. 7. The flap is installed in the ejector rob which is in front of electromagnets, After electromagnet electrified, the ejector rob contracts to drive flap rotate around of fixed axis, the front-end of the kit is jacked up by the flap at this time, when the bottom of the kit is higher than the limit block shaft, then take the medicine-out action. Then, the kit slides to belt of the elevator from the slope of the elevator.

Fig. 7. Medicine-out Driver

Elevator consists of guide rail, belt line, aluminum paddles, flap, transmission system, photoelectric sensor that is for testing drugs and self-protection sensor, as shown in Fig. 8 below. Elevator takes the lifting motion along the two guide rails in the vertical plane, after locating the position according to the layer position of medicine-store, the medicine-out driver acts and completes the medicine-out. Drugs are taken out and go through the photoelectric sensor testing surface; sensor sends

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detected signals to PLC, then count, and match with the number of drugs in the prescription. Taken drugs fall on the belt line directly, when drugs are taken completely, belt line transport drugs to the opening of medicine-out, then the flap is open, drugs are sent out, and complete the deployment of prescription drugs.

Fig. 8. Elevator

When drugs are blocked in the roller medicine-store slot because of the package quality, or because the slot surface is not smooth enough and so on, if the elevator continues to move, then the kit will interfere with its movement, when the problem is serious, which will damage the elevator and medicine-store slot. So there are two groups of bijective photoelectric sensors that are installed in elevator to be used for protection and detection. When kits or other objects block the detective light rays of sensors, the control system will stop elevator’s movement; when objects are removed, and detective light rays can pass, then the control system will control elevator to continue to move.

3 Automated Pharmacy System Control System The control system of automated pharmacy system adopts the function structure framework as shown in Fig. 9. System is divided into four functional modules: management level, monitoring level and control level, executive level. Management level: system prescribing information, drugs warehousing information, inventory information management center. Management level establishes the drug inventory database, which can receive HIS prescription information, according to the drug inventory, to construct medicine-input list, according to the principle that is “first-in first-out”, add the store address and quantity information to prescription drugs, distribute the prescription information that is dealt with, after receiving feedback value from the number of medicine-out, modify drugs inventory information, then dynamic real-time manage drugs inventory. Monitoring level: in the middle layer, makes information interaction with management level, receives management level’s prescribing information, makes task scheduling for each executive device, sends the control instruction that is generated by monitor program to control level; and communicates with control level, reads feedback quantitative values, monitors all kinds of signs and makes logical judgment processing.

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Hospital Information Management System HIS TCP/IP

Manageme nt Level

Automated Pharmacy Service Computer TCP/IP

Monitoring Level

Automated Pharmacy IPC RS232

ISA

PCI

PISO813 Data Acquisition Card

PMAC Motion Control Card

Controlling Level

CP1H PLC

AC Motors

Rotating Electromagnet

Photoelectric Sensors

Setpper Motor Drive

Bijective Sensors

Limit Level Sensors

Zero Level Sensors

Servo Drive

Llaser Sensor 3

Laser Sensor 2

Laser Ssensor 1

Executive Level

Setpper Motors

Servo Motors

Fig. 9. The Structure of Automated Pharmacy Controlling System

Control level: according to control instruction that is sent by monitoring level calls the corresponding bottom control procedures, then to control execution level parts. Executive level: accepts control level programming instructions, drives executive level motor to run and accords with requirements; kits detection, protection detection and system zero limit detection.

4 Automated Pharmacy System Software System Software system mainly consists of automatic medicine-input system and automatic medicine-output system, specific functions as follows. 4.1 Automatic Medicine-Input Software System Automatic medicine-input program flow is shown in Fig. 10 as follows.

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Beginning Initialization NO Whether medicine-in? YES Determine the number of the kits which will be put in the roller medicine-store slot. Manipulator prepare to motion. The kits which will be put in the roller medicine-store slot would be put on belt line of automatic medicine-input system. Laser sensors detect length, width and height dimensions of the kit.

Whether the kit dimensions consistent with the database?

NO

YES Delivery the kits to the manipulator Medicine-input transmission system take the manipulator to the roller medicine-store slot The manipulator let the kits slide in the roller medicine-store slot The manipulator and medicineinput transmission reset

Medicine-input accomplish

Fig. 10. The Program of Automatic Medicine-input

The combination of medicine-input testing system, medicine-input transmission system and medicine-input manipulator realized the drug batch supplies. As medicine-input, pharmacist put supply of drugs into medicine-input detection system, through the analysis of the size information that is collected by the laser displacement sensors, the drug that is correctly placed is conveyed to the medicine-input manipulator by medicine-input detection system. After the manipulator with medicine-input transmission system moves to supply medicine-store slot, the manipulator makes the action, supplies the drug into medicine-store slot of dense storage system. 4.2 Automatic Medicine-Output Software Systems The combination of medicine-output driver and elevator realized the drugs batch output. As drugs out, the system reads the drug store bits information in database, elevator moves to the location of drugs, the medicine-out driver acts, counting sensor sends the quantity of drugs of feedback to database. After completing this prescription medicine-out, elevator moves to the opening of medicine-out, the belt line of elevator and flap act at the same time, completes the medicine out. Automatic medicine-out program flow is shown in Fig. 11 as follows.

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Beginning NO

Initialization Read prescribing information

YES The elevator moves to the kits export

Belt line of elevator motion Servo motor positioning motion

Whether positioning motion of elevator is accomplished?

Whether the kits of prescription is accomplished?

NO

The flap of elevator open Delay 3 seconds, the kits slide out of the elevator The flap of elevator reset

YES Counting the number of the kits and feedback the actual number to the database

The belt line of elevator reset · Medicine-out accomplished

Fig. 11. The Program of Automatic Medicine-output

5 Conclusions This paper introduces the ontology structure, the control system and the design of software system of automation pharmacy system, at present, the operation of this system in hospital is in good condition, which proves that the system design is reasonable and feasible.

References 1. Liu, X.g., Yun, C., Zhao, X.f., Wang, W., Ma, Y.: Design and application on automatization device of pharmacy. Journal of Machine Design, 65–67 (2009) 2. Zhao, X.f., Yun, C., Liu, X.g., Wang, W.: Optimization for Scheduling of Auto-pharmacy System. Computer Engineering 193-195, 200 (2009) 3. Chen, L.: The Research and Its Implement of a New Type Intelligent Dispensing System for Chinese Medicine. Sichuan University, ChenDu (2004) 4. Subramanyan, G.S., Yokoe, D.S., Sharnprapai, S., Nardell, E., McCray, E., Platt, R.: Using Automated Pharmacy Records to Assess the Management of Tuberculosis. Emerging Infectious Disease 5(6), 788 (1999) 5. Thomsen, C.J.: A Real Life Look at Automated Pharmacy Workflow Systems. National Association of Chain Drug Stores 1, 29 (2005) 6. Thomas, M.P.: Medication Errors. Clinical Pediatrics 4, 287 (2003)

Research on Digital Library Platform Based on Cloud Computing Lingling Han and Lijie Wang Heibei Energy Institute of Vocation and Technology, Tangshan, Hebei, China [email protected], [email protected]

Abstract. Cloud computing is a new computing model. The emergence and development of cloud computing have a great effect on the development and application of digital library. Based on the analysis of the problem in the existing digital library, a new digital library platform architecture model based on cloud computing is put forward. The model consists of four lays: infrastructure layer, data layer, managment layer, and service layer. The structure and function of each layer are describled in great detail. The new digital library platform can be used to solve the problem of library resourse storing and sharing effectively, and provide fast, safe, convenient and efficient services to users. Keywords: cloud computing, digital library, security model, service interface.

1 Introduction With the development of computer, network and information technologies, digital library faces to great challenge, such as resource storing and sharing, various personal services requirement, and so on. In order to solve these problems and put digital library into full play, the existing library space and time constraints must be break. In the new time, digital library should carry out the humanist service. Cloud computing is an effective way to promote digital library development [1]. Cloud computing concept is proposed by Google firstly. IBM, Microsoft and so on also defined cloud computing. And now there is no a unified concept. In a word, cloud computing is a new new emerging computing model, which compromises the merits of Parallel Computing, Distributed Computing, Grid Computing, Utility Computing, Networkstorage Technologies, Virtualization and Load Balance. The principle of cloud computing is that integrating computers distributed in network into one entity with a strong ability to perfect computer system, and using Saas, PaaS, IaaS and MSP business model to put computing power to terminal computers. The services of cloud computing is managed by a Data processing center, who provides unified services’ Fig. 1. Cloud computing model S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 176–180, 2011. © Springer-Verlag Berlin Heidelberg 2011

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interface to users and meets users’ personal needs. Cloud computing services model is as figure 1. Since 2006, cloud computing concept is proposed by Google, cloud computing becomes a new research hot topic in IT area [2]. Now, cloud computing is wildly used in digital library, office system and so on. In 2009, the concept of cloud computing liabrary was proposed by Richard Wallis [3]. OCLC has announced that liabrary management service based on cloud computig will be supported to their number. Besides, District of Columbia Public Library and Eastern Kentucky University Library are offering services based on cloud computing. In our country, cloud computing is in the stage of theoretical research, many scholars do some research on cloud computing [4-6]. In order to promote cloud computing’s application in digital library, the paper put forward a new digital library model based on cloud computing. This model plays the role of cloud computing’s distributed store and power computing, can realize resource sharing and promote digital library serving efficiency.

2 Digital Library Model Based on Cloud Computing Today, there is a serial of problem in digital library, such as resource independent of each other, Low level of information technology, non-uniform resource form and hardware limitation. In order to solve these problems, this paper proposes a new digital library platform based on cloud computing, which can offer unified User Application Program service interface and provide personal service to different terminal users, such as computer, PC, and so on. The model Service Interface User Interface of digital library platform is as figure 2. Digital library platform consists of four layers: infrastructure layer, data Service Layer layer, management layer and service （Service Interface, Searching...） layer. Ditailed description of each layer is as figure 3. The lower and upper layer Managment Layer uses XML technology to communicat. （ Task and safety management..） Finally, the platform provides service to users through two ways: user interface Data Layer and service interface. According to （Database, Relationship…..） different authority, user can visit digital library and meet need through the above two ways. In the course of service, how Infrastructure Layer realization of the service is transparent to （Hardware, Software…..） users. Users only need to consider what Digital Library Platform services, regardless of the service implementation course. Fig. 2. Digital library platform model

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2.1 Infrastructure Layer Service Layer

User Interface Application Interface Hardware Management Data Managment Safety Management

Date Layer

Object Sets Object-relational Mapping

Cloud Computing

Managemet Layer

Databases Infrastructure Layer

The infrastructure layer of digital library platform is composed by a lot of public cloud and private cloud, which are integrated through internet to form a virtual a huge data center or a supercomputer. Refer to public cloud, library’s digital resource storage and application enviroment of data center can be built usint LaaS. Refer to private cloud, local library can build its digital library platform under main server and APP server provided by public cloud. Private cloud can protect some resource, which can not be allowed to visit, and most of resource is open to the other cloud. Through this way, it not only realizes resource sharing, but also ensures the safety of local resource.

Software

Hardware

Clound

Fig. 3. Structer of four layers

2.2 Data Layer The funciton of data layer is converting non-uniform data to unified resource object. It include databases, object-relational mapping and object sets. 2.2.1 Databases Different library platform may take different database. But there are almost useing following several databases: Oracle, SQL Server, and so on. 2.2.2 Object-Relational Mapping Different database has different driver, form of data storage. It should convert different data form to unified object. Object-relational Mapping can finish this work. 2.2.3 Object Sets Object sets include resource file, meta-information data, Source data directory, and so on, which is a set with unifrom format. The manager of digital library can complete the work of building digital library using object sets. 2.3 Management Layer Management layer is the core layer of digital library platform. Its function is to manage the hardware in Infrastructure layer, data resource in data layer, and system security.

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2.3.1 Hardware Management Hardware management is to schedule hardware in cloud to make system opreation efficiently, it include network control, server cluster, and so on. It not only makes the computing opration parallelization, but also deals with mostly system failure automatically. 2.3.2 Data Management L.Richardson proposed there are seven standard services provided by digital library platform based on cloud computing as figure 4. There are resource creating service, resource cataloging service, index creating service, resource searching service, library management, resource browsing service, and meta- information management Service [7]. These seven services are realized by different event, and can finish object create, selection and delete.

Data Management

Meta-information Management Service Library Management

Resource Browsing Service

Index Creating Service

Resource Searching Service

Resource Creating Service Resource Cataloging Service

Fig. 4. Structure of data management

2.3.3 Security Management In order to ensure system’s safety, a serial of security measure should be taken. System security model is as figure 5.

Operation Authority

User

Opretaing transparency Mechanism

Data Encryption Mechanism Internet Cloud Trust Mechanism Information Security Assessment

Fig. 5. Security model

Access Control

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In private cloud, data backup, system log, device monitor, et al are taken to ensure local resource safe. Between the different clouds, system takes information safety assesment, Mutual trust mechanism, and Data Encryption to protect the security of communications. Besides, opration is Transparent to users. The opration of data storage, computing, invalidation, and so on are all isolated to users. And digital library manager can assign different permissions according to users’ identity. 2.4 Service Layer Service layer provide visiting interface to users. Users with administrative privileges can finish the work of library management, lending management, library charges, and application development and expansion. Personal users can login digital library and enjoy online services, such as books borrow, books scheduled, documentation retrieval, and academic exchanges.

3 Summary Cloud computing is a new effctive way to build modern digital library platform. Based on cloud computing the paper presents a new digital library platform model, and its architecture is given in detail. This digital library platform implements resource storage and sharing efficiently, and provides users with fast, convenient and efficient services. This study could provide the reference effect for the design and realization of digital library.

References 1. Hu, X.J., Fan, B.S.: Cloud Computing: The Challenges to Library Management. Journal of Academic Libraries 27(4), 7–12 (2009) 2. Buyyaa, R.: Cloud computing and emerging IT platfrorm: Vision, Hype, and reality for delivering computing as the 5th utility. Future Generation Computer System 6, 599–616 (2009) 3. Wallis, R.: Cloud Computing Libraries and OCLC. The Library 20 Gang, EB (2009), http://librarygang.talis.com/2009/05/06/library-20-gang-0509cloud-computing-libraries-and-oclc/,2009-05-15 4. Zhou, X.B., She, K., Ma, J.H.: Compostion Approach for Software as a Service Using C loud Computing. Journal of Chinese Computer Systems 31(10), 942–1953 (2010) 5. Zhang, G.W., He, R., Liu, Y., Li, D.Y.: An Evolutionary Algorithm Based on Cloud Model. Chinese Journal of Computers 31(7), 1082–1091 (2008) 6. Zheng, P., Cui, L.Z., Wang, H.Y., Xu, M.: A Data Placement Strategy for Data-Intensive Applications in Cloud. Chinese Journal of Computers 8, 1472–1480 (2010) 7. Richardson, L., Ruby, S.: Restful web services, EB/OL (2010), http://home.cci.lorg/~cowan/restws.pdf

Research on Nantong University of Radio and TV Websites Developing Based on ASP and Its Security Shengqi Jing Radio and TV University of Nantong, Jiangsu, China

Abstract. The paper firstly introduced the current research and development of the ASP technology at home and abroad. Secondly it introduced particularly ASP technology based on Nantong University of Radio and TV Website, database technology, security technology of network and security of Web station. Basing on the research above, the author presented the functions of management, display, query and so on. Then I introduced particularly several technologies which had to be mastered in the aspects of security of the Web station, including encryption and attestation technology, firewall technology, intrusion detection technology, system copying technology, and so on. At last the paper made a conclusion and analysis. It presented use for reference of the exploitation and security research of information query system based on ASP and received good result. Keywords: ASP, SQL database, security, Nantong.

1 Introduction ASP (Microsoft Active Server Pages) is Microsoft's development of a service-side scripting environment, which is a collection of objects and components. ASP file is an executable script embedded in HTML documents, HTML and Active Control will combine to produce and implement dynamic, interactive, high-performance Web server applications with the extension. Asp. ASP technology is a replacement for CGI (Common Gateway Interface, Common Gateway Interface) technology. Simply speaking, ASP is a server-side script in the operating environment, through such an environment, users can create and run dynamic, interactive Web server applications, such as interactive dynamic web pages, including the use of HTML forms to collect and process information, upload and downloads, as users use their own CGI programs in the same, but it is much simpler than the CGI. More importantly, ASP uses ActiveX technology is based on an open design environment, users can define and produce their own components to join, so White has the dynamic web page with almost unlimited expansion capacity, which is the traditional CGI programs are far less than other place. In addition, ASP can use ADO (Active Date Object, Microsoft, a new data access model) easy access to the database, so that the development of applications based on WWW is possible [1]. ASP advantages.ASP technology is intuitive, easy to learn the advantages of a beginner in the short term can also write reliable code. It also provides a more powerful, S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 181–186, 2011. © Springer-Verlag Berlin Heidelberg 2011

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it can greatly speed up the development of the project. Although this is only a few years the birth of ASP technology, already widely used reasons. ASP is very obvious advantages: First, it is really nothing to do with the browser, the system is running on the server side, just the standard HTML language of the results returned to the client browser, regardless of which browser the client is; Second, it is completely server-side operating systems, software maintenance, upgrades, completely on the server side, the client does not need any preparation; again, ASP scripting language can be any Script language, as long as the engine on the line to provide the appropriate, ASP VB Script support itself and Java Script, free to decide which one to use. Now a common network database through a browser to access the technology has CGI, JDBC, etc., but the realization of the technology is much more complicated than the use of ASP, taking into account the actual needs of the system and the advantages of ASP, so use ASP technology to achieve system [2] . Specific advantages are the following: (1) Increased efficiency in development: ASP provides an easy to learn the script, and with many built-in objects, which greatly simplifies the development of Web applications, so development efficiency can be improved. (2) Interaction: ASP page is a page with computing power, it can in the run-time environment and the use of different parameters produce different HTML output. Although ASP is a server-side applications, but it can also be the traditional client-side scripting and plug the control outside the mixed use, dynamically generated for the browser running on the layout of the script and negative outside the object inserted in the client browser dynamically generated graphical user interface. (3) Security enhancements: ASP script executed on the server, the user's browser is just spread the implementation of the results of ASP generated HTML documents, this was to reduce the requirements for the browser, on the other hand strengthen the security of the system . (4) Cross-platform: ASP is the main body and platform-independent HTML and various scripts, both of which do not have to be built, the connection procedure can change the content timely, direct running in various operating environments, ActiveX component is developed by a variety of programming languages, and vendor-independent, cross-operating environment across the network implementation of binary components, and through the HTML and script, developers can easily set various functions of the ActiveX Service ASP web applications composed of a set piece. (5) IIS and ASP technologies: taking into account the interactive features of the system, you can use IIS and Active Server Pages technology (ASP) to achieve dynamic, interactive Web design [3]. IIS (Internet Information Server) is Microsoft Windows-based system provided by the Internet Information Server, the WWW service includes ASP script server to support ASP technology. IIS has a simple installation, powerful, and protocol compatibility with other Microsoft software compatibility, the company's development and so on [1]. IIS and ASP technology with simple and efficient to Web and database connections. HTML scripts, and other components will be compared to the co. Establish an efficient interactive environment for dynamic Web applications. The interaction is expressed in, according to information submitted by users and respond to, no manual update a file on

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the page to meet the application needs. Database data can change at any time, and the server application running on it without having to change [4].

2 Establish an Information Inquiry System Website 1. We click on the "Start" / "Settings" / "Control Panel" / "Administrative Tools" / "Internet Services Manager" item, you can open Internet Information Services window. 2. And then right-click "Default Web Site" in the pop-up menu, select "New" / "virtual directory" to be "Virtual Directory Creation Wizard" dialog box. 3. Click "Next" button in the dialog's "Alias" text field enter the alias news. 4. Click "Next" button to the folder that contains the site designated for the virtual directory path. (Virtual directory access permission to take the system default settings) Click "Next." 5. Click "Done" button, IIS configuration is completed [4]. Configuration Database.The system uses SQL Server2000 Chinese version of the database, the database server and Web server can be configured in the same computer can also be configured on both computers. The configuration of these two methods is similar. Specific steps are as follows: 1. In the Windows desktop, select "Start" / "procedure" / "Microsoft SQL Server" / "Enterprise Manager" menu command, open SQL Server Enterprise Manager control panel. 2. Right-click the tree menu in the "database" item, choose the pop-up menu of the "New Database" menu item. 3. In the "Database Properties" dialog "General" tab, "name" text box, enter the database name of the news, click "OK" button, create an empty database news. 4. Right-click the new database, news, pop-up menu, select "All tasks" / "Restore database" menu item. 5. In the "Restore Database" dialog box, select "From device" single option. 6. Click the "Select Device" button, select the "Choose Restore Devices" dialog "Restore from [F]: Disk" single option. Then in the text box of the original file path. 7. Click "OK" button to complete the configuration of the database restore. 8. In articleconn.asp file set the database connection string. Connstr = "PROVIDER = SQLOLEDB; DATA SOURCE = (local); UID = sa; PWD = password; DATABASE = news "[4] 2.1 Website Design A typical information search site should contain at least information management, information display and information inquiry function 3. Design objectives.Information search site to achieve the following functions: 1. Information Management information is added Information Change Delete information

① ② ③

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2. Information Display Show all information Do not display information by the query information by keyword 3. Station by keyword query [4]

① ② ③

System Functional Analysis and Design.Information query is divided into three modules: information management module, the information display module and the information query module, the function modules shown in Figure 1.

Add Management

Information Delete

Show all information Information Display

Information by Category Query information by

Information query

Check station by keyword Fig. 1. Functional Block Diagram

2.2 Database Structure Design According to the system functional design requirements and module division, information search site mainly contains information on the recorded data and data structures. 2.2.1 Database Requirements Analysis Information recorded includes the following: information record number. information about name, type of information. description. message size. Time and Views information.

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2.2.2 Logical Database Design Information recording table learning, as shown in Table 1: Table 1. Information Record Form

Allow

Column name

Data Type

Length

articleid

int

4

type

nvarchar

50

√

title

nvarchar

255

√

url

nvarchar

255

√

content

ntext

16

√

hits

int

4

√

big

nvarchar

50

√

vote

nvarchar

50

√

[from]

nvarchar

50

√

fromurl

nvarchar

255

√

dateandtime

smalldateint

4

√

air

2.3 Information Management Module Website management module contains the following sub-modules. The relationship between the page shown in Figure 2. 2.4 Information Management Login The module involves a total of three pages: login.asp, chklogin.asp, manage.asp. login.asp. This page requires the user fill out the HTML form element has only two. This page is presented to the system administrator user name and password, so not related to the operation of the database table. chklogin.asp. The page for the administrator name and password verification page, need not complete the HTML form elements, and administrator name and password for the file exists, and therefore not related to the operation of the database table. manage.asp. This page is seen after a successful administrator login page, need not complete the HTML form element, the use of the information in the system log sheet learning. Added information. The module involves a total of three pages: add.asp, save.asp, art_class1_put.asp

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Administrato r Login login.asp

Audit Account chklogin.asp Yes

No

Web page

Management Interface manage.asp

Add information add.asp

Information Change edit.asp

index.asp

Delete information delete.asp

Fig. 2. The relationship between the pages

3 Conclusions This paper describes in detail the information inquiry system based on ASP web site design and implementation process and the security of the site, which is based on ASP web development with theoretical and practical significance,at last,with the method, set up Web page of Nantong University of Radio and TV.

References 1. Wang, C.H., Xu, H.X.: Site planning, construction and management and maintenance of tutorials and training. Beijing University Press, Beijing (2008) 2. Zhang, Y.Y.: Site Management Manual. China Water Power Press, Beijing (2010) 3. Tao, T.: Dynamic Web-based ASP technology design and implementation. Fujian PC (November 2010) 4. Gu, X.M., Zhang, Y.P.: ASP-based security research. Computer Engineering and Design (August 2004) 5. Kern, T., Kreijger, J., Willcocks, L.: Exploring ASP as sourcing strategy: theoretical perspectives, propositions for practice. Journals of Strategic Information Systems (November 2009)

Analysis of Sustainable Development in Guilin by Using the Theory of Ecological Footprint Hao Wang, GuanWen Cheng*, Shan Xu, ZiHan Xu, XiaoWei Song, WenYuan Wei, HongYuan Fu, and GuoDan Lu College of Environmental Science and Engineering, Guilin University of Technology, No.12 Jiangan Road, Guilin, Guangxi, China [email protected], [email protected] Abstract. This study is a project which calculates ecological footprint of Guilin in the past decade by theory of ecological footprint. The results showed that: from 1999 to 2008, per-capita biological capacity was stable, per-capita ecological footprint grew from 1.3434 hm2/cap to 2.0499hm2/cap, per-capita ecological deficit increased in study period. Ecological footprint per ten-thousand GDP declined by almost 50%. According to the results we can find ecosystem of Guilin was in a unsustainable state. Therefore, it is necessary to accelerate economic growth mode transformation, develop ecological industries and advance biological capacity in Guilin. Keywords: Ecological footprint, Biological capacity, Sustainable development, Guilin city.

1 Introduction Natural ecosystem is the material basis on which human rely for existence, and the sustainable development should be conducted on biological capacity of ecosystem [1]. With the development of economy and increasing population, it’s important to analyze quantitative data and interpret the sustainable development in Guilin. Ecological Footprint (henceforth EF) was firstly proposed by Canadian scholar Rees and his student Wackernagel [2,3]. At prensent, many domestic and foreign scholars has been conduced much study and applied it to research the regional sustainable development [4,5]. This paper is based on EF model and statistical data [6] to calculate and analyze EF. The results showed that the state of biological capacity and resource utilization, proposing scientific suggestions during the process of sustainable development in Guilin.

2 Overview of Guilin City Guilin is located in northeast of Guangxi Zhuang Autonomous Region, main terrain of Guilin is hill country, in the north, east and west of Guilin are mountains, the elevation are higher than the central, south and northeast part of the city which are plains. The total administrative region is 27828 square kilometers. There were 508.32 million *

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inhabitants, 88.303 billion Yuan GDP and the production of three industries was 19.4: 45.2: 35.4 in 2008, It’s initially established some pillar industries such as electronics, rubber, and processed food etc.

3 Methods EF refers to the geographical space occupied by human being with ecological productivity, and providing resources or waste acceptance under the existing living standard. Calculation of EF starts from two assumption with description as follows: Firstly, humans can determine their own consumption of resources, energy and waste; Secondly, these resources and waste can be converted into biological productive areas or ecological production areas that can produce and consume them. Biological productive areas included the following 6 items: cropland, forest, grassland, fishing ground, built-up land and fossil fuel land. The formula is: ef =EF/N=∑aiAi =∑Ci/pi 2

(1) -1

ef denotes per-capita ecological footprint (hm ·cap ); EF indicates that the total ecological footprint of regional ecosystem; N is the population of Guilin; ai is equivalence factor; Ai represents one item consumption of per-capita ecological footprint (hm2·cap-1); Ci stands for one item of per capita consumption; pi is one item of the global average land productivity (kg·hm-2). Biological capacity (henceforth BC) is considered as ability for providing biologically productive areas in a country or a region. The equation is: bc= BC/N=0.88×∑aj×rj×yj

(2)

BC is biological capacity; bc denotes per-capita biological capacity; aj represents per-capita areas; yj stands for yield factor; rj is equivalence factor; N is the population Yield factor donates the dispersion between the local yield, which is represented by the items of biologically productive areas in different countries or regions and average yield of the world. The values of yield factors in this paper are: cropland 1.7, built-up land 1.7, forest 0.9, grassland 0.2, fishing ground 1.0, and fossil fuel land 0 [7]. It is used that equivalence factors to standardize different items of lands. The values of equivalence factors in this paper are described as follows: cropland 2.8, built-up land 2.8, forest 1.1, fossil fuel land 1.1, grassland 0.5 and fishing ground 0.2 [8]. It is deducted from 12% biodiversity areas in the calculation of BC. Compared resources and energy consumption of a region with its BC, it is find that whether the EF beyond its BC. If the EF is greater than its BC, it’s called ecological deficit; otherwise called ecological surplus. EF per ten-thousand GDP is a ratio of per-capita EF and the region's gross domestic product (GDP), this indicator can reflect the utilization of land resources in a region. The smaller value it is, the higher land productivity will be. Setting year and per-capita GDP as independent variables, per-capita EF as dependent variable, getting scatter plot and finding the best fitting curves, then utilizing SPSS to analyze the statistical data and judging whether the fitting curves can characterize the trends of per-capita EF with per-capita GDP and year.

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4 Results and Discussion Table 1 shows the per-capita EF and per-capita BC in Guilin from 1999 to 2008. As can be seen from the table, per-capita EF rises 52.6% during the decade(Fig.1). The proportion of cropland, forest, grassland and fishing ground representing consumption of biological resources are much higher than the proportion of fossil fuel land and built-up land representing consumption of energy in EF. It indicates that the consumption of biological resources are greater than the consumption of energy. Table 1. Per-capita EF and per-capita BC in Guilin from 1999 to 2008 [hm2/cap]

Years

Cropland

Forest

Grassland

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

1.0803 1.1246 1.1504 1.1489 1.1667 1.2265 1.3221 1.3736 1.2983 1.1599

0.1082 0.1027 0.1179 0.1345 0.1802 0.1846 0.1937 0.2266 0.2343 0.5589

0.0299 0.0318 0.0352 0.0358 0.0404 0.0450 0.0515 0.0553 0.0604 0.0495

Years

Cropland

Forest

Grassland

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

0.2452 0.2421 0.2390 0.2340 0.2233 0.2216 0.2217 0.2199 0.2177 0.2167

0.2756 0.2886 0.2835 0.2836 0.2836 0.2769 0.2774 0.2751 0.2722 0.3066

0.0006 0.0006 0.0006 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005

Built-up land 0.0008 0.0008 0.0009 0.0009 0.0012 0.0019 0.0021 0.0025 0.0029 0.0034 Built-up land 0.0758 0.0769 0.0781 0.0792 0.0803 0.0813 0.0831 0.0839 0.0845 0.0854

Fishing ground 0.0099 0.0103 0.0107 0.0109 0.0117 0.0123 0.0131 0.0141 0.0150 0.0110 Fishing ground 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0025 0.0025 0.0025

Fossil fuel Per-capita land EF 0.1144 1.3434 0.1048 1.3749 0.1163 1.4314 0.1507 1.4817 0.1977 1.5980 0.2117 1.6821 0.2225 1.8051 0.2388 1.9110 0.2829 1.8938 0.2673 2.0499 Fossil fuel Per-capita land BC 0 0.5999 0 0.6108 0 0.6038 0 0.5999 0 0.5902 0 0.5828 0 0.5852 0 0.5820 0 0.5775 0 0.6118

In the consumption of biological resources, both proportion of cropland and forest beyond 80%, mainly for the comsumption of pork and agricultural products (including cereals), fruit and wood. In the consumption of energy, fossil fuels such as coal and coke are larger than other energy. It is shown that citizens’ living conditions, urbanization and industrial development are still lag behind other affluent areas. Relatively low level of industrialization and traditional structure of energy consumption are not changed significantly. From 1999 to 2008, the EF of six items of lands showed an upward trend. With forest and built-up land grow rapidly, the average annual growth rate are 17.5% and 16.03% respectively, the growth of forest indicates that demand of forest and farm

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EF(10 6 hm 2 )

Cropland Forest 11 Fishing ground Grassland 10 Fossil fuel land Built-up land 9 8 7 6 5 4 3 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Year

Fig. 1. The proportion of ecological footprint

produce such as woods, oil cropland fruit are increased; growth of built-up land area reflects the result of urbanization in the past decade. Slower growth lands are fishing ground and cropland, average annual growth rates are 1.08% and 0.71% respectively, the results showed the limitation of natural resources, especially the major biological resources restriction. During the decade, BC remained at 0.60 hm2/cap, cropland and forest providing much than 0.5hm2/cap, while the grassland, fishing ground and built-up land provide less (Table 1). From the perspective of the growth rate of various lands, it is clearly that an increasing trend of built-up land, the average annual growth rate is 1.21%, by process of urbanization; forest changes in a weak fluctuation condition, it shows that urban ecological construction is in a relatively stable state; cropland is negative growth (-1.23%), the average annual decrease rate is roughly equal to the average annual rate of built-up land. Increasing infrastructural land is the main factor of cropland reduction. It is pivotal to insure BC and achieve sustainable socio-economic development by strengthen urban and rural planning, reduce depletion of cropland. Because of the restriction of self-sustain, self-control, the resource and environment capacity of eco-system, per-capita BC grows slowly in Guilin in the past decade. But per-capita EF increases rapidly. Hence, per capita ecological deficit grows from 0.7436hm2/cap in 1999 to 1.4382 hm2/cap in 2008, increases 93.4% (Fig.2). There is a lack of energy and main productive resources such as ironstone, phosphorite and other Per-capita Biological Capacity Per-capita Ecological Footprint Per-capita Ecological Difict

hm 2 /cap

2.5 2.0 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5

1999200020012002200320042005200620072008 Year

Fig. 2. The trend of ecological deficit

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constraints in Guilin. To maintain the sustainable development of ecosystem and improve people's living standards, it’s necessary to input biological resources and energy resources from external environment. There are different trends of per-capita GDP and EF per ten-thousand GDP from Fig.3. Per-capita GDP increases with year, but EF per ten-thousand GDP decreases from 2.3130hm2/cap to 1.1801hm2/cap. With the recent economic restructuring, economic growth mode transformation, and technology optimization and equipment upgrade in every walk of life, the efficiency of resources utilization increases and resources dependence of ten-thousand GDP decreases, leading EF per ten-thousand GDP decreasing significantly. Per-capita EF forecast with year By means of 1 to 10 instead of the years from 1999 to 2008 respectively, and analyze the main statistics by SPSS, the regression equation is y = 1.2501e 0.0491x, the main statistics are: R2 = 0.982; F = 442.615; sig = 0.000, the results show that the relationship between per-capita EF and year is notable(Fig.4). According to the equation, we can predict per-capita EF in Guilin next five years: from 2009 to 2013, the values are 2.1511hm2/cap, 2.2598hm2/cap, 2.3740hm2/cap, 2.4940hm2/cap, 2.6170hm2/cap respectively. Per-capita EF forecast with economic development Firstly, taking per-capita GDP and per-capita EF as independent variable and dependent variable respectively, then making fitting curve (Fig.5). The best fitting equation is the logarithmic equation

Per-capita GDP

EF per ten thousand GDP 2.4 2

1.6

1.6

1.2

1.2 0.8

0.8

0.4

0.4

0

EF per ten thousand GDP

Per-capita GDP 2

0 1999200020012002200320042005200620072008 Year

2.2 2.0

y = 1.2501e0.0491x R 2 = 0.982

1.8 1.6 1.4 1.2

Per-capita EF(hm 2 /cap)

Per-capita EF(hm 2 /cap)

Fig. 3. The trend of EF per ten-thousand GDP 2.4 2.2

y = 0.6617Ln( x ) + 1.7086 R 2 = 0.968

2.0 1.8 1.6 1.4 1.2

0 1 2 3 4 5 6 7 8 9 10 Year

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 Per-capita GDP(ten thousand yuan)

Fig. 4. The trend of EF with year

Fig. 5. The relationship between per-capita EF and per-capita GDP

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y = 0.6617lnx +1.7086. Analyzing the main statistics by statistical software SPSS: R2 = 0.968, F = 245.748, sig = 0.000. They indicate that the relationship between per-capita EF and per-capita GDP is notable too, the fitting equation can interpret and forecast the trend of per-capita EF with per-capita GDP. The two results showed that per-capita EF grows with year and per-capita GDP , if BC of Guilin maintained a stable state, ecological deficit would be grown year after year and eco-system will face greater pressure. Growing per-capita GDP reflects improvement of citizens’ living standards and growth of various resources consumption, but increasing consumption is satisfied by excessive consuming resources and inputing resources from outside, neither conducive to sustainable development of Guilin, nor the best way to decrease excessive resources consumption. Therefore, improving the local BC and reducing EF is imperative.

5 Suggestions (1) Controlling population size and improving population quality. Guilin has been in condition of ecological deficit in the past decade, and the deficit increased constantly. As the expansion of population year by year, biological resources and energy demand will be certainly increased, as well as the waste amount will be increased. Hence, the ecological environment will face with more pressure. It is important to control population to decrease EF. At the same time, knowledge of ecological environmental protection and sustainable development should be educated, it’s help to guide reasonable consumption and reduce resources waste in Guilin. (2) Increasing the level of technological development and promoting industrial restructuring. Science and technology are primary productive forces. The higher productivity it is, the stronger BC will be. It is important for improving BC and reducing ecological deficit to develop technology productivity. It is held to strengthen science and technology research and develop local pillar industries, promote technological innovation, transfer scientific and technological achievements to practical productive forces. Meanwhile, concentrate manpower and resources to develop local characteristics and competitive industries, such as motor vehicles and parts, food and beverage processing, rubber, pharmaceutical and biological products and promote development of industrial clusters or industrial chain (such as Fruit cultivation - Drinks and local and special products processing - Eco-tourism), improve ecological footprint of cropland and forest, accelerate economic development rapidly and reduce waste emissions. (3) Strengthening agricultural production and ensuring cropland and forest supply. Cropland consumption occupy a large proportion of the EF in Guilin, it is utilized that a business model likes "company + base + farmers" to accelerate integrative process of agricultural cultivation, processing and marketing. Furthermore adjust agricultural structure and product structure, optimize the layout of agricultural areas, improve the quality and production of major agricultural products such as food, fruits, vegetables by reforming low-yielding farmland, change farming method, improve crop varieties and cultivation techniques. Developing three-dimensional planting and breeding, promoting a planting and breeding mode expressing biogas as a link to pig, methane, fruit (vegetables) to achieve integrated development of agriculture, and enhance people's way to get rich. Forest resource is abundant in Guilin. It is important to rational exploit and utilize of forest resource in precondition of ecological protection.

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(4) Increasing the efficiency of fossil fuels and developing clean energy. Fossil fuels are the main energy consumption in Guilin, but the city have little coal resource which requires input coal resources from outside, it will bring urban air pollution. Therefore, it is necessary to promote hydropower, solar and other clean energy, making the best of straw, animal waste and other biomass resources to develop biogas energy to achieve waste recycling and accelerate eco-agricultural development. It’s beneficial to improve the energy structure and reduce dependence of external energy.

6 Conclusions In study period, EF indicated that an increasing trend, the values grew from 1.3434hm2/cap to 2.0499hm2/cap and BC was stable. Therefore, per-capita ecological deficit increased. Growing efficiency of resource utilization led to EF per ten-thousand GDP decrease; per-capita EF increased with year and per-capita GDP by predictive analysis in future. In the past decade, resource supply could not meet the resource consumption in Guilin. Ecosystem was under a condition of unsustainable development. On the basis of population control, development of science and technology should be energetically promoted, and economic growth mode should be transformed to enhance BC, meanwhile resources and energy consumption patterns should be changed to improve the efficiency of resource utilization, reduce the EF and promote socio-economic sustainable development in Guilin. Acknowledgements. The work was supported by a Program Sponsored for Educational Innovation Research of University Graduates in Guangxi Province (No.200910596R01) and the Guangxi Key Laboratory of Environmental Engineering, Protected Assessment.

References 1. Xu, Z.-m., Zhang, Z.-q., Cheng, G.-d.: Ecological Economic theory method and application. Yellow River Conservancy Press, Zhengzhou (2003) 2. Rees, W.E.: Ecological footprints and appropriated carrying: what urban economics leaves out. Environmental Urbanization 4, 121–130 (1992) 3. Wackernagel, M., Rees, W.E.: Our Ecological Footprint: Reducing Human Impact on the Earch. New Society Publishers, Gabriola Island (1996) 4. Scotti, M., Bondavalli, C., Bodini, A.: Ecological Footprint as a tool for local sustainability: The municipality of Piacenza (Italy) as a case study. Environmental Impact Assessment Review 29, 39–50 (2009) 5. Zhang, H.-Y., Liu, W.-D., Lin, Y.-X., et al.: A modified ecological footprint analysis to a sub-national area: the case study of Zhejiang Province. Acta Ecologica Sinica 29, 2738–2748 (2009) 6. Guilin Economic and Social Statistics Yearbook, editorial board: Guilin Economic and Social Statistics Yearbook. Chinese Statistics Press, Beijing (1999-2008) 7. Xu, Z.-m., Chen, D.-j., Zhang, Z.-q., Cheng, G.-d.: Calculation and analysis on ecological footprints of China. Acta Pedologica Sinica 39, 441–445 (2002) 8. Zhang, Y., Wu, Y.-m.: The eco-environmental sustainable development of the Karst areas in southwest China analyzed from ecological footprint model-a case study in Guangxi region. Journal of Glaciology and Geocryology 28, 293–298 (2006)

Analysis of Emergy and Sustainable Development on the Eco-economic System of Guilin ZiHan Xu*, GuanWen Cheng, Hao Wang, HongYuan Fu, GuoDan Lu, and Ping Qin Guilin University of Technology, Guilin, P.R. China [email protected] Abstract. Using the emergy theory, the eco-economic system of Guilin is analyzed, which has related to about 9 indexes such as net emergy yield ratio (EYR), emdollar value (Em$), emergy investment ratio (EIR). Finally,drawin g some conclusions as follows:(1)The net emergy yield ratio (EYR) of Guilin has rosen from 5.748 in 2003 to 6.749 in 2008, which indicates the net benefits of eco-economic system in Guilin has improved, and the production efficiency has enhanced. (2)The trend of environment loading ratio (ELR) of Guilin has ascended, which suggests the environmental pressure has increased. (3)The emergy index for sustainable development (EISD) of Guilin has fallen from 2.710 in 2003 to 0.865 in 2008, suggesting that the ability of sustainable development has quickly diminished. Keywords: Emergy analysis, Eco-economic system, Analysis of sustainable development, Guilin city.

Ecological economic system is the basis for sustainable development to mankind, however, with the social progress and economic development, the eco-economic system was damaged unprecedentedly, which has been a serious threat to human′s survial and development, therefor, sustainable development has become a human′s consensus and one of the main goals for the future exploration. The emergy analysis theory proposed by the famous American ecologists H.T.O dum has balanced well the energy, information and economy flow for the first time, which helps us to conduct correct analysis on the value and relationship of nature and human, environmental resources and social economy[1-3]. This article using the emergy analysis method, and looking the society, economy and environment of Guilin as a compound eco-economic system to analyse, wants to evaluate the sustainability of Guilin quantificationally and put forward corresponding countermeasures.

1 Situation in Researched Area and Research Method 1.1 General Situation in Researched Area Guilin is located in the southwest of Nanling ridge and northeast of Guangxi autonomous region, which is the typical karst landform and one of the famous scenic *

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cities and historical cities in the world. In the late of 2008, the city had 27800 km2 land area, population reached 508.32 ten thousand, and production value reached 883.02 hundred million yuan, which was 18.64% in growth over the previous year, and the structure of three industries was 19.42: 45.24: 35.34[4]. Guilin is a emerging industrial city which has a good basis, and it has formed electronics, rubber manufacturer, machine industry, cottonocracy, pharmacy, coach manufacture, handicraft, and food and light industry as its pillar industries, the construction of going to scale for industries and enterprises is effective, which makes economic increase substantially, the city's industrial enterprises above designated size has reached 765, and the output value of industry has reached 35.071 billion yuan. 1.2 Energy Analysis Method and Procedure The theory and method of emergy analysis established by H.T.Odum ststes that any form of energy is derived from solar energy, solar emergy is used as a benchmark to measure energy value of various energies in the real application. Based on the emergy, we can measure and compare the true value of different types and grades; we can also use it to transform different types and incomparable energies to emergy by emergy conversion rates. This study includes the following steps:

《

(1) Collect the relevant geographical and economic data in Economic and Social Statistic Yearbook of Guilin from 2003 to 2008. (2) According to the "energy system language" legend presented by H.T.Odum, determine the boundaries of system-wide, the main energy source, the main components of the system, and list the system processes and relationships within various components. (3) List the main items of energy input and output, and convert each category and material into common emergy unit with the corresponding conversion rate to evaluate their contribution in the system and status. (4) Merge the similar and important project. (5) In line accordance with the local characteristics, the table of emergy analysis and system classification, optimize and select the overallemergyindexes. (6) Propose the rational countermeasures based on the results.

》

2 Analysis of Research Results According to the raw data from major sources of eco-economic system and currency flows in Guilin from 2003 to 2008, the summary of emergy flows can be calculated (Table 1), from the table, it shows the city resource emergy flow is not high, of which about 74% are non-renewable resources. Resource constraint is very obvious. Meanwhile, based on the statistics in Table 1, the main indicators of economic development in Guilin from 2003 to 2008 (Table 2) are calculated. 2.1 Net Emergy Yield Ratio Net emergy yield ratio (EYR) is output emergy of the system to economic feedback emergy ratio, an indicator to measure the size of the economic contribution of the

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system′s output, and also a standard to measure the system′s efficiency. The EYR of Guilin can be seen from Table 2 that EYR of Guilin has improved overall, but still has some fluctuations, which shows the net benefit of eco-economic system in Guilin has increased, the production efficiency and competitiveness has been enhanced in the same condition of input economic emergy. Table 1. The major emergy flows of Guilin in 2003~2008 year

Items (1020sej) The emergy flow of local renewable resoures:EmR The emergy flow of local non-renewable resources:EmN The emergy flow of input renewable resoures:EmIR The emergy flow of input non-renewable resoures emergy:EmIN The emergy flow of input labor emergy:EmIL The emergy flow of actually used foreign currency:EmIM The emergy flow of input:EmI= EmIR+EmIN+EmIL+EmIM The emergy flow of input production:EmIS=EmIR+EmIN The emergy flow of currency from brought production:EmISP The total emergy:EmU=EmR+EmN+EmI The emergy flow of output production and labor:EmEO The emergy flow of waste:EmW The emergy flow of output:EmO=EmEO+EmW

2003

2004

2005

2006

2007

2008

60.20

60.40

62.90

60.70

62.50

61.60

97.53

76.18

105.05

144.87

149.21

173.92

87.97

95.76

102.90

111.80

121.69

137.22

25.82

26.53

28.18

28.76

36.54

32.75

59.40

62.10

65.30

73.60

79.10

92.70

2.48

0.90

1.16

2.06

2.61

4.41

176.67

185.29

197.54

216.23

237.33

267.08

113.79

122.29

131.08

140.57

158.23

169.98

52.07

63.55

80.03

101.84

148.87

183.35

334.40

321.87

365.49

421.80

449.04

502.60

1003.80

1060.24

1588.95

1440.18

1624.82

1788.64

11.73

11.42

11.88

11.27

13.12

13.91

1015.53

1071.66

1600.83

1451.45

1637.94

1802.55

2.2 Emdollar Value Emdollar value (Em$) is annual using emergy gross in a country or region to the gross domestic product of that year ratio. Generally speaking, the Em$ in less developed regions is higher, and their extent of economic development is lower. However, the developing regions buy a lot of external resources, and the GDP is also higher, so their Em$ are lower. Em$ of Guilin decreased year by year (Table 2), which was lower than Gansus′(11.88×1012 sej/$) in 2000 and Xinjiangs′(14.7×1012sej/$) in 1999 significantly, but still than other coastal provinces′, such as Jiangsus′3.02×1012sej/$ in 2000 and Fujians′ 2.76×1012sej/$ in 2004[5-8], showing openness of economy, extent of circulation are not high, and economic development is in a lower level. 2.3 Emergy Investment Ratio Emergy investment ratio (EIR) is economic feedback emergy to gratuitous emergy from the environment ratio, an indicator to measure the degree of economic

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development and environmental loading level, also one to assess industrial competitiveness. Currently, the global average EIR is about 2, which is lower in developing countries. The condition of EIR in Guilin from 2003 to 2008, in recent years, maintaining at 1.1 or so, its level of development was low (Table 2), demonstrating that the level of environmental loading in Guilin was not high, conducive to protection of "Guilin scenery", but its pace of economic development and level are still low, the scale of industry is smaller, and less competitive. Table 2. Table of eological economic emergy system in Guilin Indicators and methords Emergy self-sufficiency ratio:(EmR+EmN)/EmU Input emergy ratio:EmI/EmU Renewable resoures emergy ratio:EmR/EmU Emergy per capita:EmU/P (1015sej/person) Emergy density (1011sej/m2):EmU/area (m2) Population carrying capacity (person):(EmR+EmI)/(EmU/P) Emdollar value (1012sej/$):Em$ =EmU/GDP ($) Net emergy yield ratio:EYR=EmO/EmI Environment loading ratio:ELR=(EmU-EmR)/EmR Waste emergy index:EWI =EmW /(EmR+ EmIR) Fraction of emergy used from electricity:Emel /EmU Emergy exchange ratio:EER=EmIS/EmISP Emergy investment ratio:EmI/(EmR+EmN) Waste emergy/renewable emergy ratio:EmW /EmR Emergy sustainable index:ESI=EYR/ELR Emergy index for the sustainable development: EISD=EYR×EER/(ELR+EWI)

year 2003

2004

2005

2006

2007

2008

0.472

0.424

0.460

0.487

0.471

0.469

0.528

0.576

0.540

0.513

0.529

0.531

0.180

0.188

0.172

0.144

0.139

0.123

6.818

6.517

7.382

8.448

8.899

9.887

12.029

11.578

13.147

15.173

16.153

18.079

3474186

3769986

3528041

3278054

3369255

3324365

6.964

5.818

5.578

5.323

4.589

3.907

5.748

5.784

8.104

6.713

6.902

6.749

4.555

4.329

4.811

5.949

6.185

7.159

0.079

0.073

0.065

0.071

0.070

0.068

0.079

0.083

0.076

0.072

2.185

1.924

1.380

1.018

0.927

1.120

1.357

1.176

1.052

1.121

1.134

0.195

0.189

0.189

0.186

0.210

0.226

1.262

1.336

1.684

1.128

1.116

0.943

2.710

2.528

2.718

1.540

1.123

0.865

0.072 0.074 1.638

2.4 Fraction of Emergy Used from Electricity Fraction of emergy used from electricity (FEE) is the amount of electricity tothe totalamount of used emergy ratio. The case of FEE in Guilin recently fluctuated largely for many years, but decreased significantly in recent two years (Table 2). Guilin′s electrical emergy was obviously lower than Fujians′ (19%) in 2004, Jiangsus′(20.8%) in 2000, Gansus′ (11.36%) and levels of others provinces [5,7,8]. This indicates that: Guilins′ industries were underdeveloped, low level of

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electrification, and some industries might use coal. Electronics, rubber mill, machinery industry, cottonocracy, pharmacy, coach manufacture, handicraft and other pillar industries in Guilin generally used lower energy. It shows that the current orientation of industrial development in Guilin is appropriate by and large. 2.5 Emergy Density Emergy density (ED) is the total amount of used emergy in a country or region to the national or regional area ratio, which reflects the objects′ strength and level of economic development. In recent years, and the index of ED in Guilin rose from 12.029×1011sej/(m2·a) in 2003 to 18.079×1011sej/(m2·a) in 2008 (Table 2), which had an increase of 50.30%, but there was a large gap with some areas along the coast, showing that the level of economic development of Guilin is underdeveloped, and its environmental pressure is relatively limited. 2.6 Emergy Per Capita Emergy per capita (EPC) is the amount of used emergy to the total population of a country or a region ratio, it is used to evaluate the standard of people′s living. In general, the greater the EPC is, the higher the per capita emergy is. The EPC of Guilin rose from 6.818×1015sej/person in 2003 to 9.887×1015sej/person in 2008 (Table 2), showing that the living standard of Guilins′ people had been improved to some extent, but there was also a large difference with some developed cities, such as Guangzhou (13.39×1015sej/person•year) and Beijing (17.89×1015 sej/person•year)[3,9]. Currently, GDP per capita is 17435 yuan in Guilin, the disposable income of urban resident per capita is only 14636 yuan/year, and the net income of farmer per capita is 4465yuan/ year, so people's life is at such a relative low standard.Guilin is still behindhand region in southwest of China. 2.7 Environment Loading Ratio Environment loading ratio (ELR) is the amount of non-renewable resources input emergy in system to that of renewable-resources input emergy ratio. The ELR of Guilin had an increasing trend (Table 2). Looking for the reason, besides the emergy of renewable resources in Guilin was lower (Table 1), the consumption of nonrenewable resources and the emergy of total labor input increasing constantly wass the other reason, especially wood, clay, limestone and consumption of other nonrenewable resources, resulting in an increase of environment pressure. 2.8 Population Carrying Capacity Population carrying capacity (PCC) is carrying capacity of population, according to the current state of environment. From 2003 to 2008, actual population of Guilin rose from 4904663 to 5083215(Table 2), but PCC decreased from 3474186 to 3324365. In 2008, the population was 1.53 times than PCC in Guilin, suggesting that resources, ecology, environment of Guilin were faced with tremendous population pressure in the

Analysis of Emergy and Sustainable Development on the Eco-economic System of Guilin 199

present developmental patterns and economic conditions. It is vital for sustainable development of regions to protect the environment, maintain the existing plough, and develop the high efficiency agriculture and high technology industries. 2.9 Emergy Index for Sustainable Development Emergy index for sustainable development (EISD) is the product of Net emergy yield ratio (EYR) and emergy exchange ratio (EER) to the sum of environment loading ratio (ELY) and emergy waste index ratio (EWI). The EISD of Guilin decreased from 2.710 in 2003 to 0.865 in 2008 sharply(Table 2), the capability for sustainable development dropped off rapiadly. Analyzing the causes, from 2003 to 2008, the EYR of Guilin rose from 5.748 to 6.749, but the corresponding adjustment for industrial structure and circular economy did not keep up with, and the ELY and EWI decreased somewhat, making the EER decline from 2.185 to 0.927, so EISD fell quickly. With the rapid expansion of economy, the contradiction among Guilins′economic development, resources, and entironment appeared gradually, it is the key for sustainable development to speed up industrial restructure, develop the circular economy, and build circular industry with local characteristics.

3 Conclusions and Recommendations According to emergy analysis, it shows that the EIR of Guilin is about 1.1, indicating that the speed and level of economic development in Guilin are still low, and the economic development rely on external inputs excessively, which is mainly the economic expansion in number; the ELR of Guilin ascended from 4.555 in 2003 to 7.159 in 2008, but its EISD declined from 2.710 in 2003 to 0.865 in 2008 sharply, suggesting that in the process of rapid urbanization and new industrialization, the resources′ constraint increased, pressure on the environment rose, and the current approach to develop is not sustainable. For that, the following measures are presented: (1) Speed up the industrial restructuring, optimiz the structure of energy, and transform the model of economic growth. Weed out the technology or relative industries who are in serious pollution, behindhand process and equipment, and low-tech, increase investment in science and technology, strengthen the optimization and upgrade in electronics, rubber manufacturer, machine industry, cottonocracy, pharmacy, coach manufacture, and food and light industry, and develop the tertiary industry and new industries vigorously. (2) Develop and utilize local ecological resources and land resources, build sustainable resources system reasonably. Meanwhile, exploit the local renewable and non-renewable emergy at no cost moderately, such as water resource and solar energy, to provide security for sustainable development of Guilin. (3) Bulit the circular economy and build eco-industrial system. Establish ecological industries characterized by clean production and recycling economy, rely on science, technology and policy supports to develop ecological agriculture, ecological industry, and ecological services, especially the recycling industries with local characteristics such as agricultural planting and breeding-process for drug product-ecological tourism and special marketing of local products.

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Acknowledgment. The work was supported by a Program Sponsored for Educational Innovation Research of Univerisity Graduates in Guangxi Province (No.200910596R01) and the Guangxi Key Laboratory of Environmental Engineering.

References [1] Lan, S.-f., Qin, P.: Emergy analysis of ecosystem. Chinese Journal of Applied Ecology 12(1), 129–131 (2001) [2] Odum, H.T.: Guidance of energy, environmental and economic system. Oriental Press, Beijing (1992); translated by Lan sheng-fang [3] Sui, T.-h., Lan, S.-f.: Emergy analysis of Guangzhou urban ecosystem. Chongqing Environmental Science 23(5), 4–23 (2001) [4] Statistical bureau of Guilin. Economic and social statistical yearbook of Guilin. China Statistical Press, Beijing (2004-2009) [5] Zhao, S., Li, Z.-z.: Study on emergy analysis of Gansu ecological-economic systems. Northwest Botanic Journal 24(3), 464–470 (2004) [6] Li, H.-t., Liao, Y.-c., Yan, M.-c., et al.: A study on emergy evaluation of Xinjiang ecological-economics systems. Geographica Journal 58(5), 765–772 (2003) [7] Li, J.-l., Zhang, Z.-l., Zeng, Z.-p.: Study on emergy analysis and sustainable development of Jiangsu ecological-economics system. China Population · Resources and Environment 13(2), 73–78 (2003) [8] Yao, C.-s., Zhu, H.-j.: Emergy analysis and assessment of sustainability on the ecological economic System of Fujian province. Fujian Normal University 23(3), 92–97 (2007) [9] Song, Y.-q., Cao, M.-l., Zhang, L.-x.: Beijing, Emergy-based comparative analysis of urban ecosystem in Beijing, Tianjin and Tangshan. Ecological Journal 29(11), 5882–5890 (2009)

Multiple Frequency Detection System Design* Wen Liu, Jun da Hu, and Ji cui Shi The College of Information Engineering, Xiangtan University, Xiangtan, China [email protected], [email protected], [email protected]

Abstract. In electronics, the frequency is the most basic parameters, and therefore frequency measurement becomes even more important.This design frequency detection system including controller system and PC system. Controller system with AT89C51 as the key device. PC design using Visual Basic 6.0, including the serial data receiving and processing, Displaying of frequency data and curve drawing, data storage and query modulehs. With Proteus7.1 and Visual Basic 6.0 test. The System to achieve a frequency of 1-1MHZ measurement, It can in the digital tube and Visual Basic6.0 interface display the current frequency channel number and frequency value at the same time. And to store data to Access2003 database for reference , The PC hardware stucture of this system is simple and stable operation, and PC parts design is reasonable, stable operation, easy operation and maintenance, and it has certain expansibility. Keywords: Microcontroller, Therequencymeter, 89C51, frequency division circuit.

1 Introduction So-called measuring frequency is in certain time intervals count of digital pulse in simple way. In order to realize intelligent count frequency measure, a kind of effective method is to used microcontroller in the design of the frequency. The traditional frequency meter just detect external signal frequency value, and the simple display it. This method is effective, but can not continuous reflected signal frequency changes, can not track signals timely, lost a large number of signal detection of information, It harm to design of the timely analysis and processing signal .In this paper, the design combines the microcontroller and VB6.0 display interface, Measuring the frequency steps: MCU measuring frequency, the tube for display, serial transmission of data, the PC to draw the frequency curve, stored frequency data, and so on. * Project supported by Provincial Natural Science Fundation of Hunan, China (Grant No.09JJ3094). The Research Foundation of Education Bureau of Hunan Province,China (Grant No.09B022). The Open Fund Project of Key Laboratory in Hunan Universities :Hunan Institute of Engineering electrical control laboratory. Undergraduate Research Study and Innovative Test Program Projects in Hunan Province(No.09281). S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 201–206, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Frequency Measurement Principle and Scheme Selection This frequency measurement system of basic design principle is to use directly decimal number display measured signal frequency in the measuring device. It with direct measurement per unit of time pulse number, namely frequency, automatic measurement. The so-called frequency is periodic signals in unit of time (1s) change frequently. If measured in a certain time interval T may change the number of periodic signals N, then the frequency can be expressed as f = N / T. the role of pulse forming circuit will be measured signal into the pulse signal, The repetition rate equal to the measured frequency fx, Time reference signal generator to provide standard time pulse signal, if its cycle 1s, the door control for the duration of the output signal circuit that accurately equals 1s. Gate circuit controlled by standard seconds signal, as second signal came, gate opening, tested pulse signal through the gate to the display circuit. At the end of the second pulse the gate cut-off, counter stop counting. The counter was the number of pulses N is the cumulative number of times a second, so the signal frequency fx = N. 2.1 Optional Plan One Implementation of a combination of hardware and software, Main component has AT89C5y registers chip, 74LS48 bits choo1, 74HC164 drive digital displase chip counts circuit, LED digital pipe and some capacitor, resistors. Principle chart is as follows:

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The program can detect multi-channel signals, by synchronizing the gate and function switching circuit for time division multiplexing circuit, time to achieve with two counters count and event count separately. Other channels in the display data, when in another channel the data storage in the Microcontroller, and may through the corresponding keys are being set. 2.2 Optional Plan Two Pure hardware implementation method, the main components are bistable flip-flop MC4583B, count \ decoder chip CD4026, two-stage dual time base control NE556,

Multiple Frequency Detection System Design

203

Dual complementary symmetry inverter CD4007, integrated voltage regulator 7805, six digital And some capacitors, resistors, and so on. Principle chart is as follows: The program by blocking the input signal and Output divided frequency after the request for the counter input signal, namely to meet TTL input level requirements. With gate signal circuit output signal to control the count to start, stop and clearl. Finally, seven common cathode LED meter on the counter of the number of pulses was displayed. ,QSXWVLJQDO

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The first program can do more powerful, soft features better. Simple in principle, the specific circuit in real time is better, but also in achieving high accuracy in the preparation of software features is relatively high demand. Another use of traditional microcontroller chip can not be directly measured by counting the frequency of 1MHz, usually the clock frequency of microcontroller at the under of 12MHz, the machine cycle of at least 1us, if the frequency of 1MHz measured must be added frequency circuit microcontroller, This can greatly improve the frequency meter measuring range, Application of space more widely. The greatest feature of the second program is the full hiardware circuit, crcuit stability, high accuracy, without tedious debugging process, greatly reducing the production cycle, but the frequency measurement range is limited, with great limitations. The requirements of this design can be measured at frequencies up to 1MHz, which must be applied frequency circuit. In summary, the design uses the first option to achieve the frequency measurements. In conclusion, this design chooses the first implementation of frequency measurement.

3 The Hardware Design of System Simulation The frequency meter data collection system main components are AT89C51, it measured signal frequency, count and shows them. Outside it has divider, monitors and other functional devices. There can be divided into the following modules: second pulse generator module, microcontroller, frequency division circuit, channel selection unit and seven-segment LED display unit. The following simple introduction a few basic unit: 3.1 Signal Input Circuit The design uses a multi-channel signal input through the switch to select the signal down into the circuit, The circuit design of the eight frequency measurement circuit,

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Through the 74151 data selector selects one of inputs the design of frequency requirements measure frequency range up to 1MHz, so sent measure frequency value into SCM before them split processing, while D flip-flop frequency has this function,so frequency by the D flip-flop treating first. 3.2 Digital Decoding Unit This design uses 8-bit common cathode LED on the measured frequency and the number of channels selected for display, Dan connections consist of light-emitting diodes figure 8, when use some pen segment the light emitting diode luminescence can show 0 ~ 9 number. LED seven segment displays, also known as LED digital tube, the display can be divided into a total of yin and yang are two common types. The so-called digital tube of anode, is the public termination positive, when the cathode combined with low levels the section to shine. Common cathode is the digital negative public termination, when the anode with high levels the section to shine.

4 The Software Sesign of System Simulation The core of the frequency design is the AT89C51,it finish the function of signal and frequency measurement and so on, so it is necessary to develop appropriate procedures, to messure the frequency. C51 language was used to debug the led display and counter circuit, divider circuit and serial port to send the results of instruction and so on. The program can be divided into the following specific procedures for the preparation of several modules: the main program, counting process, switch the selection process, display routines, and serial port procedures. The PC software is designed to be completed based on VB6.0. Writing the corresponding function program received through the serial communication of information from the next crew to complete the system, including the frequency of sending and curve display. Software design includes the main program, counting process, switch the selection process, display routines, and serial port procedures. Main program to complete the setting of timer, serial port baud rate settings, and the interrupt type, etc. Counting program External interrupt frequency was set to 1s, during the 1s time to count on the external frequency. The frequency was the frequency of the external signal is the number of values. Switch to select program Setting P1.6, P1.7 to select the port switch from top to bottom, by choosing a different channel, determine the frequency of the channel. Display program display the measured data, open the appropriate place, call the appropriate section of code to display. Serial port and data saving program the measured frequency value was send by the serial port to PC. When PC received data curves depict, drawing the curves by different colors to correspond to the frequency value and frequency value for database save for inquiries. And the flow diagram was showed below:

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Proteus and vb6.0 was used to joint simulate. By testing, the system can function normally on a pre-requirement. The external input frequency information will be first measure by MCU and displayed by seven segment LED display decoder, through the serial port to the PC, host computer system can quickly and accurately under the crew received the frequency of information transmission. After corresponding treatment, drawing in the corresponding linear axis and the frequency of the measured data stored in the database. Simulation was shown in Figure.5 to Figure.7:

Fig. 5. Local machine measured the fifth channel frequency display

Fig. 6. Depicts the corresponding PC curves

Fig. 7. The data stored in a database query

It can be seen from Figure.3: the frequency testing by microchip is simple, practical, wide measuring range, response, compared with the traditional frequency counter it has a higher accuracy and reduce the error. From Figure.6 we can found that using serial port to send data, the measured frequency is displayed on the host

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computer, more intuitive reflecting the real-time frequency. Figure.7 showed us the measured frequency value is stored to the database, which will help on the data query and analysis.

5 Conclusion The simulation results can be seen from the above. Compared with the traditional multi-channel frequency counter the frequency based on MCU has better performance, and enhanced the overall function of the frequency meter. Of course, the whole system is still in the testing process and a lot of errors were found, such as the measurement error.also,there are some errors in the channel, such as 5-channel input 10000Hz frequency, the tests showed that as 9998Hz, but the measured data allowed within the error range.

References [1] Zhang, Y.: Microcontroller theory and applications, pp. 100–154. Higher Education Press, Beijing (2008) [2] Guoqi: Visual Basic Database system development technology, pp. 236–251. Posts & Telecom Press, Beijing (2003) [3] Cao, W.B.: C / C + + serial communication typical application programming practice, pp. 20–136. Electronic Industry Press, Beijing (2009) [4] Wang, P.: Visual Basic Programming fundamentals tutorial, pp. 77–160. Tsinghua University Press, Beijing (2006) [5] Li, X.W., Chao, J.: Electronic Measurement Technology, pp. 78–102. University of Electronic Science and Technology Press, Xi’an (2008) [6] Yan, S.: Fundamentals of electronic technology, pp. 185–213. Higher Education Press, Beijing (2004)

The Law and Economic Perspective of Protecting the Ecological Environment Chen Xiuping and Liang Xianyan Zhongnan University of Economics and Law, Three Gorges University, Yichang, Hubei [email protected]

Abstract. The core of the law and economic theory is to obtain the maximum benefits at the minimum costs. The environment and economic growth of the contradictions are becoming increasingly prominent today, how to obtain most of the economic performance with loading down the environment at the same time? The text proposed the sustainable development as guiding ideology, in coordination to develop as guiding principles, the "guidelines on prevention" as guidelines. Keywords: The law and economic theory, cost, efficiency, environmental protection.

1 The Core of the Law and Economic Theory: Costs and Benefits Law and economic theory, from jurisprudence view, "Economic analysis of law". Economic analysis of law is a theory to apply the concepts and study method of economics to study and understand the problem of the law, it rose in America firstly in the 1960s. It is Richard Allen Posner who collected the major achievements of the economic theory, his book the economic analysis of law” completed a task that comprehensive and systematic analysis and summary of the economic theory. The Law and economic theory by nature "apply the economic theory and economical methods fully in legal systems analysis.[1] In economic analysis of jurists’ eyes, "economics is one of our rational choices and in the world, resources are limited relative to the human desires " .Based on the hypothesis that man is "maximize" self—interests the economists get the core idea of the law and economics theory from the three basic principles the law of supply and deman maximize the efficienc , and maximizing value ), the core idea of the law and economics theory— “efficiency to allocate and use resources with value can be maximized.[2] Apply this theory to the legal field, he will come to a conclusion: maximized wealth is the purpose of the law. All the legal activities (including legislative and law enforcement and judicial activities etc and all the legal systems (public law system, private law system and judicial system etc) ,their ultimate aim is to wait for the most effective use of natural resources and to maximize the increasing social wealth. Therefore, the core of law and economy theory is to obtain the maximum effectiveness with the minimum costs.

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2 The Proposal of Ecological Environmental Problem Ecological environmental problem is the question that the changing nature or human activity may cause the ecological system off balance and ecological environmental degradation, and bring about the adverse effects to development of the human beings and the whole community. The ecological environment of human society in the early days of mainly laid in the lack of biological resources in local areas because of the human settlement and the increased population. Since human entered industrial society, in the condition that natural resources and environmental issues become more seriousl , and more pollution problems, the so-called public hazards. Especially after the Second World War, the productive forces improved greatly, an unprecedented increase of the ability of the using and transformating the environment, but human society especially the developed world’s level of consumption demand is growing and expanding. The human consumption of resources and discharge of wastes unprecedented grows, has brought about serious environmental problems. At present, the ecological environment has transcended national borders and become unavoidable common problems. Since the founding of New China, our government has attached great importance to protecting the ecological environment, improving environmental protection work and intensified legislation on environmental protection and law enforcement efforts, the ecological environment conditions progressively improved. However, China's ecological environment of the situation remains grim. For example, environmental pollution is still serious (the high sewage, water pollution is serious etc), the trend of ecological deterioration has continued (land degradation and reduced etc).[3] Undeniably, the existence of environmental problems, is related to how we understand conservation laws, and also related to our growing too fast population and also related to the government's decisions and acts, but the main reason is that we are anxious for utilities, we focused on the development of production and increase of GN for economic development to sacrifice the ecological environment. In other words, we are in pursuit of economic benefits whilst at the same time, we are in breach of the ecological environment, what a great cost? So now we must think such a question: how to load down the environment at the same time, most of the economic performance?

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3 Mitigate Environmental Load and Reap Higher Economic Returns 3.1 Sustainable Development as Guiding 3.1.1 Relating to Sustainable Development In the early 1980s, the united nations fought against the three big challenges mankind facing: the north-south question, disarmament and security, environment and development, set up three senior specialist committees, published three programmatic

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documents. The three documents spontaneously come to the same conclusion that world must organize and implement new strategy of sustainable development , they have repeatedly emphasized that sustainable development is the only alternative way at the end of the 20th century, and the 21st century mankind survive and develop. In June 1992 session of the United Nations conference on environment, development and sustainable development has become the most powerful voice. Human finally chose the sustainable development, this is the historical evolution of human civilization, and it is an important milestone for man to break the traditional mode of development and open the development of modern civilization. The report “Our common future” believed that human society ever gain the rapid economic growth has also brought the deterioration of ecological environment, thereby seriously restricted the human’s economic and social development further. Therefore, we must change its traditional development and choose a new development strategy to ensure social development of persistence. 3.1.2 Sustainable Development of Present Stage At this stage, the conflict between economic growth and resources and environment will still exist, in the rapid industrialization and urbanization stage it would be even more prominent. This is the product of high-speed economy development, it is also the performance of economic underdevelopment. Sustainable development is the economic and social development of a new strategic, economic and social development is the only correct choice.[4] At this stage how we cope with and how to implement sustainable development, I think we should focus on the following: First, we should turn to promote growth mode in a prominent place put more emphasis on technology progress. To develop cycle economy is significant to improve the utilization of resources and environment. Second, we should turn to optimize the industrial structure in a prominent place, put more emphasis on services, particularly modern service industries development. Third, people should be more rationally planning industrial development, and analyze market trends for long-term supply and demand, to avoid excessive heavy industry. Fourth, we should pay more attention to coordination between economic growth and saving resources and environmental protection. Fifth, we should pay more attention to construct conserve resources typical society, to eliminate waste and advocate economy in planning construction, circulation, consumption and production.

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3.2 Coordinated the Development for Guidelines 3.2.1 The Concept of Coordinated Development The coordinated development of environmental protection usually refers to economic growth and social progress mutual coordination and joint development, and therefore are often referred to as “environmental protection and economic development and social development coordinated”principle.[5]

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3.2.2 The Meaning of Coordinated Development Principle 3.2.2.1 It is effective measures to prevent environmental and ecological damage. The coordinated development learned history lessons from the pollution before the treatment, the destruction before the protection. The coordinated development review and analysis the environmental impact of decision-making on the macroscopic, and fundamentally solve environmental problems, control the policy source of the environmental pollution and ecological damage. 3.2.2.2 It is the important guarantee for government to change in policy decisions and scientific policy. The coordinated development requests changes the thinking mode that made by the department to make decision singly, change a decision-making from by individuals decision-making groups, to changeover decision-making from by the departments only to involved in all the departments. An overall making policy change from the trust of the wise leadership, to be able to rely on the system of security constraints and the rule of law. It has made decisions more comprehensive, democratization and scientific.

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3.2.2.3 It is advantageous to change people's perspectives. The coordinated development is key measures to keep sustainable development,it transfers from a single development to more complex development. Sustainable development decision-making asks for economic development to making overall plans for population resources and environment, not only to consider the economic benefit, also consider the environment efficiency and social benefit. 3.2.2.4 It facilitates optimization disposition of resources. To perform the coordinated development is the implementation of the basic state policy of environmental protection and important measure to implement sustainable development. Therefore, we must take important steps in the management and to establish and improve the coordination of development mechanism, make it standard and scientific, to utilize the limited resources in rational distribution and science, throw it into some places and projects that create good social and economic and environmental benefits. 3.2.2.5 It facilitates reduce the development costs. In the course of industrialization, our country spent a long time practicing the economic mode of extending and quantity type, economy developed at a high speed, at the same time, we pay the enormous cost of natural resources and the ecological environment. China's economic development cost higher than the average of the world, far higher than the developed countries. The coordinated development considers environmental factors and resources value, it facilitates reduce the development cost to makes a unified planning and a reasonable layout. 3.2.3 The Implementation Approach of the Coordinated Development [6] Today, the contradiction between environment and economic growth of are becoming increasingly prominent, coordinated progress has been regarded as the best option to solve conflict to the international community.

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The economic development of scientific development, not only the expansion, it needs to improve productivity and to maximize utilization of resources, but this precisely is the ultimate goal of environmental protection work. Environmental protection, refers to take various measures such as administrative, economy, science and technology, publicity and education and lega rationally use of the natural resources, preventing pollution and other hazards to protect and improve their living environment and ecology environment, make it more suitable for human existence and development. That is in the implementation of its economic development goals, not to damage the environment for the environment, or to instability and disorder in the direction of movement, especially can't make life and destruction continues to support from the web of life. The growing disintegration of the environment is environmental protection as a means to improve and promote economic growth, in order to achieve a double purpose of environmental protection and economic development. After all environmental damage because of the economic growth is not our desire and objective. If put environmental protection into economic growth system and take it as an industry, you can promote economic growth[7]. According to the China Environment News reported, with the emergence of its industry, it produced a large number of naoh and waste solid, and polluted ecological environment. To improve the ecological environment caused by pollution, government led Kunshan people to develop cycle economy actively introducing advanced technology, it can weave the "link", for over twenty families were organized to become special "eat waste" enterprises, industrial waste production can be of high added value of the new product. In the conditions of optimized growth, environmental industries become a new economic growth. Economic growth accelerated to protect the environment, manifested in the following aspects:

l,

3.2.3.1 Economic growth will make more countries in efforts to protect the environment. the purpose of economic development is enhancing the overall national strength, the country's strengthen up, we can protect and improve environment to provide the necessary financial and material resources to promote environmental quality improvement. with economic development and the improvement of people's living standards for environmental quality, higher, stronger and environmental awareness and environmental protection more conscientious, will no doubt to promote the environmental protection. 3.2.3.2 Economic growth will optimize the survival of humanity. as populations[8] With the people's material needs and environment increasing, to keep the environment of indigenous forms be more and more impossible. Only if economic developed, can people make use of the ecological guidance practice in accordance with law, to create artificial environment according to ecological systems, can we live in the earth into the most optimized human environment and the environment is more suitable for human life and social development. In summary, environment and development are mutually reinforcing and harmonious development. If the policies used wisely, they can be a sound and promote development. To improve the environment quality is human social development goals.

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3.3 Take the "Guidelines on Prevention" as Guidelines

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"Prevention first" is in short of prevention, control, comprehensive polic it is to say, the state should put prevent environmental problems in the first place in environmental protection , take preventive measures to prevent the question arises and worse; and should take positive measures to control the inevitable or have occurred in the environmental pollution and ecological damage. At present, the environmental legislation is passed from passive control pollution to active prevent the pollution, and pointed the view that we would take the environmental problems as a rule, the prevention before it appears rather than controlling pollution after pollution appears, adopted prevention and comprehensive environmental policy and make prevention, control, comprehensive policy of environmental legislation as the important principles. Prevention is for man prior to prevent all the acts interfere the environment within the existing level of technology in the possible extent, load down the environment to a minimum level. After the 1980s during every country environmental policy adjustments and the process, the policy“prevention first ”were paid more and more attentions, and become a national environmental management and an important legislative guidelines. Our country value "prevention first" truly, in general from the 1970s to the end of the early 1980s, and realized the necessity of “prevention first ”from China's great loss caused by environmental problems. According to the incomplete statistics in the early 1980s, our economic damage caused by environmental pollution every year amounted to 690 million Yuan, part of the economic loss caused by the ecological damage amounted to 765 million Yuan every year, these two adds to a total as high as 955 million Yuan, take total value of industrial and agricultural about 14 percent. Such a huge economic loss make people realize that for China it is utterly impracticable if the environment is not mentioned strategic and take effective measures, the economic development will be difficult to keep well. For this reason, "the policy of prevention first" was embodied in our law of environment protection, the law of the prevention and control of atmosphere pollution. In short, under the current grim situation of the ecological environment, we must take sustainable development view as the guiding ideology, take coordination to develop as guiding principles, take the "guidelines on prevention" as guideline, could we to mitigate environmental load and reap higher economic returns.

References [1] Posner, R.A.: Economic Analysis of Law. The Encyclopedia Publishing House of China, Beijing (1997) (preface) [2] Posner, R.A.: Economic Analysis of Law, 5th edn., New York, pp. 13–15 (1998) [3] Chen, Q.S.: The basic theory of the environmental sciences, pp. 36–37. The Environmental Sciences Press of China, Beijing (2004) [4] Zhang, K.: The theory of sustainable development, p. 74. The Environmental Sciences Press of China, Beijing (1999) [5] Zhu, B.: The resources, environmental and social development. The Impact of Science to Social 1 (1994)

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[6] Chen, Q.S.: The basic theory of the environmental sciences, p. 136. The Environmental Law Press of China, Beijing (2004) [7] Nie, G.: The economic analysis of our environmental protection in the transition period, p. 27. The China Economy Press, Beijing (2006) [8] Li, K.: The environmental economics, p. 185. The Environmental Sciences Press of China, Beijing (2003)

Research on the Management Measure for Livestock Pollution Prevention and Control in China Yukun Ji1, Kaijun Wang2,*, and Mingxia Zheng2 1

University of Science & Technology Beijing, Beijing, China [email protected] 2 Tsinghua university, Beijing, China [email protected],[email protected]

Abstract. In recent years, government and some organizations have published a series of polices and measures in order to resolve the problem of livestock pollution. Based these existing policies and economical measures, many deficiencies regarding to livestock pollution prevent and control have been analyzed. At the same time, suggestions to these problems were given. Keywords: livestock and poultry pollution, management measure, pollution abatement.

1 Introduction As the development of China’s economy, people’s matter and cultural level has been increase continuously, China's livestock breed industry has a very fast development, for example, the meat, egg and milk output increase fast, but at the same time, the livestock pollutes also more and more serious, become a main agriculture pollution source. In order to solve the livestock problem, in recent years, our country try to control the pollution by doing some policy guidance and giving some money support , we get a good result. But because the livestock pollution prevention starts late, we have some problems at management, for example, the relative regulation and standard system is not so tightness and perfect. This text has a analyzing about the development for the livestock industry form economy and policy area.

2

China's Livestock Industry Development Situation

As the development of China’s economy, people’s matter and cultural level has been increase continuously, China's livestock breed industry has a very fast development, in 2003, our country livestock breed industry is 34% of the agriculture production, becomes the biggest meat and egg produce country in the world, in 2008, the number reach to 35.5%[1]. As our country promotes new village construction, Livestock industry structure change into intensive type and the scale becomes large, According the Monitor of Agriculture Department, in 2008, the livestock breed industry ,which’s the pig's *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 214–218, 2011. © Springer-Verlag Berlin Heidelberg 2011

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production is more than 50s, cow's production is more than 10, chicken is more than 2000s, milk cow save column more than 20s, the egg chicken saves a column more than 500 , has been reach 56.0%,38.0%,81.6% 36.1% and 76.9% respectively of intensive type level, we can see that the small scale livestock raise is above 80% of the intensive type raising [1]. Compare with the livestock raising, the livestock pollution prevention level is not very high. The environmental protection department has a inspection for the 23 provinces and cities, 90% scale livestock arising didn't have the environment evaluation, 60% arising place has no anti-pollution measurement. Livestock arising has became the main pollution source for the village region. In 2008, form the state council pollution inspection result, we can see that the livestock breed industry generates the dejection as 243,000,000 tons a year, and generate wet liquid 163,000,000 tons a year. Among them, chemical oxygen demand, T total nitrogen and total phosphorus exhaust are 12682600 tons, 1024800 tons, 160400tons, and it is 41.87%, 21.67%, 37.90% of the whole country’s total pollution. Pollution from the agriculture source, more outstanding one is livestock farming pollute, the livestock farming industry chemical oxygen demand, total nitrogen and total phosphor take up 96%, 38% and 56%of the agriculture source respectively [4 1].

、

3

Livestock Breed Industry Pollution Political Measure

In recent years, as the increasing of the intensive type and scale livestock breed, its scale also became bigger and bigger, the pollution problem is getting serious. The Table 1. the main measures for anti- livestock pollution NO. GB 18596-2001 HJ/T 81- 2001 NY/T 1167-2006 NY/T 1168-2006 NY/T 1169-2006 NY/T 1221-2006 NY/T 1222-2006 HJ 497-2009

HJ 588-2010

Document for standard and regulation ljThe livestock pollution treatment manages NJ ljthe exhaust standard of The livestock pollutionNJ ljThe livestock industry pollution treatment technical specificationsNJ ljThe livestock raising place environment and hygiene control specification NJ ljThe livestock excrement treatment the specification NJ lj The livestock raising place environment controls technical specificationsNJ ljThe goingtoscale livestock arising place methane project running time in livestock farm and maintenance and it safe technique regulations NJ ljThe goingtoscale livestock arising place methane project design specificationNJ lj The livestock industry pollution treatment project technical specifications NJ ljImplementation of "urge the manage by prize" to solve the village environmental pollution treatment NJ ljThe agriculture solid pollution control technique leads NJ

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government takes a lot of measurements, standards and regulations to control the livestock pollution. The follow table shows us the main measures what our government take for the recent 10 years. (Table 1) Livestock arising guidance document is separate into three parts: administrative management, technical specifications, environment economy, the document which already put out is mainly technical specification, it has some restriction of the place chose, scale, project design, environment, pollution management, exhaust tandard etc, it will take some functions, we don’t have too much document about administrative management and environment economy, we don’t have special administrative management document for livestock pollution, even in <environment protection regulation> has no regulation about this, this is because our country take measures a little bit late, a lot of work to do to improve it. 3.1 Government Department has Different Duty Makes the Management Problem Agriculture department make the village economic development and agriculture structure as the main point of their work, recently, they adjust the industry structure intensification and going to scale, but they have not see the problem caused by this. Environment department focus on water, air, voice, waste residue, they main manage big city and industry pollution, didn’t pay attention to the livestock pollution. So, in a sort of sense, government duty doesn’t match is a reason to make livestock pollution serious. 3.2 Lack of the Regulation for the Small Livestock Breeds Industry Recently, the environment department has enhance the management about the big scale livestock breeds industry, increase the management for the big and middle scale company, "Three Meantime", environment evaluation, but small scale livestock breeds industry is more than 80% of all the livestock company, the average number is 650 pigs,22000 chicken for each small company. Big caw which is above 200 is only 5% of the total number[2].Lack of the management to the small company is a policy problem. 3.3 Lack of the Regulation to Encourage Livestock Breeds Industry to Make the Livestock Pollution Prevention livestock is influenced by ill and market, it belongs to high risk and low profits industry, recently, our country’s main management for livestock pollution is penalty, lack of related protection and policy to support, company has on interesting to build up pollution treatment equipment, even they build up the equipment, they always exhaust waste when it is no inspection. 3.4 Lack of the Related Data about Livestock Breeds Pollution Livestock breed is the main pollution in the village, but we can’t find any data about pollution situation and pollution exhaust in <Environmental conservation yearbook>, and , it will impede our livestock pollution prevention work improvement, and also impede our target come true.

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4 Conclusion and Suggestion It is a long way work of the controlling about livestock breed pollution and improving the environment, it should be done step by step, it need the policy’s guidance, new technique, and economic support, it also need management department, company and market work together, than we can have a good control of the livestock breed pollution, according our country situation, the suggestion as follow: 4.1 Improving the Regulation about the Livestock Breed Industry Improving regulation system about livestock breed industry pollution, add special regulation for livestock breed pollution prevention, for example, make < regulation for livestock breed pollution prevention>, make clear about the responsibility and obligation for the environment protection, give a serious punishment to the illegal company. Enhance the making of the inspection document about livestock breed industry, clear the responsibility of different department, to avoid administrative management problem. Focus on the whole situation; make the treatment of livestock breed industry’s pollution prevention and improving the village environment as our final target. Each department takes its own function. 4.2 Make Clear about the Department Function, Make the Livestock Breeding Industry Management Integration Environment protection is not only the work for the environment protection department, it is related to work about industry, agriculture, commerce, sanitation, programming department etc. We should let every department take their function to engage in management about the pollution prevention, they should considerate about the environment problem when they want to take any measures, enhance the pollution prevention work, to solve the problem between economic development and environment protection. Enhance the communication between department, build up the horizontal management system between each environment protection department, let the livestock breed industry under management from building up plant improvement, extension, normal inspection to pollution exhaust, control. 4.3 Enhance the Research about Economize-Type and Utility-Type Measure for Livestock and Poultry Industry’s Pollution Prevention The livestock excrement pollution projects cost for pollution prevention is very high; it is difficult to accept for the company without government support. Recently, it is hurry to enhance the research for pollution prevention technique, to reduce the livestock pollution prevention cost, and increase the treatment efficiency. Particularly increase the input of the pollution prevention technique which can change into good productivity. The livestock pollutes research should match request of market, should be economize-type and utility-type, to promote the development of the pollution prevention technique.

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4.4 Support Organic Fertilizer’s Production and Using, Manage Biogas, Biogas Slurry, Biogas Residue Exchange Market Strictly examine and approve of building up the new biogas projects, around the biogas projects should have farm, fruit tree forest to use biogas slurry, biogas residue, build up biogas projects, at the same time, finishing the piping for biogas slurry. Secondly, for which biogas projects have no enough earth, they should make the biogas slurry and biogas residue into organic fertilizer, and also supply to them the way for selling. Organic fertilizer is good agricultural fertilizer, but benefit offspring. It hasn’t more price advantage than chemical fertilizer. In order to push forward the building of biogas projects, to establish good market environment, it is the most important to strengthen organic fertilizer market management. It is necessary to encourage production and use organic fertilizer on the political and economic side. 4.5 Intensify the Livestock Breeding Industry Inspection Intensification and large-scale development is make the livestock breeding industry pollution becomes the main pollution source in the agriculture pollution. supervision and management of the livestock breed industry has been tightened. Strictly the provement of breeding place and environment evaluate, "three simultaneous" system, increase the punishment to which fails to meet the requirements for pollutant discharge. 4.6 Strengthen Management of the Small and Middle Livestock Breeding Industries Because the cost and pollution quantity is low, medium and small scaled Livestock farming always became the blind spot for the environment management, but long time pollution of the fugitive discharge will cause big problem. The medium and small scaled livestock breed industry is spread around, it is difficult to control on time, so, for the medium and small scaled livestock breed industry, our main measure is guide and encourage, and teach them the excrement treatment. Reduce the load of the organic matter in wastewater. To build fertilizer company or sewage treatment plant around medium and small scaled Livestock farming, which can resolve the fecal treatment problem of medium and small scaled Livestock farming.

References [1] National Bureau of Statistics, Ministry of Environmental Protection:China Statistical Yearbook on Environment. China Statistics Concern, Peking (2009) [2] Su, Y.: Research of Countermeasures on Waste Treating of Intensive Livestock and Poultry Farms in China. Chinese Ecosystem Agriculture College Journal 2, 15–18 (2006) [3] Yang, J.: The Tension Rings A Red Alarm. Environment 4, 4–5 (2002) [4] Peng, X.: Our Livestock Farming Pollution Treatment Policy and Its Character. Environment Economy 1 (2009) [5] Chinese The Editorial Board of The Livestock Husbandry Yearbook: Chinese Livestock Husbandry Statistical Yearbook (2008), Peking, Chinese Agriculture, Book Concern (2010)

The Design of Supermarket Electronic Shopping Guide System Based on ZigBee Communication Yujie Zhang, Liang Han, and Yuanyuan Zhang College of Electrical and Information Engineering, Shaanxi University of Science and Technology, Xi’an, China

Abstract. Based on the ZigBee networking technology and protocol analysis, The paper designs a ZigBee Network Model with the features of communication and location which mainly rests on CC2431 ZigBee network location property and further propose a mobile electronic supermarket shopping guide system which can locate expected goods , navigation and offer the latest information on supermarket product. Keywords: Wireless Networking Technology, Positioning Engine, ZigBee, CC2430, CC2431.

1 Introduction With the development of economy and society, the emergence of large supermarkets provides people with a convenient place to buy necessities. To some extent, it facilitates the purchase and save time. However, the enormous size of the supermarket with the increase quantities and types of goods makes customer inconvenient to find out what they need and get the latest goods information. This paper presents a mobile electronic supermarket shopping guide system, which can be fitted in the shopping cart locating expected goods and offering the latest information on supermarket product.

2 ZigBee Technologies ZigBee is a standard network protocols based on IEEE 802.15.4 wireless [1], communicating in the 2.4G band with high efficiency and low rate. ZigBee Network supports Full-Function Device (FFD) and Reduced Function Device (RFD) two physical devices, which are made up of Coordinator, routers and terminal equipment [2]. A Coordinator and a router are full function devices (FFD), completing a large number of services set by ZigBee protocol and communicating with any node of the network. While Terminal equipment can be either a FFD or a streamlining of the agreement node (RFD) only communicating with the FFD. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 219–224, 2011. © Springer-Verlag Berlin Heidelberg 2011

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3 Systems and the Network Model 3.1

Location

The achievement of this wireless location system mainly depends on CC2431 ZigBee network environment and the built-in wireless location engine [3]. There are three types of nodes—Central node, blind nodes and reference nodes. Central node is constituted of the coordinator (FFD), initiating a network. Blind node made up of terminal device (RFD) is a key to locate, which can calculate the current coordinate. The coordinates of Reference node comprising the router are known in their respective networks, (FFD) which can help the blind node position. CC2431 location engine is on the basis of RSSI technology [4], RSSI refers to the strength of the wireless signal the node receives. The signal propagation loss can be calculated by the strength of known transmitter node and receive node. Then it can be changed into the distance using empirical models. Then the location of the node can be known by existing algorithms and the fixed coordinates. Blind node receives the packet signal from the reference node, which access to reference node coordinates parameters and the corresponding RSSI value, and then send them into the location engine. We only need to write the required parameters into the positioning engine. The result can be read out after waiting for completion of the engine. The theoretical RSSI value can be shown as equation (1) [5]. RSSI=-(10n·lgd+A)

(1)

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Positioning operation use the " best" reference nodes — the highest RSSI value. For example, in the area as shown in Figure 1 (a), in the X, Y directions a reference node is placed every 30 m. Firstly, find a reference node with the highest RSSI values. Since each reference node of the horizontal and vertical coordinates has the maximum length of 63.75m, thus identify a 64 m × 64 m range in the center of "best" reference nodes. As the RSSI value of this node is known, the distance d1 is available

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between the blind nodes to this node. Locate the reference nodes except the "best" node and calculate these distances away from the blind node (d2 ~ d8) in the same way. After completion of this calculation, Blind node position is fixed in the global grid as is shown in figure 1(b). Finally, get the value of all fixed coordinates into the location engine and read out the results of the final position. 3.2

Network Model

The net is made up of the structural design of components based on the mesh network [6] basic network topology, as is shown in figure 2. It has self-establishment and maintenance functions without human intervention. Each node can communicate with at least one node, supporting jump multi-level routing.

Fig. 2. Network topology

Net structure of the system is shown in Figure 3, the supermarket will be divided into several region, each region based on MESH-based network topology to establish sub-networks. Central node (also known as the gateway) initiates the regional subnetworks. At the same time it completes the communication between server and the wireless network. Each shopping Cart is fitted a mobile device with a blind node to complete the positioning. Blind nodes can be discovered independently adding and exiting networks, receive and send data, but not for router. What’s more, reference nodes are established in specific locations, reference nodes in their network coordinates are known, so it can help the blind node position and routed the data. Central node for each partition of the data can be summarized by the way of wire transfer to the server. Mobile devices first add into the sub-network which carrying the blind nodes after power, reference node will notice the blind node using self coordinates by sending data packet. Blind node receives the data packet signal from the reference node, obtains the reference node coordinates and the corresponding RSSI value, sending it into positioning engine. Then the currently own position after the positioning engine calculation can be read out, that is the initial coordinates. After customers enter a query term, the initial coordinate was sent into the server with customer inquiries through the reference node and the central node. Server can obtain the aim coordinates after the sever search the query term that can calculate the best path using these two coordinate values and map of supermarket. Then server can replay this path to the mobile device in form of a set of coordinates. Customer mobile follows this path, because blind node can independently join and leave different sub network, so it can constantly refreshing the current coordinates to achieve the navigation function. In this network model, blind nodes can communicate with the server in any location, so customers can get the latest product information anytime, anywhere in the supermarket.

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4 System Configuration and Implementation 4.1 System Hardware Structure According to the above network, model system is divided into mobile device, the reference node module, the gateway node module and the server these parts. (1)Mobile device: It is composed of the touch screen (four-wire resistive screen), flash memory, power and blind node, and such Peripherals devices, which is the core produced by Samsung company ARM9 microprocessor SC2410.Touch-screen can realize the information into the query and query results display, and navigation interface display functions. FLASH memory can store of the map of the regional supermarket. Blind node designed by the CC2431 to achieve the positioning, it is shown in figure 4 (a).

Fig. 4. Hardware structure

(2) Reference node (gateway node): This part was made up with the CC2430, power supply, reset circuit and an antenna minimum system which is the basic unit in Network communication and positioning system. Structure is shown in Figure 4 (b). 4.2

System Node Software

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management, interrupt management, task management, memory management, power management and non-volatile storage management service. (1) Gateway node: It is positioning System Coordinator which connected with the server through the RS-232. Firstly, it offers the reference node and blind node configuration data and sends it to the corresponding node [8]. Secondly, the data feedback by each node was received and sent to the server. Work flow chart is shown in Figure 5. VWDU W

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5 Conclusions The paper designs a ZigBee Network Model with the features of communication and location which mainly rests on CC2431 ZigBee network location property and further proposes a mobile electronic supermarket shopping guide system which can locate expected goods and offer the latest information on supermarket product. Combining the positioning technology, communication technology and computer technology is a new and meaningful field for study accompanied by good economic and social benefits we just update the related goods information on the server and check them on mobile devices. The employment of the system can comfort customer and facilitate management of supermarket.

References 1. Qu, L., Liu, S., Hu, X.: Technology and Application of ZigBee. Press of Beihang University 2. Li, W., Duan, C.: Professional training on Wireless Network and Wireless location of ZigBee. Press of Beihang University (2006) 3. Yao, Y., Fu, X.: Network Location of Wireless Sensor based on CC2431. Information and Electronic Engineering 4. Gao, S., Wu, C., Yang, C., Zhao, H., Chen, Q.: Teaching of ZigBee Technolog. Press of Beihang University 5. Chai, J., Yang, L.: Location System of Patients based on ZigBee. Measuring and Engineering of Compter 6. Ren, F., Huang, H., Lin, C.: Network of Wireless sensoring. Journal of Software 7. Sun, T., Yang, Y., Li, L.: Development Status of Wireless Sensor Network. Application of Electronic 8. Sun, M., Chen, L.: Application of ZigBee in field of Wireless Sensor Network. Modern Electronics Technique

The Research of Flame Combustion Diagnosis System Based on Digital Image Processing YuJie Zhang, SaLe Hui, and YuanYuan Zhang College of Electrical and Information Engineering, Shaanxi University of Science and Technology, Xi’an, China Abstract. According to the characteristics of boiler combustion process, we use image processing technique to extract features that characterize the features of flame. On requirements of good real-time performance boiler burning diagnose system, we develop a set of PC add DSP real-time image acquisition and burning diagnosis system on the 200MW boilers. The results show that the system is simple, practical, and can realize combustion diagnosis in the boiler operation process. The system provides a reliable basis for the safety of the power station boilers and economic operation, and has certain engineering application prospects. Keywords: Image acquisition, combustion diagnosis, vc++.

1 Preface The combustion process inside power station boiler furnace is a complex physical and chemical process. The flame temperature field distribution and the combustion condition have the extremely vital practical significance for the safe operation of power station. With the development of computer technology and electronic technology, the flame image monitoring system based on the core of digital image processing technology becomes the mainstream day by day. This article based on the characteristic boiler combustion process, uses image processing technology to extract features to characterize the feature of flame. In view of high real time requirements of combustion diagnostics, we developed a set of PC add DSP real-time image acquisition and burning diagnosis system and tested on the 200WM power plant boiler. Finally, we have a preliminary result of the study.

2 System Hardware Structure System structure is shown in Fig.1., it is made up by the optical system, CCD camera, image processing and burning diagnosis system. 2.1 Optical System The optical system is optical periscope, we uses it to gain the flame image in the stove, after the prism changes the direction and the optical fiber draws out in the CCD camera target surface. In order to make the optical system work safely in the furnace, the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 225–230, 2011. © Springer-Verlag Berlin Heidelberg 2011

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double-decked drive pipe structure is used to decrease temperature through cooling wind and to clean the lens through the air in case dust forms. The optical system is installed 30m.above the boiler and its field of view can effectively cover the entire chamber across section to obtain the flame combustion image of the entire chamber. 2.2 CCD Camera The CCD camera uses Japanese WATEC Corporation’s WAT-250D color camera, the parameter is: 1/3’’ colored CCD, the horizontal resolution is 450, signal-to-noise ratio 48dB; the electric power supply is 12VDC.

Fig. 1. System Structure

2.3 Imagery Processing and Combustion Diagnosis System The imagery processing and the combustion diagnosis system are made up by a PC and DSP coprocessor inserted in the PC’s PCI slots. DSP coprocessor completes image collection, processing and characteristic extraction. PC as the host completes the work of real-time display combustion diagnosis result and system control. The working process of the system is that the system images through optics periscope, and passes to the CCD target surface through the image optical fiber. The CCD camera gathers flame image by the speed of 25 flames per second, and transforms it into the video signal. Gain the real-time image information of the boiler through DSP coprocessor and send the information to PC through PIC to further processing and burning diagnosis.

3 Flame Image Characteristic Quantity Extraction Through testing the system from the power plant boiler combustion flame image taken by extracting the following characteristic: flame average gray and gray variance, flame effective area and the area of variance, high temperature area and area variance, thus reflecting the combustion characteristics, reaction flame burning and finally realizing the diagnosis. 3.1 Average Gray Iavre The definition of the average gray is the ratio of gradation mathematical expectation and image gray, it reflects the average light intensity of flame radiation. Takes a threshold value r in the imagery processing process, supposes p(i) is the probability of the ith level gradation, where r
The Research of Flame Combustion Diagnosis System Based on Digital Image Processing 227

m

1 m

I aver =

∑

(1)

ip (i )

i

In the formula, m is the maximum gradation progression of the image. 3.2 Variance σ The variance had reflected the non-uniform degree of the flame temperature distributed, the bigger the variance, the bigger temperature difference in the expression temperature field space scope is. When combustion chamber in low load operation, due to the coal-burning quantity's reduction, the combustion exothermic quantity reduces along with it, thus the flame temperature in the stove and the water cooling wall surface temperature drops, so as to reduces combustion reaction speed, reduces speed the heat release rate, enables the powdered coal air current fire to have the detention compared with the high load situation. And causes the combustion flame kernel to rising, the powdered coal combustion share changes in the spatial scope, therefore stove's temperature field is evener in the spatial distribution compared with the high load situation. According to the probability of variance in knowledge can be defined as follows:

⎡ j =1 ⎣

M

N

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value at(i,j), f is the average gray, whose value is f = I . If the current burning stabilization, the grey level should be in a threshold value, and the variance should be more stable. If combustion instability, have fire extinguishing trends, which will shows: gray value falls, grayscale variance change is big. aver

3.3 Effective Area of the Flame

As geometry characteristic quantity that attributes combustion condition, it has the massive research in the combustion theory. Here, the applying flame active surface corresponds to projected area which vertical to the camera direction. Through pretreatment to the primitive flame image, we can count in the image all pixels’ total quantity in a gradation level. As for each pixel occupy flame area roughly uniform, so it essentially represents flame projector area size. Flame effective area calculation formula is as follows: S

=

i

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x x

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0 0

(4)

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3.4 Area of High-Temperature Region

Known by the combustion theory, in the case of other conditions certain, the higher the combustion temperature is, the more stable combustion will be, the flame ability of resistance disturbance is strong, and the combustion is stable. Therefore the flame’s effective area and the high temperature region area value may reflect the combustion the stability, and can take the combustion diagnosis as the basis.

4 System Software Design DSP uses the C language programming, completes the debugging and the development under the CCS integrated development environment, and downloads through the JTAG connection to the DSP memory. The superior machine uses the VC++6.0 programming, completes combustion diagnosis and other works. 4.1 DSP Software Design

The flow is the DSP loads the program and initializes the system after power-on reset,, After self-checking unmistakably, DSP sends out the gathering signal, carries on the digital image gathering work. After DSP completes confirmation odd and even field image gathering, and makes two field data composite into a frame, then enters into the image processing program, reads the image gray value, and filters, divides noise, detects edge, extracts image feature amount ion, finally transmits the image data and the result to PC through the PCI interface. VWDUW LQLWLDOL]H

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4.2 PC Software Design

The PC is the interactive window between system and the operation personnel, using the image information processed by DSP, completes the combustion diagnosis, the

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warning output, the flame combustion situation real time display, the entire chamber combustion information and the temperature field and so on. PC software uses VC + +6.0 for development, including the data communications module, the data recording module and historical trends module.

5 Test and Result By using the system described, we carried on the performance test on some 200MW utility boiler.

Fig. 3. Flame Original Image

Fig. 4. Image Characteristic Quantity Extraction Surface

Fig. 3. is an image with bituminous coal altogether burns in the starting process. Fig. 4. shows computed result of the flame image pretreatment and the characteristic size through DSP.

Fig. 5. Flame Combustion Condition History Tendency Chart

Fig. 5. is the history tendency chart in the starting process recorded by PC, the left box is the history tendency after the image potential, in the chart A is the flame average gradation, B is the average gradation variance, C is the flame active surface, D is the active surface variance; right side of the box is settings for the relevant

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parameter. We may see from this chart, the above flame characteristic quantity is able real-time to reflect the boiler flame’s combustion condition, and it is take the basis for the combustion diagnosis.

6 Conclusion Compares with the traditional flame examination method, the method based on imagery processing's combustion diagnosis has the incomparable superiority. The preliminary experiment indicated that this article designs on the PC machine adds DSP the real-time image gathering and the combustion diagnosis system, can realtime completes the image processing and effective carries on the combustion diagnosis.

References 1. Wei, C., Yan, J., Shang, M.: Combustion diagnosis based on stove in flame image. J. Power Engineering 24(3), 2420–2427 (2003) 2. Yujie, Z., Pinglin, W., Changming, L.: Research based on digital image processing and neural network chamber temperature field survey and combustion diagnosis method. J. In Thermal Energy Electricity Generation (7), 18–21 (2004) 3. Wang, Y., Liu, H.: Combustion diagnosis method study based on stove flame image. J. Modern Electric Power 23(2), 64–67 (2006) 4. He, W., Shen, A., Wu, Q.: Flame detector system based on DSP and digital video technology image. J. Chinese Electric Power (10), 64–67 (2000) 5. Mu, H.: Coal-fired boiler’s visualization combustion diagnoses and discharges the forecast. D. Chinese Academy of Science master’s degree paper (2006)

Design and Research of Virtual Instrument Development Board Lin Zhang1, Taizhou Li2, and Zhuo Chen2 1 School of Mechanical and Engineering, Huazhong University of Science and Technology 2 School of Electronic Information, Wuhan University [email protected]

Abstract. At present, the technology of virtual instrument has been developed very quickly in the field of electronic measurement and automatic control. The virtual instrument is a kind of functional instrument combining of software and hardware .This article is from the perspective of exploration and research, and as a reference when encounter hardware problems in the research and development of virtual instrument. Virtual Instrument Development board, based on LabVIEW development platform, can achieve virtual oscilloscope, virtual signal generator, virtual spectrum analyzer and so on. And the use of virtual reality on the oscilloscope signal testing and analysis, while the virtual signal generator's output signal also had a measured and analysis, the results are satisfactory, the virtual spectrum analyzer at the request of the software is relatively high, in this paper did not achieve this feature, but the hardware has been tested successfully. Keywords: Virtual Instrument Development board, DSP, FPGA(CPLD), SCM, LabVIEW ,Quartus II.

1 The Conception of Virtual Instrument As traditional instruments, virtual instruments contain the same data acquisition and control, data analysis, which resulted in the expression of three function modules. Virtual instrument in a transparent way combines the computer resources and equipment hardware testing capabilities to achieve functional operation of the instrument. Virtual instrument with a variety of icons or controls simulates a variety of conventional devices on the virtual instrument panel. By kinds of icons to achieve instrument power switch-off; The button icons from a variety of test signals to set the "magnification", "channel" and parameters; A variety of display controls use values or waveforms to display measurement or analysis results; Using computer mouse and keyboards operation to simulate the traditional practice on the instrument panel; Using a flow chart of the graphical programming software to achieve a variety of signals measurement and data analysis. Electrical parameters based on virtual instrument by the tester hardware and software, most of the structure percent. Virtual instrument hardware usually consists of general-purpose computer and peripheral hardware devices. General-purpose computer can be a notebook computer, desktop computers or workstations. GPIB peripheral hardware devices can choose the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 231–238, 2011. © Springer-Verlag Berlin Heidelberg 2011

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system, vxl system, PXI systems, data mining collection system or other systems, and you can also choose from two or more systems consisting of hybrid systems. One of the most simple and cheapest form of ISA or PCI bus based data acquisition card, or based on RS - 232 or USB bus portable data acquisition module. Virtual instrument software, including operating systems, instrument drivers and application software at three levels. Operating system can be WindowSgx/NT/2000/XP, SUN05, Linux and so on. Instrument driver software is the direct control made a variety of hardware interface drivers, and application software and peripheral equipment drive hardware modules to achieve a communication link. Functional applications include software programs to achieve equipment and implement virtual instrument panel. The user through the virtual surface Interact communicates with the virtual instrument panel.

2 The Choice of Virtual Instrument's Development Environment Currently, the test system used for virtual instrument development, and relatively mature software platform, there are two main categories: one category is common visualization software programming environment, and there are Microsoft's Visual C + + and Visual Basic, inprise company's Delphi and C + + Builder, etc.; the other is the introduction of a number of companies dedicated to the development of software programming virtual instruments Environment, mainly Agilent Company (former HP company, a separate company) Agilent graphical programming environment VEE, NI's Lab VIEW graphical programming environment, and text programming environment Lab Windows / CVI. Common visualization software VB, VC, Delphi, are based on the text of a certain graphical features of the programming language. They are just text language graphical environments Or as support visual environments, not the graphical languages. Development of virtual instrument application softwares based on these platforms, require a lot of text programming languages,therefore the difficulty was increased, difficult to upgrade, and the efficiency is not high. A dedicated virtual instrument software, instrument-oriented interactive C language development platform Lab Windows / CVI has programming simple and intuitive that they have to provide automatic code generation and a large number of standardized instruments meet VPP driver source code available for reference and use, etc., is a virtual instrument system integrators to use more of the software programming environment for the formation of large multi-based test systems or complex virtual instrument. Agilent VEE and Lab VIEW is a graphical programming environment or as G programming environment and programming language used is different from the text of the flowchart programming method, suitable for professionals formed small test systems and simple virtual instrument.

3 Design of Virtual Instrument Development Board 3.1 Design of MCU and PC3.1.1 RS232 Computer Interface with the PC Because PC-232 logic level is different from MCU interface level, so you need level conversion, PC machines only can communicate with the microcontroller.

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Fig. 1. MAX232 chip design for applications with PC computer interface

3.1.2 PS / 2 Interface 1: data line (DATA); Figure. 1 MCU and PC computer interface circuits Figure. 2 SP / 2 wins 0 figure cited 2: Not used: 3: Power ground (GND); 4: Power (+5 V); 5: Clock (CL K); 6: not used Now widely used PC, PS / 2 interface is miniODIN6pin connector, and PS / 2 devices are the main from the points, female socket with the master device from the vice device using Male plug. Now widely used PS / 2 keyboard and mouse are working under the vice device. PS / 2 interface clock and data lines are open collector structure, must be an external pull-up resistor (generally Pull-up resistor to set the main device 1.Data communication between master and slave synchronous serial bidirectional transmission, the clock signal from the Generated from the device).

Fig. 2. PS/2 pin

3.2 CPLD Application Circuit Design 3.2.1 CPLD Hardware Design Because many of the virtual instrument development equipment, instruments, need to work on high speed, so I use CPLD chip to achieve. One chip manufacturer, is used as

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the mainstream-ALTERA CPLD, mainly due to the cost-effective feature of ALTER, and because the free build environment, the company's chips in many instruments devices have applications, such as with the 7000S series EPM7128SLC84-6 chip. This development board with CPLD is to achieve a special selection of waveform and high-speed transformation, meanwhile, CPLD and DSP-left interface, can achieve spectral analysis, high-speed oscilloscopes and other functions.

Fig. 3. CPLD(EPM7128SLC84——15)

3.2.2 Design of CPLD Interface with AD As a result of CPLD interface with the AD, through the CPLD to achieve Data buffer and primary treatment, AD in 12 bit AD1674, AD1674 minimum conversion time l0us,

Fig. 4. AD circuit

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can choose the less precision of speed 8-bit AD to make higher conversion. Then, higher in accuracy can be used 12-bit, general requirements for precision can be achieved in the virtual instrument development board. Consequently, this chip can complete the application needs, different requirements for the development of virtual instruments. 3.2.3 CPLD Interface Design and DA

Fig. 5. DA circuit

3.2.4 JTAG Interface JTAG is the FPGA (CPLD) program download interface, using ByteBlasterMV parallel download cable, ByteBlasterMV parallel download cable has standard parallel port connector with the PC's 25-pin , support 3.3V Vcc voltage Or 5.OV,allowing PC users from the MAX + PLUS II or Quartus II development software to download the data.

Fig. 6. JTAG Interface

3.3 Low Pass Filter Design Figure 7 for the 30MHz-pass filter design parameters and circuit diagram.

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Fig. 7. 30MHz low-pass filter

3.4 Single Chip Design Figure 8 is the minimum external circuit of single chip ATM89S52.the microcontroller bidirectional data bus as port PO which connected with the CPLD's 10.one-way read-write control output control bus including the Rd and Wr, address latch signal ALE (AddressLockEnable). 232 serial access microcontroller achieve Serial Port Communication, and Pl connect with DDS chip complete data transfer, register the command bus. The relationship of the DDS output frequency f0,the reference clock fr, the phase accumulator length N and the frequency control word FSW is: fO = fr.FSW/2N DDS frequency resolution is: AfO = fr/2N Because the maximum DDS output frequency by the Nyquist sampling theorem limit, so: fmax = fr / 2 [1 1] Currently, DDS products have Qualcomm's Q2334, Q2368; AD's AD7008, AD9850, AD9851, etc., This development board uses the company's AD9851 AD design. Meanwhile, SCM needs to do data type conversion.

Fig. 8. Basic circuit microcontroller

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3.5 Reservation and DSP Interface

Fig. 9. Interface with DSP

4 Verilog HDL Language Design Triangular Wave Generator 4.1 Keil C Compiler Environment Cx51 compiler and expansion of the 8051 traditional microprocessor optimized C compiler and library reference.

Fig. 10. Keil C interface

4.2 Build Successful Window

Fig. 11. Build successful window

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5 The Test of Signal Generator Serial debugging assistantis an indispensable tool in the research of the microcontroller serial PC with SCM communication, and virtual instrument development board uses serial communication, so I applied to serial debugging assistant for testing the development board. Figure 12 for the test signal generator waveform.

Fig. 12. signal generator waveform

References [1] IEEE1451.2 A Smart Transducer Interface for Sensors and Actuators-Transducer to Microprocessor Communication Protocols and Transducer Electronic Data Sheet (TEDS) Formats. IEEE Standards Department [2] Andrade, H.A., Kovner, S.: Software synthesis from dataflow models for G and LabVIEW TM. In: IEEE (ed.) Proceedings of the IEEE Conference Record of the 32nd Asilomar Conference on Signals, Systems and Computers, vol. 2. IEEE, Pacific Grove (1998) [3] Goldberg, H.: What is Virtual Instrumentation? IEEE Instrumentation and Measurement Magazine 3(4) (2000)

Substantial Development Strategy of Land Resource in Zhangjiakou Yuqiang Sun1, Shengchen Wang2, and Yanna Zhao3 1

Hebei Province Soils and Fertilizers General Station, Shijiazhuang, China 2 Hebei Province Yuanshi county Agrotechnical Centre, China 3 Shijiazhuang University of Economics, Shijiazhuang, China [email protected]

Abstract. Land resource is the foundation of the human beings’ survival and development, and as well as a kind of nonrenewable resource. So substantial development of land resource is very important. This paper analyses problems of the development of land resource in Zhangjiakou. Then we put forward some proposals such as classifying the land resource, improving land use efficiency etc. Keywords: land resource, substantial development, strategy.

1 Introduction Marx has said that land is the first resource for human being, is “mother of wealth”, and is the origin of all production and wealth. Indeed, land resource is the basement and origin of human being’s life and development, and is non-renewable. However, Chinese people occupy lower per capita land resource, and the growing contradiction between human and land makes people realize the importance and necessity of earth resource’s substantial development. Hence, to cherish every inch of land, develop, use and manage land resource reasonably and scientifically, and achieve land resource’s substantial development is one important task we are faced with now.

2 Main Problems during the Land Resource’s Substantial Development in Zhangjiakou Zhangjiakou lies in the northwestern of Hebei province, it is next to the capital Beijing in the east, to Datong in the west, to NC in the south, and to Mongolia in the north. The whole city is divided into 2 sectors of dam-top and dam-bottom, 7 areas and 13 countries, with the total column of 37000km² and population of 4600000. Among these sections 4 countries in the middle-dam lie to the south of Mongolia, with the column of 13800km² and population of 1060000. There is plow land of 8630000 hm², among which only irrigated land of 2420000 hm², 28% of the total. Zhangjiakou belongs to the symbolic continental arid and semi-arid climates area, where has much sand and strong wind. So there appear the following bad aspects during the development: S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 239–243, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2.1 Little Land and Worse Environment Little lands in Zhangjiakou are covered with plants, and are full of water resource, which leads to less mountains, bold and sandy earth, and prohibits the substantial development. In detail, these bad aspects are represented in the following: earth erosion. 63.8% of the basin is eroded, among which 9.6% of strong erosion scale 10000t/(km²·a) , 15.6% of serious erosion 5000-10000t/(km²·a) , 52.4% of medium erosion 500-50000t/(km²·a) ,and 22.4% of light erosion 500t/(km²·a) . Besides, there are about 30000hm² topsoil(0-10cm) eroded per year. lack of water. As 86% of the plow land is lack of water, some agricultural activities cannot be taken as usual. some is short of nutrient. Rapidly-available phosphorus in 81% of the plow land is less than 5mg/kg, total nitrogen in 46% of the land is less than 0.075%, organic matter in 27% of the land is less than 1%, and Rapidly-available potassium in 44% of the land is less than 100 mg/kg. And the land which is lack of trace element is: boron in 24% is less than 0.5 mg/kg, aluminum in 82% is less than 0.15 mg/kg, iron in 51% is less than 4.5 mg/kg, manganese in 81% is less than 5 mg/kg, and zinc in 79% is less than 0.5 mg/kg. thin earth. Here 2.5% of the earth is thinner than 30cm, so it is not good for the forest to grow. more salinity-alkalinity. 7.4% of the land here is salty land. some bad-produced soil. 22.6% of the soil has calcium deposition layer, with 92% within 50cm far away from the topsoil, besides, 4% of the soil has red soil, 4.45 of the soil has sand and gravel layer,1.44% of the topsoil is hardened, and there is more than 10% of gravel in 21% of the topsoil.

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2.2 Unreasonable Land Resource Development The economy in Zhangjiakou develops rather slowly, and belongs to the poor continent in Hebei Province with poor agriculture. Because of the serious natural environment, there exists much system output and little system input, which is really not balanced. And then, because of the strong wind and much sand, and over-ploughed land, 1200000hm² of the land has been desertification, which is 33% of the city’s total land and 44.1% of the province’s desertification. And among these sections, the desertification in Kangbao, Zhangbei, uyuan and Sangyi are the most serious. And according to the research in Kangbao, the thickness of the eroded soil has declined by 5-10cms, and this has been the prominent aspect which influences local development. Therefore, after the savage, simple and week balance is broken, the new one is ongoing, the eco-system lost its self-sustaining ability, and will absolutely give rise to a set of malignant recycle.

3 Strategy 3.1 Calcify the Land Resource The first class land lies in vally-basin in river-bottom, irrigation-silted soil in lake-side, brown soil and cinnamon soil, which should be the material foundation when solving

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the problem of grains. The third class land lies in the meadow soil on the hill, brown calcium soil, chestnut soil and meadow soil, and forage should be planted to enlarge the grazing capacity and fertilize the soil, which is helpful for little input and much output. The second class land is the link between the above two sorts. After the reorganization, the barn feeding of animal husbandry will be replaced with grazing, for the barn feeding can not only enhance the forage grass’s using ratio, but also roost the soil fertility, and decrease the harm and quicken kinds of forests grow, therefore, a new scientific eco-balance will be on the way. 3.2 Extend the Use of Dry Farming As we know, water is the first problem to solve in Zhangjiakou. There are two ways: open source and throttling. The former refers to develop and use water, develop irrigation farming and water conservancy projects, dig hells and build reservoirs. All these buildings are helpful on the whole. But at the same time we should realize the facts that there is little surface water, much losing water, poor groundwater, deep bury and unearthing difficulties. Therefore, solving the water problems in a short period of time is beyond the city’s economic ability. Besides, throttling refers to making full use of the existed water and rain, enhance the using ratio and developing dry farming. So, developing dry farming is suitable for the natural conditions in Zhangjiakou, and is one necessary choice. At first, basic construction and building should be achieved to enhance the agricultural production. For instance, basic dry farms should be built in the dam-top area; in the dam-bottom hill area, water should be rechanneled and collected; and in the dam-bottom deep-water area, the low-production farms should be transformed. And then, we should fertilize the soil and plant plants. When doing these, spreading farm manure and fertilizing soil should be the basic points. And more than 45m3of farm manure and 450kgs of phosphate in per acre land, with the advanced fertilizing technology popularized. Meanwhile, building some shelter forests and caragana korshinskii or medlar is necessary. And at last, we should reorganize the dry-land plants’ layout, and popularize the drought resisting and drought-enduring sorts. For example, in the dam-top and dam-bottom areas, the wheat and naked oats should be controlled, and potatoes and beans should be enhanced; but in the dam-bottom hills area grains and potatoes should be the main. 3.3 Adjust Measures to Local Conditions and Manage Comprehensively The dam-top area’s unbalance is the most serious one in Hebei. There are so frequent drying, wind and sand, salinization and so on that many lands are medium-low yield field. Hence, we should keep the number and quantity of the basic lands, improve the low-produced and sandy soils, prevent the soil from desertification and degradation, and developing throttling agriculture, choose the lands and plant according to water, and not open up virgin soil aimlessly. In the addition, the sandstorm should be managed

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in desert areas. And grass should be planted in agriculture- husbandry areas. In the detail: Firstly, in the northern dam-top plateau, 2 sand-preventing systems should be built. Referring to a sort of bad aspects, improving the sandy earth within the nets could be achieved by returning the plow lands, forests and grasses; taking those advantages, we can cover the soil with plants, enlarge the covering rate, to build a set of new eco-balance and re-represent the grass scenery. And then, the main problems which exist in the southeast dam-bottom area are, serious water-eroded, thin soil layer and shortage of nutrient; but there are also many advantages. Hence, preventing from soil erosion, protecting earth and fertilizing the soil are the prominent aims. Added to these, there are lots of disadvantages in the southern dam-bottom area: sparse plants, large yellow land, serious soil erosion, thin hill soil layer, dry soil and little nutrient. Meanwhile, it is suitable for agriculture; therefore, preventing from soil erosion, protecting earth, keeping water, and fertilizing the soil are the prominent aims. However, when using the hills, the covering rate should be largely enlarged. Besides, grain producing base with crops and melons and fruits should be built. 3.4 Enlarge the Technology Input, Soil Using Efficiency and Benefit First and foremost, depending on dry farming technology subjects, we should exclude the obstacles to low production, to form stable comprehensive producing capability. At the same time, concluding the experience of managing storm-sand-soil, we should hold the key technologies (such as water-saving Irrigation on dry farmland, manage and improve planting techologies and so on )and matched technologies, and make the best of them. In addition, we should increase the capital and material input, to alleviate the contradiction between input and output. Secondly, we should develop precision farming, protect the basic land,practice multiple cropping, and develop land-saving agriculture; popularize water-saving irrigating technology, and develop water-saving agriculture, and make best of lands, and develop courtyard economy and cubic economy. What is more, we should intake and bring the advanced agricultural technologies, and set up scientific farming pattern. In the end, we can enhance the land using efficiency and benefit by improving the matching and level of technological personnel and fostering technology model households.

4 Conclusion This article analyzed the causes of the unreasonable development of land resource in Zhangjiakou and figured out some detailed strategies, such as optimum use of land, promoting management and enhancing high-technology input etc. The author hopes that these measures could do something for the substantial development of land resource in Zhangjiakou.

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References 1. Sun, G., Wang, S.: Scientific and Technological Progress Promoting the Sustainable Development of Land Resources of TaiHang Mountainous Areas in Hebei Province. Chinese Agricultural Science Bulletin 18, 504–506 (2009) 2. Li, J.: Issues and Some Strategies of Sustainable Development of Black Soil Resources in Black Soil Zone in Northeast China. Chinese Agricultural Science Bulletin 4, 32–36 (2005) 3. Lin, D.: Continuous development and utilization of soil resources. Journal of Science of Teachers College and University 3, 75–78 (2002) 4. Wang, L.-b., Zhang, R.-p.: Mortuary Management and Sustainable Development of Land Resources. Ecological Economy 7, 43–46 (2008)

Computational Classification of Cloud Forests in Thailand Using Statistical Behaviors of Weather Data Peerasak Sangarun, Wittaya Pheera, Krisanadej Jaroensutasinee, and Mullica Jaroensutasinee Centre of Excellence for Ecoinformatics, School of Science, Walailak University, Nakhon Si Thammarat, 80160, Thailand {ppsangarun,wittayapheera,krisanadej,jmullica}@gmail.com

Abstract. This study attempted to distinguish the atmospheric characteristic of cloud forest quantitatively in order to classify their typical features. The nine weather stations were installed in different sites divided into three specific areas: (1) four cloud forest areas (Duan Hok, Dadfa, Mt. Nom and Doi Inthanon stations), (2) two lowland rainforest areas (Huilek and Mt. Nan Headquarters stations) and (3) three coastal areas (Walailak University, Khanom and Nakhon Si Thammarat stations). The atmospheric data consisted of temperature, the percentage of relative humidity and solar radiation collected from July 2006 to April 2010. The bimodal distribution and power law distribution were used to analyze parameters and classify atmospheric characteristics of the obtained data then classified them by cluster analysis. The results showed that those study sites can be classified into two groups: (1) cloud forest and (2) lowland rainforest and coastal area. Keywords: cloud forest, atmospheric data, weather station, bimodal distribution, power law distribution.

1 Introduction Tropical Montane Cloud Forests (TMCFs) occurs in mountainous altitudinal band frequently enveloped by orographic clouds [3]. This forest obtains more moisture from deposited fog water in addition to bulk precipitation [4] and [6]. The main climatic characteristics of cloud forests include frequent cloud presence, usually high relative humidity and low irradiance [4]. TMCFs normally found at altitudes between 1,500 to 3,300 m a.s.l., occupying an altitudinal belt of approximately 800 to 1,000 m. at each site [7]. The lowermost occurrence of low-statured cloud forest (300–600 m a.s.l.) is reported from specific locations like small islands, where the cloud base may be very low and the coastal slopes are exposed to both, high rainfall and persistent wind-driven clouds [1]. On small tropical islands, TMCFs can be found at lower altitudes. TMCFs obtain more moisture from deposited fog water in addition to precipitation [1], [8] and [9]. All tropical forests are under threat but cloud forests are S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 244–250, 2011. © Springer-Verlag Berlin Heidelberg 2011

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uniquely threatened both by human and by climate change impacting on temperature, rainfall and the formation of clouds in mountain areas [2]. Grace and Curran [5] used a bimodal distribution to model daily maximum temperature frequency distribution at southern Australian coastal sites. The model could assess impact of changes in the local atmospheric circulation patterns. This study attempted to quantify weather variables from automatic weather stations i.e. temperature, the percentage of relative humidity and solar radiation by using bimodal distribution and power law distribution, so that we can learn more about their seasonality. This study investigated the atmospheric data from nine study sites (Fig. 1a and 1b). This study was aimed to use weather data monitoring by automatic weather stations at cloud forests study sites and the other sites for studying and analyzing the atmospheric characteristics. Furthermore, we may use these data to predict the possibility of climate change and global warming of Thailand in the future.

2 Materials and Method Mt. Nan National Park is situated at Noppitam sub-district, Thasala district, and Sichon district in Nakhon Si Thammarat province, Thailand (Fig. 1a and 1b). Mt. Nan is a part of Nakhon Si Thammarat mountain range lie in North-South direction with an area of 406 km2. 90% of the area in Mt. Nan is a primary tropical evergreen forest which is an important watershed source of Nakhon Si Thammarat. There were nine study sites: three coastal sites (Khanom, Walailak University and Nakhon Si Thammarat), two tropical rainforest sites (Mt. Nan Headquarters and Huilek), and four cloud forest sites (Dadfa, Duan Hok, Mt. Nom and Doi Intanon) (Fig. 1a and 1b). Khanom (KHN), Walailak University (WLU) and Nakhon Si Thammarat (NST) sites were coastal area with the elevation of 8 m a.s.l. Mt. Nan Headquarters (NHQ) and Huilek (HUL) sites were tropical montane rain forests located within Mt. Nan National Park with the elevation of 182 and 234 m a.s.l., respectively. Dadfa (DFC) cloud forest site is a lower montane cloud forest located at Khanom district, Nakhon Si Thammarat province near coastal area with the elevation of 680 m a.s.l. Mt. Nom (MNC) cloud forest with the highest peak of 1,270 m a.s.l. and Duan Hok (DHC) cloud forest with the highest peak of 1,053 m a.s.l. are located at Mt. Nan National Park. Doi Intanon (DIC) cloud forest is located at Jomtong district, Maejam district, Maewang district and Doilo sub-district, Changmai Province. The geographical characteristic of Doi Intanon is a high mountainous range in North-South direction which is a part of Thanonthongchai mountain range with the elevation range of 400-2,565 m a.s.l. 2.1

Data Collection

We installed automatic weather station (Davis weather station model Vantage Pro II Plus) at nine study sites (Fig. 1a and 1b). There were different installation periods at each study site as followings: (1) KHN (September 2007), (2) WLU (August 2006), (3) NST (June 2006), (4) NHQ (September 2007), (5) HUL (November 2006), (6)

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DFC (January 2009), (7) DHC (March 2007), (8) MNC (January 2009) and (9) DIC (March 2008). We used the data logger for data storage interval time of 30 min. for all weather data.

(a)

(b)

Fig. 1. (a) The map of Thailand and Doi Intanon (DIC) study site (9) and (b) Mt. Nan National Park. The numbers represent (1) KHN, (2) WLU, (3) NST, (4) NHQ, (5) HUL, (6) DFC, (7) DHC, and (8) MNC.

2.2

Data Analysis

In this study, the weather data (i.e. temperature, relative humidity and solar radiation) at nine study sites were used to fit the bimodal and power law distribution of relative frequency. For temperature data, we used a bimodal distribution to fit the histogram distribution curves in all sites, except at DIC where it had three normal distributions. For relative humidity data, we analysed data as followings: (1) the bimodal distribution was used to analyse KHN, WLU, NST and NHQ sites and (2) the power law distribution was used to fit the first subpopulation distribution and the normal distribution was then used to fit the second and third subpopulation distributions where it applied. For solar radiation data, solar radiation data during 0600-1800 hours were used for data analysis. The power law distribution was used to fit the first subpopulation distribution and the normal distribution was then used to fit the second and third subpopulation distributions at all sites. The bimodal distribution and power law distribution are given by equation (1) and (2), respectively.

(1)

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3 Results

Relative Frequency

The temperature at all sites was bi-modally distributed, except at DIC site (Fig. 2a-2i) which showed multimodal distribution according to three subpopulations. Cloud forest sites had lower and than other sites (Fig. 2a-2i). The relative humidity at KHN, WLU, NST and NHQ sites were fitted by the bimodal distribution (Fig. 3a-3d). HUL, DFC, DHC and MNC sites were fitted by power law distribution and normal distribution (Fig. 3e-3h). DIC site was different from others sites that was fitted by power law and bimodal distribution (Fig. 3i).

(a)

(b)

(c)

(d)

(f)

(g)

(h)

(i)

(e)

Fig. 2. Temperature distribution with bimodal curve at nine study sites. (a-c) coastal sites, (d-e) lowland rainforests and (f-i) cloud forests

Solar radiation at KHN, WLU, NST, NHQ and MNC sites were fitted by power law and bimodal distribution (Fig. 4a-4d and 4h). HUL, DHC and DIC sites were fitted by power law and normal distribution (Fig. 4e, 4g and 4i). DFC site was fitted by power law distribution (Fig. 4a-4i).

Relative Frequency

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(a)

(b)

(c)

(d)

(f)

(g)

(h)

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Relative Frequency

Fig. 3. The percentage of relative humidity distribution with bimodal curve at nine study sites. (a-c) coastal sites, (d-e) lowland rainforests and (f-i) cloud forests

(a)

(b)

(c)

(d)

(f)

(g)

(h)

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Fig. 4. Solar radiation distribution with bimodal curve at nine study sites. (a-c) coastal sites, (d-e) tropical forests and (f-i) cloud forests

The results from cluster analysis of temperature, relative humidity and solar radiation identified clarification of two different groups of forests: (1) DFC, DHC, DIC, HUL and MNC study sites. (2) NHQ, NST, KHN and WLU sites (Fig. 5).

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Fig. 5. Cluster analysis of temperature, relative humidity and solar radiation data

4

Discussion

The bimodal model of temperature distribution composed of two subpopulations which were the mean temperature in rainy and summer season. DIC site had three subpopulations. The coolest subpopulation was the mean temperature in winter. The solar radiation was also grouped in the study sites into two differences: (1) DFC, DHC, DIC and HUL study sites. (2) MNC, NHQ, NST, KHN and WLU sites (Fig. 5). This study showed that MNC, DHF and DFC lower and than other sites. This indicated the peak of first subpopulation can be used as an indicator of cloud forest that is located near the equator. On the other hand, this could not be applied to high latitude cloud forest like DIC because in winter (November to February) the temperature was lower than the other month. The first peak of temperature was 6.97 ˚C and the second peak was 11.75 ˚C that was the mean temperature in rainy season and the third peak was showed the mean temperature in summer was 14.95 ˚C. It was found that DFC had slightly higher temperature than DHC and MNC that = 21.12, 19.22, 17.80 ˚C respectively. This could be due to the fact that DFC was located near coastal area at low elevation (i.e. 700 m a.s.l). These results support the Bruijnzeel’s study that can be found in TMCFs at lower altitudes. [1], [8] and [9]. The atmospheric characteristics of nine study sites could be classified by cluster analysis into two groups of forests within cloud forest sites; MNC, DFC, DHC and DIC and coastal sites; NHQ, NST, KHN and WLU. HUL site was different from the other sites. This may be the result from the influence of specific location, HUL was located at the valley that had frequent cloud presence and the water stream. The canopies of the tall trees in this site are covered with fog in the morning. MNC study site was located at the top of the hill that is exposed to the solar radiation and didn’t have the canopy cover. The bimodal distribution of solar radiation showed the mean of the first and second subpopulations and . NHQ, NST, KHN and WLU had higher than the other sites.

5

Conclusion

Bimodal distribution of temperature can be used to separate forest types. From nine study sites, the mean and variance of the bimodal distribution can group them into two types: (1) four cloud forest sites (DHC, DFC, MNC, and DIC stations), (2) two

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lowland rainforests (HUL and NHQ stations) and three coastal sites (WLU, KHN and NST stations). In this study, the relative humidity distribution of coastal sites that were WLU, KHN and NST sites was fitted by power law and bimodal distribution of 4 study sites and by using power law and normal distribution of 5 study sites. The data of temperature, relative humidity, and solar radiation could be used to analyze the weather variation and distribution. Further, these data could be generalized for better understanding of the fluctuation of weather which tends to change according to the global warming climate situation. Acknowledgments. This work was supported in part by PTT Public Company Limited, TRF/Biotec special program for Biodiversity Research Training grant BRT R351151, BRT T351004, BRT T351005, Walailak University Fund 05/2552 and 07/2552, WU50602, and Center of Excellence for Ecoinformatics, the Institute of Research and Development, Walailak University and NECTEC. We thank Mt. Nan National Park staff for their invaluable assistance in the field.

References 1. Bruijnzeel, L.A., Proctor, J.: Hydrology and biochemistry of tropical montane cloud forest: what do we really know? In: Hamilton, L.S., Juvik, J.O., Scatena, F.N. (eds.) Tropical Montane Cloud Forest, pp. 38–78. Springer, New York (1995) 2. Bubb, P., May, I., Miles, L., Sayer, J.: Cloud Forest Agenda. UNEP-WCMC, Cambridge (2004) 3. Foster, P.: The potential negative impacts of global climate change on tropical montane cloud forests. Earth-Science Reviews 55, 73–106 (2001) 4. González-Mancebo, J.M., Romaguera, F., Losada-Lima, A., Suárez, A.: Epiphytic ryophytes growing on Laurus azorica (Seub.) Franco in three laurel forest areas in Tenerife (Canary Islands). Acta Oecologica 25, 159–167 (2004) 5. Grace, W., Curran, E.: A binormal model of frequency distributions of daily maximum temperature. Australian Meteorology Management 42, 151–161 (1993) 6. Hamilton, L.S., Juvik, J.O., Scatena, F.N.: The Puerto Rico Tropical Cloud Forest Symposium: Introduction and Workshop Synthesis. In: Hamilton, L.S., Juvik, J.O., Scatena, F.N. (eds.) Tropical Montane Cloud Forests, pp. 1–23. Springer, New York (1995) 7. Stadtmüller, T.: Cloud forests in the humid tropic: a bibliographic review, pp. 1–81. The United Nations University, Tokyo (1987) 8. Still, C.J., Foster, P.N., Schneider, S.H.: Simulating the effects of climate change on tropical montane cloud forests. Nature 398, 608–610 (1999) 9. Weathers, K.C.: The importance of cloud and fog in the maintenance of cosystems. Trends in Ecology and Evolution 14, 214–215 (1999)

Research on Establishing the Early-Warning Index System of Energy Security in China Yanna Zhao1, Min Zhang2, and Yuqiang Sun3 1 School of Management Science & Engineering, Shijiazhuang University of Economics, Shijiazhuang, China 2 China Geological Survey, Beijing, China 3 Hebei Province Soils and Fertilizers General Station, Shijiazhuang, China [email protected]

Abstract. Energy security is an important factor that affect development of economy in our country. So, China has faced a great challenge on energy security. Firstly, this paper defined the energy security from three aspects. Secondly, it analyzed the factors that affected energy security in China. Finally, the scientific index system of energy security were established in order to using for reference to macro-management of energy security in China. Keywords: energy, security, early-warning, index system.

1 Introduction Energy is the important material base on which people rely during surviving and producing, is the artery of our economy. Minable reserve of oil in China is 3% of the volume of the world. In recent years, Chinese energy security is faced with unprecedented threat. Take the oil for example, our cost amount of oil is only less than that of America, so we have to make up the gap between the poor selfsufficiency ability and the increasing cost demand by importing. According to the survey, our importing proportion has increased to more than 50% in 2008 from 7.6% in 1995, which undoubtedly enhanced the uncertainty of oil supply. On the other hand, with fluctuation of raw oil price at the international market, for instance, it had been 100 dollars per hail since February 2nd 2008, and just has increased to 147.24 dollars per hail, which has enhanced the cost of our oil trade, besides, the large fluctuation will extends to the national economy, which will not only influence people’s normal life, but also pose a threat to national safety. So, the energy security has been a sensitive issue.

2 The Basic Concept of Energy Security With the development of social economy, people’s awareness of the energy security has experienced about 3 periods: In 1950s, with the technological advancement and global industrialization, the energy consumption has increased and great changes have been taking place on the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 251–256, 2011. © Springer-Verlag Berlin Heidelberg 2011

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consumption system, and the coal-cored has transferred to the oil-cored system, and as the oil energy is dense on the earth, it evokes people’s sorrow towards the oil supply assurance. At that time, energy security refers to whether there is enough energy storage, productivity and smooth selling channel. In 1970s, about during the forth Middle-East War, when the oil exporter countries enhanced the raw oil price, the most serious global economic crisis after the second world war prevailed the world. And until then, did people realize that the fluctuation of the energy price could influence national economic work. So the concept of energy security extended to enough supply and stable price. With the increasing of global energy cost, a series of problems such as global warming and air pollution have been turned out. And people begin to realize that the energy use should not pose a threat to human’s survival and environment. Therefore, the meaning of energy usage safety is mixed into the previous concept of energy security. The concept of energy security mainly includes the following 3 levels: enough supply, which refers to the energy supply which could meet a country or an area’s need; stable price, which refers to the price fluctuation could not exceed the country or area’s convey; safe use, which refers to the energy could not threaten the environment which human beings depend on. Among these 3 levels, the first one is the base, and the most focused one as well.

3 The Analysis on the Factors Which Influence Energy Security of China In the 21st century, with Chinese industrialization and modernization, and the advanced energy consumption system, our energy security is faced with the ever most serious challenge. On the whole, there are lots of reasons which influence our energy security: supply and demand, price, and safety. 3.1 The Analysis on Energy Supply 1) Energy reserves shortage leads to the poor assurance ability China is a developing country with large population, which is lack of per-capita energy, has no balance between energy system and storage. According to calculation, we have comparatively rich coal energy, among which the concealed costs 33.8%, and the left is 90 billion tons. And if we conceal like this, we can still do it for 100 years. So we have strong coal assurance ability. But we have comparatively short oil energy, of which the left is 2.3 billion tons; the per-capita is only 8.1%. So the left can be concealed for 14 years. Besides, as the oil energy is related to the politics, military, living and economy, the poor oil assurance ability has influenced the national energy security. 2) Low technological level reduces the productive efficiency of energy prodution From the previous data, we can see that China is a country with little oil energy, and low use rate, which worsens our oil energy. For we own poor concealing technology, mainly water injection concealing, which only leads to the rate of about

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30%, and means the other 70% is left under the earth. But in fact, the rate with some advanced technology is 50% to 60%. So the oil productivity in the developed countries is once or twice higher than our country. 3) The highly centralized trade routes leads to the more serious supply crisis of energy Entering the 21st century, our oil imports amount increase fast with the economic growth. And because the home product cannot meet the increasing oil consumption demand, so we mainly import. In 2007, the total imports amount is 211.394 million tons, which is 62% of our total consumption. And since 2000, we have imported about over 50% of oil from the Middle-East, and more year by year. So our oil depends much on the outside, and the area from where we import is dense, in the Middle-East, which is the most unsteady area in society, politics, and military, because of its oil energy. As oil is not renew, so only if there is no new fuel to take place of oil, international conflict for oil would not stop. 3.2 The Analysis on Energy Demand As the largest developing country in the world, Chinese economy is developing quickly recently. As the calculation, our GDP increase in 1990s is about 9%. But it is clear that our economic developing depends on the extensive consumption. The highconsumed industry is the major strength of our economy, and will be the more one. Though the technology has been increased, the consumption is still too high and the low technology leads to low productivity, especially high consumption. On the whole, our use rate is only about 33%, 10% lower than that of the developed countries. Currently, our product of high-consumption industry is the first in the world. Our steel product is 502 million tons; the cement is 1.388 billion tons, all the first in the world. Currently, our 8 industries unit consumption is 40% higher than that the international levels. As we see, the extensive consumption system and the low use rate give rise to the high demand, which further expand the supply chasm. 3.3 The Analysis on Energy Price Oil is not only the important energy in the national economy, but also the important raw material in chemical industry, so we can say that oil is the food of industry. So we call it “black gold” and “economic blood. Wolfenson has said that if the oil price of per hail keeps enhancing 10 dollars for one year, the international economic rate will decline by 0.5%, but the developing country’s will decline by 0.75%, so the influence with the oil price fluctuation is more obvious. As in 2008, the fluctuation in the international oil price has once made our country faced with serious inflation, so once the oil price inflates, a series of reactions will come out: it will increase the cost, which will lead to national economic inflation and recession. On the other hand, too low price will influence the interest of the oil industry, which decides to limit and stop producing, which will give rise to the oil crisis, and once the supply stops, it will also influence the national economic development. So no matter too high or too low, the oil price will pose a serious threat to our national economic development.

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3.4 The Analysis on the Use Safety of Energy In the middle 1980s, with the global warming and declined air quantity, the environmental problem is once again focused on. Our consumption system is unreasonable, though lots of experts are calling for declining the rate of coal; coal’s present rate is about 70% of the total energy consumption. As coal is impure energy, especially the raw coal is not completely burned, sending out a lot of CO2 and SO2, and worsens the environment. We all know that SO2 is the maker of soar rain, and CO2 is the leader of the global warming, as 80% is directly burned, so it further worsens the pollution, which will threaten our present environment but also influence our international image, and spread to our descendants and damage our long-term interest.

4 The Establishing the Early-Warning Index System of Energy Security in China This article bases on the energy security, builds the energy security early-warning index system according to its 3 levels, as is shown in the follow chart: Table 1. Early-warning index system of energy security in China

Level 1

Degree of energy security

Level 2 1)Oil reserve-production ratio 2)Oil recovery ratio 3)Concentration ratio of oil imports 4)Dependency of oil consumption on import 5)Energy consumption per GDP 6)Energy consumption elastic index 7)Rate of change in oil price 8)Reducing discharge rate of CO2 9)Reducing discharge rate of SO2

1)Oil reserve-production ratio Oil reserve-production ratio oil left storage/oil concealed this year It refers to the life span of the oil left, according to the present concealing scale. It is used for measuring the storage assurance ability. The higher it is the stronger the assurance ability is and the safer the energy is. 2) Oil recovery ratio It is used for measuring the oil concealing rate, and refers to the ratio between the total oil concealed within this period and the initial oil storage. The higher it is the higher the concealing rate is, which means that while others remain, the oil selfsufficiency ability and energy security are enhanced.

＝

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3)Concentration ratio of oil imports Concentration ratio of oil imports=the total net importing amount from the 3 first importing countries/the total net importing amount It refers to the density of the oil importing areas, the higher it is the more dense the oil importing areas are, and once some emergencies happen lead to unsmooth importing channel, and will give rise to big risk, so the energy security will be not so well. 4) Dependency of oil consumption on import Dependency of oil consumption on import=importing amount/national consumption It shows how heavy the national consumption depends on the outside. The higher it is the larger the supply uncertainty is and the lower the energy security is; or the higher the energy security is. 5) Energy consumption per GDP Energy consumption per GDP=the total energy consumption/10000 yuan GDP It refers to the energy consumption during producing per 10000 yuan GDP, within one period. And it shows the economic outcome produced by energy consumption, so the lower it is the more economic outcome is and the higher the energy using rate is, so the safer the energy will be. 6) Energy consumption elastic index Energy consumption elastic index=the energy consuming average increasing rate/GDP average increasing rate It shows the relationship between the energy consumption and national economic development, and it identifies the restrict relationship between the energy development and social economic development and the developing trend and principle, and the energy using rate at the same time. The lower it is the higher the energy using rate is and the safe the energy will be. 7) Rate of change in oil price Rate of change in oil price = (the current price-the basic price)/ the basic price It identifies the oil price changes in the international market. When it is more than 0, the current oil price is increasing when compared with the basic price, and the cost of the oil product will enhance, and the relevant industries’ cost will enhance too, so some negative impact will be put. And the bigger the number is the lower the safety is; or the higher the safety is. When it is less than 0, the oil price in the international market will decline, and the larger it is the higher the safety will be. 8) Reducing discharge rate of CO2 Reducing discharge rate of CO2= (the previous emission-the current emission)/ the previous emission 9) Reducing discharge rate of SO2 Reducing discharge rate of SO2 = (the previous emission-the current emission)/ the previous emission Reducing discharge rate of CO2 and Reducing discharge rate of SO2 are used for identifying the energy using safety. The higher they are the better the harmful gas is controlled and the smaller the influence towards environmental pollution is and higher the energy using safety is.

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5 Conclusion The problem of the energy security has begun to hinder the further development of the national economy and threat the social stability. This article has built a set of energy security early-warning index system based on the analysis of national energy security. At the same time, the changing of index can reflect the problems of national energy security. The author hopes that the energy security early-warning index system this article builds could do something for strengthening the management on risk and realizing sustainable development of the national economy.

References 1. Kong, L.B., Hou, Y.B.: Study on the National Energy Safety Model. Metal Mine 11, 3–5 (2002) 2. He, Q.: Discussion and Strategy about the Energy Security of China. China Safety Science Journal 6, 52–57 (2009) 3. Ma, W., Wang, Z., Huang, C.: Some Issues of Energy Security of China and Tentative Solutions. Studies In Interntional Technology and Economy 4, 7–11 (2001) 4. Gao, J.-l., Ou, X.-y.: Discussion on China’s Low-carbon Economy under the Restriction of Energy Security. Journal of Lanzhou Commercial College 2, 38–43 (2010) 5. Li, S.-x.: Study on the Energy Efficiency Strategy and the Improvement of National Energy Security. Journal of China University of Geosciences (Social Sciences Edition) 3, 47–50 (2010)

Artificial Enzyme Construction with Temperature Sensitivity Tingting Lin1, Jun Lin1, Xin Huang2, and Junqiu Liu2 1

College of Instrumentation & Electrical Engineering, Jilin University, Changchun, 130061, China [email protected] 2 State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun, 130061, China

Abstract. Poly (N-isopropylacrylamide) (PNIPAAm) is one of the most popular thermoresponsive polymers, which shows dramatic and reversible phase transition behavior in water. Therefore two strategies for the design of temperature-sensitive enzyme model based on PNIPAAm derivatives are presented: 1) A temperaturesensitive block copolymer (PAAm-b-PNIPAAm-Te) with a glutathione peroxidase-like active site was synthesized via ATRP. 2) An artificial bifunctional enzyme with both superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities was constructed by the self-assembly of a porphyrin core with four suspensory adamantyl moieties and b-cyclodextrin-terminated temperaturesensitive copolymer (β-CD-PEG-b-PNIPAAm-Te) through host–guest interaction in aqueous solution. With increasing temperature, the PNIPAAm chain becoming hydrophobic leads to a change in the self-assembly structure of the polymer, which plays a key role in modulating the catalytic activity. And two new artificial enzymes were found to exhibit the highest enzymatic catalytic efficiency in close to physical temperature. Keywords: biomimetic, block copolymers, micelles, temperature sensor, synthesis.

1 Introduction In biological organisms, overproduction of reactive oxygen species (ROS), such as superoxide anions, H2O2, organic peroxide, and hydroxyl radical, can result in a variety of human diseases, example for ischemia/reperfusion injury, atherosclerosis, neurodegenerative diseases, cancer, and allergy etc [1]. The antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) contribute dominatingly to enhance cellular antioxidative defense against oxidative stress in the human body [2]. SOD is a metalloenzyme that catalyzes the dismutation of superoxide radical anion to form H2O2 and dioxygen. H2O2 is then detoxified either to H2O and O2 by catalase (CAT) or to H2O by glutathione peroxidase (GPx) [3]. However, only when an appropriate balance between the activities of these enzymes is maintained could the optimal protection of cells be achieved [4]. Owing to their biologically crucial role, considerable effort has been devoted to designing artificial S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 257–262, 2011. © Springer-Verlag Berlin Heidelberg 2011

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enzymes that mimic the properties of antioxidant enzymes in recent years. Importantly, a desirable antioxidant enzyme model should be regulated by some environmental stimulation, such as temperature, pH, ion strength or magnetism. Then the properties of ROS can be controlled wisely.

Fig. 1. Schematic representation of the enzyme model (A) the smart GPx enzyme model (B) preparation of the bifunctional enzyme model

In the last decade, stimuli-responsive polymers have attracted strong scientific and technical interest due to their reversible properties in response to changes in environmental factors such as pH or temperature [5]. Among these materials, the thermal sensitive poly(N-isopropylacrylamide) (PNIPAAm) attracts particular attention. PNIPAAm are also called “smart” material. They have a volume phasetransition temperature or lower critical solubilization temperature (LCST) at about 32 ºC. This means that below the LCST, the particles are swollen and above this temperature they are collapsed [6]. A detailed knowledge and control of the swelling behavior will also invoke a better physical understanding of the mechanism of the observed volume phase transition. This knowledge can then be used to design complex materials. Due to the reversible phase transition, PNIPAAm based microgels can be used in many different application fields, for example, as functional materials for drug delivery, optical filtering and controlled biomolecule recovery. To construct antioxidant mimics with high catalytic efficiency, we focus on PNIPAAm in the following aspects: 1) we designed and synthesized a smart GPx enzyme model, the block copolymer PAAm-b-PNIPAAm-Te, by ATRP, in which the GPx active site (tellurium moiety) was incorporated into the PNIPAAm chain (the designed functional monomers and the substrates structure are given in Fig. 1A). 2) To further design a smart bifunctional antioxidant enzyme model with both SOD and

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GPx activities which is close to the body’s physiological environment, we used a temperature-sensitive block copolymer (b-CD-PEG-b-PNIPAAm-Te) which can selfassemble with MnTPyP-M-Ad through host–guest complexation (Fig. 2B).

2 Result 2.1 Stimuli-Responsive Micellization Fig. 2A shows the temperature dependence of the average hydrodynamic radius for PAAm-b-PNIPAAm-Te in aqueous solutions. The critical micellization temperature of PAAm-b-PNIPAAm-Te was found to be 34 ºC, which is higher than that of PNIPAAm homopolymers. This is due to the fact that PNIPAAm is now attaching with a hydrophilic PAAm. Furthermore, the actual morphology of the micellar structure was observed by SEM (Fig. 3A).

Fig. 2. Temperature dependence of the hydrodynamic diameters of the PAAm-b-PNIPAAm-Te block copolymer (A) and using a Malvern ZETAS12-ERNANOSERIES instrument. From a to e, the temperature was 15, 25, 33, 35 and 45 ºC, respectively. b-CD-PEG-b-PNIPAAm-Te (B) was also determined. From a to d, the temperature was 30, 35, 37 and 35 ºC, respectively.

A

B

Fig. 3. SEM images for PAAm-b-PNIPAAm-Te (A) and b-CD-PEG-b-PNIPAAm-Te(B) at silica wafer on a JEOL FESEM 6700F scanning electron microscope with primary electron energy of 3 kV

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Fig. 2B shows the temperature dependence of the for the pseudo-block copolymer and b-CD-PEG-b-PNIPAAm-Te in aqueous solutions.Then, the morphology of the b-CD-PEG-b-PNIPAAm-Te and star-shaped pseudo-block copolymer was intuitively characterized via SEM, and the average diameter was about 300 and 150 nm, respectively (Fig. 3B). 2.2 Catalytic Behavior The GPx-like activity of the block copolymer catalyst for the reduction of cumene hydroperoxide (CUOOH) by 3-carboxyl-4-nitrobenzenethiol (TNB, 1) was evaluated according to a modified method reported by Hilvert et al [7]. The activities were given (vide infra) assuming one molecule catalytic center (Te-moiety) as one active site of the enzyme. The content of tellurium in the polymer was determined via UV titration analysis. The reaction was initiated by the addition of hydroperoxide, and the decrease of the absorbance at 410nm (pH 7.0) was recorded for a few minutes to calculate the reaction rate. The relative activities are summarized in Table 1. Assuming that the rate has a first-order dependence on the concentration of catalysts, these data suggest that the GPx activity of the block copolymer catalyst is at least 251000-fold more efficient than that of PhSeSePh, and is also about 7-fold more efficient than the previously reported selenium-micelle enzyme model [8,9]. Table 1. The Initial Rates for Reduction of Hydroperoxides by Thiol TNB and NBT in the Presence of PAAm-Te-b-PNIPAAm

In addition to PAAm-b-PNIPAAm-Te, MnTPyP-M-Ad was assembled with b-CDPEG-b-PNIPAAm-Te through host–guest interaction. The SOD activity of the enzyme model was quantified using the standard xanthine/xanthine oxidase assay system first developed by McCord and Fridovich [10]. In order to determine the concentration of the catalyst which achieves 50% inhibition (IC50) of the reaction (a generally used indicator for comparing the efficiencies of enzymes and enzyme mimics), it equals to 2.15% of the activity of native SOD enzyme (Table 2). The GPx activities were given assuming one molecule catalytic center (Te-moiety) in the enzyme model as one active site of the enzyme, and the content of tellurium in the model was determined by ICP. The relative activities were summarized in Table 3.

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Table 2. SOD Activity of Star-shaped pseudo-block Copolymer Catalyst

Table 3. GPx Activity of Star-shaped pseudo-block Copolymer Catalyst

3 Conclusion Through preparation of a novel block copolymer by ATRP, We have designed and synthesized two block copolymers (BCP) which exhibited stable antioxidant catalytic efficiency with temperature-responsive dependence characteristic. We anticipate that this study will open up a new field in artificial enzyme design with environmental responsive functions, and hope that such smart enzyme mimics could be developed to use in an antioxidant medicine with controlled catalytic efficiency according to the needs of the human body in the future.

References 1. Mugesh, G., du Mont, W.W., Sies, H.: Chemistry of biologically important synthetic organoselenium compounds. Chem. Rev. 101, 2125–2179 (2001) 2. Berlett, B.S., Stadtman, E.R.: Protein oxidation in aging, disease, and oxidative stress. J. Biol. Chem. 272, 20313–20316 (1997) 3. Flohé, L., Loschen, G., Günzler, W.A., Eichele, E.: Glutathione peroxidase, V. The kinetic mechanism. Hoppe. Seylers. Z. Physiol. Chem. 353, 987–999 (1972) 4. Spector, A.: Oxidative stress-induced cataract: mechanism of action. FASEB. J. 9, 1173– 1182 (1995)

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5. Stayton, P.S., Shimoboji, T., Long, C., Chilkoti, A., Chen, G., Harris, J.M., Hoffman, A.S.: Control of protein-ligand recognition using a stimuli-responsive polymer. Nature 378, 472–474 (1995) 6. Karl, K., Alain, L., Wolfgang, E., Thomas, H.: Volume transition and structure of triethyleneglycol dimethacrylate, ethylenglykol dimethacrylate, and N,N′-methylene bisacrylamide cross-linked poly(N-isopropyl acrylamide) microgels: a small angle neutron and dynamic light scattering study. Colloids. Surf. 197, 55–67 (2002) 7. Wu, Z.P., Hilvert, D.: Selenosubtilisin as a glutathione peroxidase mimic. J. Am. Chem. Soc. 112, 5647–5648 (1990) 8. Huang, X., Dong, Z.Y., Liu, J.Q., Mao, S.Z., Xu, J.Y., Luo, G.M., Shen, J.C.: Telluriumbased polymeric surfactants as a novel seleno-enzyme modelwith high activity. Macromol. Rapid. Commun. 27, 2101–2106 (2006) 9. Huang, X., Dong, Z.Y., Liu, J.Q., Mao, S.Z., Xu, J.Y., Luo, G.M., Shen, J.C.: Seleniummediated micellar catalyst: An efficient enzyme model for glutathione peroxidase-like catalysis. Langmuir. 23, 1518–1522 (2007) 10. McCord, J.M., Fridovich, I.: Superoxide dismutase. An enzymic function for erythrocuprein (hemocuprein). J. Biol. Chem. 244, 6049–6055 (1969)

An Efficient Message-Attached Password Authentication Protocol and Its Applications in the Internet of Things An Wang1, Zheng Li2, and Xianwen Yang2 1

Key Lab of Cryptographic Technology and Information Security Ministry of Education, Shandong University, 250100 Jinan, China [email protected] 2 Department of Electronic Technology, Information Science and Technology Institute, 450004 Zhengzhou, China {lizhzzdy,yxw200420042004}@163.com

Abstract. Based on the shortcoming of low efficiency of secure message transmission in the Internet of things, a new design philosophy is proposed: combining the authentication with message transmission. Accordingly, a secure and efficient message-attached password authentication protocol is presented. We design universal message transmission architecture of the Internet of things, consisting of clients, server, and network node. As a result, some experiments show that our scheme is efficient and convenient which can solve all the security problems. Keywords: Information security, the Internet of things, message-attached password authentication protocol, cryptography engineering.

1 Introduction and Motivation The Internet of things [1, 2], an Internet for connecting all kinds of things together, is becoming a central research direction of information security. Many companies have designed their products, such as household electrical appliances, street lamp, display monitor, et al. These products usually consist of a remote controller / monitor and some local devices. According to cryptographic protocol [3], we may just as well call the former “server” and the latter “client”. The conventional basic architecture of the Internet of things is described in Figure 1. Because of the insecure of internet channel, almost all products of the Internet of things adopt some security strategies. With the help of hash functions or public key cryptographic schemes [3], the mutual authentication protocols [3] are used for the identity authentication and digital signatures are used for verifying the prime source of information. By this method, the former usually includes no less than three steps, and the latter must cost one or two transmissions. In most cases of the Internet of things, the message transferred between server and clients is very short, sometimes even only one bit (such as a switch of street lamp). In fact, to finish such a simple task so wordily is not expected, and the low efficiency is becoming a serious problem in this field. Therefore, we present the concept of message-attached authentication protocol in order to solve this problem. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 263–269, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Server

Client

Computer

Function Module Wired/Wireless

Internet Interface

Channel

Internet Interface

Fig. 1. Principle of the Internet of things

A new design philosophy of the message transmission scheme for the Internet of things is proposed in this paper: combining the authentication with message transmission. The outstanding character of our scheme is the decrease of interaction. The number of steps in the whole protocol can be decreased to three, and one signature will be economized. How to design a message-attached authentication protocol? We can borrow ideas from the currently existing homogeneous protocols. The conventional password authentication protocol is one of the most simple, convenient and most widely used authentication modes. Lamport [4] first proposed encrypting the user’s password with the safe one-way hash function. Hwang and Yeh [5] proposed a mutual authentication protocol. Although the original author claimed that this scheme could resist the known attacks, Chun et al [6] pointed out that this protocol was vulnerable to denial of service (DoS) attack. Peyravian and Jeffries [7] also raised a hash-based authentication proposal and declared that it could resist DoS and off-line password guessing attacks. In 2008, Wang et al [8] proposed a mutual anonymous password authentication scheme and declared that the efficiency was equivalent to the Hwang and others’ protocol but it was more secure. We find that due to the application of public key cryptography, the efficiency of Wang’s protocol is much lower than the Hwang and others’. Besides, the characteristics of resist-DoS are not very good and the so-called “weak password attack” isn’t really inexistent. In this case, an efficient message-attached password authentication protocol based on hash functions is proposed and we also evaluate the security and efficiency in detail. Based on the new message-attached password authentication protocol, we design universal system architecture of the Internet of things. Experiments show that the protocol given in this paper, with high efficiency, can resist a variety of known attacks and achieve the security requirement of the Internet of things perfectly.

2 Efficient Message-Attached Password Authentication Protocol A new message-attached password authentication protocol is proposed in this part for the security problem of Wang’s scheme [8] and security requirement of password authentication. The new proposal can improve the efficiency greatly, make up the Wang’s security deficiencies and resist various known attack.

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2.1 New Scheme Initial Conditions and Symbols. S / C: the server / clients; M: a message from S to C or from C to S; IDC: the identity of user C (unique); PWC: the password of user C; H(): strong collision free hash function; Rc, Rs: random number generated by C, S; SKC: symmetric key between C and S; Comma in the message: splice. User Register. When the user C registers at the server S, C passes H(PWC), the hash value of the password PWC , to the server S. Then S establishes the password verifier, which is shown in Table 1. Table 1. Password Verifier User ID ID1 ID2 … IDn

Password’s Hash Value H(PW1) H(PW2) … H(PWn)

Furthermore, S generates the symmetric key SKC, imparts the value to C and both sides store the key in safety. Implementation Step 1: C or S submits the communication request to the other participant. Step 2: S sends a random number RS to C. Step 3: C generates a random number RC, calculates H(H(PWC), RS, RC, IDC, SKC, MC) with key SKC, and then sends the hash value to S with RC, IDC, MC . Step 4: After receiving the data from C, S looks up the password verifier and gets H(PWC) based on the IDC. Then S calls SKC, calculates the hash value of H(PWC), RS, RC, IDC, SKC, MC, and then verifies whether this value is the same with the received hash value. If the same, S will authenticates C successfully, save the message MC, and the protocol can continue; Otherwise S will refuse the authentication request from C. Step 5: S calls the key SKC, calculate the hash value of RS, RC, IDC, SKC, MS, and then sends this value to C with MS. Step 6: C calls the key SKC to calculate the hash value of RS, RC, IDC, SKC, MS, and verifies whether this value is the same with the received hash value. If the same, C will authenticate S successfully, save the message MS, and give a notice to S, which means the protocol is accomplished; Otherwise C will refuse the authentication request from S.

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A. Wang, Z. Li, and X. Yang C → S (or S → C ) : Request a communication S → C : RS C → S : RC , IDC , M C , H ( H ( PWC ), RS , RC , IDC , SK C , M C ) S verifies C and saves M C S → C : M S , H ( RS , RC , IDC , SK C , M S ) C verifies S and saves M S

Fig. 2. Message-attached password authentication protocol

2.2 Security Analysis Denial of Service Attack. When an attacker carries out the denial of service attack on the server S, S can discover the user’s illegality in Step 4. S doesn’t need to do complex calculations before that and just needs to receive and send data three times. Meanwhile the step of verification just needs one look-up table and one calculation of hash. The RS can be reused when the authentication failed, so the overhead of random number generation can be completely ignored under the DoS attack. Therefore this protocol can resist DoS attack very well. Replay Attack. The preimage of the hash used to verify the identity contains the random number chosen by the verifier, so the preimage will never repeat as long as the random number doesn’t repeat. Namely, ever-used hash values will arise with a neglectable probability, which is equal to the probability of the collision in the hash algorithms. Therefore this protocol can resist the replay attack very well. Password Guess Attack. Password guess attack can be divided into two kinds: online and offline. The online password guess attack can be prevented by limiting the logins. The offline attack is still equivalent to the probability of the collision of hash algorithms. So the protocol can resist the password guessing attack because of the neglectable probability. Stealing Verifier Attack. In the new proposal, there are nothing else than the user’s identities and the hash values of the password in the verifier stored by S. The symmetric key is not stored so the attacker can’t generate the right hash value even if he gets the password verifier, not to mention obtaining any useful information. For the management of the symmetric key, we can usually adopt USB key and other technologies to ensure the storage security. Forge Server Attack. If an attacker wants to forge the server S, he must call the key SKC to calculate the hash value of RS, RC, IDC, SKC, MS or attempt to “replay” by means of previous hash value. Obviously the latter is not possible. Although the preimage of the hash operation is transported in a public unsafe channel, it’s impossible for the attacker to obtain the key SKC. As a result, the attacker can not forge the server to communicate with users.

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Forge Client Attack. Because the replay is infeasible, the attacker can but calculate the hash value of H(PWC), RS, RC, IDC, SKC, MC to fake C. But even he can steal the verifier and get H(PWC), he will not be able to generate the right hash value without the key. Consequently it is also impossible to fake the client. 2.3 Performance Evaluation In this paper we implement password authentication protocol based on hash function and message-attached technology, which decreases an authentication of message’s source and a communication at least. Due to the absent use of public key, it’s far more efficient than the Wang’s authentication protocol based on the public key. Because the server doesn’t have any large overhead before the server authenticate the client, the proposal in this paper is better to resist the DoS attack than Wang’s. In addition, the use of hash functions avoids the symmetric encryption algorithms, which improves the overall efficiency greatly [9]. 2.4 Contrast In this part, Hwang’s scheme proposed in 2002 [5], Peyravian’s scheme proposed in 2006 [7], Wang’s scheme proposed in 2008 [8] and the new proposal in this paper are compared from security and efficiency. The security details are given in Table 2, which “Yes” means the scheme can be against the attack and “No” means the resistance to the attack is in vain. Table 3 gives the efficiency contrast of the four schemes. As is shown in the table, the scheme proposed in this paper is the most effective, meeting the security needs, and is better than the other three. We will take security system of the Internet of things for example and discuss the specific implementation and application in the following. Table 2. Security Contrast

DoS Replay Password Guess Verifier Lost Forge S Forge C

Hwang No No Yes No Yes Yes

Peyravian Yes Yes Yes No Yes No

Wang No Yes Yes Yes Yes Yes

Our Scheme Yes Yes Yes Yes Yes Yes

Table 3. Efficiency Contrast

Without PKC Hash Function Number of (practical) Steps Number of Authentications

Hwang Yes Yes 4 4

Peyravian Yes Yes 4 4

Wang No Yes 4 4

Our Scheme Yes Yes 3 2

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3 System Architecture and Implementation Figure 3 shows universal system architecture of the Internet of things consisting of three parts - the devices which are the clients of our protocol, the central controller or monitor of the whole system which is the server of our protocol, and a network node which transfers messages between the server and some clients. Usually, the channel between remote server and local node is wired network. But in local network, the devices can interactive with the node through either wired or wireless channel. Device (Local Client) Function Module

Controller /Monitor (Remote Server)

Network Node (Local Node)

Function Interface

Computer

Central Controller

Cryptographic Controller

Internet Interface

Wired Channel

Network Interface

Wireless Channel

Wireless Interface

Fig. 3. Universal system architecture

We implement a system of street lamps with the fashion of the Internet of things. In a control center, a computer can transfer a command for switching on or off some lamp. The message is attached into our password authentication protocol which is carried out between the control center and the concrete lamps. According to a further test, we conclude that client and server can carry out our scheme exactly. That’s to say an adversary can’t finish any attacks on our system of street lamps.

4 Conclusions In this paper, we proposed a message-attached password authentication protocol and universal system architecture of the Internet of things. And this scheme can also solve some problems of similar products such as low efficiency, complex procedure et al. So it is of great significance and practical value to the development of the Internet of things in the future. Next, we will continue to study the various needs of the users of the Internet of things and design special schemes for different users. Moreover, as people are highly dependent on mobile phones [10], we can design more function-rich and practical products of the Internet of things with the control of mobile phones to provide with human more convenient services.

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Acknowledgments. Supported by the National Natural Science Foundation of China (NSFC Grant No.61072047), Innovation Scientists and Technicians Troop Construction Projects of Zhengzhou City (096SYJH21099), and the Open Project Program of Key Lab of Cryptologic Technology and Information Security (Shandong University), Ministry of Education, China. Moreover, I’m very grateful to the anonymous referees for their helpful suggestions.

References 1. International Telecommunication Union (ITU), ITU Internet Reports, The Internet of Things (2005) 2. European Research Projects on the Internet of Things (CERP-IoT) Strategic Research Agenda (SRA), Internet of Things – Strategic Research Roadmap (2009) 3. Menezes, A.J., Van Oorschot, P.C., Vanstone, S.A.: Handbook of Applied Cryptography. CRC Press, Boca Raton (1997) 4. Lamport, L.: Password Authentication with the Insecure Communication. Communications of the ACM 24, 770–772 (1981) 5. Hwang, J., Yeh, T.: Improvement on Peyravian-Zunic’s Password Authentication Schemes. IEICE Transactions on Communications E85-B(4), 823–825 (2002) 6. Chun, L., Hwang, T.: A Password Authentication Scheme with Secure Password Updating. Computers & Security 22(1), 68–72 (2003) 7. Peyravian, M., Jeffries, C.: Secure Remote User Access Over Insecure Networks. Computer Communications 29(5/6), 660–667 (2006) 8. Wang, B., Zhang, H., Wang, Z., Wang, Y.: A Secure Mutual Password Authentication Scheme with User Anonymity. Geomatics and Information Science of Wuhan University 33(10), 1073–1075 (2008) 9. Koc, C.K.: Cryptographic Engineering. Springer, Heidelberg (2008) 10. Google: Google Projects for Android (2010), http://code.google.com/intl/en/android

Research on Simulation and Optimization Method for Tooth Movement in Virtual Orthodontics Zhanli Li and Guang Yang College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an, China [email protected]

Abstract. Based on the analysis of the path planning on tooth movement in virtual orthodontics treatment system. The objective of path planning and the constraints of tooth moving were proposed and a mathematical model was established. The A* algorithm was selected to solve the path planning on tooth movement. The destination was defined that the smaller of the sum of all teeth’s move distance and rotation angle the better, meanwhile it is satisfy with the constraints of physiology, so we should consider many constraints in the system and then design a new heuristic function so as to get the better routes. At last, according to these information we use stage algorithm to iterate out each stage data on tooth movement. Based on the model and method, we made an experiment in the matlab, at last the results showed that this method is reliable and effective. Keywords: Tooth movement, A*algorithm, Open Table, Closed Table.

1 Introduction People's living conditions have been greatly improved with the progress of economy, and people gradually pay more attention to their appearance. In recent years, with the development of image processing technology, computer technology, and virtual reality technology, virtual surgery have become hot research topics[1]. The virtual orthodontics can help medico design the treatment and can output data, the tooth path planning is the important part in the virtual orthodontics, it can simulate the tooth movement in the dental treatment and medico can look at the whole processes and results in virtual treatment.

2 Description of the Path Planning for Tooth Movement The tooth path planning for tooth movement is to form a movement path from the initial position to the target position for each tooth. According to S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 270–275, 2011. © Springer-Verlag Berlin Heidelberg 2011

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characteristics of tooth movement. The moving of each tooth is restricted by the adjacent tooth. This is a very complex non-linear constrained optimization problem. 2.1 Objective of Path Planning Assume there are N teeth, and M stages for teeth movements from the initial position to the final position (M is determined by doctor according to the teeth maximum moving distance d0 and experience). There are two kinds of movement for each tooth in every stage, one is translation and the other is rotation. The first objective is to minimize the sum of all teeth’s translational distance. The calculation formulas are defined as follows:

fA =

⎛ m ⎜ ∑ d ij ∑ ⎜ i =1 ⎝ j =1

⎞ ⎟ ⎟ ⎠

n

(1)

dij = (xij − xij−1 ) +(yij − yij−1 ) + (zij − zij−1 ) 2

2

2

(2)

Where d ij represents the movement distance of tooth i in stage j. x ij , y ij , z ij is the coordinates of tooth i in phase j. The second objective is to minimize the sum of teeth’s rotation angle. The calculation formulas are defined as follows:

η ij = arccos fB =

n

∑

i =1

(L ， L ) G

G

ij − 1

ij

⎛ m ⎜ ∑ η ij ⎜ ⎝ j =1

⎞ ⎟ ⎟ ⎠

(3)

(4)

G Where η ij is the rotation angle of tooth i in stage j, L ij is the direction of tooth i in stage j.

2.2 Constraints of Tooth Movement In the process of tooth movement, the tooth may collide to each other. Assume f c is the times of collision, it can be expressed as follows: n −1

g 1 = f c = ∑ ci = 0

(5)

i =0

Where

ci represents tooth i collide to tooth i-1, if the collision occurred, its value is

1, otherwise is 0. In addition, according to medical experts’ experience, the translation

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or rotation angle should not be too high each time in the orthodontic process. The dij ηij in mathematical model must meet the following constraints: d0 and

η0

are the maximum move distance and maximum angle of rotation of each stage.

g 2 = d ij − d 0 ≤ 0

(6)

g 3 = η ij − η 0 ≤ 0 3 Principle of Algorithm

A* algorithm is a typical heuristic intelligent algorithm, because it contains predict function to calculate the path which will go, so it include the information of heuristic and it is better than other local search algorithm[3]. 3.1 The Improved Heuristic Function of A* Algorithm According to the heuristic algorithm of A*, we offer a new fitness function to meet this problem combine with move distance and angle of rotation, the function such as follows:

f =g+

h + sin δ cos γ

(7)

The above formula is the new fitness function based on the A* algorithm combined with the constraints of tooth movement. Where g represents the distance which teeth has moved and suppose the distance as diagonal mode. The angle γ ( 0 0 ≤ γ ≤ 90 0 )is composed by the vector which is formed by the current node and it’s parent’s node and the other vector is formed between the initial point 0 0 and the target point, such as figure 1, δ ( 0 ≤ δ ≤ 90 )is the vector which is formed between the current motion vector and it’s previous motion vector, such as figure 2. The δ reflects the characteristic of rotary movement of each teeth, which the formula ( h + sin δ ) just is the new heuristic function. cos γ Initial point

Parent point

Previous motion vector

γ

Current point

Fig. 1. The angle of γ

Target point

δ Current motion vector

Fig. 2. The angle of δ

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3.2 The Analysis and Determination of Collision Points of Tooth According to the features of A* algorithm, we need to first determine the collision points in the process of tooth movement. First we should consider whether the mobile vectors of adjacent tooth are in one plane. If in one plane, we can get the number d which is the diagonal length of bounding box and the d will be the diameter of the projection circle. Then we calculate the angle θ formed by the adjacent teeth’s motion vectors. If the θ is less than 45 degrees, then to calculate the distance D between the center points of projection circles, and assume D is the threshold. Generally speaking, the D is the distance of the center points of adjacent projection circles. If the actual distance D is less than D , then the collision occurred. If the routes are not in one plane, meanwhile to calculate the line which perpendicular the two motion vector, if the intersection points are between the two motion vectors, then to calculate the intersection points which just are the collision points, otherwise we assume that the collision does not occur temporarily. At this time the teeth p1 can move in the plane formed by points p1p2p1’, and the teeth p2 can move in the plane formed by points p1p2p2’, The area Q and Q ’ are the two teeth’s collision area, such as follows : ’

’

’

P1'

P2'

P2'

P1' Q Qÿ

P1

P2

Fig. 3. In one plane

P2'

Fig. 4. In Different plane

P1'

P2'

P1 ' Q

Q

Qÿ

Qÿ

p1

P2

P1

p2

Fig. 5. The collision area of teeth p1

P1

P2

Fig. 6. The collision area of teeth p2

In this system, the number d determines the size of the projection circle, and the projection circle area just is the collision area in the grid environment. Based on the collision area and A* algorithm this system search the final path, the flow chart of collision points as follows:

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Start

Split tooth model and build bounding box and get initial coordinates

Get the arch wire and the target coordinate

Calculate the length of diagonal of bounding box

Whether the adjacent routes are in one plane

yes

Whether the angle of motion vector less than 45 degree

Calculate the line perpendicular the two motion vector

no No collision and keep move

Calculate the diameter d and the distance of two center of circle and the sum of r1 and r2

D<=r1+r2

no

yes

no

no

No collision and keep move

No collision and keep move

Whether the intersection points are between motion vectors

yes

yes Collision occurred ,the circle area just is the collision area

End

Fig. 7. The flow chart of collision points

4 Implementation and Results The partial results of path planning are shown in matlab as follows:

Initial state

（1）

process

（2 ）

process

Make one circle based on the d and intersection points ,the circle is the collision area

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（3）

process

（4）

process

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（5 ）

process

5 Conclusions The path-planning on tooth movement is a complex, parallel, multi-target, nonlinear system. In this article, A* algorithm is used to solve the problem of path planning on tooth movement. The results showed that the model and the method is effective. It is a new attempt of theory and application in the virtual orthodontics system.

References 1. Sen, Y.: Orthodontic diagnosis and treatment plan. World Publishing Company, Singapore (2002) 2. Gao, H., Yan, Y., Qi, P., et al.: Three-dimensional digital dental cast analysis and diagnosis system. Computer Aided Design and Computer Graphics 3. Gao, Q.J., Yu, Y.S., Hu, D.: The feasibility of improving the path search and optimization based on A* algorithm. College of China Civil Aviation (August 2005) 4. Huizhong puzzle of Beijing Science and Technology Co. Ltd., Client programming about online game / Information Ministry software and integrated circuit promotion center 5. Wang, W.: Principles and Applications of Artificial Intelligence. Electronic Industry Press, Bingjing 6. Lihui, Z., Zhang, L., Hou, M.: The application of A* algorithm in game routing. Inner Mongolia Normal University (February 2009)

An Interval Fuzzy C-means Algorithm Based on Edge Gradient for Underwater Optical Image Segmentation Shilong Wang, Yuru Xu, and Lei Wan National Key Laboratory of Science and Technology on Autonomous Underwater Vehicle, Harbin Engineering University, Haerbin, China [email protected]

Abstract. In underwater environment, the underwater images would have low S/N and the detail is fuzzy due to scattering and absorption of a variety of suspended matter in water and the water itself and uneven lightness. If traditional methods are used to dispose underwater images directly, it is unlikely to obtain satisfactory results. As the mission of the vision system of autonomous underwater vehicle (AUV), it should deal with the information about the object in the complex environment rapidly and exactly for AUV to use the obtained result for the next task. So, aiming at realizing the clustering quickly on the basis of providing a high qualified segmentation of an underwater image, a novel interval fuzzy c-means algorithm based on gradient edge for underwater image segmentation is proposed. Experimental results indicate that the novel algorithm can get a better segmentation result and the processing time of each image is reduced and enhance efficiency and satisfy the request of highly real-time effectiveness of AUV. Keywords: underwater image, image segmentation, autonomous underwater vehicle (AUV), fuzzy C-means, real-time effectiveness.

1 Introduction Autonomous underwater vehicle (AUV) is an important carrier for exploring in ocean area and survey of sea-bed service. Underwater target detection, search and identify are the premise for AUV to execute certain task and has become the key to realize autonomy[1]. Therefore, underwater vision system is particularly important, and image information processing capacity is the essential premise to dynamic sensing environment, fast locating and tracking object at all. Underwater images are much sensitive to various noises and other interference[2]. The underwater image segmentation is one of the classic topics in computer vision research field, and is also one of the difficulties in underwater image processing. Thousands of current image segmentation algorithms are mostly for specific issues, no general algorithm can be applied to all images segmentation[3]. Compared with traditional hard segmentation algorithms, fuzzy segmentation has drawn increasing attention, because it can keep more original image information. Especially Fuzzy C S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 276–283, 2011. © Springer-Verlag Berlin Heidelberg 2011

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means (FCM) proposed by Dunn [4] and promoted by Bezdek[5], has been widely used in various areas of image segmentation[6-7]. In the actual operation of underwater robots, because of the vibration of imaging equipment and other electronic interference, result in the existence of measurement error of the pixel information, that is to say, the actual data obtained are inaccurate. In order to study this imprecision clustering, the most basic form of data - interval-valued data is set for analysis. Using weighted interval number, Ishibuchi et al. designed an interval neural networks[8]. Z Lv, et al. given similarity measure method of interval numbers with Gauss distribution[9]. In the areas of unsupervised classification, many scholars have conducted in-depth discussion. Fan Jiu-lun et al. proposed an interval-valued fuzzy cmeans (FCM) clustering algorithm to deal with unsupervised classification problems[10]. Francisco et al. presented a fuzzy clustering algorithm for symbol data[11]. Intuitionistic fuzzy sets clustering algorithm are discussed in detail by Z Xu, et al.[12]. Antonio Irpino, et al.[13] proposed a dynamic clustering algorithm based on interval-valued data Wasserstein distance. Marie-Helene, et al.[14] used credibility function to interval-valued data clustering. However, above various algorithms are based on simulated data, an interval segmentation algorithm based on underwater image is firstly put forward in this paper, and in order to improve the timeliness of calculation, combining with edge gradient for image segmentation. Comparative experiments show that the new algorithm can achieve better quality and higher timeliness and can be applied to the actual task of AUV. Although the new algorithm is based on underwater images, but the principles have also a high reference value for dealing with other types of image segmentation, the knowledge about the interval clustering segmentation will be fully tapped.

2 FCM Segmentation Algorithm Based on Interval Boundary 2.1 Theory Introduction

) = {x | x = [ x − , x + ] ⊂ R + } x ∈ I ( R ) , x is called as a interval − + number, which x and x is left value and right value of the interval, respectively. Suppose I ( R

+

And interval median and interval size are defined as follows:

x& =

x− + x+ 2

， xˆ = x

+

− x−

(1)

Let an image sized M × N , f ( x, y ) is gray value at the position of ( x, y ) , f ∈ {0,1,...L − 1} , L is the maximum gray. Taken ( x, y ) as center, its a × a neighborhood is as follows: (here, a = 5 )

278

S. Wang, Y. Xu, and L. Wan ⎡ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢⎣

f ( x − 2, y − 2 ) f ( x − 1, y − 2 ) f ( x , y − 2 ) f ( x − 2, y − 1) f ( x − 1, y − 1) f ( x , y − 1) f ( x − 2, y ) f ( x − 1, y ) f ( x, y) f ( x − 2, y + 1) f ( x − 1, y + 1) f ( x , y + 1) f ( x − 2, y + 2 ) f ( x − 1, y + 2 ) f ( x , y + 2 )

f ( x + 1, y − 2 ) f ( x + 2, y − 2 f ( x + 1, y − 1) f ( x + 2, y − 1) f ( x + 1, y ) f ( x + 2, y ) f ( x + 1, y + 1) f ( x + 1, y + 2 )

⎤ ⎥ ⎥ ⎥ ⎥ f ( x + 2, y + 1) ⎥ f ( x + 2 , y + 2 ) ⎥⎦

(2)

In the a × a region, the mean and standard deviation are denoted by Ex , y and σ x , y , respectively, and then given the following definitions: Definition 1: Define interval characteristics of any point in an image as follows: interval median being x& = Ex , y , interval size being xˆ =2 σ x , y , and the pixel value at this point being [ f ( x, y ) − σ x , y ,

f ( x, y ) + σ x , y ] .

Definition 2: Let any two points pixels in the image are represented as:

[ f ( x1 , y1 ) − σ x1 , y1 , f ( x1 , y1 ) + σ x1 , y1 ] , [ f ( x2 , y2 ) − σ x2 , y2 , f ( x2 , y2 ) + σ x2 , y2 ] , f ( x1 , y1 ) − σ x1 , y1 = f ( x2 , y2 ) − σ x2 , y2 , two pixels are equal.

only when

Definition 3: By interval median and interval size, the distance between two pixels is defined as follows:

D = ( x&1 − x&2 ) 2 + ( xˆ1 − xˆ2 ) 2 = ( Ex1 , y1 − Ex2 , y2 ) 2 + (σ x1 , y1 − σ x2 , y2 ) 2 (3) Definition 4: Let the cluster number of FCM clustering be c and a total number of pixels of the image is n= M × N , if satisfy the following conditions: c

n

i =1

k =1

(1)∑ μik = 1, k = 1, 2,L , n ; (2)∑ μik > 0, i = 1, 2,L , c

U = ( μik )c×n is called fuzzy membership matrix, U is called as (c, n) − fuzzy partition, U f (c, n) is denoted as the whole set of (c, n) − fuzzy Then

partition. Definition 5: Define objective function of interval FCM clustering is: c

n

J (U ,V ) = ∑∑ ( μik ) m vi − xk

2

i =1 k =1

Where,

V = {v1 , v2 , L , vc } ⊂ R is the set of cluster centers, μik expresses the

membership of

+

k -pixel interval value xk belonging to i -class center vi .

2.2 Introduction of Gradient Operator Edge is important feature to image understanding and pattern recognition and can keep feature information while effectively reducing the amount of data processing.

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279

The first derivative can be used to detect whether a point is edge to highlight the details of the image. By gradient sharpening [15] , the gradient of image at position

( x, y ) can be obtained:

∇f = [Gx G y ]−T = [

∂f ∂f −T ] ∂x ∂y

(4)

Definition 6: Define image gradient as follows:

∇f = ( Ei, j − Ei +1, j ) 2 + (σ i, j − σ i +1, j )2 + ( Ei , j − Ei, j +1 )2 + (σ i, j − σ i , j +1 )2

(5)

Where, (i + 1, j ) and (i, j + 1) are respectively right and below point of (i , j ) in four neighborhood. And use specified threshold to determine the validity of a value, that is to say, if

∇f is greater than the threshold, the gradient will take the place of

the gray value, or else, keep the gray value of the point unchanged. 2.3 Steps of the Algorithm

Step 1: by definition 1, the original pixel is converted to interval value; Step 2: according to definition 6, the gradient is calculated; Step 3: randomly given original clustering center:

，

vi = {Ei , σ i } here, i = 1, 2,L c

；

V = {v1(0) , v2 (0) ,L , vc (0) }

，

Step 4: By definition 3 to calculate the distance between every pixel interval value and the cluster centers, and the membership μik of k - pixel interval value

xk belonging to i -clustering center vi can be expressed as follows:

，if d

For any

i, k

For any

i, j , k

ik

，if d

>0

ik

，

=0

dik m2−1 then μik = 1/ ∑ ( ) j =1 d jk c

，then μ

Step 5: update cluster center matrix:

ij

⎧1, j = k =⎨ ⎩0, j ≠ k

n

n

k =1

k =1

(6)

(7)

vi = ∑ μik m xk / ∑ μik m , i = 1, 2,L , c (8)

Step 6: by definition 5 to calculate the objective function J, and compare with the previous calculated value of J. if the difference is less than the threshold ε, then the loop ends, continue to step 6, otherwise go to step 4 to continue the loop. Step 7: post-processing: by the obtained cluster centers and fuzzy membership matrix, execute the fuzzy clustering based on the interval value of every pixel identified in step 1 and get the segmentation results.

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3 Experimental Results and Analysis To validate the feasibility and effectiveness of edge gradient based FCM algorithm, compared it with the traditional FCM and the algorithm proposed in literature [16] using for underwater image segmentation. 3.1 Comparison of Accuracy of Segmentation Results

In a computer with XP operating system, the main frequency is 2.60GHz, the memory is 2G. For four types of representative underwater targets (image size is 576 × 768), using the three algorithms for the segmentation experiments, iteration stop threshold ε is set 1e-9, let clustering number be 2, and a taken 7. The segmentation results were shown in Figs.1-4. (a-d is respectively to the original image, the traditional algorithm, algorithm in literature [16], and new algorithm).

Fig. 1. The three-prism segmentation results

Fig. 2. The four-prism segmentation results

Fig. 3. The ellipsoid segmentation results

Fig. 4. The multi-objects segmentation results

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Figs. 1-2 show that the segmentation results by three different segmentation algorithms can reflect clustering effects to different degree, and to deal with images captured with low light environment all is indicative of the excellence. However, it can be seen from the segmentation results of three-prism that the traditional FCM method failed to separate the complete region of the target, and to the algorithm proposed in literature [16], the results is better, but the upper part noise of the target is still present, and the new algorithm not only can obtain a clear edge, but also to the four-prism segmentation, can clearly distinguish details such as the cable in the lower right of the image. To the targets with serious uneven light and heavy noise, it can be seen from figs. 3-4 that the object in image can not be segmented from the background by traditional FCM clustering algorithm, and using of the algorithm in literature [16], only few object information can be segmented out when processing ellipsoid image, but for multi-objects with more serious noise, it is very difficult to obtain the whole outline, and the new algorithm can clearly obtain most of edge information of the target, what’s more, we can see the cable above the ellipsoid from the segmentation result of multi-objects. In summary, the segmentation results from figs. 1-4 sufficiently show that using the new algorithm can all obtain good segmentation results to process the images both with insufficient light and with heavy noise and serious uneven illumination. With the good accuracy, high robustness and broad applicability, the new algorithm has irreplaceable advantages on segmenting images captured in complex environment with noise difficult to be eliminated. 3.2 Analysis and Comparison on Timeliness

To one of four types of targets, take 50 pieces of images captured in pool as the samples, and to three algorithms, the number of cluster is set 2 and the let threshold be ε = 1.0 ×10−9 , the average time consumption of single image is in table 1. Table 1. Single image time consumption with different algorithms

target

three-prism

four-prism

ellipsoid

multi-objects

FCM

1.094

1.109

1.513

1.969

literature [16]

0.844

0.765

1.032

0.906

new algorihm

0.11

0.109

0.141

0.201

It can be seen from table 1 that to four types of underwater image segmentation, the time consumption using the new algorithm can save about 10 times than traditional FCM algorithm, and the timeliness is improved 4-8 times than the algorithm in literature [16], which fully show that the new algorithm can excellently meet the need of timeliness for AUV to execute practical underwater task.

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4 Conclusions Through the analysis and research on FCM algorithm, considering the inevitable errors in the imaging process, for four types of images taken in pool, an interval fuzzy c-means algorithm based on edge gradient is proposed, and some definitions and parameters are given, and thus the membership matrix and clustering center matrix are modified. Experimental results show that compared with the traditional FCM and the algorithm in literature [16], using the new algorithm, segmentation quality are obviously good, especially to the image with serious noise and uneven light, the segmentation result is with high robustness. Moreover, the computing speed of the new algorithm is quicker than the other two algorithms. Above all, by the new algorithm, not only good quality segmentation is obtained, but also the timeliness is improved, which meet the certain requirement for AUV to complete the special mission[17], and provide a strong guarantee to feature extraction and target tracking.

References 1. Yuan, X.H., Qiu, C.C., et al.: Vision System Research for Autonomous Underwater Vehicle. In: Proceedings of the IEEE International Conference on Intelligent Processing System, vol. 2, pp. 1465–1469 (1997) 2. Wang, S.-L., Wan, L., Tang, X.-D.: A modified fast fuzzy C-means algorithm based on the spatial information for underwater image segmentation. In: ICCDA 2010, vol. 1, pp. 1524–1528 (2010) 3. Zhang, M.-j.: Image Segmention. Science Press, Peking (2001) 4. Dunn, J.C.: A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters. J. Cybern. 3, 32–57 (1974) 5. Bezdek, J.C.: Pattern recognition with fuzzy objective function algorithms. Plenum Press, New York (1981) 6. Szilagyi, L., Benyo, Z., Szilagy, S.M., et al.: MR Brain Image Segmentation Using an Enhanced Fuzzy C Means Algorithm. In: Proc. of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, vol. 1, pp. 724–726 (2003) 7. Rezaee, M.R., Zwet, P., Lelieveldt, B., et al.: A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering. IEEE Trans. on Image Processing 9(7), 1238–1248 (2000) 8. Ishibuchi, H., Tanaka, H.: An Architecture of Networks with Interval Weights and Its Applications to Fuzzy Regression Analysis. Fuzzy Sets and Systems 57(1), 27–39 (1993) 9. Lv, Z., Chen, C., Li, W.: A new method for measuring similarity between intuitionistic fuzzy sets based on normal distribution functions. In: Fourth International Conference on Fuzzy Systems and Knowledge Discovery, Haikou, China, vol. (2), pp. 108–113 (2007) 10. Fan, J.-l., Pei, j.-h., Xie, W.-x.: Interval fuzzy c-means clustering algorithm. In: Fuzzy Sets Theory and Applications- The Ninth Annual Meeting of the Committee with the Fuzzy System and Fuzzy Mathematics in China, pp. 127–213 (1998) 11. de Francisco, A.T., de Carvalho: Fuzzy c-means clustering methods for symbolic interval data. Pattern Recognitions Letters 28(4), 423–437 (2007) 12. Xu, Z., Chen, J., Wu, J.: Clustering algorithm for intuitionistic fuzzy sets. Information Sciences 178(19), 3775–3790 (2008)

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13. Irpino, A., Verde, R.: Dynamic clustering of interval data using a Wasserstein-based distance. Pattern Recognition Letters 29(11), 1648–1658 (2008) 14. Masson, M.-H., Denoeux, T.: Clustering interval-valued proximity data using belief functions. Pattern Recognition Letters 25(2), 163–171 (2004) 15. Gonzalez, R.C., Woods, R.E.: Digital image processing, 2nd edn., pp. 97–99. Electronic Industry Press, Beijing (2002) 16. Wang, S.-l., Wang, L., Tang, X.-d.: An improved fuzzy C-means algorithm based on grayscale histogram for underwater image segmentation. In: CCC 2010, vol. 1, pp. 2778–2783 (2010) 17. Balasuriya, A., Ura, T.: Vision-based underwater cable detection and following using AUVS. In: Proceedings of the Oceans 2002 Conference and Exhibition, pp. 1582–1587. IEEE, Piscataway (2002)

A Generic Construction for Proxy Cryptography Guoyan Zhang School of Computer Science and Technology, Shandong University [email protected]

Abstract. Proxy cryptosystem allows the original decryptor to delegate his decryption capability to the proxy decryptor. Due to the extensive application of proxy cryptography, some schemes have been presented, but there are not a general model for proxy cryptography. In this paper, we give the first general model and security model for proxy-protected anonymous proxy cryptography in which only the proxy decryptor can decrypt the ciphertexts for the original decryptor. Finally we give one concrete scheme according to the model as example.

，

Keywords: Proxy Cryptography Proxy-Protected, DBDH.

1 Introduction The need of delegation of cryptographic operation leads to the introduction of proxy cryptography. M.Mambo, K.Usuda and E.Okamoto first invented the notion of the proxy cryptosystem[1] in 1997. In their scheme, the original decryptor can delegate his decryption capability to the proxy decryptor, but only after the ciphertext being transmitted into another ciphertext, the proxy decryptor can recover the plaintext. In comparison to proxy signature, only few research efforts have been put on delegation of decryption progresses. In 1998, M. Blaze, G. Bleumer, M. Strauss[2] proposed the notion of atomic proxy cryptography. In this method, the original decryptor and delegated decryptor together publish a transformation key by which a semi-trusted intermediary transforms ciphertext encrypted for the original decryptor directly into ciphertext that can be decrypted by the delegated decryptor. In order to relax the burden of transformation, series ciphertext transformation-free proxy cryptosystems, in which the proxy (or proxies) can do the decryption operation without ciphertexts transformation[3,4,5], have also been studied. Recent related works on Proxy Reencryption[6,7,8] needed the proxy to transform the ciphertext. Because we can't always trust a person, the drawback of delegation is important in proxy cryptography, especially in proxy decryption. There is not a more efficient method to solve the problem. In this paper, we introduce a model which is implicit delegation, it is to say, the encryptor needn't checks the validity of delegation, because, if the decryption power of a proxy decryptor is revoked, he can not get the plaintext. Further in our model, the channel between the original decryptor and the proxy decryptor needn't be secure and authenticated. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 284–289, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Our Generic Model and Attack Model 2.1

The Generic Model

Definition 1. A proxy-protected anonymous proxy decryption (PPAPD) scheme includes the following five algorithms: −Setup: Given the security parameter 1k , the delegater runs the key generation

algorithm of id-based encryption scheme IBEGen to get the master secret key SK O as

his secret key and the master public parameter PKO as his public key. −Delegation Algorithm : The delegation algorithm includes two phases: user secret key generation and the partial proxy private key derivation. Secret Key Generation: Taken the public parameter PKO as input, the delegatee

randomly picks a secret key SK P and computes the corresponding public key PK P . Following, he chooses an existential unforgeable signature scheme S = (Gensign , Sign,Verify ) , and computes the signature δ for the public

key PK P . Finally, he sends (δ , PK P ) with the verifying public key to the delegater. Partial Proxy Private Key Derivation : Assuming the proxy time is t . Given the

tuple (δ , PK P ) , the public key PKO , the secret key SKO and the proxy time t , the delegater first checks the validity of the public key PK P and of the signature δ , if either invalid, he aborts, otherwise, he runs the private key extraction algorithm of idbased encryption scheme IBEExtract of IBE , and gets the partial proxy private key SK pp . Then he sends SK pp to the delegatee. −Encrypt : Taken the public keys PKO and PK P , the proxy time t and the message M , the probabilistic encryption algorithm Enc returns a ciphertext C on message M . −Decrypt : On receiving the ciphertext C , the delegate gets the plaintext m using the secret key SK P and the partial proxy private key SK pp , or outputs the special symbol ⊥ indicating invalid. 2.2 The Attack Model

In our notion, we consider all potential actions of the adversary. There are two types of adversaries: the Type adversary presents the outside adversaries who aren't delegated, the Type Ⅱ adversary presents the delegatee.

Ⅰ

Definition 2. A proxy-protected anonymous proxy decryption ( PPAPD) scheme is secure against adaptive chosen ciphertext attack (IND-CCA) if no probabilistic polynomial time bound adversary has non-negligible advantage in either Game 1 or Game 2.

286

G. Zhang

Game1

Ⅰ

This game for Type adversary. Taken a security parameter1k , the challenger runs the Setup algorithm to get the delegatee's secret key SK O and the delegatee's public key PKO , and he gives PKO to the adversary, keeping SK O secret. The adversary can request two oracles: Partial-Proxy-Private-Key-Oracle and Decryption Oracle. − Partial − Proxy − Private − Key − Oracle : On receiving the oracle < PK P , SK P , ti , δ = Sign( PK P ) > : The challenger checks the validity of the public key and the signature δ , if either invalid, he aborts. Otherwise, he searches the PartialProxyPrivateKeyList for a tuple < PK P , SK PP , ti > , if exists, he sends SK PP to the adversary. Otherwise, the challenger runs the Partial-Proxy-Private-Key-Derivation algorithm to get SK PP , and adds the tuple < PK P , SK PP , ti > to the PartialProxyPrivateKeyList. He sends SK PP to the adversary. − Decryption − oracles: On receiving the oracle < PK P , SK P , Ci , ti > : The challenger checks the validity of the public key, if invalid, he aborts. Otherwise, he searches the PartialProxyPrivateKeyList for a tuple < PK P , SK PP , ti > , if exists, he decrypts the ciphertext Ci using SK PP and SK P . And he sends the plaintext M to the adversary. Otherwise, the challenger runs the Partial-Proxy-Private-Key-Derivation algorithm to get SK PP , and adds the tuple < PK P , SK PP , ti > to the PartialProxy PrivateKeyList. He decrypts the ciphertext Ci using SK PP and SK P to get M and sends the plaintext M to the adversary. −Challenge: The adversary generates a request challenger

< PK

P*

, SK

, t* , M 0 , M1 > , ti* is the proxy time, and M 0 , M1 are equal length P* i

plaintext. If the public key PK and sets C* = Enc( M b , ti* , PK

P*

P*

is valid, the challenger picks a random bit b ∈ {0,1}

, PKO ) . It sends C* to the adversary.

The adversary can make polynomial queries, and the challenger responds as the second steps. At the end of the game, the adversary outputs b′ ∈ {0,1} and wins the game if b = b′ , furthermore, there are also two restrictions that the adversary has never request the partial proxy private key oracle on a tuple < PK decryption oracle on a tuple < C * , ti* , PK Game 2

P*

, SK

p*

P*

, SK

, t * > and the P* i

>.

Ⅱ

This game for Type adversary. Taken a security parameter1k , the challenger runs the Setup algorithm to get the delegatee's secret key SKO and the delegatee's public key PKO , and he gives ( PK O , SK O ) to the adversary.

A Generic Construction for Proxy Cryptography

287

The adversary can request one oracle: decryption oracle. − Decryption − oracles : On receiving the oracle < PK P , SK P , Ci , ti > : The challenger checks the validity of the public key, if invalid, he aborts. Otherwise, he searches the PartialProxyPrivateKeyList for a tuple < PK P , SK PP , ti > ,

if exists, he decrypts the ciphertext Ci using SK PP and SK P . And he sends the plaintext M to the adversary. Otherwise, the challenger runs the Partial-Proxy-Private-Key-Derivation algorithm to get SK PP , and adds the tuple < PK P , SK PP , ti > to the PartialProxyPrivateKeyList. He decrypts the ciphertext Ci using SK PP and SK P to get M and sends the plaintext M to the adversary. The adversary generates a request challenger −Challenge : < PK

P*

, SK

, t* , M 0 , M1 >, ti* is the proxy time, and M 0 , M1 are equal length P* i

plaintext. If the public key PK and sets C* = Enc( M b , ti* , PK

P*

P*

is valid, the challenger picks a random bit b ∈ {0,1}

, PKO ) . It sends C* to the adversary.

The adversary can make polynomial queries, and the challenger responds as the second step. At the end of the game, the adversary outputs b′ ∈ {0,1} and wins the game if b = b′ , furthermore, there are also one restriction that the adversary has never queried the decryption oracle on a tuple < C * , ti* , PK

P*

>

3 The Proxy-Protected Proxy Decryptionur Generic Model 3.1 The Construction

Let (G , GT ) be bilinear map groups of order p > 2k and let e : G × G → GT denote a bilinear map. H1 :{0,1}* → {0,1}n and H 2 :{0,1}* → {0,1}n are two collisionresistant hash functions. Setup(1k , n) : The original decryptor chooses g as a generator for G . Set g1 = gα for

random

α ∈ Z *p

,

and

pick

a

group

element

g2 ∈ G

and

vectors (u ′, u1 , …, un ), (v′, v1 , …, vn ) ∈ G n +1 . These vectors define the following hash functions: n

i

n

w

Fu (W1 ) = u ′ ∏ (u jj ), and Fv (W2 ) = v′ ∏ (v j j ), i =1

i =1

288

G. Zhang

where W1 = i1i2 …in and W2 = w1w2 … wn . The original decryptor's public key is PKO = (G, GT , e, g , g1, g 2 , u ′, u1, u2 , …, un , v ′, v1 , v2 , …, vn ), and the original decryptor's secret key is SK O = α . Delegation algorithm : Secret key generation : The proxy decryptor P randomly picks x ∈ Z *p , and

computes the public key PK P = ( X , Y ) = ( g1x , g 2x ) . He runs Gensign of a secure signature scheme S = (Gensign , Sign,Verify ) to get the signature key pair ( sk , vk ) , and he runs Sign to get the signature δ on ( X , Y ) . Finally he sends (( X , Y ), δ , vk ) to the original decryptor O . Partial proxy private key derivation : Given (( X , Y ), δ , vk ) , the original decryptor

O verifies : e( X , g 2 ) = e(Y , g1 ), Very (δ , X , Y , vk ) = 1. If either fails, O outputs

invalid. Otherwise, assuming the proxy time is t , he chooses random number r ∈ Z *p r r and computes W1 = H1 ( X , Y , t ), SK PP = (d1 , d 2 ) = ( gα 2 ·Fu (W1 ) , g ). O

sends

SK PP = (d1, d 2 ) to proxy decryptor P . Encrypt : Assuming the proxy time is t . In order to encrypt message m ∈ GT ,

parse PK P = ( X , Y ) , and check the validity of the public key by the equation e( X , g 2 ) = e(Y , g1 ) . If so, choose s ∈ Z *p and compute the ciphertext as follows: C = (C0 , C1, C2 , C3 ) = (m ⋅ e( X , Y ) − s , g s , Fu (W1 ) s , Fv (W2 ) s ), where W2 = H 2 (C0 , C1 , C2 , PK P ) . Decrypt : The proxy decryptor P first computes W2 = H 2 (C0 , C1 , C2 , PK P ) and checks the validity of the ciphertext by the following equation: e(C1, Fu (W1 ) Fv (W2 )) = e( g , C2C3 ). If the equation doesn't hold, he outputs invalid. 2

Otherwise, he decrypts the ciphertext: m = C0 (e( d1, C1 ) / e(C2 , d 2 )) x . 3.2 Security Analysis Theorem 1. The proxy-protected anonymous proxy decryption scheme is IND-CCA secure against Type adversary assuming the Decision Bilinear Diffi-Hellman problem is hard.

Ⅰ

Theorem 2. The proxy-protected anonymous proxy decryption scheme is IND-CCA secure against Type Ⅱ adversary assuming the Decision Bilinear Diffi-Hellman problem is hard.

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4 Conclusion In this paper, we give a generic proxy-protected anonymous proxy cryptography followed with the security model. Our model not only captures all the properties introduced by Lee et al., but also we also give a corresponding security model which makes the schemes have precise security guarantee. Especially, in our model, the encrypter needn't verify the validity of the public key of delegated decryptor, Furthermore, the original decryptor can also run cryptographic operations as the delegated decryptor does, but he cannot impersonation any delegated decryptor. Thus this model not only protects the privacy of the delegated decryptor, but also the one of the original decryptor. This is the first generic model satisfying the above properties in literature. Finally, we give a concrete proxy decryption as examples. Acknowledgement. This work is Supported by the National Natural Science Foundation of China (No.60873232), Open Research Fund from Key Laboratory of Computer Network and Information Integration In Southeast University, Ministry of Education, China (No. K93-9-2010-10), Shandong Natural Science Foundation (No.Y2008A22) and Shandong Postdoctoral Special Fund for Innovative Research (No.200902022).

References 1. Mambo, M., Okamoto, E.: Proxy cryptosystem: Delegation of the power to decrypt ciphertexts. IEICE Trans., Fundamentals E80-A, 54–63 (1997) 2. Blaze, M., Bleumer, G., Strauss, M.: Divertible protocol and atomic proxy cryptography. In: EUROCRYPT 1998. LNCS, vol. 1403, pp. 127–144. Springer, Heidelberg (1998) 3. Mu, Y., Varadharajan, V., Nguyen, K.Q.: Delegation decryption. In: Walker, M. (ed.) Cryptography and Coding 1999. LNCS, vol. 1746, pp. 258–269. Springer, Heidelberg (1999) 4. Sarkar, P.: HEAD: Hybrid Encryption with Delegated Decryption Capability. In: Canteaut, A., Viswanathan, K. (eds.) INDOCRYPT 2004. LNCS, vol. 3348, pp. 230–244. Springer, Heidelberg (2004) 5. Wang, L., Cao, Z., Okamoto, E., Miao, Y., Okamoto, T.: Transformation-free proxy cryptosystems and their applications to electronic commerce. In: Proceeding of International Conference on Information Security (InfoSecu 2004), pp. 92–98. ACM Press, New York (2004) 6. Canetti, R., Hohenberger, S.: Chosen-ciphertext secure proxy re-encryption. In: ACM Conference on Computer and Communications Security, pp. 185–194 (2007) 7. Libert, B., Vergnaud, D.: Tracing Malicious Proxies in Proxy Re-Encryption. In: Galbraith, S.D., Paterson, K.G. (eds.) Pairing 2008. LNCS, vol. 5209, pp. 332–353. Springer, Heidelberg (2008) 8. Weng, J., Deng, R.H., Chu, C., Ding, X., Lai, J.: Conditional Proxy Re-Encryption Secure against Chosen-Ciphertext Attack. In: Proc. of the 4th International Symposium on ACM Symposium on Information, Computer and Communications Security (ASIACCS 2009), pp. 322–332 (2009)

VCAN-Controller Area Network Based Human Vital Sign Data Transmission Protocol Atiya Azmi1,2, Nadia Ishaque2, Ammar Abbas2, and Safeeullah Soomro1 1 Department of Computer Science and Engineering, Yanbu University College, Yanbu Al-Sinaiyah, Kingdom of Saudi Arabia {atiya.azmi,safeeullah.soomro}@yuc.edu.sa 2 Sir Syed University of Engineering and Technology, Pakistan {ammarabbas,786.nadya}@gmail.com

Abstract. The vital signs diagnostics data is considered high risk critical data that requires time constrained message transmission. The continuous real time monitoring of patient allows prompt detection of adverse events and ensures better response to emergency medical situations. This research work proposes a solution for acquisition of human vitals and transferring this data to remote monitoring station in real time, over Controller Area Network Protocol (CAN).CAN is already been used as an industrial standardized field bus used in a wide range of embedded system applications where real time data acquisition is required. Data aggregation and few amendments in CAN are proposed for better utilization of available bandwidth in context to patient’s vital sign monitoring. The results show that proposed solution provides efficient bandwidth utilization with sufficient number of monitored patients. Even with high frame rate per patient per second, adequate number of patients can be accommodated. Keywords: Controller Area Network, Human Vital signs, Data Aggregation, Real Time Monitoring.

1 Introduction Real time patient monitoring is the most important part of post operative or emergency situation medical aid provision. Vital sign monitoring data forms messages whose untimely delivery can lead to life threatening damage or serious injury. The Vital signs data considered for monitoring consist of Heart Rate (HR), Systolic blood pressure (SBP), Diastolic blood Pressure (DBP), Electrocardiogram (EKG), Oxygen Saturation (SP02) and Body Temperature (Temp) [1]. Different mediums and standards have been proposed by researchers to accomplish this task [2] [3] [4]. This research work proposes a simplified solution that sense, store, process and transmit human vitals using Controller Area Network Protocol with some proposed amendments in the frame format. The CAN protocol is selected for its cost effectiveness, robustness, minimum error rate and utilization in time critical applications [5] [6]. The solution gives provision for each patient’s context data entry at the bedside, to medical staff, in order to set ranges for the vital signs alarm values. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 290–296, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 System Descriptions The proposed system is divided into six major units. 1 illustrates the proposed system using Controller Area Network (CAN) protocol for transferring patient vital sign data. Following is a brief description of each unit.

Fig. 1. Block diagram of proposed system

1.

2.

3.

4.

Sensing and Digitizing Unit (SDU). The Sensing and Digitizing unit (SDU) provides interface to the sensors attached to the patients for monitoring current vital signs. It receives data from different sensors and digitizes the input if needed. Analog to Digital conversion is required for most of the sensors monitoring the vitals. SDU receives input from Context Data Input (CDU) unit to change the sampling rate as per requirement of doctor or medical staff, for an individual patient. Bed Side Display Unit (BDU). Patient bed side display (BDU) unit is available at patient’s bed sides. It displays currents vitals of the patient for visiting doctors and support staff. Context Data Input Unit (CDU). Every patient is treated differently according to his specific disease and condition. Sometimes some vital sign values are acceptable for a particular patient but can be alarming for the others with immediate medical attention required. Patient Context Data Input Unit (CDU) provides doctors and supporting staff to enter range against patient’s each vital sign that can be alarming for him, according to his current medical condition. CDU provides the input parameter to Processing and Aggregation Unit (PAU). The given parameters are utilized by SDU, for setting alarm if the current vital sign data is not within specified range. Processing and Aggregation Unit (PAU). The Processing and Aggregation Unit (PAU) is the most important unit of proposed System. Major processing tasks are performed in this section. PAU gets the sensors data from SDU and buffers it for processing. The buffered data is checked against the parameters provided by CDU. If the current data value for any vital sign is not in the normal range, PAU triggers an alarm at patient’s BDU and sets Ro bit for CAN Frame. Another major task of PAU is that it aggregates the data of the six sensors into one data set (56 bits) and provides it to CAN interface as a single value along with Ro bit value. This reduces the control bits overhead that arise when data from individual

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sensor is sent separately. This Ro bit is utilized by CAN receiver to set alarm at remote monitoring site. Controller Area Network Interface Unit (CANI.). Controller Area Network Interface Unit (CANI) gets the aggregated data from PAU as a single value of 56 bits. CANI adds control bits according to CAN protocol and also sets Ro bit, as given by PAU. Finally CAN PDU is sent on the CAN bus to remote monitoring station.

3 Benefits of Using CAN Transferring patient vital sign monitoring data imposes different network protocol requirements then transferring large blocks of data on a communication networks. The data should be sent and received in real time with, minimum error rate and reliability. Following are the facts that significantly support the possible use of CAN protocol for this purpose • • • • • • • •

CAN has been utilized and proven efficient in time critical application that requires guaranteed timely delivery of data for processing and decision making[5]. Error rate of CAN protocol network is minimum [5]. CAN provide deterministic and secure data exchange [6]. Fault confinement is another important aspect of CAN that automatically drops the faulty node from the network and prevents any node from bringing down the network [7]. Ethernet and other already used protocols have much higher overhead in terms of control bits and management messages then CAN protocol. CAN support wired medium for transmission of signal that reduces the possibility of interference. Wired medium is generally recommended for use within hospital limits where numerous interfering equipments are present. CAN is an industrial standardized protocol (ISO 11898), with maximum speed of 1Mb/sec and can be implemented in real time systems [5]. Plug and play support in CAN provides opportunity to add new nodes (patients) on run time [5], [7].

4 CAN Protocol Controller Area Network (CAN) is a serial communication protocol introduced by BOSCH [7] in 1980.Varient of CAN are utilized as low level messaging protocol by many vendors and researchers[8][9][10] for different time critical application. This research work is based on standard CAN 2.0A protocol.

Fig. 2. CAN2.0A Frame Format

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Standard CAN 2.0A: CAN 2.0A uses very simple and minimum control data bits frame. Fig 1 shows the frame format of CAN2.0A [7]. Start of Frame (SOF): Used for marking start of message and also helps synchronization. Identifier: An 11 bit identifier that identifies the CAN module. Lower the binary value of identifier higher is the priority for bus access. Remote transmission request (RTR): RTR is used to request data from a particular node. Identifier extension IDE: IDE used to define that extended or standard CAN identifier is used. Reserved bit (Ro): A reserved bit that can be utilized for any new functionality. Data Length Code (DLC): DLC defines how many bytes of data are contained in CAN Frame. DATA: CAN2.0A can accommodate up till 8 bytes of data per frame. Cyclic Redundancy Check (CRC): CRC of 16 bits used for error detection. ACK: 2 bits ACK utilized for indicating error free message. End of Frame (EOF): EOF comprising of 7 bits that marks end of CAN frame. Inter frame space (IFS): IFS is required before next CAN frame arrives.

5

Vital Sign Data

Main Vital signs considered by all physicians are heart rate, blood oxidation level, temperature, and blood pressure. Apart from these standard signs, EKG is an additional diagnostic medical data that is considered important in most of the cases [10].Vital signs indicate the body’s functionality level and help in assessing any abnormalities from a person’s normal and healthy state. Normal ranges of measurements of these vital signs change with the person’s age, sex and medical condition. The nursing staff is responsible to make this patient’s context data entry to bed side monitoring device and set the ranges of alarm values for each vital sign. Table 1. Human Vital Sign Data Ranges

Vital Sign

Data Range

Max. Values

No of Bits

Temp

96-108 F

13

8

Heart Rate

30-200 (bpm)

171

8

SPO2

0-100%

101

8

SBP

40-250

211

8

DBP

15-200

186

8

EKG

30-300

270

16

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In case of any abnormalities, necessary treatment or medical procedure can be adopted for a particular patient. The Table 1 illustrates the ranges of vital signs that are usually supported by most vendors and corresponding number of bits that are utilized to represent that range

6

Proposed Changes in Controller Area Network Protocol: The VCAN

Following are the minor changes and enhancements that are recommended in CAN protocol to make its efficient use for human vital sign data transmission in real time to remote patient monitoring station. We call this enhanced protocol the VCAN.

7

Results and Discussions

This section presents quantitative analysis of maximum number of patients, bandwidth utilization with increasing number of patients and bandwidth requirement per patient. The results are based on the VCAN protocol described in section 5.

Bandwidth Requirement per Patient 46

50

kbps

40 30

24

28

20 10 0 256

300

500

Frame Rate per Patient

Fig. 3. Bandwidth Requirements per Patient in kbps

Fig 3 illustrates bandwidth requirement per patient. On X-axis frame rate per patient and on Y-axis bandwidth in kilo bits per second (kbps) is represented. Different possible rates of 256 frames per second, 300 frames per second and 500 frames per second are presented. The reason for selecting such rates is that ECG/EKG is sampled by different devices at different rates [10].The result shows bandwidth requirement for a single user will be close to 24kbps, 28 kbps and 40kbps with 256, 300 and 500 frames respectively sent for single user per second. Figure 4 and 5 shows bandwidth utilization with increasing number of patients. Figure 6 depicts number of possible patients that can be monitored by our system with proposed amendments in CAN2.0A protocol. In ideal condition with availability of

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1000 900 800 700 600 500 400 300 200 100 0

24 Kbps 28 Kbps

c

36

31

26

21

16

6

11

46 Kbps

1

Bandwidth Kbps

Bandwidth Utilization (1024 Kbps)

No of Users

Fig. 4. Maximum bandwidth utilization (1Mbps)

Bandwidth Utilization (800 Kbps)

Bandwidth kbps

900 800 700 600 500 400

24 Kbps 28 Kbps 46 Kbps

300 200

33

29

25

21

17

13

9

5

1

100 0 No of Users

Fig. 5. Bandwidth utilization with consideration of 20% losses

maximum bandwidth i.e. 1 Mbps, the maximum No. of patients whose vital signs data can be transferred to remote monitoring location are 39, 33 and 20, with bandwidth requirements of 24kbps, 28 kbps and 40kbps respectively. These data rates as defined earlier depend upon frame rates set selected per patient. Figure 6 also shows decreased number of patients, when 20% bandwidth loss due to line errors and other overheads is considered. But still the number of patients that the given solution will support would be 33, 28 and 17 patients respectively. That is still a high number of patients that can be supported with high frame rates in real time.

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Maximum No. of Patient 45 40 No of Patient

35

39 33

33 28

30 25

20

20

1 Mbps 17

800 Kbps

15 10 5 0 24

28

46

Kbps

Fig. 6. Maximum number of patients accommodated by system with Mbps per patient and 800kbps per patient

References 1. Ahmed, A., Riedl, A., Naramore, W.J., Chou, N.Y., Alley, M.S.: Scenario-based Traffic Modeling for Data Emanating from Medical Instruments in Clinical Enviornment. In: 2009 World Congress on Computer Science and Information Engineering. IEEE Computer Society, Los Alamitos (2009) 2. Keong, H.C., Yuce, M.R.: Analysis of a Multi-Access Scheme and Asynchronous Transmit-Only UWB for WBANs. In: Annual International Conference of the IEEE, EMBC (2009) 3. Farshchi, S., Pterev, A., Nuyujukian, P.H., Mody, I., Judy, J.W.: Bi-Fi: An Embedded Sensor/System Architecture for Remote Biological Monitoring. IEEE Transaction on Information Technology in Biomedicine 11(6) (November 2007) 4. Wang, P.: The Real-Time Monitoring System For In-Patient Based on Zigbee. In: Second International Symposium on Intelligent Information Technology Application (2006) 5. Chen, H., Tian, J.: Research on the Controller Area Network. In: IEEE International Conference on Networking and Digital Society (2009) 6. Klhmet, U., Herpel, T., Hielscher, K., German, R.: Real Time Guarantees for CAN Traffic. In: VTC Spring 2008, pp. 3037–3041. IEEE, Los Alamitos (2008) 7. Bosch: CAN Specification Version 2.0. J. Robert Bosch GmbH, Stttgart, Germany (1991) 8. Misbahuddin, S.: Al-Holou. N.:Efficient Data communication Techniques for Controller Area Network (CAN) protocol. In: Proceedings of ACS/IEEE International Conference on Computer and their Applications, Tunis, Tunisia (July 2003) 9. Cenesiz, N., Esin, M.: Controller Area Network (CAN) for Computer Integrated Manufacturing Systems. Journal of Intelligent Manufacturing 15, 481–489 (2004) 10. Zubairi, J.A., Misbahuddin, S., Tassudduq, I.: Emergency Medical data transmission System and Techniques. HandBook of Research on Advances in Health Informatics

Study on the Some Labelings of Complete Bipartite Graphs WuZhuang Li, GuangHai Li, and QianTai Yan Dept. of Computer. Anyang Nomal University, Anyang Henan 455002, P.R. China [email protected]

Abstract. If the vertex set V of G =< V,E > can be divided into two un empty sets X and Y , X ∪ Y = V,X ∩ Y = ∅ , but also two nodes of every edge belong to X and Y separately, the G is called bipartite graph. If ∀xi ∈ X,yi ∈ Y,(xi ,yi ) ∈ E then G is called complete bipartite graph. if X = m,Y = n , the G is marked Km,n . In this paper the graceful labeling, k-graceful labeling, odd graceful labeling and odd strongly harmonious labeling are given. Keywords: complete bipartite graphs, graceful labelings, k-graceful labelings, odd graceful labelings, odd strongly harmonious labelings.

1 Introduction Graph theory is a branch of mathematics, especially an important branch of discrete math-ematics. It has been applied in many different fields in the modern world, such as physiccs, chemistry, astronomy, geography, biology, as well as in computer science and engineering. This thesis mainly researches on graph labeling. Graph labeling traces its origin to thefamous conjecture that all trees are grceful presented by A. Rosa in 1966. Vertex labeling is amapping that maps the vertex set into integer set. According to the different requirement for themapping, many variations of graph labeling have been evolved. In 1988, F. Harary introduced the notion of a (integral) sum graph. Sum graph was generalied to mod sum graph by Bolland, Laskar, Yurner and Domke in 1990. The concepts of sum graph and integral sum graph havebeen extended to hypergraphs by Sonntag and Teichert in 2000. Bipartite graphs are widely applied, but not all bipartite graphs are graceful graphs, therefore, it is necessary to research their gracefulness further. Based on the conjecture put forwarded by professor Ma Kejie that crown of complete bipartite graphs is k - graceful (m≤n, k≥2),the conjecture is proved in construction method when (m = 1or 2 , k ≥2); (m ≥ 3, k ≥ (m − 2)(n − 1)) in the paper. And the demonstration extend the k - graceful research rang. Along with the development of computer, The labelings of graphs is more and more extensive in the application and realms, such as network and telecommunication...etc. But these years of various labelings of graphs have already deveolped many kinds, Among them, the search of the graceful labelings and

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harmoniously labelings more active. This text will vs a type of special labelings, Talk about its various labelings.In this paper the graceful labeling, k-graceful labeling, odd graceful labeling and odd strongly harmonious labeling are given.

2 Lemma Definition 1. Let G =< V,E > be a simple graph, if each one of Nonnegative integers f (v) to satisfied:

, there exist a

v ∈V

1) ∀u, v ∈V , u ≠ v, f (u) ≠ f (v) ; 2) max{ f (v) | v ∈V } = E ; 3) ∀e1 , e2 ∈ E , the

G

e1 ≠ e2 ,

f (e1 ) ≠ f (e2 ), Where f (e) = f (u ) − f (v) , e = uv

，

is called graceful graph, and f is called graceful labeling.

Definition 2. Let G =< V,E > be a simple graph, G is called k -graceful, if there exist a injection f:V(G) → { 0,1,2, , E + k − 1 } such that induced mapping f *:E(G) → {k,k + 1, , E + k − 1 } becomes a bijection. Where the induced mapping f * is defined as ∀e = uv ∈ E, f *(uv) = f(u) − f(v)

, then

is called

G

k

-graceful graph,

f

is called

k

-graceful

value. Definition 3. Let G =< V,E > be a simple graph, G is called odd graceful, if there exist a injection f:V → { 0,1,2, ,2 E − 1 } such that induced mapping f *:E(G) → {1,3,5, ,2 E − 1 } becomes a bijection. Where the induced mapping called odd graceful graph,

f

f*

is defined as

∀e = uv, f *(uv) = f(u) − f(v)

, then

G

is

is called odd graceful value.

Definition 4. Let G =< V,E > be a simple graph, if there exist a injection f:V → { 0,1,2, ,2 E − 1 } such that induced mapping f *:E(G) → { 1,3,5, ,2 E − 1 } becomes a bijection. Where the induced mapping graph,

f

f*

is defined as

∀e = uv ∈ E, f *(uv) = f (u ) + f (v )

, then

G

is called odd graceful

is called odd strongly harmonious labelings value.

Definition 5. If the vertex set V of G =< V,E > can be divided into two un empty sets X and Y , X ∪ Y = V,X ∩ Y = ∅ , but also two nodes of every edge belong to X and Y separately, the G is called bipartite graph. If ∀xi ∈ X,yi ∈ Y,(xi ,yi ) ∈ E then G is called complete bipartite graph. if X = m,Y = n , the G is marked K m,n . Discussed below the graceful labeling, k-graceful labeling, odd graceful labeling and odd strongly harmonious labeling.

3 Main Result and Proof In bipartite graph K m,n , nodes of

K m,n

is marked

Study on the Some Labelings of Complete Bipartite Graphs

X = {x1, x2 ,…, xm }, Y = { y1, y2 ,…, yn }. ( xi , y j ) ∈ E ( K m, n ), (i = 1,2, … , m; j = 1,2, … , n) .

Theorem 1.

K m,n

is graceful graph.

Proof. Give

K m,n

labeling

f

as follow : f(x i ) = i − 1, (i = 1, 2,… , m ),

f(y i ) = jm, ( j = 1, 2 , ...,n ),

We proved

f

is a graceful value.

，

f(y j )( j = 1, 2, … , n ) the (1) f(x i )(i = 1,2,… , m ) the maximum is m − 1 minimum is m then f : V ( K m, n ) → {0,1,…, mn} is a injection.

，

(2) The labeling of edges as follow f * ( xi y j ) = f ( xi ) + f ( y j ) = i − 1 + jm ,

when

i ∈ {1 , 2 , ..., m } , j ∈ {1 , 2 , ..., n }

,

f (xi , y j ) ∈ ( j = 1,2,… , n ) . *

Then f * : E (Km, n ) → {1,2,…, mn} is a bijection. Hence we proved f is a graceful value. Theorem 2.

K m,n

is k -graceful graph.

Proof. Give K m,n labeling

f

as follow:

f(xi ) = i − 1, (i = 1, 2, … , m ), f(y i ) = k + m − 1 + ( j − 1) m, ( j = 1, 2 , ...,n ),

We proved

f

is a k -graceful value.

(1) all appearance,

f

: V ( K m, n ) → {0,1, …, k + E − 1}( E = mn) is a injection.

(2) f ( xi y j ) = f ( xi ) + f ( y j ) = k + m + i − 2 + ( j − 1)m , When i ∈ {1 , 2 , ..., m } , j ∈ {1 , 2 , ..., n } , *

f *(x i , y j ) ∈ ( k , k + 1,… , k + E − 1)

Then f : E( K ) → {k , k + 1,…, k + E − 1} is a bijection. According to the (1) and (2) , Hence we proved m,n

f

is a k -graceful value.

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Theorem 3.

K m,n

is odd graceful graph.

Proof. Give K m,n labeling

f

as follow: f(xi ) = 2(i − 1), (i = 1, 2,… , m ),

f(y j ) = 2 ( m − 1) + 1 + 2 m ( j − 1) = 2 mj − 1, ( j = 1, 2 , ...,n ),

We proved

f

is a odd graceful value.

，

In f ( x ) , the maximum is 2(m − 1) in f(y ) ,the minimum is 2(m − 1) + 1 , then f : V ( K m , n ) → {0,1,3, … ,2mn − 1} is a injection. i

j

* (2) f ( xi y j ) = 2(i + mj) − 3 ,

i ∈ {1 , 2 , ..., m } , j ∈ {1 , 2 , ..., n }

When

,

f *(xi , y j ) ∈ {1,3,5,… , 2 E − 1} .

Then f : E ( K ) → {1,3,5,…,2 E − 1} is a bijection. Hence we proved f is a odd graceful value. *

m, n

Theorem 4.

K m,n

is odd strongly harmonious graph.

Proof. Give K m,n labeling

f

as follow:

f(xi ) = 2(i − 1), (i = 1, 2, … , m ), f(y j ) = 1 + 2 m ( j − 1) , ( j = 1, 2 , ...,n ),

We proved

f

is a odd strongly harmonious value.

，

(1) f ( x ) is even numbers f(y ) is odd numbers, then f : V ( K m, n ) → {0,1,2,…,2 E − 1} is a bijection. (2) f * ( xi y j ) = 2i + 2m( j − 1) − 1 , i

j

When i ∈ {1 , 2 , ..., m } , j ∈ {1 , 2 , ..., n } and ( E = mn ), Then f * : E (Km,n ) → {1,3,5,…,2 E − 1} is a bijection. Hence we proved f is a odd strongly harmonious value.

4 Conclusion Bipartite graphs are widely applied. In this paper, the conjecture is proved in construction method the graceful labeling, k-graceful labeling, odd graceful labeling and odd strongly harmonious labeling.

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References 1. Ma, K.: Graceful Graphs. Beijing University Press, Beijing (1991) 2. Slater, P.J.: On k-graceful graphs. In: Proc. of the 13th S.E. Conference on Combinatories Graph theory and Computing, Boca Raton, pp. 52–57 (1982) 3. Maheo, M., Thuillier, H.: On d-graceful graphs. Ars Combinatorics 13(1), 181–192 (1982) 4. Gallian, A.: A dynamic survey of graph labeling. The Electronic Journal of Combinatorics (July 2000) 5. Ma, K.J.: Graceful Graph. Peking University Press, Beijing (1991) (in chinese) 6. Slater, P.J.: On K- graceful graphs. In: Proc(C). of the 13th S. E. Confernece on Combinatorics, Graph theoryand Computing, Boca Raton, pp. 52–57 (1982) 7. Kotzig, A.: Recent results and open problems in of graceful. Congressus Numerantium 44, 197–219 (1984)

An Effective Adjustment on Improving the Process of Road Detection on Raster Map* Yang Li1,**, Xiao-dong Zhang1, and Yuan-lu Bao 2 1

Beijing Jiaotong University, Beijing, China [email protected] 2 University of Science and Technology of China, Hefei, China Abstract. This research goal is to improve whole process of recognizing and extracting road layer from raster map, and to make the whole process as a closed feedback system with output measurable, state controllable and recognition sub-process optimally adaptable. The scheme is building an integrated system with its output road layer measurable by selecting two (or more) methods of perfect comparatively identifications with their mechanism complementary and then parallel collecting them as the controlled sub-process objects of the integrated system. Based on approach thought of microscopic identification and macroscopic elimination, the system realized first the road layer initial recognition and last road map level completely to withdraw via some output layers re-clustering and feedback control. In view of the standard municipal transportation map, the path and the region valve value condition has determined. Through re-clustering to the noise the whole map can be completely divided into two parts of road and non-road (region). The feedback re-clustering strategies of recognition for the transportation road networks are based on the core characteristic of obtain road constitution. The convergence of the feedback re-clustering of road layer guarantees the map level optimization Keywords: nonlinear adjusting, Recognition Vector Map, Adaptive Control.

1 Introduction Digital times requires digital communications, digital times make mass-production and update the traffic vector map task to China. The current transportation system due to population concentration and a high degree of modernization has several serious problems. GPS traffic management, vehicle monitoring, the development and practices of personal navigation technology to alleviate traffic congestion and maintain the role of social security has become apparent. All applications involving GPS navigation system of traffic management or control cannot do without the road location, in a sense, the development of GIS vector traffic has become critical and bottlenecks of precipitate traffic management. The digital map in Geographic Information System (GIS) can be divided into grid (image) map and vector map of two categories. Vector map is obtained from the grid *

This work was supported in part by the National Natural Science Foundation of China under Grant 60974092. ** Corresponding author. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 302–308, 2011. © Springer-Verlag Berlin Heidelberg 2011

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map by computer processing. On the grid map of the road network traffic information extraction process improvement has become established the basis for automatic production vector map link. The current, literature proposed road network to recognize the various methods of the grid map, many have the original, it is also very effective for some map. However, from the perspective of system analysis, the whole identification process is an open-loop system. It is need to manually observe the road layer and the way of manually adjust the road sampling threshold. How to make road information as significant variables of the system output, identification of the road network throughout the recognition process into a feedback system to deal with it, to solve these problems and improve identification process of the traffic grid road map information, to achieve automatic recognition of the critical. Improve the traffic information grid taking the whole process of identification, making a measurable output, a target can control, the recognition process can be adaptive optimized closedloop system.

2 Basic Principle The road map information comprehensive identification system is shown in Figure 1. The basic idea is to adjust the recognition threshold by the output of the road layer. Realization process is shown in Figure 2. Closed-loop system control objectives for the measure R∩A→0 and the measure R A→M. This goal in control of the controlled object Road, Recognition subsystem output R1→R→all roads (that is A2→0) and Area recognition subsystem output A1→A→all non-road area (that is R2→0). In other words, Comprehensive road map information identification system optimization directly corresponds to the output path information to improve recognition accuracy. Road of map comprehensive information identification system output optimization directly corresponds to the output path information to improve recognition accuracy.

∪

Fig. 1. Map of road information the initial design of an integrated identification system schematic

Realization process is shown in Figure 2. Closed-loop system control objectives for the measure R∩A→0 and the measure R A→M. This goal in control of the controlled object Road, Recognition subsystem output R1→R→all roads (that is A2→0) and Area recognition subsystem output A1→A→all non-road area (that is

∪

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R2→0). In other words, Comprehensive road map information identification system optimization directly corresponds to the output path information to improve recognition accuracy. Road of map comprehensive information identification system output optimization directly corresponds to the output path information to improve recognition accuracy. First of all, to conventional treatment before the traffic grid map identify the image, including the elimination of obvious noise points, color brightness contrast adjustment and so on. Images respectively to the road network layer image recognition process and non-road block layer recognition process after conventional raster. Recognition of the road network layer selected recognition algorithm, mainly based on the color of the road, network-wide connectivity and parallel edge feature, Recognition of non-road block layer, mainly based on region color, simply connected shapes, closed border and so on. Attention to the two sub-processes as related to controlled weak pattern recognition process, and get their sensitive evaluation function threshold adjustment range.

Fig. 2. Road of map information comprehensive identification system the initial design process of the identification error

Comprehensive identify road network layer to the connectivity decision the key factors of the correct identification of progress and feedback control. Just setting out from the classical system design theorem, only consider systems with external input and simple output feedback control that is difficult to control the internal process of comprehensive identification system. The simple planning of the comprehensive identification, one is the road, the other is the region. These two factors (equivalent to the two dominant poles within the system) are attributable to simplify the handling process. Take into account the recognition system's internal processes, recognition result of each sub-process the image in fact is always constituted by the three elements complete. These three elements are: road pixel block, regional block and pixel noise pixel block. Need to improve the processing within the system, in the middle of each process into a noise re-clustering process. The contents of each noise re-clustering process:

① Noise pixels block are planning to road or region; ② The result of re-clustering, that is identify connectivity of the center line of the

road network layers, the width of feeder roads and other measurable characteristics to

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distinguish, determine the reasonableness of the road network, whether the final result of output. Road network does not meet specifications, is based on irrational part of the pixel block to modify the standardization map before this noise clustering, it should not plan the road into the region on the change. Start a new round of sub-processes of noise re-clustering. Synthesis of the information used in the road map identification system diagram is shown in Figure 3.

③ ④

Fig. 3. Consider the system's internal road of map information processing integrated identification system

3 Road of Traffic Map Identification of the Extraction on Process Map of road comprehensive information identification system is shown in Figure 4. In general, Improve identification of the city grid road traffic map extraction process is divided into the following sub-processes, are as follows:

Fig. 4. Improve identification of the city grid road traffic map extraction process

3.1 Image Pretreatment Sub-process The characteristic module matching printed map to eliminate the unique is not conducive to identification road marking, getting color maps T1 after pretreatment. In the future, T1 will serve as a map of road identifying the input source extraction view.

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3.2 Traffic Map Normalization on Sub-process This sub-process implementation re-clustering of road R and regional A. Obtained including all noise N0 (covering the white on the road and the gray area layer) the color traffic maps, as standardized map T2 k , (k = 1,2,..., n) . Roads and regional standardization algorithm propose separate closed-loop road feature recognition algorithm and regional characteristics of closed-loop identification algorithm by shape of the road layer and layers of standardized regional approach, The method is based on gray-scale map can be achieved with the recognition of urban traffic map automatically standardized. Block diagram of the realization is shown in Figure 5.

Fig. 5. Automatic normalization algorithm schematic with the recognition

3.3 Noise Re-clustering Process The way of eliminate noise N0 is to identify points or determine the noise to achieve its conversion to a road or area, as noise road re-clustering and noise area reclustering. Until the noise set Nn empty set, Obtained complete clustering of road R and regional A, as black and white binary image T2k +1 (k = 1,2,..., n) . Used is based on the direction of extension features eight pixel noise completely re-clustering guidelines. Including unbiased clustering and biased clustering criteria guidelines. Use unbiased clustering criteria alone cannot completely remove the noise, however, there is partial clustering criteria alone can completely remove the noise. Shown in Figure 6 that T in = RUAUN and T out = RUA, as complete clustering process.

Fig. 6. Noise of based on the direction of extension features eight pixel completely re-clustering

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3.4 Close-Loop Feedback to Improve the Recognition of the Road Sub-process Based on binary image T2 k +1 road centerline violation criterion change the normalization map T2 k corresponding noise block to become regional, obtain improved feedback color map T2k +2, output or to the next round of the process of normalization and noise re-clustering process. Until the binary image T2 k +1 on the no road centerline violations is the end. First extract closed-loop feedback process from the map of road the normalized T2. Then noise re-clustering. Finally T3 into this section introduce of road to be irregularities promoter identification and closed-loop feedback process. T2k updated on the map noise re-clustering again. Constitute closed-loop feedback path identification process. A closed-loop feedback process, create two new maps, as T2k and T2k +1, (k = 1, 2, … , n). Road irregularities promoter identification and closedloop feedback process can be described as: First binary image T2k +1 road Refinement, obtain road centerline and original plans placed in the formation T2k′; Criteria based on the road centerline irregularities change the normalization map T2k of the corresponding noise block content, obtain improved color map feedback T2k +2, output standardization sub-process to the next round of closed-loop process. Until the binary image T2k +1 on the no road centerline violations occur, cycle end, output the final result T2 n+1. A complete closed-loop feedback path identification process schematic is shown in Figure 7.

② ③

Fig. 7. Closed-loop feedback path diagram extract

3.5 The Road Conventional Treatment and Network Integrity Verification Road network layer output binary bitmap black and white. As the previous cycle has normalized threshold without changing the premise of complete correction of the road network, if have problems in testing process, it will start the feedback process and adjustment the threshold relevant of standardized maps, from the original map to start a new identification process

4 Effect and Conclusions of Road Information Automation Identification Improved grid road traffic information recognition process map has been compiled into the corresponding software RoadExtr.exe and obtain software copyright

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registration (Registration No. 2005SR09787). The important results obtained directly can field validation): All the major cities (including Hong Kong and Taipei) of "China Highway Traffic Atlas" CD-ROM have 39 color city maps for the road transport network automatic extraction, Consistent results obtained. Total time spent in 4 hours. Digital platform with the map, using a GPS track of part the city road, can in 20 minutes, starting from the grid map Automatic Identification, use of independent research and development laboratory automatically generated digital maps and calibration platform, achieve position has been the basic calibration of vector map of the city traffic. From the appendix of maps of Hefei, the process of generating and calibration instructions cities road network, automatic identification and extraction process and the results, Road map that we construct an integrated identification system platform information to achieve the desired effect of road information automatically identify, is a success

(

References 1. Li, D.: Digital Earth and the Three S” technology. GIS Forum (2001), http://www.gischina.com 2. Fan, C., Li, Z., Ye, X., Gu, W.: The edge of the road approach recognition system and its real-time implementation. Signal Processing 14(4), 337–345 (1998) 3. Zhang, W., Huang, X., Bao, Y., Shi, J.: Automatic generation of vector electronic map. Microelectronics and Computer 16(4), 30–32 (1999) 4. Shen, q., Tang, l.: Introduction to Pattern Recognition. National Defense University Press (1991) 5. Guo, J., Yao, Z., Bao, Y., Zhang, W.: An automatic correction algorithm of vector map. China Image and Graphics 4(5), 423–426 (1999) 6. Cherkassky, B.V., Goldberg, A.V., Radzik, T.: Shortest paths algorithms: Theory and Experimental Evaluation. Technical Report 9321480, Computer Science Department, Stanford University 7. Zhang, Z.: A Feed Close Loop Road Extraction of Color City Map. Journal of Engineering Graphics 26(4), 21–26 (2005) 8. Hai, T.: Recognition and Extraction of Road from Color Raster Traffic map Image. Journal of Computer Aided Design & Computer Graphics 17(9), 2010–2014 (2005) 9. Li, J., Taylor, G., Kidner, D.B.: Accuracy and reliability of map-matched GPS coordinates. Computers & Geosciences 31, 241–251 (2005) 10. Haibach, F.G., Myrick, M.L.: Precision in multivariate optical computing. Appl. Opt. 43(10), 212–217 (2004)

Multi-objective Optimized PID Controller for Unstable First-Order Plus Delay Time Processes Gongquan Tan, Xiaohui Zeng, Shuchuan Gan, and Yonghui Chen School of Automation and Electronic Information Engineering, Sichuan University of Science & Engineering, 643000, Zigong, China [email protected], [email protected], {g.s.c,cyh0418}@163.com

Abstract. A conventional proportional integral derivative (PID) controller has three independent adjustable parameters, which can be used to meet requirements of closed-loop systems in aspects of stability, speed and accuracy. For an unstable first-order plus delay time (FOPDT) process, parameters of the PID controller are optimized with the maximum complement sensitivity, damping ratio and the integral gain which are special selected for above requirements. Simulation results show that the proposed approach is an effective method for unstable FOPDT processes with different time-delay ratio and its corresponding closed-loop systems have proper robustness stability and response performance. Keywords: Unstable process, FOPDT, PID controller, Multi-objective optimized.

1 Introduction In rectification, chemical, pulp and paper making industries, PID controllers are spread-wide used in 97% control loops. However, the practical application of PID controller does not meet the expectations of state. More than 30% of controllers operate in manual mode and control errors are less when operate in manual mode than in auto mode for 65% of control loops. Lots of tuning methods for PID controller have been proposed recent years, most of which are for self-regulating processes. Controlling unstable processes are much more difficult. Besides stabilizing problems of control systems, the reachable performances for unstable processes may be obviously differ from that of stable processes [1-3]. The goals for an unstable process control should include: stabilizing unstable poles, having a good servo tracking, and eliminating unknown disturbance. There are two difficulties for achieving these targets in fact. One is the problem of servo tracking and disturbance rejection, the other is the robustness and performance. For the former problem, with two-degree-of freedom control structure has been able to deal with effectively. Reference [3] introduces a method to obtaining the weighted coefficients of proportional and derivative action for known PID. Reference [4] introduces a two loops control structure to equivalent the conventional single loop PID, and meanwhile S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 309–315, 2011. © Springer-Verlag Berlin Heidelberg 2011

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elaborates the partition coefficients for two loops. Solution methods for the latter problem include robust method, optimization method, internal model control (IMC) method, improved Smith design method, and direct design method, etc. In commonly, dynamic performances are not good for robust criteria as a merely objective, and stable margin will not good if the integral performance is only used. In IMC method, Smith method, and direct design method, adjustable parameter λ is a compromise between robustness performance and dynamic performance, which has a great advantage. But realization structures are relatively complex when they are used in controls of unstable plus delay time processes. Otherwise, the value of the adjustable parameter λ is also a problem. A multi-objective optimized PID control method for unstable first-order plus delay time (UFOPDT) processes in industry is proposed in the paper.

2 Question Description The structure of a two loops control system is as shown in figure 1. In which, r, d, u, y, and e are the set-point signal, disturbance signal, control variable, controlled variable, and error signal respectively. The controller C(s) is consists of three elements A(s), B(s) and Kb, and P(s) is the process model, and these are expressed as below

A( s) =

K a (1 + sTa ) , K b B( s) = K b (1 + sTb ) s P(s) =

K p −sL p e 1 − sT p

(1)

(2)

where, Ka, Kb and Kp are static gain, Ta, Tb and Tp are time constant, and Lp is a delay time. Tr=Tp/Lp is the ratio of lag time to delay time. Controller C(s) can be equivalent to the weighted PID controller, that is

u = K c (a +

1 1 + bTd )r − K c (1 + + Td ) y sTi sTi

(3)

K K = ( aK c + i + bK d ) r − ( K c + c + K d ) y s s where Kc, Ki, and Kd are the proportional gain, integral gain and derivative gain, Ti and Td are integral time constant and derivative time constant, and a and b are the r

e

A(s) Kb

B (s)

u

d

P(s )

y

C ( s)

Fig. 1. The structure of a two loops control system

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proportional and derivative weighted coefficient respectively. Parameters of Equation (2) and equation (3) have the relationships as below.

⎧ K c = K a (Ta + Tb ) + K b Ta + Tb Ta ⎪ Ki = K a ,a = ,b = ⎨ Ta + Tb + K b / K a Ta + K b / K a ⎪ K = ( K T + K )T a a b b ⎩ d

(4)

Performance indexes of a closed-loop system include three aspects of stable, fast and accurate. Methods, such as IMC, adjust filter time constant λ to satisfy requirements at three aspects, which is quite simply and direct, but disadvantages are also obviously. Firstly, the control structures for open-loop unstable processes with time delay are very complicated. Second, the choosing of adjustable filter time constant is also a problem. Considering the generalization and simplification of PID controllers and experiences of engineers in parameter adjustments, a design method introduced in the paper is based on PID controller directly. There are three adjustable parameters of a PID controller, obviously three performance indexes can be chosen for target optimizations. For stability, Nyquist criterion is adopted, that is, the maximum complement sensitivity Mt, the maximum sensitivity Ms, or the maximum sensitivity and complement sensitivity Mst is selected. The Mt index is more representative to describe stabilities and expected response of systems than phases and gain margins[6]. Reference [2] derives that the maximum sensitivity of unstable processes with time delay has lower bound, that is

M t = T (s) ∞ =

L( s) 1 + L( s)

= sup T ( jω ) ≥ e1 / Tr ∞

(5)

ω

where T(·) is the function of complement sensitivity, ||·||∞ is the H∞ norm. The smaller Tr is, the greater lower bound of Mt is, and the robustness of the system will decrease. For a stable process, the recommend Mt =1.3[7]. But it is hard to determine the value of Mt for an unstable process with time delay. In reference [8] and [9], the integral gain Ki is recommended as the index of disturbance rejection. In reference [10], it is proved that the integral gain and the integral absolute error (IAE) have similar behaviour for a stable process, but the integral gain is easier. Moreover, we expect the load-step response of our closed-loop system is almost no oscillations. In my experiences, this type of response waves can be guaranteed by damping ratio ξ. In conclusion, the maximum complement sensitivity Mt, damping ratio ξ and integral gain Ki are selected as performance and robust indexes for describing a closed-loop system, and also as optimization indexes for three parameters of a PID controller.

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3 Optimization of PID Controllers Assume the inner feedback element Kb=0, then the controller C(s) is the series form PID, that is

C (s) =

K a (1 + sTa )(1 + sTb ) s

(6)

With the 1/1 Pade approximating the time delay, loop transfer function L(s) is

K p K a (1 + sTa )(1 + sTb )( 2 − sL p )

L( s) = P( s)C ( s) ≈

s( sT p − 1)(2 + sL p )

(7)

K ( sT + 1)( sTbr + 1)(2 − s ) = r ar s( sTr − 1)(2 + s) where, K r = K p K a L p , Tr = T p / L p , Tar = Ta / L p , Tbr = Tb / L p , ωr = ωn L p . Arrangements with the 1+L(s) = 0, we can have the character factors as

Δ ( s ) = (Tx s + 1)(

s2

ωn

2

+

2ξ

ωn

s + 1)

(8)

where the coefficient relationships between equation (7) and equation (8) satisfies

K r = ωr

(2Tr − 1 − 2ξω rTr )(Tbrω r + 2) + (2Tbr − 1 + 2ξω rTbr )(Trω r + 2) (9) 2 2 (Tbrωr + 2) 2 + (ωr − 2ωrTbr + 4ξ )(ωr − 2ωrTbr − 2ξωr Tbr ) 2

2

Trωr + 2 ω − 2ωrTbr + 4ξ + r 2 2 K ir (Tbrωr + 2) ωr (Tbrωr + 2)

2

2

Tar =

(10)

Because Kr is proportional to the integral gain Ki, so it is reasonable to select a ωr which makes Kr maximum. From equation (9), the ωr that makes Kr maximum can be calculated mathematically under given ξ and Tbr. Simultaneously, Tar can be gotten from equation (10) from this case. In other words, for a given ξ and Tbr, optimal parameters Kr=Krm and Tar=Tarm can be obtained, that is

K rm (Tbr ) = sup K r (Tbr , ωr ) → Tarm (Tbr )

(11)

ωr

This means we have got the loop function and we can calculate the Mt with equation (5). Obviously, Mt is a function with the variable Tbr. We can select a Tbr = Tbm to make the optimal robust index for Mt, that is,

M tm = inf M t (Tbr ) Tbr

(12)

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In conclusion, for a UFOPDT described by equation (2), if damped ratio ξ is selected properly, three parameters Km= Krm(Tbm), Tam= Tarm(Tbm) and Tbm of a series PID controller described by equation (6) can be acquired through the optimization of the integral gain and the maximum complement sensitivity. Therefore, three targets on stable, fast and accurate of closed loop system, are achieved. As an example, this method are used to optimize PID parameters at ξ=0.707 for UFOPDT under different Tr. In this case, three formulas using numerical fitting for lots of optimal parameter values are as follows

⎧ Km = −2ln(3.126 − 0.1528 / Tr − 2 8 Tr ) ⎪⎪ 2 ⎨ Tam = (0.6926 + 0.8609 Tr − 0.41914 Tr ) / Km ⎪ ⎪⎩Tbm = −2ln(0.7492 − 0.008822Tr + 0.07364 Tr )

(13)

These formulas are obtained under condition Kb=0. This would make the control variable u have the derivative term of set-point signal r. We can equivalent moving this term to feedback tunnel, that is, there is an appropriate Kb=Kbm satisfies

K bmTbm = K d = K mTamTbm → K bm = K mTam

(14)

So, the parameters of the final set-point weighted PID (SW-PID) controller of equation (3) are

Kc =

K m (Tam + Tbm ) , Ti = (Tam + Tbm ) L p , Kp

(15)

T T Tbm Td = am bm L p , a = ,b = 0 Tam + Tbm Tam + Tbm

4 Simulations Proportional and derivative weighted coefficients of all PID controllers list below are set uniformly from equation (15) expect the improved IMC, which is realized according to its complex structures in reference [3]. 4.1 Example 1: An UFOPDT with Large Tr. An unstable first-order plus delay time process with large Tr is expressed as P(s) = es /(8s-1). Select Lee PID[11] (λ=2L, Kc=5.552, Ti=6.4645, Td=0.2843, Ki=0.8588, Mt=1.6323), Wang PID [1] (Ms=1.6, Kc=5.4582, Ti=5.8705, Td=0.1318, Ki=0.9298, Mt=1.8691), and modified IMC[12](λ=2L, Mt=2.5003) compared with the proposed PID (Kc=6.19, Ti=4.6398, Td=0.2276, Ki=1.3341, Mt=1.9163). Its step response of the control system for set-point step at 0s and load step at 40s are as shown in figure 2.

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Step Response

1 0.8 step Proposed PID Lee PID Modified IMC Wang PID

0.6 0.4 0.2 0

0

10

20

30

40 Time

50

60

70

80

Fig. 2. Step responses of an UFOPDT with large Tr

4.2 Example 2: An UFOPDT with Medium Tr An unstable first-order plus delay time process with medium Tr is expressed as P(s) = e-0.4s/(s-1). Select Lee PID[11](λ=2L, Kc=2.1681, Ti=3.9753, Td=0.1368, Ki=0.5454, Mt=2.4535), Wang PID[1] (Ms=1.6, Kc=2.0484, Ti=2.7727, Td=0.0785, Ki=0.7388, Mt=3.6623), modified IMC[12] (λ=2L, Mt=2.9498) compared with the proposed PID (Kc=2.4644, Ti=2.5172, Td=0.1287, Ki=0.979, Mt=2.7867). Its step response of the control system for set-point step at 0s and load step at 40s are as shown in figure 3. As shown in figure 2 and 3, the proposed method is more appropriate for robustness and performance trade-offs.

Step Response

1 0.8 step Proposed PID Lee PID Modified IMC Wang PID

0.6 0.4 0.2 0

0

5

10 Time

15

20

Fig. 3. Step responses of an UFOPDT with medium Tr

4.3 An UFOPDT with Small Tr Considering an UFOPDT with small Tr [2] as P(s) = e-1.2s/(s-1). PID controllers introduced in many references, for example Wang PID[1], can not be used in this situation. Select Lee PID[11](λ=2L, Kc=1.21, Ti=37.9706, Td=0.5832, Ki=0.0319, Mt=13.209), Huang PID[2] (Kc=1.1716, Ti=52.724, Td=0.5188, Ki=0.0222, Mt=11.3067), modified IMC[12] (λ=2L, Mt=10.7886) compared with the proposed PID (Kc=1.1727, Ti=56.8756, Td=0.0.5039, Ki=0.0206, Mt=12.2816). Its step response of the control system for set-point step at 0s and load step at 40s are as shown in figure 4. Because the control difficulty of this process is great, and the maximum sensitivity of the closed-loop system with the perturbation model is large, the expected robust stability is primary. As shown in the figure 4, the proposed method has also better robust stability than others.

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Step Response

1 0.8 step Proposed PID Lee PID Modified IMC Huang PID

0.6 0.4 0.2 0

0

20

40

60 Time

80

100

120

Fig. 4. Step responses of an UFOPDT with small Tr

5 Conclusions For unstable first-order processes with time delay, the damping ratio is used to constrain response waveforms, and the integral gain which represents disturbance rejection and maximum complement sensitivity which represents robust stability are optimized for PID controller. It has a clear physical meaning to use the damping ratio for stationary response of a system, and it is easy for understanding and application. Because damping ratio can be given appropriately, the proposed method is a twodegree searching approach. It shortens the optimization time and it is worth to be applied for large scale of time-delay ratio. Simulations are proved these results.

References 1. Wang, Y., Xu, X.: A PID Controller for Unstable Processes Based on Sensitivity. Academic Journal of Shanghai University of Technology 31(2), 125–128 (2009) 2. Huang, H.P., Chen, C.C.: Control-system Synthesis for Open-loop Unstable Process with Time Delay. IEE Proc. Control Theory & Appl. 144(4), 334–346 (1997) 3. Chen, C.-C., Huang, H.-P., Liaw, H.-J.: Set-Point Weighted PID Controller Tuning for Time- Delayed Unstable Processes. Ind. Eng. Chem. Res. 47, 6983–6990 (2008) 4. Kaya, I., Tan, N., Atherton, D.P.: A Refinement Procedure for PID Controllers. Electrical Engineering 88, 215–221 (2006) 5. Jeng, J.-C., Huang, H.-P.: Model-Based Auto- tuning Systems with Two-Degree-ofFreedom Control. Journal of Chinese Institute of Chemical Engineers 37(1), 95–102 (2006) 6. Thirunavukkarasu, I., George, V.I., Saravana Kumar, G., Ramakalyan, A.: Robust Stability and Performance Analysis of Unstable Process with Dead Time Using Mu Synthesis. ARPN Journal of Engineering and Applied Science 4(2), 1–5 (2009) 7. Luyben, W.L.: Simple Method for Tuning SISO Controller in Multivariable Systems. Ind. Eng. Chem., Process Des. Dev. 25, 654–660 (1986) 8. Åström, K.J., Hägglund, T.: Advanced PID Control. Instrument Society of America, North Carolina (2006) 9. Tan, W., Liu, J., Chen, T., Marquez, H.J.: Comparison of Some Well-known PID Tuning Formulas. Computers and Chemical Engineering 30, 1416–1423 (2006) 10. Chen, Y., Zeng, X., Tan, G.: Auto- tuning of Optimal PI Controller Satisfying Sensitivity Value Constraints. Advanced Materials Research 204-210, 1938–1943 (2011) 11. Lee, Y., Lee, J., Park, S.: PID Controller Tuning for Integrating and Unstable Processes with Time Delay. Chemical Engineering Science 55, 3481–3493 (2000) 12. Zhu, H., Shao, H.: The Control of Open-loop Unstable Processes with Time Delay Based on Improved IMC. Control and Decision 20(7), 727–731 (2005)

Water Quality Evaluation for the Main Inflow Rivers of Nansihu Lake Yang Liyuan1, Shen Ji2, Liu Enfeng2, and Zhang Wei1 1

College of Resources and Environment, University of Jinan, Jinan 250022, China [email protected] 2 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

Abstract. Based on water quality monitoring data of four inflow rivers of Nansihu Lake in 2006, 2007 and 2008, the water qualities were evaluated according to the method of comprehensive water quality identification index, with the indicators of dissolved oxygen, CODMn, biochemical oxygen demand and ammonia nitrogen. The results show that the rivers has been in the state of serious pollution, in which the monitoring section of Si River was in Grade III of water quality standard, and others were in Grade IV and V. The evaluation results have offered interesting scientific basis for environmental controlling to the inflow rivers of the Nansihu Lake. Keywords: Water quality assessment, Water quality identification index, Nansihu Lake.

1 Introduction At present, water eutrophication and water quality deterioration are very serious, and have become a global environmental problem. In the past two decades, water quality deterioration of lakes in our country has become increasingly serious, a large number of human activities has a negative impact on the lake environment. Water eutrophication has become one of the major environmental problems to perplex China’s economic development. Nansihu Lake locates in the southwest of Shandong Province, It consists of four sublakes: Nanyanghu Lake, Dushanhu Lake, Zhaoyanghu Lake and Weishanhu Lake, which belongs to Sihe River system in Huaihe River basin. It covers an area of 1266 km2 with a North-south length of 126 km. It has divided into Upper and Lower Lake by a dam which was built in 1960. North of the dam is Upper Lake with catchment area of 2.69×104 km2, which accounted for 88.4% of the whole catchment area; south of the dam is Lower Lake with catchment area of 0.35×104 km2, which accounted for only 11.6% of the whole area [1]. At present, the national pollution problems in rivers and lakes continue to appear, which has brought serious negative impact. For lakes, the vast majority of non-point source pollutants can enter into the lake through inflow rivers[2], and water quality of inflow rivers is closely related to water quality of the lakes, so it is essential to evaluate the water quality of rivers into the lake. This paper, the method of S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 316–323, 2011. © Springer-Verlag Berlin Heidelberg 2011

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comprehensive water quality identification index, through the survey of representative organic pollution indicators, was used to evaluate the water quality of four inflow rivers of Nansihu Lake, in order to provide the scientific basis for pollution prevention and control.

2 Material and Method 2.1 Monitoring Data Sources In order to monitor the water quality conditions of inflow rivers, according to basin environment, pollution emissions along the rivers and hydrological characteristics, we identified 25 monitoring sections. All collected samples were sent to the Hydrology and Water Resources Survey Bureau of Jining for analysis. The detection methods were according to Quality Standard of Surface Water Environment (GB38382002) and Water and Wastewater Monitoring and Analysis Methods (Fourth Edition).As the inflow rivers with great catchment area mainly located in Upper Lake, The cross-section data of four major inflow rivers were selected from 2006 to 2008, which injected into Upper Lake to be the analysis objects: Malou monitoring section of Baimahe River, Xiyao monitoring section of Dongyuhe River, Yingou monitoring section of Sihe River and Yulou monitoring section of Zhuzhaoxinhe River. According to monitoring data and the actual situation of pollution into the rivers, we selected a group of organic pollution indicators to be evaluation indices which were closely related to the water quality: DO, CODMn, NH3-N and BOD5. The evaluation criterion was according to Quality Standard of Surface Water Environment (GB3838-2002) .

《

《

》

》

》

《

2.2 Water Quality Identification Index In recent years, many water quality evaluation methods had been proposed by scholars[3 - 6], such as fuzzy comprehensive evaluation method, nutrition status index method, and artificial neural network method. There were certain advantages in the application of these methods on water quality evaluation, but it could not select the indicators that not reach the standard, and could not estimate the quantitative difference between water quality status and functional area objectives. Method of comprehensive water quality identification index, as a new method proposed in 2003, have overcome the shortages of some evaluation methods, and it also have been widely used on water quality assessment. 2.2.1 Single-Factor Water Quality Identification Index Single-factor water quality identification index p was composed of one integer, decimal point and two significant figures after the decimal point. It can be expressed as follows: pi = X 1 ⋅ X 2 ⋅ X 3 .

X1 represents the water quality type of i indicator; X 2 represents the location of monitoring data in the range of X 1 grade changes; X 3 represents the Where:

comparison of water quality type and setting type of function area.

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Determination of

Ⅰ

Ⅴ

X 1 ⋅ X 2 : (1) When the water quality was between types

of and , for the general indicators(except for pH, dissolved oxygen, water temperature) :

α i − α subscript α sup erscript − α subscript α i − α subscript X1 ⋅ X 2 = a + 1 − , α sup erscript − α subscript X1 ⋅ X 2 = a +

For DO: Where:

αi

represents the measured concentration of i indicator;

α sup erscript

,

α subscript represent the upper limits and lower limits in water quality standard interval of a of i indicator; a =1、2、3、4、5, and the determination of this value is based on comparison of monitoring data and national standards. (2) When the water quality was equal to or worth than the type of , a = 6 , for the general indicators(except for pH, dissolved oxygen, water temperature):

Ⅴ

X1 ⋅ X 2 = a +

For DO:

X1 ⋅ X 2 = a +

α i − α sup erscript⋅of ⋅ν α subscript ⋅of ⋅ν

α sup erscript⋅ν − α i ×m α sup erscript⋅ν

Where: m represents the correction factor of the formula, and in general it is taken 4. Determination of Where:

X 3 : X 3 = X 1 − f1 .

f1 represents objective types of water environmental function area.

2.2.2 Comprehensive Water Quality Identification Index Comprehensive water quality identification index was composed of total average of single-factor water quality identification index, the number of participating indicators that worse than functional area objective, and the comparison of comprehensive water quality type and functional area standard. The formula: Where:

I wq =

∑p n

i

（ ∑np ） X i

3

X4

represents the total average of single-factor water quality

identification index, that is X1 ⋅ X 2 ;

n represents the number of evaluation indices;

X 3 represents the number of participating indicators that worse than functional area objective; X 4 represents the comparison of comprehensive water quality type and functional area standard.

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2.2.3 Determination of Water Quality Type The level of comprehensive water quality identification index in the inflow rivers of Nansihu Lake can be determined as follows (Tab.1)[4]: Table 1. Determination of comprehensive water quality levels

﹒x 1.0≤x ﹒x ≤2.0 2.0＜x ﹒x ≤3.0 3.0＜x ﹒x ≤4.0 4.0＜x ﹒x ≤5.0 5.0＜x ﹒x ≤6.0 6.0＜x ﹒x ≤7.0 x ﹒x ＞7.0 x1

2

1

2

1

2

1

2

1

2

1

2

1

1

2

2

Comprehensive water quality level

Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ Ⅴ Ⅴ

Grade Grade Grade Grade Grade Worse than Grade but not black-odor Worse than Grade and black-odor

3 Results and Analysis 3.1 Single-Factor Water Quality Identification Indices of Selected Sections from 2006 to 2008 Calculate single-factor identification indices according to the annual average of water quality index of monitoring sections (Tab.2, Tab.3). Table 2. Monitoring results of selected sections from 2006 to 2008 Monitoring Time Year 2006

Year 2007

Year 2008

River Name Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River

Monitoring Section Malou Xiyao Yingou Yulou Malou Xiyao Yingou Yulou Malou Xiyao Yingou Yulou

Unit: mg/L

DO

CODMn

NH3-N

BOD5

6.57 5.80 6.98 6.60 6.77 6.01 6.39 6.82 6.09 6.27 6.80 7.49

10.61 9.64 9.10 15.82 7.74 7.24 6.40 8.21 6.20 8.20 6.75 6.64

2.61 1.14 0.54 6.19 2.14 1.10 0.50 2.86 0.76 0.37 0.38 3.31

4.53 4.59 4.43 12.42 3.68 4.18 4.42 7.09

Note: In 2006, there were no values of BOD5 due to sampling.

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As can be seen from Table 3 during the period of 2006-2008, only DO all met the standards for raw water environment function, and the change range of single-factor water quality identification indices was not large. Single-factor could determine that these several rivers were in Grade II or III of water quality standard. The remaining three indicators existed excessive phenomena of different levels, such as monitoring section of Yulou of Zhuzhaoxinhe River in 2006, the single-factor water quality identification index of indicator CODMn was 6.13, single-factor evaluation of this river was worse than Grade V, and this had a difference of three grades compared to the functional area objective. For NH3-N and BOD5, the concentrations had a large difference in different rivers. The single-factor water quality identification indices in Baimahe River and Zhuzhaoxinhe River were large, and they had poor water quality. The concentration of BOD5 exceeded serious in Zhuzhaoxinhe River during the years 2007 and 2008, single-factor evaluation was Grade V or worse than Grade V. Table 3. Single-factor water quality identification indices of selected sections from 2006 to 2008 Monitoring Time Year 2006

Year 2007

Year 2008

River Name Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River

Monitoring Section Malou Xiyao Yingou Yulou Malou Xiyao Yingou Yulou Malou Xiyao Yingou Yulou

DO

CODMn

NH3-N

BOD5

2.60 3.20 2.30 2.60 2.50 3.00 2.70 2.50 2.90 2.80 2.50 2.00

5.71 4.91 4.81 6.13 4.40 4.31 4.11 5.82 4.00 4.61 4.21 4.21

6.32 4.31 3.10 8.15 6.02 4.21 2.00 6.43 3.50 2.60 2.70 6.73

4.30 4.31 4.21 6.23 3.70 4.01 4.21 5.72

3.2 Comprehensive Water Quality Identification Indices of Selected Sections from 2006 to 2008 Calculate comprehensive water quality identification index according to single-factor water quality identification index (Tab.4). Table 4. Comprehensive water quality evaluation River Name

Monitoring Section

Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River

Malou Xiyao Yingou Yulou

Comprehensive Water Quality Identification Index Year 2006 Year 2007 Year 2008 4.920 (IV) 4.121 (IV) 3.410 (III) 5.622 (V)

4.310 (IV) 4.031 (IV) 3.320 (III) 5.232 (V)

3.500 (III) 3.520 (III) 3.420 (III) 4.731 (IV)

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From every value of comprehensive water quality identification index in Table 4, we could know that the water quality of Baimahe River in 2008 was Grade III, and it met the standard of functional area. The water quality was inferior to the functional area standard at one level in Dongyuhe River in 2006 and 2007. Although the water quality reached standard of Grade III in 2008, there were still two indicators more than the standards. The water quality of Sihe River was the best of the four rivers, although individual indicators were not compliance, the comprehensive water quality level had reached Grade III. Zhuzhaoxinhe River was the worst in water quality, which was most polluted, the comprehensive water quality level was inferior to one to two levels compared to the standard, and there were an average of two or three indicators non-compliance in four indicators that involved the overall water quality assessment. All these can help to establish the treatment direction and intensity for pollution control in inflow rivers of Nansihu Lake. 3.3 Analysis of Change Trends of Water Quality Identification Indices from 2006 to 2008 From Fig.1, we could see that the development trend of four indicators in Baimehe River was good during the years from 2006 to 2008, especially the content of NH3-N decreased more, which made the single-factor evaluation changed from worse than Grade V to Grade III. The values of single-factor water quality identification indices in Sihe River were small and changed little, water quality was quite stable. In Dongyuhe River, the concentrations of DO and BOD5 changed little, concentration of NH3-N decreased significantly in 2008, content of CODMn declined slightly in 2007, but it rebounded in 2008. Except for DO, the other three indicators were higher than year 2006

7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00

year 2007 year 2008

year 2006 year 2007 year 2008

5.00 4.00 3.00 2.00 1.00 DO

CODMn

NH3-N

BOD5

0.00

（a）Baimahe River

DO

year 2006 year 2007 year 2008

year 2006

5.00

NH3-N

BOD5

year 2007 year 2008

8.00

4.00

6.00

3.00

4.00

2.00

2.00

1.00 0.00

CODMn

（b）Sihe River

0.00

DO

CODMn

NH3-N

（c）Dongyuhe River

BOD5

DO

CODMn

NH3-N

BOD5

（d）Zhuzhaoxinhe River

Fig. 1. Tendency of Single-factor water quality identification indices from 2006 to 2008

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the standard in Zhuzhaoxinhe River. Although they all had downward trends, because of their large cardinal numbers, single-factor evaluations were still inferior to one or two grades compared to functional area objectives. As can be seen from Fig.2, the comprehensive water quality identification indices of Sihe River were the smallest, comprehensive water quality evaluation was Grade III, and it reached the standard of functional area. Water quality from good to bad of the other three rivers was in the following order: Dongyuhe River, Baimahe River and Zhuzhaoxinhe River. Water quality trends of these three rivers were getting better during the three years, especially in Baimahe River, water quality had been changed from Grade IV in 2006 to Grade III in 2008. Though water quality of Zhuzhaoxinhe River improved somewhat, it was the same as single-factor evaluation due to its large cardinal numbers, water levels were still not meet the standard of functional area. So this river had the most serious polluting condition. 6

5.62

5.5 5 4.5 4 3.5 3

5.23

4.92

4.73

4.31

4.124.03 3.52

3.50 Baimahe River

Dongyuhe River

3.413.323.42 Sihe River

Zhuzhaoxinhe River

year 2006 year 2007 year 2008

6 5.5 5 4.5 4 3.5 3

Baimahe River Dongyuhe River Sihe River Zhuzhaoxinhe River

year 2006

year 2007

year 2008

Fig. 2. Tendency of comprehensive water quality identification indices from 2006 to 2008

4 Conclusion During the period of 2006 to 2008, only DO all met the standards for raw water environment function, single-factor could determine that these several rivers were in Grade II or III of water quality standard. The remaining three indicators existed excessive phenomena of different levels. Water quality conditions in these four rivers all had good development trends during the years from 2006 to 2008, especially in Baimahe River, water quality had been changed from Grade IV in 2006 to Grade III in 2008. Though water quality of Zhuzhaoxinhe River improved somewhat, water levels were still not meet the standard of functional area due to its large cardinal numbers. So this river had the most serious polluting condition. Acknowledgments. The study was financially supported by the national Natural Science Foundation of China (Grant No. 40672076,No.40702058).

References 1. Yang, L., Shen, J., Liu, E., et al.: Characteristic of nutrients distribution from recent sediment in Lake Nansihu. Lake Sci. 19(4), 390–396 (2007) 2. Song, H., Lv, X., Li, X.: Application of fuzzy comprehensive evaluation in water quality assessment for the west inflow of Taihu Lake. Journal of Safety and Environment 6(1), 87–91 (2006)

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3. Guo, M.: Application of mark index method in water quality assessment of river. Environmental Science and Management 31(7), 175–178 (2006) 4. Xu, Z.: Comprehensive water quality identification index for environmental quality assessment of surface water. Journal of Tongji University: Natural Science 33(4), 482–488 (2005) 5. Fan, Z., Wang, L., Chen, L., et al.: Application of water quality identification index to environmental quality assessment of Dianshan Lake. Journal of Shanghai Ocean University 18(3), 314–320 (2009) 6. Chang, H., Che, Q.: Study on methods of evaluation for water eutrophication. Journal of Anhui Agri. Sci. 35(32), 10407–10409 (2007)

Software Piracy: A Hard Nut to Crack __A Problem of Information Security Bigang Hong Department of Economics and Management, Shaoyang University, Shaoyang, China [email protected]

Abstract. Software piracy is becoming increasingly rampant in the world. In order to effectively check this trend, we analyse the present situation in both developing economies and developed economies. Through a comparison, we conclude that software piracy can be psychologically, economically, technologically and institutionally based. Results show that the age of an individual as well as a country’s stage of development and the quality of governance have the largest impact on the incidence of software piracy. Mature age, greater economic and political freedoms are shown to have opposite effects on piracy. Greater diffusion of the Internet and of computer technologies, other things equal, actually promote the legal use of software. Higher access prices help to reduce piracy. Overall, psychological, economic, institutional, and technological factors may exert influences on software piracy to some extents. Finally, some suggestions are offered. Keywords: software piracy, Internet, Causes, Measures.

1 Introduction Easier Internet access in recent years has enabled software firms to distribute their products online, instead of through traditional distribution channels. At the same time, the cheap and easy channels have made the issue of protection of intellectual property become more difficult and imperative. On the one hand, software products are hard to protect due to their peculiar attributes and, thus, the traditional instruments of protecting intellectual property such as patents seem ill-suited. On the other hand, modern technologies make piracy easier in terms of its speed, absence of geographic constraints, and the absence of the need for a middleman. The Internet is a doubleedged sword when it comes to software distribution. Negligible distribution cost is not only true for the legitimate firms, but it is also true for the pirate firms which takes advantage of the anonymity of the virtual world, bringing about large losses of benefit for legitimate firms, and which in return has a negative impact on the industy itself and the economy on the whole. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 324–329, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Rampant Software Piracy Situation Software is one of the most valuable technologies of the Information Age, running everything from PCs to the Internet. Yet, because software has become such an important productivity tool, the illegal copying and distribution of it – software piracy – persists globally. Software piracy refers to unauthorized copying or distributing copyrighted software, including copying, downloading, sharing, sales or installing multiple copies of copyrighted software in either personal computers or office computers. As Business Software Alliance's (BSA) statistics show, unauthorized copying is rampant all over the world (see Figure 1). The magnitude of software piracy can be gauged from the fact that nearly half of the software acquired globally is pirated. North America has the lowest software piracy, 21% in both 2008 and 2009. Asia-pacific, Latin America and Central/Eastern Europe have a much higher percentage, 61% and 59%, 65% and 63%, 66% and 64% respectively in 2008 and 2009. 1-Asia-Pacific, 2-Central/Eastern Europe, 3-Latin America, 4-Middle East /Africa, 5-North America, 6-Western Europe, 7-European Union, 8-Worldwide The situation is even darker when we take a look at individual countries inside the regions (Table 1). A number of factors contribute to regional differences in piracy— —the strength of intellectual piracy protection, the availability of pirated software, and cultural differences, etc. All the nations in the Top-20 with the highest software piracy can be counted as developing countries, Georgia being No 1 with 95%. The most interesting finding is that the least developed countries of the world are missing from BSA's list. This can be attributed in the first place to the fact that those countries severely lack computers; i.e., no computer, no software. Developing countries do not typically have much internal reason to enforce copyright. Their national cultural industries are weak and the trade balance distorted towards the rich countries. This is even truer for software copyright, which is sometimes seen to benefit only multinational companies. Combined with the strong cultural tradition of copying, which can be found in certain parts of world—especially in Asia has resulted in the widespread violations of software copyright described in the statistics above. The conventional opinion suggests that piracy reduces the sale of legitimate software, thus

（

）

70 60 50 40

2008 2009

30 20 10 0

1

2

3

4

5

6

7

8

Source: Based on Seventh Annual BSA/IDC Global Software Piracy Sdudy

Fig. 1. Percentage of Software Piracy in 2008&2009

326

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hurting software producers’ profits. However, several articles on the economics of software piracy actually argue in favor of piracy. They claim that software piracy might not be harmful for software that exhibits positive network externalities. The reason is that for those kinds of software, the larger the user base, the higher utility a user gets from using it. Because pirate software increases the size of user base, consumers get higher utilities, and hence they are willing to pay a higher price. The higher prices then lead to higher profits for software producers, meaning piracy is actually beneficial. Still some argue that piracy protection raises the cost of pirating, causing some would-be pirates to buy and others to do without the product. The resulting smaller user base produces a lower software value and may actually reduce profits. For certain types of software, where the word-of-mouth interaction among users and potential users is critical to the growth of the user base over time, pirates play an important role in converting potential users into users of the software, many of whom legally purchase the software. They demonstrated their modeling approach by analyzing the diffusion of spreadsheets and word processors in the United Kingdom. The results indicated that since the late 1980s, out of every seven software users, six had pirated copies. On the other hand, the pirates significantly influenced the potential users to adopt this software. In fact, they contributed to generating more than 80% of the unit sales for these two types of software. This may explain to some extent the unwillingness of the developing nations in implementing strict piracy protection and the rampant software piracy in these nations.

3 Causes for Piracy on Personal Computers Motives are regarded as the basic causes and determinants of all behaviours which are not haphazard, trivial, or purely habitual. Motives can be psychologically, economically, institutionally, and technologically based. In 2009, consumers continued to spend on PCs and software despite the soft economy. PC shipments to consumers rose 17%, compared with a 15% drop in shipments to businesses, governments and schools. More than half of all new PCs shipped went to consumers. Furthermore, consumers were much more active installing new software than businesses, governments or schools. More than three quarters of all software shipped in 2009 went to consumers. This shift in the PC market has an impact on piracy, as software piracy rates are generally higher on consumer PCs than those of other segments of the market. So software piracy constitutes a hard nut to crack in the emerging economies in the years to come. Here we will analyze the motivations for software piracy, witn an aim to working out more effective measures accordingly. First, motivation can be psychologically based when the individual seeks affirmation of personal values. Individuals may aim to gain group acceptance and, subsequently, to gain status. Intrinsically motivated behaviour is of two kinds. First, an individual may seek to behave in ways which allow them to feel competent and self-determining. The second kind of intrinsically motivated behaviour involves conquering challenges. When an individual conquers the challenges that they encounter, he will feel achievement. According to Maslow , there was ‘‘a basic desire to know, to be aware of reality, to get the facts, to satisfy curiosity’’. This factor may well explain the fact that many crackers of software are not paid for their activities.

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Secondly, there is economically based motive. Economic factors deal with potential purchasing power of an individual or a firm. Other things being the same, both individuals and firms in wealthier nations are better able to afford legal software and thus find the piracy of software relatively less attractive. In addition, the opportunity cost of being detected and punished for the possession of pirated software should be higher in more affluent societies. This is why we see software piracy is more rampant in developing countries. Higher prices of legal software make the production of pirated software more attractive. Thirdly concerned is institutional factor. The importance of institutional aspects in economic decision-making has been well recognized in the literature and the piracy of software is no exception. Other things being the same, more politically free nations might have lower rates of piracy because their citizens have access to an established and equitable system of rule of law and freely-elected representatives make it less likely that politicians are able to hand out undue favors. Software pirates have greater fear of exposure in politically free nations for support of this argument. More economically free nations may experience lower piracy rates due to lower prices of legal software from enhanced competition making illegal software less attractive. Fourthly, technological capabilities influence the propensities of pirates to copy software. Software products are hard to protect due to their peculiar attributes and, thus, the traditional instruments of protecting intellectual property such as patents seem ill-suited for these purposes. Still, modern technologies make piracy easier in terms of its speed, absence of geographic constraints, and the absence of the need for a middleman In other words, it is easy for someone situated in a remote location to write/sell pirated software and ship it almost costlessly and instantaneously via the Internet to almost any part of the world.

4 Ways Out in the Campaign Widespread and rampant software piracy leads to lost opportunities for the businesses and related sectors. Information technology is the driving force of economic and social progress. Through the visionary and balance of public policy, the government can promote a thriving technology industry for domestic and global economic benefits. The policy activities BSA aims to establish a dynamic international market in which software industry innovation, growth and prosperity can take place. Around the world, along with governments and multilateral organizations,Business Software Alliance strongly advocates software innovation, effective intellectual property rights protection, and network security, aiming to reducing trade barriers and other emerging technology policy questions. Given the psychological, economic, institutional and technological motivations to software piracy and differences across nations, adequate actions can be taken to check software piracy, which would have important implications for software producers, and more generally, for technology policy and eventually the pace of technological change and ecomonic development. Generally, we have two kinds of controls against software piracy. Firstly, preventive means. The purpose of preventive controls is to increase the costs of piracy through copy protection schemes, including software encryption and hardware locks. The target against piracy through preventive means can be achieved by the following

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steps: (1) to increase transaction costs—software incurs high installation and implementation costs. (2) to increase learning costs—learning how to use a specific software is costly and could be difficult. Secondly, deterrent means. In contrast to preventive means, the latter do not directly increase the cost of pirating software. The target is achieved by the perceived threat or fear of sanctions. Deterrent meanss include government-to-government negotiations, educational campaigns, and legal activity related to expanding domestic copyright laws and seeking to enforce those laws. Although allowing piracy may help firms to get some market share in the early stage of competition, it does not necessarily lead to higher profits. Hence, we believe that software firms are better o. protecting their products. The software protection environment is vital in the campaign against piracy. The environment first contains two main measurements: good laws of a nation covering software piracy, and effective enforcement of the laws by the government. Legal institutions are crucial in terms of outlining the set of rules for legal transactions and punishments for illegal acts. The strength and efficacy of these institutions would deter pirates. Legal institutions could affect both the buyers and sellers of pirated software. Stronger property rights protection, other things being the same, would deter pirates. Because of the attributes of software, the Internet has no boundaries, which makes it the ideal tool for distributing software products globally. However, nations have boundaries and software protection environments vary tremendously across nations. Different legal and economic systems lead to different evolution paths for software protection environments in different countries. Thus, international coordination is required to make sure there is no safe heaven for the pirates in the whole world. Socio-cultural differences across nations might crucially affect illegal activities in general and software piracy in particular. For instance, cultural norms might dictate attitudes towards protection of intellectual property.21 Besides shaping individual behavior, such differences can also affect government policies towards protection of proprietary information.

5 Conclusion According to BSA, installations of unlicensed software on PCs dropped in 54 of the 111 individual economies studied, and rose in only 19 in 2009. It is clear that antipiracy education and enforcement campaigns spearheaded in recent years by the software industry, national and local governments, and law enforcement agencies continue to have a positive impact in driving legal purchases and use of PC software. It is well recognized that a country’s stage of development and the quality of governance may have a major impact on the incidence of software piracy. Greater economic prosperity makes legal software more affordable on the one hand, and increases the opportunity cost associated with illegal acts on the other hand. More prosperous nations might also have better and strict monitoring mechanisms to check piracy. The risk of exposure by a free press in politically free nations will surely become a negative incentive machanism to software pirates. Consequently, the major step to take in the campaign against global software piracy is to increase public

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education and awareness. Reducing software piracy often requires a fundamental shift in the public’s attitude toward it. Public education is critical. Governments can increase public awareness of the importance of respecting creative works by informing businesses and the public about the risks associated with using pirated software and encouraging and rewarding the use of legitimate products. It is crucial for the dedeloped countries, and for the develpoing economies as well in the long term. As a new emerging economy, China still has a long way to go, for its own development, and for the responsibility it should bear as a large economy.

References 1. Yang, D., Sonmez, M.: Economic and cultural impact on intellectual property violations: A study of software piracy. Journal of World Trade 41, 731–750 (2007) 2. Piquero, N.L., Piquero, A.R.: Democracy and intellectual property: Examining trajectories of software piracy. Annals of the American Academy of Political and Social Science 605, 104–127 (2006) 3. Greenstein, S., Prince, J.: The diffusion of the internet and the geography of the digital divide in the United States. National Bureau of Economic Research, working paper # 12182 (2006)

Study of Bedrock Weathering Zone Features in Suntuan Coal Mine XiaoLong Li, DuoXi Yao, and JinXiang Yang School of Earth and Environment Anhui University of Science and Technology, Huainan, China [email protected] Abstract. Lithological characteristics, mineral composition, physical properties of water and physical and mechanical properties, weathering zone distribution and other factors of bedrock weathering zone in coal-seam roof determine the strength of its watertight performance, while its performance has a direct impact on impermeable overlying loose surface water aquifers as well as the possible collapse into the roadway. Therefore, we can prove and correctly evaluate the hydro geological conditions of bedrock weathering zone in the working surface, which has an important practical significance on reasonable safe mining coal rock pillar height and upper limit of mining, increasing the recovery rate of coal resources, fully developing and utilizing coal resources. And it provides a reliable basis for mine to achieve a sustained normal safety production. Keywords: coal-seam roof, bedrock weathering zone; mineral component; lithological characters.

1 Introduction In recently years many researchers at home and abroad have studied a lot on lithological characters, distribution rules and watertight performance in bedrock weathering zone. But compared with the focus attention- Cenozoic bottom aquifer ('the fourth below'), it is quite out of proportion. Coal mine is deeply buried in bedrock weathering zone of coal-seam roof, and has great difference in hydrology and engineering geology features with weathering zone. And also it is quite inconvenient for study and research to drill but to get imperfect core most of the cases in this area. Lithological characteristics, mineral composition, physical properties of water and physical and mechanical properties, weathering zone distribution and other factors of bedrock weathering zone in coal-seam roof, determine the strength of its watertight performance, while performance has a direct impact on impermeable overlying loose surface water aquifers as well as the possibility of collapse into the roadway. Therefore, we can prove and correctly evaluate the hydro geological conditions of bedrock weathering zone in the working surface, which has an important practical significance on reasonable safe mining coal rock pillar height and upper limit of mining, increasing the recovery rate of coal resources, fully developing and utilizing coal resources. And it also provides a reliable basis for mine achieve sustained normal safety production. The 7211working surface is the fourth fully-mechanized working face of the first area in 72 coal seams of 81 mining area in Suntuan Coal Mine and its original S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 330–335, 2011. © Springer-Verlag Berlin Heidelberg 2011

Study of Bedrock Weathering Zone Features in Suntuan Coal Mine

331

（

design Cap elevation is -250m, its Floor elevation is -315m, its dispersion is 65m.Its mineral seam is mainly 72 coal seams. The working surface inner fault F10 fall head 10 120m , F10-1 fall head 0 5m , DF10 fall head 0 8m is of northeast spread, and F10 crosses inclined the working surface. It set a large coal block height when designing it, thus overstocks a great deal of coal resources which causes serious resource damage. And it is seriously questioned of its technical economy rationality. Damaged resource has the following characters as high degree of prospecting, shallow buried depth, complete production system, and good mining technical conditions. Therefore, whether the coal block height is reasonable or not becomes one of the theoretical and technical difficulties to be solved in Suntuan coal mine. It shows, according to the data of 7211 working surface and its eleven drill holes around, that its Cenozoic loose bed thickness is 203.00 210.85m,its average thickness is 205.97m, its bedrock face elevation is -176.70 -184.99m, its average elevation is -179.89m. Generally, the working surface bedrock face elevation lessens gradually from southwest to northeast.

～

）

（

～ ）

～

（

～ ）

～

2 Data and Methods 2.1 Weathering Zone Lithological Characters and Mineral Components With drilling to get the core form 09 SHUI 3 drill in the working surface, it can be known that it mainly comprises sandstones and mudstones. Sandston: amaranth, small grain, mainly comprises quartz, feldspar, calcium cement. It is cross bedding and medium separation sorting. Its ridge is seriously damaged, its core is broken and becomes soft and mud state because of strong weathering. Its bottom is clay bank, small grain and mainly comprises quartz, feldspar, calcium cement. It is bedding stratification and medium separation sorting. Mudstone: clay bank, light gray partly, bulk, soft, easy- broken by weathering. Its bottom mudstone is clay bank or amaranth, bulk, soft core, and easy-broken. It takes six rock samples of 09 SHUI 3 drill to make x-radial diffraction and scanning electron microscope to make its rock-soil component and tiny proximate analysis. It is shown in Tab.1, Fig 1-2. Minerals in it are mainly quartz and feldspar filled with clay minerals which are mainly kaolin and kaolinite. Table 1. Weathering zone sample XRD qualitative analysis result table hole number

position

lithology sandstone sandstone

sample depth 206.80~207.00 209.50~209.70

Bedrock 09SHUI3

Weathering

mineral composition kaolin

kaolinite.

less than

more than

medium

medium

less than medium

mudstone

214.00~214.20

-

mudstone

215.50~215.70

medium

mudstone

217.30~217.50

-

Zone

medium more than medium less than medium more than medium

quartz

chlorite

calcite

others

medium

-

-

little

medium

-

-

-

-

-

-

-

-

little

-

-

little

medium

mica

tiny

medium tiny

332

X. Li, D. Yao, and J. Yang >677;7@    

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Fig. 1. Decency sandy putty rock sample XRD ingredient correspondence intensity chart

Fig. 2. Decency sandy putty rock sample scanning electron microscope

2.2 Water-Physical Properties and Physico-Mechanical Properties It has not conducted mechanical test with 09 SHUI 3 drill, but comparing water-physical properties and physico-mechanical properties in the Weathering Zone with that of mining area102 and referencing the experimental analysis data in 09 SHUI 1,SHUI 2, we think its rock is of low compression strength and soft, but it has good expansibility and certain water proof ability.

Study of Bedrock Weathering Zone Features in Suntuan Coal Mine

333

2.3 Distribution Characters in the Weathering Zone The thickness of the zone is determined by many factors as lithology and fracture development degree. The Various inspection holes wind oxidation zone depth of Suntuan Coal Mine is shown in Tab.2. Table 2. Various inspection holes wind oxidation zone depth data sheet 6WURQJ ZLQG R[LGDWLRQ ]RQH +ROH QXPEHU

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According to its data, zone of weathering depth of the field is 15m; oxidation zone depth is 25m. Its rocks are mainly khaki, motley, and taupe. When they are decayed rocks, there is often full of crevice water in the fracture, but its degree mainly depends on breakover degree and tiny fracture development. The rocks are soft, mostly fragments, fracture development and low strength. The study, with data statistic analysis of 7211 working surface and its eleven drilling holes around, draws up bed rock surface ancient topographic map, elevation contour map and weathering zone allocation plan, as are shown in Tab.3, picture 3, 4. Table 3. 7211 working surface and nearby drill hole exposition “weathering zone” thickness statistical table 1XPEHU

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Fig. 3. 7211 bedrock surface ancient landform chart

Fig. 4. 7211 bedrock surface elevation isograms

3 Conclusions (1) Minerals in it are mainly quartz and feldspar filled with clay minerals with certain water proof ability. (2) Ancient landform is mainly low in southeast and high in northwest which has an obvious influence with the weathering zone development thickness change. Terrain goes from high to low from north to south, and thickness in the weathering zone slightly increases. It deposits gravel layer and claypan with different thicknesses in lower area of ancient landform, and these two have good water-resisting property.

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(3) From lithology and water-physical properties and physico-mechanical properties of working surface Weathering Zone it can be known that its rock has low compression strength and is soft, but it has good expansibility and certain water proof ability. It can function as resisting caving zone and water flowing fractured zone, which is very beneficial to lessen waterproof coal rock pillar.

References 1. He, J.: Study of engineering-geological features of weathered zone of Wugou Coal Mine’s base rock. Mining Engineering 24(11) (June 2008) 2. Xuan, Y.-q.: Study on the weathered damage attributes of rock and the law of reduction for coal column protection. Chinese Journal of Rock Mechanics and Engineering 24(11) (June 2005) 3. Xuan, Y.: The possibility study of increasing the upper limit in combined working face under the thick loose layer containing water. Journal of Anhui University of Science and Technology 20(1), 42–45 (2000) 4. State Bureau of CoalIndustry. In: Retaining Coal Column of the Building, Water Body, the Railway and the Main Mine Tunnel and Exploitation Rules of the Coal Pressed. China Coal Industry Publishing House, Beijing (2000) 5. Yang, B.: The testing study of the key technology safely mining coal seam in weathered zone. Journal of China Coal Society 28(6), 608–612 (2003) 6. Yang, B.: Examination and study of retaining sands resisting coal column under the moderate water-bearing layer. Journal of China Coal Society 27(4), 342–346 (2002)

Mercury Pollution Characteristics in the Soil around Landfill JinXiang Yang, MingXu Zhang, and XiaoLong Li The School of Earth and Environmental Anhui University of Science and Technology, Huainan Anhui, China [email protected]

Abstract. In recent years, landfill and incineration of waste is considered a new mercury pollution, which is paid widespread attention by domestic and foreign scientists. This paper studies mercury pollution Characteristics in the soil around Landfill taking landfill in Huainan City for an example and using AMA 254 Advanced Mercury Analyzer produced by US LECO Company. The result shows that: mercury content distribution in surface soil around landfill has the certain laws: S50(0.0411ppm)> S20(0.0345)>S100(0.0257), and the distribution of surface soil in different directions is as follows: WS (0.0525ppm) >W(0.0441ppm)>WS (0.0255ppm)>ES(0.0218ppm); The vertical distribution is as follows: mercury content in the southeast increased with increasing depth and the rest direction decreases with depth increasing.

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Keywords: landfill, soil, mercury.

1 Introduction After outbreak of "Minamata" disease which shocked the world in the 50’s, Mercury, as a global pollutant, has caused widespread attention and study. In recent years, landfill and incineration of waste is considered a new mercury pollution, which is paid widespread attention by domestic and foreign scientists and the relevant government departments. Europe and other developed countries attach great importance to mercury pollution and release problems of landfill. From the 1980s, the U.S. EPA and other agencies have carried out research work in this area. Research staff of Oak Ridge National Laboratory (ORNL) surveyed on atmospheric mercury concentrations of several landfill in the Florid USA, the result showed that mercury concentrations of downwind in the atmosphere is usually 30 to 40 times of upwind or more[1-2]. Li Zhonggen and others analyzed Mercury (Hg) in waste and soil at four municipal solid waste (MSW) landfills in Guiyang and Wuhan City, the result showed that there is Hg pollution risk associated with MSW land filling [3]. Ding Zhen, Wang Wenhua and others determined with an AMA 254-Automatic Solid/Liquid Mercury Analyzer in topsoil samples from the Laogang Landfill, and it is shown that mercury is released in the form of gaseous mercury [4]-[7]. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 336–340, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Materials and Methods 2.1 Materials Soil samples are collected from Datong landfill in Huainan City. The principle of distribution: according to geographical and terrain conditions of landfill, taking it as the center, we lay a line in the West (W) and East South (ES)each , two lines in southwest (WS , WS ); we arrange three points in each line in light of different distances from the landfill , namely 20m(S20), 50m(S50), 100m(S100), and taking 20cm as a profile unit we set three sections of 20cm 0-20cm ,20-40cm and 40-60cm in each point.

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2.2 Methods (1) Sample pretreatment The soil samples are put in a ventilated, cool and dry place to naturally air dry. After dried, the stones, plant roots and other debris are picked out from the samples, and then according to quartering, the samples are discard the excess part to retain about 300 g or so. Finally the samples are put in agate mortar for grinding, passed through 200 eye nylon screen mesh for screening, and sealed into zip lock bag to prepare for determination. (2) Determination of mercury Mercury content is determined with an AMA 254 Advanced Mercury Analyzer produced by US LECO Company. This instrument is a unique Atomic Absorption Spectrometer that uses an element-specific mercury lamp to emit light at a wavelength of 253.7 nm and a silicon UV diode detector to detect mercury content. This method does not require sample digestion, and the results are not affected by matrix.

3 Results and Analysis 3.1 Analysis of Mercury Content in Surface Soil Analysis results of mercury content in surface soil near the landfill are shown in Table 1, and using EXCEL software for statistical analysis, the results are shown in Figure 1 From Table 1 and Figure 1, it is known that mercury content distribution in surface soil around landfill has the certain laws. The mercury concentration in surface soil at 50m away from the garbage dump is higher than that at the 20m and 100m, the order is: S50 (0.0411ppm)> S20 (0.0345ppm) >S100 (0.0257ppm); and mercury concentrations in surface soil near the landfill in different directions are as follows: WS (0.0525ppm)> W (0.0441ppm)> WS (0.0255ppm)> ES(0.0218ppm). But the surface soil is not contaminated by mercury.

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J. Yang, M. Zhang, and X. Li Table 1. Mercury content in surface soil near the landfill (Unit: ppm)

Sampling Point

Mercury Content of Sampling Sites at Different Distances

Position

Average Value

S20

S50

S100

0.0352

0.063

0.0342

0.0441

0.0284

0.0305

0.0177

0.0255

0.055

0.0499

—

0.0525

ES

0.0193

0.0208

0.0253

0.0218

Average Value

0.0345

0.0411

0.0257

0.0360

W

Ⅰ WSⅡ WS

Content ppm

）0.06 0.05 （0.04 0.03 0.02 0.01 0 W

Ⅰ

WS

Ⅱ

WS

ES Position

Fig. 1. Mercury content distribution diagram in surface soil near the landfill

3.2 Vertical Analysis of Mercury Content According to mercury content in the different section soil, using EXCEL for the vertical analysis, the results were shown in Figure 2. From Figure 2, it could be seen that the mercury content of different sampling points in the rest direction decreases with depth increase, in addition to mercury content of the three sampling points in the southeast increases with increasing depth and abnormal occurring at the place of 50m in the southwest No.

Ⅰ.

Mercury Pollution Characteristics in the Soil around Landfill

Ⅰ Ⅰ WSⅠ100

0.14

WS 20 WS 50

0.12 0.1 Content(ppm)

339

W20

0.08

W50 W100

0.06

ES20 0.04

ES50

0.02

ES100

Ⅱ Ⅱ

WS 20

0 0-20

20-40

Profile

40-60

WS 50

Fig. 2. Vertical analysis diagram of mercury content in the soil

4 Conclusions (1) mercury content distribution in surface soil around landfill has the certain laws: S50(0.0411ppm)> S20(0.0345)>S100(0.0257). The main reason may be that mercury in the form of particulate matter and gaseous contaminates soil around with wind migration and the influence range is about 50m Secondly, mercury distribution of surface soil in different directions is as follows: WS (0.0525ppm) >W(0.0441ppm)>WS (0.0255ppm)>ES(0.0218ppm).The main reason may be due to the influence by the dominant wind direction in Huainan where dominant wind direction is south-east of Huainan in summer and is northeast in winter. (2) The vertical distribution of mercury content in the soil landfill around is as follows: mercury content in the southeast increases with increasing depth. The main reason may be that the underlying soil in southwest is coal gangue which makes the mercury distribution in the soil show this trend in the southeast. And the mercury content of different sampling points in the rest directions decreases with depth increase, this result shows that mercury pollution in the soil around the landfill is mainly concentrated in the topsoil. Because the work time is short and the amount of data is limited, the study on mercury pollution characteristics is not comprehensive, and other heavy metals pollution in the soil near landfill has not yet been analyzed. Therefore, the research work in future needs further study.

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References 1. Pukkala, E., Pnk, A.: Increased incidence of cancer and asthma in houses builton a former dump area. Environ. Health Perspect. 109(11), 1121–1125 (2001) 2. Vrijheid, M., et al.: Chromosomal congenital anomalies and residen -ce near hazardous waste landfill sites. The Lancet 9303(359), 320–322 (2002)

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3. Li, Z.-g., Feng, X.-b., Tang, S.-l., et al.: Distribution Characteristics of Mercury in the Waste, soil and Plant at Municipal Solid Wastelandfills. Earth and Environment 34(4), 11–18 (2006) (in Chinese) 4. Ding, Z.-h., Wang, W.-h., Tang, Q.-h., et al.: Release of Mercury From Laogang Landfill, Shanghai. Earth and Environment 33(1), 6–10 (2005) (in Chinese) 5. Bartolacci, S., Buiatti, E., Pallante, V., et al.: A study on mortality around six municipal solid waste landfills in Tuscany Region. Epidemiol. Prev. 29(5-6 suppl.), 53–56 (2005) 6. Tang, Q.-h., Ding, Z.-h., Wang, W.-h.: Pollution and Transference of Mercury in Soil-Plant System of Different Landfill Units. Shanghai Environmental Sciences 22(11), 768–775 (2003) (in Chinese) 7. Chang, Q.-s., Ma, X.-q., Wang, Z.-y., et al.: Pollution characteristics and evaluation of heavy metals in municipal rubbish landfill sites. Journal of Fujian Agriculture and Forestry University (Natural Science Edition) 36(2), 194–197 (2007) (in Chinese)

The Research on Method of Detection for Three-Dimensional Temperature of the Furnace Based on Support Vector Machine Yang Yu1, Jinxing Chen1, Guohua Zhang2, and Zhiyong Tao2 1

School of Information Science & Engineering, Shenyang Ligong University, 110159 Shenyang, China 2 Shenyang Artillery Academy of PLA, 110162 Shenyang, China [email protected], [email protected]

Abstract. SVM is a rising in common use learning technology base on Statistical Learning Theory. In view of the variety of the changes of burning flame in large-scale boiler, in order to master the status of the furnace flame in real time. In this paper, it introduces the SVM network absorb the basic method of flame-picture's temperature, to study thoroughly discussed about the SVM network model, and puts forward an improved SVM network method, as for the method to calculate three-dimensional temperature field, which has many advantages to the traditional optimization method. Taking the SVM network using to test the three-dimensional temperature field in the furnace is feasible by the simulation studies and the experimental results. Keywords: SVM, Three-dimensional temperature field, Test.

1 Introduction The flame burning process in the boiler furnace taking place in a large space within the constantly fluctuating, and has obvious three-dimensional characteristics of the physical and chemical processes. The stability of the furnace flame directly affects the safety of productions. Therefore, testing the three-dimensional temperature field in the furnace has important practical significance [1-2]. In this paper, taking CCD (charge-coupled device) camera as a two-dimensional radiation energy distribution of the furnace sensors, receiving the heat radiation signal of three-dimensional in the furnace, taking further research in the BP algorithm. The CCD camera under the visible light received by the RGB three-color signal value as the three SVM network input blackbody calibration furnace 50 groups of red visible RGB three-color signal values corresponding to the temperature T value as output to train the SVM network and temperature was established SVM network. SVM predicted temperature of the network model results are analyzed, and SVM using wellestablished network of two-dimensional image of the flame radiation temperature for the strike, combined with the regular method to complete the three-dimensional S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 341–346, 2011. © Springer-Verlag Berlin Heidelberg 2011

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combustion flame temperature field reconstruction. Finally, the trained SVM which is simulated and analyzed verifies that the results are ideal, which also proves that SVM network using to obtain three-dimensional temperature distribution is feasible.

2 Principle of SVM Network Temperature Measurement The basic idea of SVM can be summarized as: first transform the input space by a nonlinear transformation into a high dimensional space, and then strike a new space in the optimal linear separating hyperplane, which is a nonlinear transformation inner product by defining the appropriate function to achieve. Training sample set of input space dimension q , In the input space to feature space,

{ϕ ( x )}

l

j

j =1

represents a set of nonlinear transformation, l that the dimension of feature

space. Act as decision-making side of this hyperplane can be defined as Eq1 a feature space. l

∑ω ϕ ( x) + b = 0 j =1

When ω = [b, ω1 , ω2 ,

j

(1)

j

, ωl ] , Φ ( x ) = ⎡⎣1, ϕ1 ( x ) , ϕ2 ( x ) , T

, ϕl ( x ) ⎤⎦ , the decision T

hyperplane can be further simplified as:

ωT Φ ( x) = 0

(2)

At this point, the objective function: K ( xi , x j ) = Φ ( xi )iΦ ( x j )

(3)

The dual form becomes: n

Q (α ) = ∑ α i − i =1

1 n ∑ αiα j yi y j K ( xi i x ) 2 i =1

(4)

If α i* is the optimal solution, then the algorithm of the other conditions are unchanged, but n

ω * = ∑ α i* yi Φ ( xi )

(5)

i =1

The corresponding decision function becomes: ⎧ n ⎫ f ( x ) = sgn ⎨∑ α i * yi K ( xi i x ) + b* ⎬ ⎩ i =1 ⎭

(6)

SVM output is some linear combination of the middle layer nodes, each corresponding to middle layer nodes in the input sample and a support vector inner product, obtained form the decision-making function is similar to a neural network, therefore, be called support vector network, as shown in Figure 1.

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K ( x1, x)

x1

α 1 y1

K ( x2 , x)

x2 xm−1

• • •

• • •

α 2 y2 αh−1yh−1

sgn (

∑

y

)

K ( xh−1, x)

xm

αh y h

K ( xh , x)

Fig. 1. Schematic diagram of support vector machines

3 SVM Network Model of Temperature 3.1 Sample Selection and Processing

With blackbody furnace, the use of temperature control system, intake of different temperature thermal radiation burn the image. A total of 50 groups for red (R), green (G), blue (B) three-color signal value and the corresponding relationship between the temperature T, the sample data in Table 1. Table 1. Blackbody calibration furnace sample data of 50 groups R

700 135 141 154 173 180 182 186 183 190 192 193 194 194 198 200 201 201 204 206 208 210 211 214 216

G

52

58

62

75

92

98

56

65

103

79

84

85

90

98

103 104 107 112 118 115 148 112 115 139 152

B

1

3

3

9

13

14

28

33

37

39

38

40

36

11

19

28

11

12

50

43

20

13

17

32

55

T/C 700 732 781 797 876 884 894 905 913 927 930 938 945 952 962 971 980 984 994 1008 1011 1020 1022 1033 1049 R

217 220 221 225 227 234 235 237 240 242 247 249 252 255 252 255 255 255 255 255 255 255 255 255 255

G

155 160 166 170 185 134 197 200 176 146 146 150 167 171 183 190 198 201 207 215 220 223 227 228 231

B

57

59

58

60

61

23

64

66

55

36

28

32

51

61

75

77

80

81

82

83

84

85

86

87

89

T/C 1052 1068 1072 1090 1105 1125 1138 1149 1152 1167 1178 1182 1198 1205 1216 1227 1249 1255 1260 1271 1283 1305 1316 1321 1330

3.2 The Choice of Kernel Function

Selected kernel function in this article is Gaussian kernel function (also known as RBF kernel function), and its representation as:

⎧⎪ x − xi K ( x, xi ) = exp ⎨ − σ2 ⎩⎪

2

⎫⎪ ⎬ ⎪⎭

(7)

In the formula: σ is the width of the Gaussian distribution. 3.3 SVM Network Training

This choice SVM network input nodes is 3, the output nodes is 1. Characteristics of the network using SVM, we construct the 3-layer SVM network, input layer of the

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three, namely R, G, B three color values, the output layer one, the flame radiation images of the two-dimensional temperature T. Network training are listed in Table 1. Kernel parameter (g) and the penalty factor (c) is the SVM network are two important parameters. This training process in the network range of the c value is set to -10 to 10, g value range is set to -5 to 5. Obtained by training SVM parameter optimization of the network diagram shown in Figure 2.

Fig. 2. SVM parameter optimization map

3.4 SVM Network Model Predictions of Temperature

In the SVM network training is completed, its prediction accuracy for the simulation analysis. Specific simulation results shown in Figure 3. -3

4

• • • • •

x 10

• • • • • 3

3 2

2

Absolute error

• • • •

Relative error

1

0

-1

0

-1

-2

-2

-3

1

0

5

10

15

20

25 • •

Sample

30

35

40

45

50

-3

0

5

10

15

20

25 • •

30

35

40

45

50

Sample

(a)SVM network plans relative prediction error (b) SVM network prediction absolute error map Fig. 3. The simulation results of prediction accuracy

Figure 3(a) SVM network prediction for the relative error curve, the curve can be seen that the prediction of the relative error of less than 0.4%, the prediction accuracy is very high. Figure 3(b) is the absolute prediction error of SVM network graph can be seen from the figure the prediction of the absolute error of less than 3 . Sum can be drawn, after training the SVM network has good prediction accuracy.

℃

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4 Simulation Experiments and Results Color CCD camera for the furnace flame combustion at a particular moment shown in Figure 4. On Figure 4 from the installation of heating in the north of the city center of Beijing, Shunyi 1 # 90 tons of large coal-fired hot water boiler. Flame color CCD camera detector arrangement with the boiler corners. Monitoring system grate furnace combustion space is within the area above 2.1m. By the trained SVM network to strike a flame temperature part of the image area (first 10 lines of the first 10 columns) cell corresponds to the temperature shown in Table 2.

Fig. 4. CCD camera to get the furnace flame picture Table 2. SVM method to strike the flame image in part (first 10 lines of 10) regional units of the temperature unit:

℃

Temperatue/oC

Fig. 5. SVM-based network to strike a flame temperature of the third layer of three-dimensional surface chart

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Using regularization method [6] completed a three-dimensional temperature field reconstruction to achieve the furnace. Boiler furnace combustion flame temperature corresponding to the third floor of the three-dimensional surface as shown in Figure 5.

5 Conclusion The CCD cameras use two-dimensional radiation energy distribution as a sensor, to receive from the three-dimensional furnace heat radiation signal, according to a new model of radiation imaging two-dimensional temperature images of flame and threedimensional relationship between combustion temperature equation, the regularization of the reconstruction methods dimensional combustion flame temperature field reconstruction. Two-dimensional image of the flame temperature distribution of radiant energy to strike, the introduction of SVM temperature measurement network, with 50 groups of blackbody calibration furnace sample data for training SVM network. After the network with the trained SVM two-dimensional images of flame radiation temperature for the strike, combined with the regular method to complete the three-dimensional combustion flame temperature field reconstruction. Through the combustion flame temperature field reconstruction of three-dimensional, and further realized the boiler safety, economic, clean operation, to guide the optimization of boiler combustion is of great significance.

References 1. Zhou, H.C., Han, S.D., Sheng, F., Chu-Guang, Z.: Numerical Simulation on a Visualization Monitoring Method of Three-Dimensional Temperature Distribution in Furnace. Power Engineering 23, 2154–2156 (2003) 2. Chun, H.: Furnace flame detection principles and techniques of visual. Science Press, Beijing (2005) 3. Wang, S.Z.: Support vector machines and application. PhD thesis, Harbin Institute of Technology, 19-24 (2009) 4. Deng, N.Y., Tian, Y.J.: A new data mining method - support vector machine. Science Press, Beijing (2004) 5. Peng, B.: Support Vector Machine Theory and Engineering Application. Xidian University Press, Xi’an (2008) 6. Zhou, H.C., Han, S.D., Shen, G.F., et al.: Visualization of three-dimensional temperature distributions in a large-scale furnace via regularized reconstruction from radiative energy images: Numerical studies. J. of Quantitative Spectroscopy and Radiative Transfer 72, 361–383 (2002)

Study on Wave Filtering of Photoacoustic Spectrometry Detecting Signal Based on Mallat Algorithm Yang Yu1, Shuo Wu1, Guohua Zhang2, and Peixin Sun2 1 School of Information Science & Engineering, Shenyang Ligong University, 110159 Shenyang, China 2 Shenyang Artillery Academy of PLA, 110162 Shenyang, China [email protected], [email protected]

Abstract. According to the concept of wavelet, the thesis analyse the peculiarity of wavelet, and applies Mallat algorithm of wavelet method to treat the photoacoustic signals of water content in oil. Mallat algorithm is a kind of multi-resolution wavelet transform. In large scale space roughly corresponds to the signal profile,in small scale space roughly corresponds to the signal details. This algorithm is especially suitable for processing seismic signals, photoacoustic signals, voice signals and other non-stationary signal, and the ideal effects of noise removal and filtering have been achieved for the photoacoustic signals through this method. Keywords: Mallat algorithm, optical wavelet transform, filtering, noise removal.

1 Introduction With the technological progress, there are more and more the signal processing methods. The choices of the signal processing methods are closely connected with the characteristics of the signals to be tested, so even the same method can results in huge discrepancies for the processing effects of different signals to be tested. To achieve the expected signal processing effects, the researchers are always trying to study the effective methods for processing all kinds of signals. The signal processing has experienced the course from imitation to number and from definitive signals to random signals, and it is striding towards the signal processing age with the unsteady and non-gauss signals as main study objects and with the non-linear and uncertain characteristics as main study features.

2 The Wavelet Algorithm Study The basic idea of the wavelet analysis is utilizing a group of functions with local characteristics to denote or approach other functions. This group of functions is called “wavelet function system”, which is formed by a series of extension and translation of the wavelet functions, and the wavelet transform analyzes the signals on the basis of the wavelet through extension and translation. The wavelet signals’ function group is {ψ a ,b } , and the expression is the Eq. 1. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 347–352, 2011. © Springer-Verlag Berlin Heidelberg 2011

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1

ψ a ,b ( t ) =

|a|

⎛t −b ⎞ ⎟ ⎝ a ⎠

ψ⎜

a , b ∈ R, a ≠ 0

(1)

In Eq.1, a is an extension factor, b is a translation factor. 2 Suppose f ( t ) ∈ L ( R ) , the continuous wavelet transform is:

W f ( a, b ) =< f ,ψ a ,b >=

1

∫ |a|

+∞ 1 ⎛t −b⎞ ⎛t −b⎞ f ( t )ψ ⎜ f ( t )ψ ⎜ ⎟ dt = ⎟dt ∫ −∞ a |a| ⎝ ⎠ ⎝ a ⎠

+∞

−∞

(2)

The opposite Eq. f ( t ) recomposed by W f ( a, b ) is:

f (t ) =

1 Cψ

+∞

+∞

−∞

−∞

∫ ∫

W f ( a, b )ψ a ,b ( t )

dadb a2

(3)

The Cψ expression is: b Cψ = ∫

+∞

−∞

2

ψˆ (ω ) ω

−1

dω

(4)

The continuous wavelet transform is mainly used for theoretic analyses and derivations, and in the actual signal processing course, we need the discrete wavelet transform more. Here the so-called discretization refers to the continuous measure factor a and translation factor b , but not the time variable t . First discretize the measure factor a and get the binary wavelet and the binary wavelet transform. Then discretize the time center factor b in the binary integral way. The continuous wavelet function is: 1

ψ a,b ( t ) =

a

⎛t −b⎞ ⎟ ⎝ a ⎠

ϕ⎜

b ∈ R, a ∈ R +

(5)

In the Eq. 5, discretize the measure and the translation parameter of the continuous wavelet transform. When j and k are integral numbers, the discrete wavelet is: 1

ψ j,k (t ) =

a0j

−j ⎛ t − kb0 a0j ⎞ −j ⎟ = a02 ψ ( a0 t − kb0 ) j a 0 ⎝ ⎠

ψ⎜

(6)

The corresponding discrete wavelet transform is: −j

W j ( j , k ) = f ,ψ j , k a02

∫

+∞

−∞

−j

f ( t )ψ j , k ( t ) dt = a02

∫

+∞

−∞

f ( t )ψ ( a0− j − kb0 )dt

(7)

If there are positive value constants A and B , and 0 < A ≤ B < ∞ , f ( t ) ∈ L2 ( R )

A f ≤ ∑∑ f ,ψ j , k j

2

≤B f

(8)

k

Therefore ψ j , k forms one of the wavelet frame of L2 ( R ) , in which A and B are the frame border.

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3 The Wavelet Mallat Algorithm The multi-resolving power signal analysis with different measures is to show the signal features under the condition of different resolving powers, so the essence of multiresolving power is to resolve the signals on different space layers. The huge measure space corresponds with the rough appearance of the signals, the small measure space corresponds with the tiny parts of the signals. With the constant changes of the measure spaces, we can observe the signals from rough to precision for respective measure spaces, and this is the thought of the multi-resolving power analysis. The essence of the multi-resolving power analysis is a series of subspaces in L2 ( R ) meeting some specific requirements. Now it can be defined as follows: the

multi-resolving power analysis in L2 ( R ) space refers to the space sequence

{V , j ∈ Z } j

meeting the following requirements, which has the monotonous,

progressive perfect, flexible, stable translation and other characteristics. From the definition of the multi-resolving power analysis, we can obtain the standard orthogonal basis of the V j space: j − ⎧ −j ⎨φ j , n ( x ) = 2 2 φ ( 2 x − n ) , ⎩

φ ( x ) ∈ V0 ∈V−1

Because basis

{

and

⎫ n∈ Z⎬ ⎭

there

is

the

(9) standard

orthogonal

}

2φ ( 2 x − n ) , n ∈ Z , so there must be a factor column {hn , n ∈ Z } ∈ L2 ( Z ) ,

and this is the measure equation of the wavelet. Suppose φ ( t ) and ψ ( t ) are the measure function and the wavelet factor of the function f ( t ) approached by the resolving power 2 j , the discrete C j f (t )

approaching

and

the

detail

∞

as C j f ( t ) = ∑ c j , k φ j .k ( t ) and D j f ( t ) = −∞

part

∞

∑d −∞

ψ

j ,k

j .k

D j f (t )

can

be

expressed

( t ) , in which d j , k and c j , k are the

measure factor and the wavelet factor with the resolving power 2 j . According to Mallat Algorithm, C j f ( t ) is resolved as the summation of the rough

image C j −1 f ( t ) and the detail image D j −1 f ( t ) , and the expression is: C j f ( t ) = C j −1 f ( t ) + D j −1 f ( t )

(10)

Replacing the Eq.11 and Eq.12 into Eq.10 can form the Eq.13: C j −1 f ( t ) =

D j −1 f ( t ) =

∞

∑C

m =−∞

∞

∑d

m =−∞

φ j −1, m ( t )

(11)

ψ j −1, m ( t )

(12)

j −1, m

j −1, m

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∞

∑C

m =−∞

φ j −1, m ( t ) +

j −1, m

∞

∑D

m =−∞

ψ j −1, m ( t ) =

j −1, m

∞

∑C

m =−∞

φ j,m (t )

j .m

(13)

Then for the tower-style resolving course analysis of Mallat Algorithm, the expression is: C 0 ( n ) → C1 ( n ) → "" C J −1 ( n ) → C j ( n ) ↓

↓

D ( n) 1

↓

D ( n) 2

D

(14)

J −1

( n)

C 0 ( n ) is the result data of the experiment; C j ( n ) and D j ( n ) are called “discrete approaching” and “discrete detail”. C j ( n ) = C j −1 ( n ) ∗ H = h ( l − 2n )C j −1 ( l )

∑ l∈Z

is the low frequency component of the original data, j j −1 j −1   is the high frequency component, D ( n ) = C ( n ) ∗ G = ∑ g ( l − 2n ) C ( l )

and J is

l∈ z

the biggest resolving frequency. H = h ( l ) , l ∈ Z and G = { g ( l ) , l ∈ Z } means: the mirror filter of the discrete

{

}

filter H and G . Though this kind of algorithm is very convenient, it requires that the point number the original data C (0) ( n ) must be a multiple of 2( N ) , and the resolving data point becomes half every time after resolving. Then the analysis result of the optical spectrum becomes discontinuous, and this brings some difficulties for the analysis of the optoacoustic signal result. Therefore this article adopts the improved Mallat algorithm to filter the optoacoustic signals, and the expressions are: C( j) ( n) =

D( j ) ( n ) =

l ( j ) −1

∑ h ( ) ( l ) C ( ) ( n − 1) j

j −1

(15)

l =0

l ( j ) −1

∑ g ( ) ( l ) C ( ) ( n − 1) j

j −1

(16)

l =0

4 The Noise Removal Example Analysis of the Optoacoustic Signals This article applies the improved Mallat algorithm into the optoacoustic signal processing of detecting water in oil by the optoacoustic optical spectrum. The study object of optoacoustic optical spectrum detection is the course that the substance absorbs light, get stimulated and transit to return its original state through nonradiation. Therefore the photons having been absorbed, annihilated or interacted can also be detected and analyzed.

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The detecting platform for the optoacoustic optical spectrum to detect the water content in oil consists of laser, chopper, preamplifier, ARM9 data processing module, filter, phase-locked amplifier, microphone, and so on. By the experiment platform, a great deal of oil-in-water optoacoustic data is collected, and because of the huge amount, a part of the data is listed in Table 1. Table 1. The Oil-in-Water Optoacoustic Data Unit: v Collection number of times 1 2 3 4 5 6 7 8 9 10 11

Optoacoustic data 0.957031 0.957071 0.95459 0.949707 0.952158 0.952153 0.959473 0.959493 0.964356 0.961911 0.961914

Collection number of times 12 13 14 15 16 17 18 19 20 21 22

Optoacoustic data 0.969238 0.97168 0.96923 0.974141 0.974121 0.97168 0.981445 0.966797 0.966787 0.959473 0.952148

This article adopts the Eq.15 and Eq.16 to filter and remove the noise for the j optoacoustic data collected in this article. h ( ) shows the factor of the low pass filter in the computing course; g ( j ) shows the factor of the high pass filter in the computing course; l ( j ) shows the data point number of the filter; as the resolving number of

times increases once, the l ( j ) value doubles correspondingly, and this kind of improved algorithm is suitable for processing the optoacoustic signals more. The optoacoustic data curve before filtering is shown in Fig.1.

Fig. 1. The Optoacoustic Optical Spectrum Data Curves before Filtering

Collecting the oil-in-water optoacoustic signals by the microphone and amplifying the optoacoustic signals to about 0.9V by the preamplifier, we can know that a lot of noise signal curves are mixed in this signal curve by observing Fig.1. The noise signal curves can influence the transformed results a lot, and this kind of influence can lower the precision of the optoacoustic optical spectrum experiment results finally.

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The optoacoustic data curves obtained after the Mallat algorithm filter is shown in Fig.2. The optoacoustic curves after the wavelet Mallat algorithm filter are much clearer. There is less influence of the noise curves on the optoacoustic curve result, and such curves can decrease the influence on the water content in oil transform results and be beneficial to enhancing the precision of the experiment results a lot.

Fig. 2. The Optoacoustic Optical Spectrum Data Curves after Filtering

The transform from the optoacoustic curves to water content in oil is realized by the Eq. 17. S = CPL Nσ

(17)

In the Eq.17, S shows the voltage value of the optoacoustic signals; PL shows the luminous frequency of the semiconductor laser; N shows the volume fraction of the water content in the sample oil; σ shows the water optical spectrum absorbing factor; C shows the cell constant of the photocells and depends on all the factors such as the sensitivity of the microphone and the geometric structure of the photocells. By Fig.1 and Fig.2, the actual filtering experiment proves that the Mallat algorithm based on orthogonal wavelet transform has very good filtering and noise removal effects for the optoacoustic signal processing. This kind of filtering and noise removal processing lays a foundation for the processing of the experiment platform results, and this example also proves that this kind of wavelet transform algorithm is practical for applying in the optoacoustic optical spectrum detection.

References 1. Zheng, J.: Research on retrieving and analysis of the characteristic information of photoacoustic signal. South China University of Technology 2. Han, L., Tian, F.: Optical implementation of Mallat algorithm. Optics and Precision Enginering (8) (2008) 3. Li, C.H., Hu, B.J.: Radar Target Signal Denoising Based on Wavelet Mallat. Algoritlunm Mechatronics (16) (2010) 4. Liu, J.C.: Research on application of seismic signal de-noising based on Mallat algorithm. HuNan University

Ontology-Based Context-Aware Management for Wireless Sensor Networks Keun-Wang Lee and Si-Ho Cha* Dept. of Multimedia Science, Chungwoon University San 29, Namjang-ri, Hongseong, Chungnam, 350-701, South Korea {kwlee,shcha}@chungwoon.ac.kr

Abstract. Wireless sensor network (WSN) can provide the popular military and civilian applications such as surveillance, monitoring, disaster recovery, home automation and many others. All these WSN applications require some form of self-managing and autonomous computing without any human interference. Recently, ontology has become a promising technology for intelligent contextaware network management. It may cope with various conditions of WSNs. This paper describes an ontology-based management model for context-aware management of WSNs. It provides autonomous self-management of WSNs using ontology-based context representation, as well as reasoning mechanisms. Keywords: Ontology, Context-Aware, Self-Management, Network Management, Wireless Sensor Network.

1 Introduction Network management is the process of managing, monitoring, and controlling the behavior of a network. Wireless sensor networks (WSNs) pose unique challenges for network management that make traditional network management techniques impractical [1]. WSN consists of a large number of small sensor nodes having sensing, data processing, communication, and ad-hoc functions. WSNs have critical applications in the scientific, medical, commercial, and military domains. Examples of these applications include environmental monitoring, smart homes and offices, surveillance, and intelligent transportation systems [2]. WSNs are characterized by densely deployed nodes, frequently changing network topology, variable traffic, and unstable sensor nodes of very low power, computation, and memory constraints. These unique characteristics and constraints present numerous challenging problems in the management of WSNs which are not encountered in the traditional wireless networks [3][4]. The management of WSNs requires to be lightweight, autonomous, intelligent, and robust [5]. A network management system needs to handle a certain amount of control messages to cope with various conditions of the network. With WSNs, it is extremely important to minimize the signaling overhead since the sensor nodes have limited battery life, storage, and processing capability. Given the dynamic nature of *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 353–358, 2011. © Springer-Verlag Berlin Heidelberg 2011

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WSNs, an adaptive management framework that autonomously reacts to the changes in the network condition is required. To do this, We had proposed and implemented the sensor network management (SNOWMAN) framework [6] employs the policybased management (PBM) approach for letting the sensor nodes autonomously organize and manage themselves. The SNOWMAN framework displayed smaller energy consumption for network management and longer network lifetime than the existing schemes for practical size network. In the SNOWMAN framework, sensor nodes are managed by policy information base (PIB). It is to dynamically respond to specific events by letting the sensor nodes make local decisions by themselves using the policies. However, it may not cope with various conditions of WSNs. Therefore, it is necessary to introduce more intelligent and context-aware management mechanisms so that the sensor nodes can adapt themselves to changing situations. These days, ontology has become a promising technology and it seems that it may be used in the intelligent context-aware approach for network management [7]. With the advance of context-aware computing, there is an increasing need for developing context models to facilitate context representation and reasoning. Ontologies allow the network management system to organize the information gathered from various sensors and infer from the information and find out the status of the network. Therefore, the appropriate management actions for WSN can be automated. In addition, ontologies can automate information sharing and processing among WSN's members, and allow WSN management systems to interwork between them by modeling and organizing WSN environments clearly. This paper presents an ontology-based context-aware management model to automatically manage WSNs by applying ontology-based languages, and provides a possible scenario to implement autonomic self-management using the proposed ontology-based model. The rest of the paper is organized as follows. Section 2 discusses the application of ontology and related languages, and Section 3 introduces the proposed ontology-based model. The context reasoning is discussed in Section 4. Finally, in Section 5, conclusions are made including the future research.

2 Ontology and Semantic Web Ontologies are used in knowledge management and artificial intelligence to solve questions related to semantics, with current relevance in the Semantic Web. Ontology is a formal representation of knowledge by a set of concepts within a domain and the relationships between those concepts. Ontology provides a vocabulary of classes and relations to describe a domain, stressing knowledge sharing and knowledge representation. It can be therefore used to reason and describe about the properties of a domain. The use of ontologies to represent and reason information related to the network management will be important [7]. Web Ontology Language (OWL) [8] is the Web standard language to represent ontologies. The OWL is based on Resource Description Framework (RDF) [9] and RDF Schema [10]. Currently, OWL is evaluated as the most powerful reasoning languages, and is also the most widely used. The RDF is a framework for representing

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information on the Web, and has an abstract syntax that reflects a simple graph-based data model. OWL enables the definition of domain ontologies and sharing of domain vocabularies and RDF provides data model specifications and XML-based serialization syntax. OWL is an object-oriented approach and a domain is described in terms of classes and properties. OWL can be used to specify management information, and can be employed in modeling and reasoning about context information in WSNs. OWL provides three increasingly expressive sub-languages designed for use by specific communities of implementers and users. OWL Lite supports those users that primarily need a classification hierarchy and simple constraints. OWL DL supports users who want more expressiveness. OWL DL (‘DL’ for Description Logic) generally includes all OWL language constructs, but they can be only used under certain restrictions. OWL Full is meant for users who want maximum expressiveness and the syntactic freedom of RDF with no computational guarantees. In this paper, OWL DL will be used to create an ontology model to represent and interpret facts, because it represents a good compromise between expressivity and computational complexity [11].

3 Ontology-Based Context-Aware Management Model The proposed ontology-based context-aware management model for WSNs includes a Context Manager, a Context Reasoner, an Ontology Manager, one or more Sensor/Actuator Manager, a Context Repository, a Rule Repository, and a large number of sensors and/or actuators in Fig. 1. All but sensors and actuators are located in the base station of the WSN.

Internet / Satellite etc

Manager Node

Context Broker

Context Manager

Ontology Manager

Context Repository

Logic Rules

Context Reasoner

Sensor Manager

Actuator Manager

Sensor Manager

Sensors

Actuators

Sensors

Base Station

Context Providers & Action Executors

Fig. 1. Overview of the Ontology-Based Context-Aware Management Model

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The Context Manager collects data from heterogeneous context providers such as sensor nodes. The Ontology Manager manages the context repository for context awareness. The Context Broker manages queries from manager and defines the knowledge and rule files. The Context Repository is knowledge base for context model and instance storage. And the Logical Rules to infer the situation are used by the Context Reasoner. Ontology-based context model and instances are stored in the Context Repository that is the MySQL relational database. The Sensor Manager and the Actuator Manager read the status information from various sensor nodes and execute the management actions on that sensors or WSN through various actuators, respectively. The Ontology Manager, the Context Manager, and the Context Reasoner are based on Jena framework [12] and Jess rule engine [13]. Fig. 2 illustrates a partial definition of specific ontology for managing WSNs. The context model is structured a set of abstract entities, each describing a physical or conceptual object including Location, Activity and CompEntity (computational entity), as well as a set of abstract sub-classes. A specialized object for the SensorParameter class is added for each specific sensing parameter which is monitored (e.g Temperature, Humidity, Acoustic, etc.). Measurement values are used to determine network or target status by comparing these values with a set of parameter ranges (PrameterRange). Each range is specified in terms of upper and lower thresholds and related activity level; when a measured value falls out of the thresholds, a corresponding management activity is then triggered. ContextEntity

hasThresholdParameter

... CompEntity

Location

TheresholdParameter

Activity

...

hasParameterName isOutOfRange : Boolean

Device

isLocatedIn

hasReferenceRange

TemperatureSens or

Filtering

HumiditySensor

Actuating

ParameterRange AcousticSensor

hasUpperValue hasLowerValue hasRangeID

Sensor

hasSensorParameter

Notification ... SensorParameter

hasSensorStatus TemperatureRange Actuator HumidityRange AcousticRange SeismicRange

...

SensorStatus hasSensorID hasSensorEnergyLevel hasDataSeningValue

Temperature Humidity

hasOutofRangeParameters OutOfRangeDataParameter isOutOfRange : Boolean = true

Fig. 2. Context-Aware Management Ontology

Acoustic ...

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When one or more measurement values fall out of the thresholds, the WSN's status is updated with associations to current OutOfRangeDataParameters and the corresponding Activity events. An activity can be triggered by abnormal SensorParameters. When the system has automatically discerned that a critical situation has occurred, due to abnormal sensor parameter values and/or potentially dangerous environmental conditions, proper intervention actions should be planned.

4 Context Reasoning In this section, we will describe context reasoning based on the proposed management model to demonstrate the key feature of the ontology based context model. In the context model, we represent contexts in first-order predicate calculus. The context model has the form Predict(subject, value), in which Predict is the set of predicate names (for example, has status, has sensor ID, or is owned by). subject is the set of subject names (for example, a sensor, location, or object) and value is the set of all values of subjects (for example, temperature value, vibration value, or gas leak). Temperature(sensor12, 100) means that the temperature of sensor12 is 100o F. The ontology reasoning mechanism of the proposed ontology-based context-aware management supports RDF Schema and OWL DL. The OWL reasoning system supports constructs for describing properties and concepts (classes), including relationships between classes. The RDF Schema rule sets are needed to perform RDF Schema reasoning. For example, (?a rdfs:subClassOf ?b), (?b rdfs:subClassOf ?c) → (?a rdfs:subClassOf ?c). Userdefined rules provide the logic inferences over the ontology base. We have defined a set of rules in order to determine if an alarm has to be triggered and which alarm level should be activated, according to measurement values and corresponding thresholds. For instance, the example shows a rule activating an alarm when both following conditions occurs: the perceived value from an acoustic sensor is higher than 100kHz and the sensed value from a seismic sensor is higher than 10Hz: (?A rdf:type AcousticValue) ^ (?A hasMeasResult ?B) > (?B, 100) ^ (?C rdf:type SeismicValue) ^ (?C hasMeasResult ?D) > (?D, 10) → (?SensorStatus hasActivity Alarm). As previous mentioned, my context reasoner is built using Jena framework [12], which supports rule-based inference over OWL/RDF graphs. It provides a programmatic environment for RDF, RDF Schema and OWL, SPARQL and includes a rule-based inference engine. Its heart is the RDF API, which supports the creation, manipulation, and query of RDF graphs. The current RDF API provides a query primitive, a method for extracting a subset of all the triples that a selector object selects in a graph. A simple selector class selects all the triples matching a given pattern.

5 Conclusion In this paper an ontology-based context model for autonomous sensor management of the WSNs has been proposed. The paper employed OWL to describe the context

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ontologies because it is more expressive than other ontology languages. And the paper showed a context reasoning example to implement autonomic self-management by using the proposed ontology-based model in the WSN. The ontology-based context model will be feasible and necessary for reasoning and automatic managing in WSN environments. Future research activities will be devoted to implement and evaluate the proposed ontology-based context model and logic-based context reasoning schemes in real WSN environments.

References 1. Lee, W.L., Datta, A., Cardell-Oliver, R.: Network Management in Wireless Sensor Networks. School of Computer Science & Software Engineering, University of Western Australia, http://www.csse.uwa.edu.au/~winnie/ Network_Management_in_WSNs_.pdf 2. Sheetal, S.: Autonomic Wireless Sensor Networks. University of Southern California, http://www-scf.usc.edu/~sheetals/publications/ AutonomicWSN.doc 3. Mini, R.A.F., Loureiro, A.A.F., Nath, B.: The Distinctive Design Characteristic of a Wireless Sensor Network: the Energy Map. Computer Communications 27(10), 935–945 (2004) 4. Zhao, F., Guibas, L.: Wireless Sensor Networks: An Information Processing Approach. Morgan Kaufman, Elsevier (2004) 5. Phanse, H.S., DaSilva, L.A., Midkiff, S.F.: Design and Demonstration of Policy-based Management in a Multi-hop Ad Hoc Network. Ad Hoc Networks 3(3), 389–401 (2005) 6. Cha, S.-H., Lee, J.-E., Jo, M., Youn, H.Y., Kang, S., Cho, K.-H.: Policy-based Management for Self-Managing Wireless Sensor Networks. IEICE Transactions on Communications E90-B(11), 3024–3033 (2007) 7. Xu, H., Xiao, D.: A Common Ontology-based Intelligent Configuration Management Model for IP Network Devices. In: First International Conference on Innovative Computing, Information and Control (ICICIC 2006), pp. 385–388. IEEE, Beijing (2006) 8. Semantic Web Standard: Web Ontology Language (OWL). W3C OWL Working Group (2007), http://www.w3.org/2004/OWL/ 9. Semantic Web Standard: Resource Description Framework (RDF). W3C RDF Working Group (2004), http://www.w3.org/2004/RDF/ 10. W3C Recommendation: RDF Vocabulary Description Language 1.0 – RDF Schema (2004), http://www.w3.org/TR/rdf-schema/ 11. Kim, J.: An Ontology Model and Reasoner to Build an Autonomic System for U-Health Smart Home. Master thesis, POSTECH (2009) 12. Jena framework, http://jena.sourceforge.net/ 13. Jess rule engine, http://www.jessrules.com/

An Extended Center-Symmetric Local Ternary Patterns for Image Retrieval Xiaosheng Wu1 and Junding Sun1,2 1

School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China 2 Provincial opening laboratory for Control Engineering key disciplines, Jiaozuo, China {wuxs,sunjd}@hpu.edu.cn

Abstract. A new texture spectrum descriptor was proposed for region description in the paper, which is an extension of center-symmetric local ternary pattern (CS-LTP). Different from CS-LTP, the central piexl of the region are considered together in the definition of the extended centersymmetric local ternary pattern (eCS-LTP). Without adding the dimension of CS-LTP, the proposed operator contains more information of the region. The two methods, CS-LTP and eCS-LTP were tested on two commonly used texture image databases in the context of image retrieval and the experimental results show that eCS-LTP gives better performance than CS-LTP. Keywords: local binary pattern, center-symmetric local binary pattern, centersymmetric local ternary pattern, extended center-symmetric local ternary pattern.

1 Introduction Because of the simplicity and robustness to variations on illumination and orientation in texture analysis and pattern recognition, local binary pattern (LBP) [1] and its extensions [2-4] have been widely used in many fields, such as face recognition [5], image retrieval [6] and medical image analysis [7],etc. The LBP and its extensions are simple descriptors which generate a binary code for a pixel neighbourhood. The origion LBP operator prodeces a 8-bit code (a long histogram of 256-bin) for an 8-nieghbourhood, which make it difficult for interest region description. In order to reduce such problem, Heikkilä et al introduced the center-symmetric local binary pattern (CS-LBP) for region description in [8], which is defined according to the defference of opposing pixels around a given pixel and produces a 4-bit code (a 16-bin histogram). In [9], Gupta et al presented the centersymmetric local ternary pattern (CS-LTP) for region description based on CS-LBP. Different from CS-LBP, CS-LTP only uses the diagonal comparisons and produces a histogram of 9 bins for each spatial bin. However, whether CS-LTP or CS-LBP, the central pixel of a region was ignored. Therefore, they can not describe the gradient of the neighborhood efficiently. CS-LBP was improved in our previous work [10]. In this paper, CS-LTP was also further extended to enhance its efficiency by considering the central pixel. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 359–364, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Center-Symmetric Local Binary Pattern The CS-LBP was proposed in [8]. Different from LBP, CS-LBP does not compare the gray-level of each pixel with the center pixel, but the gray-level difference of the pairs of opposite pixels in a region. For an 8-neighborhood (see Fig. 1), the definition of CSLBP is given as follows, 3

CS _ LBP(T ) = ∑ s ( pi − pi + 4 ) × 2i i=0

(1)

⎧1, x ≥ T s ( x) = ⎨ ⎩0, else

where pi and pi + 4 (i = 0,1, 2,3) correspond to the gray-level of center-symmetric pixels, T was set to obtain the robustness on flat image regions. Since only 4 comparisons are made, CS-LBP generates a 4-bit code. That is to say, it produces a 16-bin histogram, which make it be more effective for region description than the origion local binary patterns.

p5

p6

p7

p4

pc

p0

p3

p2

p1

Fig. 1. 8-neighborhood

p5

p6

p7

p4

pc

p0

p3

p2

p1

Fig. 2. Illustrative diagram for CS-LTP operator. (D=2)

3 Center-Symmetric Local Ternary Pattern The center-symmetric local ternary pattern was introduced in [9]. In its defination, only the diagonal comparisions are used to generate the CS-LTP code for a given pixel. It is clear that CS-LTP produces a histogram of 9 bins for each spatial bin. Mathematically, the CS-LTP at a D neighboring distance is given as, CS _ LTP ( D, T ) = f ( p5 − p1 ) + f ( p7 − p3 ) × 3

⎧ 2, x > T ⎪ f ( x) = ⎨0, x < −T ⎪1, else ⎩ Fig. 2 gives an example for D=2.

(2)

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4 Extended Center-Symmetric Local Ternary Pattern Though CS-LTP is a effective extension of CS-LBP, the gradient information is not considered entirely because of the ignorance of the center pixel pc. In order to fully use the information of the region, an extended center-symmetric local ternary pattern (eCS-LTP) was introduced in this paper. In the new definition, the relation of the center pixel and the diagonal pairs of pixels are considered together instead of the gray-level difference between the diagonal pairs as CS-LTP. Mathematically, the defination of the new operator eCS-LTP was given as follows, eCS _ LTP( D, T ) = g ( p5 − pc , pc − p1 ) + g ( p7 − pc , pc − p3 ) × 3

⎧2, x > T & y > T ⎪ g ( x, y ) = ⎨0, x < −T & y < −T ⎪1, else ⎩

(3)

Though 4 comparisons are made in the defination of eCS-LTP, it is clear that it also produces a 9-bin histogram as CS-LTP.

5 Experimental Results Two commonly used image database for research purposes are employed as test beds and χ 2 distance is chosen as a measurement criterion of. In the experiments, we chose D=1 for CS-LTP and eCS-LTP.

χ 2 ( H1 , H 2 ) = ∑ i =1 (h1i − h2i ) 2 (h1i + h2i ) K

(4)

where H1 and H 2 are the texture spectrum histograms of two images. For the two databases, PN - the precision of the first N retrieved images and RN the recall of the first N retrieved images are chosen as the evaluation criterion [11], which are defined as, Pi , N (q ) = ∑ j =1 N

φ ( I j , Ri ) N

, Ri , N (q ) = ∑ j =1 N

φ ( I j , Ri ) Ri

(5)

where Ri denotes the i-class texture which contains Ri similar images, and q is a query image, and I 1 , I 2 ," , I j ," , I N are the first N retrieved images and

⎧⎪0, if I j ∉ Ri . ⎪⎩1, if I j ∈ Ri

φ ( I j , Ri ) = ⎨

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5.1 The Performance on Image Set 1

Image Set 1 were chosen form CUReT database. This database includes 45 classes and each class has 20 texture images (http://www.robots.ox.ac.uk/~vgg/research/). Fig. 3 shows the 45 example textures.

Fig. 3. Example images in set 1

This experiment employs each image in the first 20 classes as query images, and 400 retrieval results are obtained. Fig. 4 (a) and (b) present the comparision graph of the average results of 400 queries. The retrieval results show that eCS-LTP produces better performance than CS-LTP.

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Fig. 4. Comparison on the first database

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5.2 The Performance on Image Set 2

Image Set 2 includes one hundred and nine 640×640 pixel gray level texture images downloaded from http://www.ux.uis.no/~tranden/brodatz.html. Each image is then partitioned into 16 non-overlapping images (160×160) which are considered as similar images in this experiment. Therefore, we can get 1744 texture images. Fig. 5 shows the 109 example texture images in Set 2.

Fig. 5. Example images in set 2 0.8

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This experiment employs each image in the first 30 classes as query images, and 480 retrieval results are obtained. Fig. 6 presents the comparision graph of the average results of 480 queries. The retrieval results also show that eCS-LTP produces better average recall and precision than CS-LTP.

6 Conclusion This paper points out the shortcoming of CS-LTP, and proposed an extended CS-LTP operator. Because of the considering of the central pixel, more information of a region is fused in the new descriptor. The new operator also keeps the robustness characteristics of CS-LTP and CS-LBP, such as simplicity, robustness to variations on illumination and orientation, a short dimension histogram, etc. The two methods CSLTP and eCS-LTP were compared in image retrieval experiments, and two commomly used texture image database sets were chosen as test beds. Experimental results show that the proposed method is very robust and can achieve significant performance improvement over the CS-LTP operator. Acknowledgment. This work was supported by the Key Project of Chinese Ministry of Education (210128), the Internal Cooperation Science Foundation of henan province (084300510065, 104300510066), provincial opening laboratory for Control Engineering key disciplines (KG2009-14).

References 1. Ojala, T., Pietikäinen, M., Hardwood, D.: A Comparative Study of Texture Measures with Classification based on Feature Distribution. Pattern Recognition 1, 51–59 (1996) 2. Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 7, 971–987 (2002) 3. Zhou, H., Wang, R.S., Wang, C.: A Novel Extended Local-Binary-Pattern Operator for Texture Analysis. Information Sciences 22, 4314–4325 (2008) 4. Guo, Z.H., Zhang, L., Zhang, D.: Rotation Invariant Texture Classification using LBP Variance (LBPV) with Global Matching, vol. 3, pp. 706–719 (2010) 5. Tan, X., Triggs, B.: Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions. IEEE Transactions on Image Processing 6, 1635–1650 (2010) 6. Sun, J.D., Wu, X.S.: Content-base Image Retrieval based on Texture Spectrum Descriptors. Journal of Computer-Aided Design & Computer Graphics 3, 516–520 (2010) (in Chinese) 7. Loris, N., Sheryl, B., Alessandra, L.: A Local Approach based on a Local Binary Patterns Variant Texture Descriptor for Classifying Pain States. Expert Systems with Applications 37, 7888–7894 (2010) 8. Heikkilä, M., Pietikäinen, M., Schmid, C.: Description of Interest Regions with Local Binary Patterns. Pattern Recognition 3, 425–436 (2009) 9. Gupta, R., Patil, H., Mittal, A.: Robust Order-based Methods for Feature Description. In: CVPR, pp. 334–341 (2010) 10. Sun, J.D., Wu, X.S.: Image Retrieval Based on an Improved CS-LBP Descriptor. In: IEEE International Conference on Information Management and Engineering, pp. 115–117 (2010) 11. Ru, L.Y., Peng, X., Su, Z., et al.: Feature performance evaluation in content-based image retrieval. Journal of Computer Research and Development 11, 1560–1566 (2003) (in Chinese)

Comparison of Photosynthetic Parameters and Some Physilogical Indices of 11 Fennel Varieties Mingyou Wang*, Beilei Xiao, and Lixia Liu Agronomy Department, Dezhou University Dezhou 253023, China [email protected]

Abstract. Net Photosynthetic rate(Pn), relative electrical conductivity and MDA content of 11 fennel varieties were tested using LI- 6400 portable photosynthesis system. The results showed that Pn of XJ0710 has distinct difference with other varieties in which there is no obvious difference. But the relative electrical conductivity and MDA of the varieties have obvious difference. Under environmental stress, all of the varieties had different stress resistance. This study provides reference for selecting good fennel varieties. Keywords: Net photosynthetic rate, Relative electrical conductivity, MDA, Comparison.

1 Introduction Fennel is apiaceae, foeniculum adans herbage and which place of origin is mediterranean sea. The history of cultivation are more than 1000 years, and the fennel can be found everywhere in our country. Fennel can be used as vegetable, Chinese traditional medicine and flavor. In this report, we studied the differences of physiological characters through comparing photosynthesis rate and other indexes of 11 fennel varieties, in order to selected fine varietie and offered valuable reference.

2 Materials and Methods 2.1 Experimental Field The experimental field is located in the Dezhou university, and is within east longitude 115°45′-117°36′and north latitude 36°24′25"-38°0′32". Dezhou city is in a warm temperate zone, and has a continental monsoon climate with four distinct *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 365–369, 2011. © Springer-Verlag Berlin Heidelberg 2011

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M. Wang, B. Xiao, and L. Liu

℃

seasons. The annual average temperature is 12.9 , Highest temperature history is 43.4 , and Minimum temperature history is -27 . Average annual rainfall is 547.5mm, and the average frost-free period is 208 days.

℃

℃

2.2 Materials The meteials are 11 fennel varieties: DC0410, DC0415, DC0503, LX0611, LY0901, NJ0712, PY0811, QY0811, XJ0603, XJ0710, XJ0712. 2.3 The Methods The leaves of same parts on 11 fennels were examined net photosynthesis rate (Pn), intercellular CO2 concentration (Ci), Stomatal conductance (Gs), Transpiration rate (Tr) by Photosynthetic apparatus (LI-6400). The relative conductivity (L) and Malondialdehyde (MDA) were examined by the methods of Zhao et al. (2000). All experiments was examined 3 times at least. The analysis of variance and discrepancy comparison ware analysised by the software SPSS (13.0).

3 Results and Discussion 3.1 Pn and Tr of 11 Different Fennel Varieties Pn and Tr of 11 different fennel varieties were examined, which showed obvious differences between different varieties. As shown in Table 1, the Pn of LY0901 is highest, about 23.7umolCO2 m-2s-1, and the Pn of XJ0710 is lowest, about Table 1. Pn and Tr of 11 fennel varieties

Variety

Test of

Pn (umolCO2.m-2.s-1)

significance 5%

Variety

Tr

Test of

mmolH2O.m-2.s-1

significance 5%

1%

LY0901

23.7

a

1% A

LY0901

4.723

a

A

QY0811

23.33

a

A

XJ0712

4.257

a

A

XJ0712

22.8

ab

A

XJ0603

4.257

a

A

XJ0603

22.233

ab

A

DC0503

4.183

a

A

DC0410

20.767

ab

A

QY0811

4.113

a

AB

NJ0712

20.7

ab

A

NJ0712

4.1

a

AB

DC0415

20.7

ab

A

LX0611

3.77

a

AB

LX0611

20.567

ab

A

PY0811

3.69

ab

AB

PY0811

20.3

ab

A

DC0415

3.577

ab

AB

DC0503

20.067

ab

A

DC0410

3.503

ab

AB

XJ0710

18.633

b

B

XJ0710

2.547

b

B

Comparison of Photosynthetic Parameters and Some Physilogical Indices

367

18.633umolCO2 m-2s-1. The array of all Pn is : LY0901>QY0811>XJ0712> XJ0603>DC0410> NJ0712 >DC0415 >LX0611 >PY0816 >DC0503 >XJ0710. The Tr of LY0901 is highest, about 4.723mmolH2Om-2s-1, and The Tr of XJ0710 is lowest, Which is consistent with the Pn value. The array of all Tr is : LY0901>XJ0712>XJ0603> DC0503> QY0811 > NJ0712 >LX0611>PY0816> DC0415 > DC0410>XJ0710. 3.2 Ci and Pn/Ci of 11 Different Fennel Varieties

，

From Table 2 we can see there is no obvious difference among all the fennel varieties. The Ci value of all array is: DC0503> PY0811> NJ0712> LX611> LY0901> DC0410> XJ0710> XJ0712> XJ0603> QY0811> DC0415. But the Pn/Ci value of QY08 is highest, about 8.7×10-2, and which of XJ0710 is lowest, about 6.5×10-2, among the 11 fennel varieties. The results of Pn/Ci have obvious difference among all the fennel varieties except three varieties DC0503, LX0611and XJ0710. The Pn/Ci value of all array is: QY0811> LY0901 >XJ0712 >XJ0603> PY0811> DC0415> DC0410> NJ0712> DC0503> LX0611> XJ0710. Table 2. Ci and Pn/Ci of 11 fennel varieties

Variety

Ci

Test of

(UmolCO2.mol-1)

significance 5%

1%

Variety

Pn/Ci ˄Pn/Ci˅(×10-3)

Test of significance 5%

1%

DC0503

303

a

A

QY0811

87

a

A

PY0811

289.667

a

A

LY0901

83

ab

A

NJ0712

288.667

a

A

XJ0712

82

ab

A

LX0611

288

a

A

XJ0603

81

ab

A

LY0901

288

a

A

PY0811

77

ab

A

DC0410

284.667

a

A

DC0415

76

ab

A

XJ0710

282.333

a

A

DC0410

73

ab

A

XJ0712

279.667

a

A

NJ0712

72

ab

A

XJ0603

279

a

A

DC0503

67

b

A

QY0811

271.333

a

A

LX0611

65

b

A

DC0415

270.667

a

A

XJ0710

65

b

A

3.3 Gs of 11 Different Fennel Varieties There is no obvious difference among Gs of all the fennel varieties (Table 3). The Gs value of all varieties array is: Y0901>DC0503>XJ0712>PY0811> NJ0712>XJ0603> LX0611>QY0811>XJ0710>DC0410>DC0415. This result indicated Gs is not the factor that effecting the otherness between XJ0710 and other varieties.

368

M. Wang, B. Xiao, and L. Liu Table 3. Gs of 11 fennel varieties

Variety

Test of significance

Gs -2

-1

(molH2O.m .S )

5%

1%

LY0901

644

a

A

DC0503

608.333

a

A

XJ0712

521.667

a

A

PY0811

520.667

a

A

J0712

511.333

a

A

XJ0603

500.667

a

A

LX0611

493.33

a

A

QY0811

491.333

a

A

XJ0710

480.667

a

A

DC0410

466.667

a

A

DC0415

403.33

a

A

3.4 Rrelative Conductivity and MDA of 11 Different Fennel Varieties Relative membrane permeability (RMP) of plant cell is an important index to stress tolerance. The change of relative conductivity (L) can reflect the relative membrane permeability of cell under cold stress[3-4]. Low relative conductivity indicated low harm for palnt[5]. As showed in Table 4, the L of NJ0712 is highest, and which of QY0811 is lowest, about 6% and 2.7% respectively. Table 4. Relative conductivity and MDA content in 11 fennel varieties

variety

Relative conductivity (%)

Test of

MDA

significance 5%

1%

variety

Test of significance

(umol.g-1 FW)

5%

1%

NJ0712

6

a

A

PY0811

7.323

a

A

DC0410

5

b

B

DC0415

6.347

b

B

PY0811

4.1

c

C

QY0811

6.345

b

B

XJ0710

4

c

C

NJ0712

5.213

c

C

XJ0712

3.7

d

CD

DC0503

5.072

d

C

LX0611

3.4

de

DE

DC0410

4.88

e

D

DC0503

3.4

de

DE

XJ0712

4.847

e

D

XJ0603

3.345

de

DE

PY0811

4.408

f

E

LY0901

3.3

e

DE

XJ0603

4.232

g

EF

DC0415

3.1

e

EF

XJ0710

4.179

g

F

QY0811

2.7

f

F

LX0611

3.593

h

G

Comparison of Photosynthetic Parameters and Some Physilogical Indices

369

MDA is the lipid peroxidation product that can be induced to a higher level when plants are exposed to a highly osmotic environment, and can be an indicator of increased oxidative damage[6]. the MDA of fennel variety PY0811 is highest, ahout 7.323umol.g-1 FW, and which of LX0611 is lowest, about 3.593 umol.g-1FW. Both Ls and MDAs are obviously difference among all the fennel varieties. These results indicated all fennel varieties have different stress tolerance.

4 Discussion and Conclusions RMP is another index response to plant stress tolerance such as low temperature, drought and salt. When membrane permeability increases, RMP also increases, going with ion leakage out of cell. MDA is the lipid peroxidation product that can be induced to a higher level when plants are exposed to a highly osmotic environment, and can be an indicator of increased oxidative damage[7-8].The MDA accumulation maybe is damage to membrane and cell. Among the 11fennel varieties, Pn of XJ0710 has distinct difference with other varieties in which there is no obvious difference. But the L and MDA of 11fennel varieties have obvious difference. This showed different varieties have different stress tolerance, which offers groundwork to select good variety for agriculture. Acknowledgement. The authors gratefully acknowledge the help from Gao Fangsheng and Zhang hong at Dezhou University, China. This work was supported by the Grants from the Important Program of Shandong thoroughbred engineering: Packing up, screening and utilization of Fennel cultivar resources in Dezhou city (2009).

References 1. Jansen, P.C.M.: Spices, condiments and medicinal plants in Ethiopia, their taxonomy and agricultural significance, pp. 20–29. Pudoc, Wageningen (1981) 2. Li, H.S., Sun, Q., Zhao, S.J.: Experiment principle and technology of plant physiology and biochemistry, pp. 134–137. Higher Education Press, Beijing (2000); pp. 258–260 (in Chinese) 3. Wang, S.G., Zhang, H.Y., Guo, Y., Sun, X.L., Pi, Y.Z.: Sammarize of biomembrane and fruit tree cold resistance. Tianjin Agricultural Sciences 6(1), 37–40 (2000) (in Chinese) 4. Huang, L.Q., Li, Z.H.: Advances in the research of cold-resistance in landscape-plants. Hunan Forestry Science & Technology 31(5), 19–21 (2004) (in Chinese) 5. Li, H.S., Sun, Q., Zhao, S.J.: Experiment principle and technology of plant physiology and biochemistry, vol. 260, pp. 134–137. Higher Education Press, Beijing (2000) (in Chinese) 6. Wise, R.R., Naylor, A.W.: Chilling-enhanced photooxidation: evidence for the role of singletoxygen and superoxide in the break down of pigments and endogenous antioxidants. Plant Physiol. 83, 278–282 (1987) 7. Chinta, S., Lakshmi, A., Giridarakumar, S.: Changes in the antioxidant enzyme efficacy in two high yielding genotypes of mulberry (Morus albaL.) under NaCl salinity. Plant Sci. 161, 613–619 (2001) 8. Verslues, P.E., Batelli, G., Grillo, S., Agius, F., Kim, Y.S., Zhu, J.H., et al.: Interactionof SOS2 with nucleosidediphosphate kinase 2 and catalase sreveal sapoint of connection between salt stress and H2O2 signaling in Arabidopsis thaliana. Mol. Cell Biol. 27, 7771– 7780 (2007)

Effect of Naturally Low Temperature Stress on Cold Resistance of Fennel Varieties Resource Beilei Xiao, Mingyou Wang*, and Lixia Liu Agronomy Department, Dezhou University, Dezhou 253023, China [email protected]

℃

Abstract. After being affected by naturally low temperature (-4~0 ), the changes of relative electrical conductivity and MDA content of 11 fennel varieties were tested. The experiment studied the relationship between the cold resistance and changes of relative electrical conductivity and MDA content of varieties. The results showed that the relative electrical conductivity and MDA content were higher than CK under naturally low temperature stress. The varieties had different increasing amplitude. The differences were significant. The comprehensive comparison indicated that the cold resistance of XJ0712 was the strongest, while that of XJ0710 was the worst. Keywords: Fennel, Naturally low temperature, Relative electrical conductivity, MDA, Cold resistance.

1 Introduction Low temperature is the key environmental factor that effected plant growth, development and geographic distribution. It is reported that there are hundred billions loss on agriculture because of low temperature[1]. And the loss will be increased with extreme weather frequently by earth warming[2]. Therefore, studying plant physiological mechanism under low temperature has become one of the researches focus in this field. In this report, we studied the changes of relative electrical conductivity and MDA under low temperature stress. These results can offer some reference to screen good fennel varieties resisting low temperature.

2 Materials and Methods 2.1 Experimental Field The experimental field is located in the Dezhou university, and is within east longitude 115°45′-117°36′and north latitude 36°24′25"-38°0′32". Dezhou city is in a warm temperate zone, and has a continental monsoon climate with four distinct seasons. The annual average temperature is 12.9 , Highest temperature history is

℃

*

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 370–374, 2011. © Springer-Verlag Berlin Heidelberg 2011

Effect of Naturally Low Temperature Stress on Cold Resistance

℃

371

℃

43.4 , and Minimum temperature history is -27 . Average annual rainfall is 547.5mm, and The average frost-free period is 208 days. In march every year, cold wave, gale and frost are the main baneful weather in Dezhou city. 2.2 The Materials The meteials are 11 fennel varieties: DC0410, DC0415, DC0503, LX0611, LY0901, NJ0712, PY0811, QY0811, XJ0603, XJ0710, XJ0712. 2.3 The Methods

～ ℃

We selected the leaves samples of 11 fennel varieties at am 8:00- 9:00 on 23 march 2010. The temperature of that day is 5 15 . And other samples were selected at the same time on 24 march 2010 after a light snow in the night. The relative conductivity (L), damage degree and Malondialdehyde (MDA) were examined by the methods of Zhao et al. (2000) [3]. All experiments was examined 3 times at least. The analysis of variance and discrepancy comparison ware analysised by the software SPSS (13.0).

3 Results 3.1 The Changes of Relative Conductivity of 11 Fennel Varieties After Cold Stress Relative membrane permeability (RMP) of plant cell is an important index to stress tolerance. The change of relative conductivity (L) can reflect the relative membrane permeability of cell under cold stress. Low relative conductivity indicated low harm for plant[4-5]. As showed in Figure 1, after cold stress the relative membrane permeability were increased compared with the controls. The relative conductivity change and damage degree of PY0811variety were least compared with other 10 25

) % ( y t i v i t c u d n o c c i r t c e l e e v i t a l e R

20

CK Low temperature

15

10

5

0 DC0410

DC0503

XJ0603

LX0611

XJ0710

NJ0712

XJ0712

QY0811

PY0811

LY0901

DC0415

Variety

Fig. 1. Phylogenetic analysis of ZmPP2C and PP2Cs from other plants. All selected genes’ function are tangible in some degree now.

372

B. Xiao, M. Wang, and L. Liu

varieties (Table 1). And the second was XJ0712. On the contrary, the relative conductivity change and damage degree of XJ0710 variety were highest. These results indicated that PY0811variety has highest cold tolerance, and XJ0712 variety has lowest cold tolerance among all 11 fennel varieties. Table 1. Changes of low temperature stress on the relative electric conductivity of leaf in fennel and membrane damage degree

Variety

Increase of RMP (%)

XJ0710 XJ0603 DC0415 DC0410 NJ0712 LX0611 QY0811 LY0901 DC0503 XJ0712 PY0811

387.4 251.5 152.7 125.7 121.4 105.9 105.8 82.5 78.5 70.3 53.5

Test of significance 5% 1% a A b B c C cd CD cd CD cde CD cde CD de CD de CD de CD e D

Variety

Damage degree(%)

XJ0710 XJ0603 NJ0712 DC0410 DC0415 LX0611 QY0811 LY0901 DC0503 XJ0712 PY0811

16.3 8.7 7.8 6.7 4.9 3.5 2.9 2.8 2.8 2.7 2.3

Test of significance 5% 1% a A b B b BC bc BCD cd CDE de DE de DE de E de E de E e E

3.2 The Changes of MDA of 11 Different Fennel Varieties MDA is the lipid peroxidation product that can be induced to a higher level when plants are exposed to a highly osmotic environment, and can be an indicator of increased oxidative damage[6]. MDA often was be considered as a guideline that response to cold stress[5]. From Figure 2, MDA contents obviously increased after 9

CK Low temperature

8 7 ） W F g / l o m u （ t n e t n o c A D M

6 5 4 3 2 1 0 DC0410

DC0503

XJ0603

LX0611

XJ0710

NJ0712

XJ0712

QY0811

PY0811

LY0901

Variety

Fig. 2. Changes of low temperature stress on MDA content leaf in fennel

DC0415

Effect of Naturally Low Temperature Stress on Cold Resistance

373

cold stress. The MDA increase of all varieties array is: XJ0710 (92.7 %)>LX0611 (50.8%)> PY0811( 40.8%) > DC0503(39.3%) >NJ0712(35.1%) > QY0811(31.3%)> DC0410(28.4%)>LY0901(24%)>DC0415(16.6%)> XJ0603(14.5%)> XJ0712(8.6%). This result illustrated that XJ0710 suffered greatest oxidative damage than other variety with the same cold stress treatment, and XJ0712 suffered least.

4 Discussion and Conclusions The plant cell plasma membrane is differentially permeable membrane that some particles can pass through, macromolecules cannot. But when cell membrane was damaged, macromolecules can pass through out and took harm to plant growth[7]. So RMP is another index response to plant stress tolerance. When membrane permeability increases, RMP also increases, going with ion leakage out of cell [8-9]. Relative electrical conductivity increased more and the cold tolerance is lower[11]. From Figure 1, we can see PY0811 damaged the lowest, XJ0712 damaged lower, and XJ0710 damaged the highest, which consisted with PY0811 has high cold tolerance and XJ0710 has low cold tolerance. MDA is one of main production of lipid peroxidation. And MDA content and changes can showed plant cold tolerance in one side [10-11]. The changes in figure 2 indicated that PY0712 has the highest cold tolerance and XJ0710 has the lowest cold tolerance. In comprehensive analysis of all data, PY0712 has the highest cold tolerance and XJ0710 has the lowest cold tolerance in the 11 fennel varieties. Acknowledgement. The authors gratefully acknowledge the help from Hong Zhang and Fangsheng Gao at Dezhou University, China. This work was supported by the Grants from the Important Program of Shandong thoroughbred engineering: Packing up, screening and utilization of fFennel cultivar resources in Dezhou city (2009).

References 1. Deng, J.M., Jian, L.C.: Advances of studies on plant freezing tolerance mechanism: freezing tolerance gene expression and its function. Chinese Bulletin of Botany 18(5), 521–530 (2001) 2. Bertrand, A., Castonguay, Y.: Plant adaptations to overwintering stresses and implications of climate change. Canadian Journal of Botanical 81, 1145–1152 (2003) 3. Li, H.S., Sun, Q., Zhao, S.J.: Experiment principle and technology of plant physiology and biochemistry, pp. 134–137. Higher Education Press, Beijing (2000); pp. 258–260 4. Wise, R.R., Naylor, A.W.: Chilling-enhanced photooxidation: evidence for the role of single to xygen and superoxide in the break down of pigments and endogenous antioxidants. Plant Physiol. 83, 278–282 (1987) 5. Huang, L.Q., Li, Z.H.: Advances in the research of cold-resistance in landscape-plants. Hunan Forestry Science & Technology 31(5), 19–21 (2004) (in Chinese) 6. Zhu, J.K.: Plantsalttolerance. Trends Plant Sci. 6, 66–71 (2001) 7. Prasad, T.K.: Role of calalase in inducing chilling tolerance in pre-emergent maize seedlings. Plant Physiol. 114(4), 1369–13761 (1997)

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8. Wahid, A., Shabbir, A.: Induction of heat stress tolerance in barley seedlings by presowing seed treatment with glycinebetaine. Plant Growth Regul. 46, 133–141 (2005) 9. Wahid, A., Perveen, M., Gelani, S., Basra, S.M.: Pretreatment of seed with H2O2 improves salt tolerance of wheat gene ZmPP2C of Zea mays roots. J. Plant Physiol. Mol. Biol. 31, 183–189 (2005) 10. Chinta, S., Lakshmi, A., Giridarakumar, S.: Changes in the antioxidant enzyme efficacy in two high yielding genotypes of mulberry (Morus albaL.) under NaCl salinity. Plant Sci. 161, 613–619 (2001) 11. Verslues, P.E., Batelli, G., Grillo, S., Agius, F., Kim, Y.S., Zhu, J.H., et al.: Interaction of SOS2 with nucleoside diphosphate kinase 2 and catalase sreveal sapoint of connection between salt stress and H2O2 signaling in Arabidopsis thaliana. Mol. Cell Biol. 27, 7771–7780 (2007)

Survey on the Continuing Physical Education in the Cities around the Taihu Lake JianQiang Guo ChangZhou University, Changzhou 213164 China [email protected]

Abstract. Through the material and questionnaire survey analysis thinks: As for the Physical Education (PE) attended by On-the-job adult students in college among the cities around the Tai Lake(taihu lake), the teaching plan, training goal and teaching material contents formulation must satisfy the physical, psychological and healthy needs of on-the-job adult students, meet the demands of social sports, meet the needs of the development of discipline intact. Keywords: The cities around Tai Lake, Continue the sports education, Teaching situation, survey.

Preface Continuing sports education aims to cultivate interest of on-the-job adult students participating in physical exercise, to maintain, recover and enhance their physique, improve their working efficiency and establish lifelong exercise habits. Continuing sports education is a part of the school physical education and the connections of links between school sports and social sports. In recent years, with the continuous development of our society, with the reform of education system, and with the gradually expanding scale of adult high schools, How to improve college adult sports teaching work, let students gain all-round development in process the re-education, has been a problem that is worth paying attention to.

1 The Object of Study and Methods 1.1 The Object of Study: students who receive the continuing sports education in the high schools, city circle around the Tai Lake(suzhou ,wuxi, Changzhou,huzhou, jiaxing), which open the continuing sports education classes. 1.2 Research methods: 1.2.1 The questionnaire: sending out 900 questionnaires and withdrawing available 824 ones in the city circle around the Tai Lake(suzhou ,wuxi, Changzhou, huzhou, jiaxing).The recovery is 91.6%. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 375–380, 2011. © Springer-Verlag Berlin Heidelberg 2011

376

J. Guo

1.2.2 The methods of mathematical statistics: using computer processing all the statistics , recycling the available questionnaires and handling the statistics with using statistical software ,the SPSS11. 5. 1.2.3 The methods of looking into materials: looking into the relevant materials on the continuing sports education in china.

2 Results and Analysis 2.1 Structure survey on origins of students who receive the continuing sports education in the high schools in the city circle around the Tai Lake. Table 1. Continue to sports education students come from structure statistics JHQGHU    PDWULFXODWH     FROOHJH   7HFKQLFDOVHFRQGDU\VFKRRO        +LJKVFKRRO QXPEHU  SURSRUWLRQ˄˅QXPEHU SURSRUWLRQ˄˅ QXPEHU  SURSRUWLRQ˄˅ PDOH

      



                    

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The city circle around the Tai Lake lies in the developed economic regions, has instinctive geographical features. In this area, the engineering education and higher vocational high schools are developed well. Relatively speaking, a significant number of technical school students have the desire to study further. As table 1 shows the fact that 73.2% of students own the degree of Technical secondary school or senior colleges can prove the point mentioned. There are many universities in the city circle around Tai Lake. Every university has numerous subordinates schools, students there continue their physical education and have physical exercise. The scale of admission of full-time students who will receive continuing education focus on the students who has finished the high school or who are willing to receive higher education in the engineering education.

，

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Survey on the Continuing Physical Education in the Cities around the Taihu Lake

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Table 2 show that students who receive continuing education have sports exercises to enhance their physique (accounted for 30.5%), to master of sports skills and technology (accounted for 18.5 percent). Therefore, as to the teaching form, we should take a variety of forms, such as basic sports classes Special improve classes, sports health classes. As to the selection of teaching material contents, ball games and the body buildings should be the important parts. As to the teaching form, we should carry out Hierarchical teaching . Otherwise, it will damage the enthusiasm of students' learning sports severely [1]. Students’ value orientations in participating in sports activities focus on two aspects: "enhanced physique" and "entertainment and peaceful mind and inner tranquility" .Their value orientations reflect that as to the social, cultural and psychological functions in the sports of "improving ability to adapt the society " ,this choice rate is low. It shows the sports consciousness of contemporary college students is required to be guided to establish the comparatively complete sports value. This article will classify the socialization course into physical education curriculum system and emphasize and give play to this function of sports. In addition, a not high choice rate in the "mastering sports skills and technology" also shows that the traditional guiding ideology on the sports curriculum and students’ main needs remain docking. 2.3 The survey on the sports that students like Table 3. Continue education students like PE class project TAB

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According to table 3, we can see that surveyed students who are receiving the continuing education like the following sports courses most: basketball, aerobics, table tennis, badminton, football, martial arts, bodybuilding and volleyball. And in the report of China mass sports present situation investigation results published by our national sports administration in 2002, the top 10 sports mentioned above in the report were included [2]. 2.4 The survey on the teaching form of continuing education According to table 4, we can see that, among the students who are receiving the continuing education in city circle around Tai Lake. Boys pay little attention to the teaching form, while girls’ requirements in the teaching form differed a lot. Mixed classes or small classes are required. It has a direct links to the continuing students origin structure in high schools in this city circle around Tai Lake. Relatively speaking, girls are in a small age. Majority of them are in junior colleges, technical secondary schools, high schools and very shy physiologically. Their preferences in

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teaching form respectively are: elective classes (54.5%), club type classes (26.7%), basic classes (17.6 percent). The reasons are: teaching mode of elective course emphasize the sports ability. It is classified by the content of the project, so the students have more choices. The advantage of Elective PE teaching mode is that it can sufficiently meet the continuing students’ demand of development in personality. It is beneficial to cultivate the ability of sports and fitness and interests. The guiding ideology of club of teaching mode is to fully exert students' subjective initiative, attach importance to cultivating students' interest in sports. The main purpose is to improve students' sports ability and train students' life-long physical exercise habit. In the basic class, the initiative of middle school students' is greatly depressed. Students cannot make their choices on their own. It also hinder the development trend of individualism.

3 Conclusions 3.1 The students who are receiving the continuing education in city circle around Tai Lake based on the level of college and engineering schools. At the same time, due to the geographical position, junior colleges and technical secondary schools are the main matriculate. Our continuing sports education curriculum arrangement should consider the characteristics of the students origin. We suggest that the time P.E. class should increase from ordinary 70 hours appropriately to 100 hours and open four semesters, which will be consistent to the time of ordinary time. We should formulate plans to ensure continuing students have more sports time, cultivating habit of participating in regular physical exercise. Increasing the teaching hour and teaching the necessary sports knowledge to students, Vary from person to person, enable the student to master at least one of the value of exercise with lifelong sports. The content of Continuing PE should combine the physiological and psychological, social sports needs, colleges should arranged the sport lessons according to the reality .Featured by interest, safety, entertainment, confrontational, general audience ,aerobic exercise program can help them keep fit and strong ,improve their own interests, vent their emotions, learn the necessary physical theory knowledge, and can learn the necessary physical theory knowledge, 1-2 sport skill, make oneself can not only for the lifelong sports exercise, and participation in social sports activities [3].

〕

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3.2 According to the continuing students’ motivation of participating in sports activities in the city circle around Tai Lake, to make the continuing students actually develop a habit of having sports exercises. First, we should strengthen the construction of external factors, such as building campus sports culture; cultivating sports backbones to make them have the ability to organize, inspire people. We should develop strong administrative measures to make continuing students continue to participate in sports, strengthen the construction of sports facilities and new sports hardware construction, and so on. Second, we should strengthen the teaching in sports knowledge, technology and skills, enables the student to really get the benefits from sports, arouse their intrinsic motivation, which makes their physical exercise habit stronger [4]. 3.3 According to students like science city sports course project reasonable setting, paying attention to exercise enhanced physique while, enhance physical foundation of education of theoretical knowledge, enables the student to clear the human body and its development, sports on development, try choosing to adapt to the influence of modern social needs, and to help students' future of sports theory content, such as sports value and function of the basic law, sports and nutrition, health care to learn, and human body measurement and evaluation of environmental infrastructure such as knowledge. 3.4 The education science city continue sports jagged, level students ages span, the students' physical and mental characteristics, interests, hobbies and gender differences between the different level. Should be based on the differences of students' practical teaching, and take small groups, the education sports teaching goal continues to build on the student lifelong education "concept to implement", on the basis of the reform of the teaching system, ability in the teaching process arouses student's enthusiasm, ability makes the current sports teaching quality a substantial breakthrough. The teaching process implementation "humanistic" thinking, the teacher must set up the students as the center of modern education concept, everything from students start, everything for the student, the student all services, thus creating an orderly and sentient beings, hard work and harmonious classroom teaching atmosphere [5]. 3.5 Establishing a suitable sports education achievement standard of appraisal. Achievement evaluation leads the direction of course assessment, so, in the process of achievement evaluation, we need to combine the characteristics of adult education, evaluate scientifically from the Angle of cultivating the ability. Each course should be combined with the characteristics of the subject. We should do well in the links, such as the homework and we should not linger on the surface. With the ideas of P.E. teaching change, new exam has been a sure way to go, test should be divided into three parts : inspector technical theory, technology assessment and teaching analysis. Acknowledgments. The paper is supported by 2010 liberal arts development fund projects in Changzhou University (No. ZMF100200449).

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References [1] Wu, T.P.: (1) of adult college students. The sport motivation research. Journal of Chinese Sports Science and Technology (article 37 roll) supplement 19-20 (2001) [2] Mass sport in China present situation investigation results report. The state general administration of sports, adrenal system. br [3] Cheng, D.F., Wang, Q.: student sports teaching employed adults. Chinese Adult Education 10, 164–165 (2006) [4] Wang, Q.J., et al.: Zhejiang education sports teaching model selection of adult. Ningbo University Journal (Education Science Edition) 26(5), 108–109 [5] Chen, Q.S.: Theory of adult education sports education characteristics and countermeasures study. Journal of Adult Education Sports 25(1), 3–4 (1993)

The Gas Seepage and Migration Law of Mine Fire Zone under the Positive Pressure Ventilation HaiYan Wang, ZhenLong Zhang, DanDan Jiang, and FeiYin Wang Resources and Safety Engineering School, China University of Mining and Technology (Beijing), Xueyuan Road. D11,100083 Beijing, China [email protected] Abstract. A fire developing tendency mathematical model of mine fire zone under positive pressure ventilation was established and was validated based on the particularly serious fire accident of Fuhua “9.20” in Heilongjiang province. Then the law of positive pressure ventilation influence on the fire zone developing tendency and its enlightenment to work safety were obtained. Under positive pressure ventilation, high temperature fire source has an obvious tendency to spread toward the gob, but with the development of fire, the aerotactic movement of combustion makes the high temperature fire source zone also slowly spread toward the roadway of mine. As the fire developing, a lot of smoke flows into the roadway, and distension of high temperature gas accelerates the gas flow rate in the roadway. The acceleration directly results in the spread and diffusion velocity of gas in the ventilation system, which will aggravate the accident. Keywords: positive pressure ventilation, mine fire zone, fire spread, smoke.

1 Introduction The main fans in the mine have three common ways of ventilation: positive pressure ventilation, negative pressure ventilation and hybrid ventilation. In the mine of forced ventilation, after the main fan works, it forces fresh air into the roadway, making the absolute pressure of underground mine greater than that outside of the mine or the atmospheric pressure outside of air duct with the same elevation. Its relative pressure is positive, and thus turns forced ventilation into positive pressure ventilation [1]. The influence of positive pressure ventilation on the spread of fire zone in the mine is mainly its influence on the migration of smoke currents and high temperature points corrected pressure ventilation in the mine fire.

2 The Mathematical Model of Fire Developing Tendency in the Mine Fire Zone under Positive Pressure Ventilation 2.1 Roadway Flow Field Model The gas flow in the roadway can be considered as an unsteady three-dimensional turbulent field along with the heat and mass transfer process. The fluid flow within S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 381–389, 2011. © Springer-Verlag Berlin Heidelberg 2011

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the roadway follows relevant equations of the motion of fields, the law of heat and mass conservations and the basic equations of chemical fluid dynamics established by taking them as the starting point[2], namely continuity equation

∂ρ ∂ ( ρu j ) = 0; + ∂x j ∂t

(1)

momentum equation (i direction) ∂( ρui ) + ∂( ρu j ui ) = ∂ ⎛⎜ μ ∂u j ⎞⎟ + I ; ⎜ ⎟ uj ∂t

energy equation

∂x j

∂ ( ρh) ∂ ( ρu j h) ∂ + = ∂t ∂x j ∂x j

∂x j ⎝ ∂x j ⎠

⎛ ∂h ⎞ ⎜ Γh ⎟+I ; ⎜ ∂x ⎟ h j ⎠ ⎝

(3)

component equation (l component) ∂ ( ρml ) + ∂( ρu j ml ) = ∂ ⎛⎜ Γ ∂ml ⎞⎟ + I . ⎟ l ⎜ h ∂t

∂x j

∂x j ⎝

(2)

∂x j ⎠

(4)

Where: u-velocity, m.s-1; h-enthalpy, K; m-quality fraction; Гh-transport coefficients; I is source term. 2.2 Combustion Model in Mine Fire Zone Goaf, top-coal caving region, and coal pillar in coalmine belong to double porous media with hole and fracture. The wind flow in roadway penetrates into the coal, and the oxygen in the air and coal molecules undergo physical adsorption, chemical adsorption and chemical reactions, while producing a large amount of heat. Under the adapted heat accumulated conditions, the coal continues to be oxidized and heated. And when the temperature reaches the ignition point, it will lead to coal combustion. According to the mass and energy conservations, the mathematical models for spontaneous combustion of loose coal such as the coal in the gob can be obtained. The effect of buoyancy can not be ignored during the combustion of fire zone. Therefore, the seepage flow equation [3] of air leakage in fir zone follows, K K (5) − ∇h + ρ 0 gαΔTk = ( A + Bυ )v .

K

Where: v -permeability velocity of air flow, m.s-1; υ -modulus of permeability velocity, m.s-1; ∇-Hamiltonian operator; h-total pressure, h=p+ρ0gz, Pa; p-leakage wind pressure, here means the positive values, Pa; z-perpendicular coordinate, m; ρ0gas density of fresh wind flow in the roadway, kg.m-3; g-acceleration of gravity, m.s-2; α-gas expansion coefficient; ΔT-temperature difference, ΔT=T-T0, K; T-loose coal temperature, K; T0-temperature of the fresh wind flow in the roadway, K; ρ-gas K density, kg.m-3; k -vertical upward unit vector; A-linear drag coefficient, A=nρν/k; B-quadratic drag coefficient, B=nρDmβ/k; ν-movement viscosity coefficient, m2.s-1; nporosity; Dm-the average diameter of porous media skeleton, m; -permeability; βgeometric figure coefficient.

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The combustion process in fire zone is release accompanied by heat dissipation. dissipation rate, the coal temperature will According to energy conservation equation drawn as follows,

ρ e / Ce

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a dynamic development process of heat When heat release rate is greater than rise and eventually lead to combustion. [4], temperature field distribution can be

∂T K = λe ∇ • ( ∇T ) − nρ g C g ∇ • ( v T ) + q(T ) . ∂t

(6)

Where: T-coal temperature, K; t-time variable, s; ρɛ-loose coal density, kg.m-3; Cɛ-heat capacity of loose coal, J.Kg-1.K-1; λe-thermal conductivity coefficient of loose coal, W.m-1.K-1; ρg-gas density, kg.m-3; Cg-gas specific heat, .Kg-1.K-1; q(T)-heat intensity of coal, J.s-1.m-3. Oxygen is a necessary condition for spontaneous combustion. Oxygen migration is a complex process accompanied by the consumption and dilution of oxygen in coal under simultaneous convective diffusion and molecular diffusion. According to mass transfer law [5], oxygen migration meets dC K + ∇ • (v C ) = ∇ • ( D • ∇C ) − V (T ) . dt

(7)

Where: D-gas diffusion coefficient, m2.s-1; V(T)-oxygen consumption rate of coal combustion, mol.m-3.s-1. 2.3 Coal-Oxygen Chemical Reaction Model Coal is a complex organic molecule composed of various functional groups and chemical bonds. Its structure is very complicated, which determines the complexity of chemical reaction between coal and oxygen involving processes such as adsorption (including physical adsorption and chemical adsorption) and chemical reaction. Coaloxygen reaction includes general coal-oxygen combustion reaction and spontaneous combustion reaction of coal, and the coal-oxygen combustion reaction involved in the paper is more complex than general combustion reactions. Due to the complexity of spontaneous combustion process of coal, to simplify the study, the paper considers the elements of coal involved in combustion as C, H, O, and divides the chemical reaction of spontaneous combustion of coal into four steps including the decomposition of coal, gasification and coke combustion, C a H b Oc →a 1 C + a 2 CO2 + a 3 CO +

b H2 2

(8)

C + O 2 → CO 2 2CO + O 2 → 2CO2 2 H 2 + O2 → 2 H 2 O

.

Where: a, b, c, a1, a2 and a3 - coefficients, among which a1+a2+a3=a, 2a2+a3=c. The ratio of a, b and c can be attained by elementary analysis. On the basis of reference [6], the ratio of a1, a2 and a3 can take 213:18:10.

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2.4 Boundary Conditions In terms of solid boundary and artificial boundary, the physical boundary condition during the process of spontaneous combustion includes seepage field boundary condition and concentration field boundary condition. The seepage field boundary conditions are as follows: first kind boundary - given constant pressure φ =P;

(9)

− Kgrad φ = m .

(10)

second kind boundary - given flow

third kind boundary -given wind pressure or value or given air volume. The concentration field boundary conditions are as follows: first kind boundary - given concentration on the boundary (11)

C = f1 ;

second kind boundary - given concentration dispersion flux on the boundary Dij

∂C ⋅ ni s = f 2 ∂x j

;

(12)

third kind boundary - given gas flux on the boundary ⎞ ⎛ ⎜ Cvi − Dij ∂C ⎟ ⋅ ni s = f 3 . ⎜ ∂x j ⎟⎠ ⎝

(13)

Where: φ-variable; K-coefficient of permeability; m-mass flux; f1, f2, f3-concentration function.

3 Case Selection and Conditions Set 3.1 Fuhua Coal Mine “9.20” Fire Accident It was during the repeated mining process of No.11 coal seam when the accident happened. The repeated mining thickness was 2 to 8 meters, and the inclination angle of coal seam 20 degree. Coal seam roof and floor were composed of sandstone. It belonged to low-gas coal mine. The volatile matter of coal was 30 percent. Coal-dust was explosive-gas mixture, with an explosion index of 70 percent. The spontaneous ignition tendency of coal seam was identified as grade one with a combustion stage of 6 to 8 months. The ventilation system is central tied forced ventilation, with auxiliary shaft intaking the air and the main shaft returning the air. At 2:28 on September 20, 2008, the mine had a particularly serious fire accident, causing the death of 31 people. The direct cause of the accident was: the second blind air shaft of the mine was arranged at the bottom of mined No.11 coal seam. The coal pillar at the top of the

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roadway broke, exposed to the air and had air leakage, which caused spontaneous combustion with temperature ascend because of coal oxidation, and leaded to the fire incident. Figure 1 is a schematic diagram of ignition point. Based on this fire incident, this paper analyzed the gas seepage and flow features of smoke in the goaf and mine ventilation system after the accident, which provided theoretical support to avoid similar incidents in the future.

Fig. 1. Schematic diagram of ignition point

3.2 Physical Model and Initial and Boundary Conditions According to the basic conditions of the accident mine ventilation, the paper selects the pillar of fire existing area, the upper goaf, the lower end of coal and rock and the ventilation system. As the accident occurred in the upper areas of the second blind air shaft and fourth crossheading, there occurred no spontaneous combustion in 01 face area, the second old blind main shaft, second new blind main shaft, sixth crossheading, and the upper areas of 02 and 03 drifting faces and areas near the two faces. The roadways of above areas are mainly circulation areas of gaseous products, therefore, in the paper, the mine ventilation system after the crossing of the second blind air shaft and fourth crossheading is simplified. Hexahedral structured grid is adopted to divide and the number of grids is about 3.45 million. The paper taking into account the complex structure of flow field in spontaneous combustion area, local mesh refinement is applied in the grids of fire part and some parts. The simplified physical model was shown in Fig.2. Basic parameters and boundary conditions are as follows: the normal air inlet speed of the second blind air shaft is 3 m.s-1, the porosity of coal pillar is 0.2, and porosity of the gob is 0.2 to 0.3. The seepage field boundaries of the gob and face boundary conditions are shown in Eq.10, namely, the mass flow of given penetration is 0.01g.m-2. Gas concentration field boundary condition takes the second kind boundary condition (Eq.12), namely normal no penetration. Outlet of the blind main shaft adopts pressure exit boundary conditions. The side wall of the roadway below the second blind air shaft along the fourth crossheading is impermeable, and the side wall of second new blind air shaft is impermeable.

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Fig. 2. Simplified physical model

4 Validation of Model of Fire Developing Tendency in the Mine Fire Zone under Positive Pressure Ventilation and Analysis of Simulation Results 4.1 Validation of the Mathematical Model Table 1 showed the mine data and phenomena explored and observed by the rescue team somewhere after the accident in the ambulance during the emergency-rescue process. Fig.3 is a stimulating concentration contour of carbon monoxide of the center sections along the length direction of the second blind air shaft and fourth crossheading at the stage of full development of spontaneous combustion. As it can be seen from the figure, the second blind air shaft, fourth crossheading and second new blind main shaft are full of dense smoke, and the concentration value of CO balances between 0.0105 and 0.011. The simulation result approximately approaches the actual monitoring result and observation. The error mainly arises from the simplification of ventilation network. Through the above analysis it can see that the simulation results Table 1. Concentration of carbon monoxide and temperature measured before the adjustment of the ventilation system during the accident rescue and observed phenomena Location

volume fraction Temperature of CO To 5 m below the main shaft 0.00125 To 240 m of second new blind main shaft To the bend at the shaft bottom 0.007 bypassing to 95 m of the second old blind shaft To 80 m below the +180 0.014 35 crossheading

℃

phenomena Dense smoke Moderate smoke throughout the whole tunnel -

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basically agree with the development state of the accident, thus indicating the accuracy and reliability of the mathematical model of fire developing tendency in the mine fire zone under positive pressure ventilation. 4.2 Analysis of Numerical Simulation Results and Enlightenment to Safe Production Fig.3 is the volume fraction contour of carbon monoxide at the direction of center section of the second blind air shaft and fourth crossheading in the fire accident. The figure shows: due to the compression of mechanical wind pressure under positive pressure ventilation, most gas in the fire zone flows into the goaf, and the fire has an evident tendency to spread upwards from the goaf and coal pillar part. The trend of carbon monoxide volume fraction contour during the initial period of fire reveals the volume fractions of carbon monoxide in the second blind air shaft and fourth crossheading are almost 0, and carbon monoxide enters into the upper part of the goaf. But with the development of the fire, after the formation of fire center, the carbon monoxide gas gradually spreads from the fire center towards the direction of the roadway, and enters into the second blind air shaft, while a lot of smoke begins to appear in the ventilation system. The volume fraction of carbon monoxide near the second blind air shaft and fourth crossheading remains at about 0.01, which is close to the concentration values actual measured by the ambulance crew while doing the rescue work. Fig. 4 is a velocity contour through the direction of center section of the second blind air shaft and fourth crossheading during the development of the fire. The figure shows that as the smoke that enters into the roadway at the initial stage of fire is exiguous, it has little flow effect on the airflow inside the roadway. But with the development of fire, a lot of smoke flows into the roadway, and the expansion of high temperature gas speeds up the gas flow rate in the roadway. The acceleration will lead directly to the spread and diffusion rate of smoke in the ventilation system, resulting in the aggravation of accident.

Fig. 3. Volume fraction contour of carbon monoxide at the section x=1.3, z=61.72

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Fig. 4. Velocity contour at the section x=1.3, z=61.72

Fig. 5. Temperature contour on the section x=1.3, z=61.72

On the basis of the above simulation results and description of the process of the accident, it shows that the following aspects should be concerned for fire monitoring in mine safety: Firstly, for areas with crushing coal on the side wall of the roadway and serious air leakage, effective measures to prevent and control spontaneous combustion and air leakage should be timely adopted, so as to get rid of the major hidden danger of spontaneous combustion. Positive pressure ventilation can not avoid the reverse spread of spontaneous combustion near the wind in the goaf. That is why the fire accident occurred in the Fuhua coal mine. Secondly, carbon monoxide, as a warning index gas of spontaneous combustion of mine, should pay attention to the impact and effect of the volume and flow of the air. Using positive pressure ventilation will pressure most gases produced by spontaneous combustion into the goaf, making the concentration of carbon monoxide within the return airway significantly reduce, which increases the difficulty of gas monitoring and timely warning of spontaneous combustion. Furthermore, the air leakage of coal in the goaf is serious, so a lot of fire smoke gas containing carbon monoxide directly seeps from the gap of coal, which also greatly enhances the difficulty of making early warning. This is also one of the major reasons for not timely warning of the fire

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accident. Also, it should be noted that positive pressure ventilation may still reverse the spread of spontaneous combustion due to spread with absorption of oxygen. Thirdly, correct the misconception of using 24ppm carbon monoxide concentration as the warning index value. The mine is in the return airflow with the air volume of 1150 m3.min-1. The concentration of carbon monoxide gradually increased from 2 ppm on September 1st to 7ppm on September 14th, and reached 10ppm or so before the accident happened, which showed signs of spontaneous combustion, but brought no vigilance. Taking the standard of 24ppm carbon monoxide concentration as the limit to toxic and harmful gases injurious to health as the warning index of spontaneous combustion lost the opportunity of timely warning spontaneous combustion. The problem exists in many mines of China, but still gets no attention.

5 Conclusion Firstly, the model of fire developing tendency in the mine fire zone under positive pressure ventilation was established, including roadway flow field, the fire zone combustion, chemical reaction model between coal and oxygen and boundary condition models. Then, based on the prototype of the particularly serious fire accident of Fuhua “9.20” in Heilongjiang province, the paper verified the rightness of the mathematical model above, and obtained the law of positive pressure ventilation influence on the fire zone and its enlightenment to safety in production. Acknowledgement. Funded by 11th Five-year Plan National Science and Technology Infrastructure Program 2006BAK03B05, Youth Fund of CUMTB 2009QE05 and national innovation experiment program for university students 101108z.

References 1. Zhang, G.S.: Ventilation Security. China University of Mining and Technology Press, Xuzhou (2007) 2. Wang, H.Y.: Study on Three-Dimensional Smoke Flowing Theory and the Application Technology of VR in Passage Fire. China University of Mining and Technology, Beijing (2004) 3. Peng, B., Reynolds, R.G.: Culture algorithms: Knowledge Learning in Dynamic Environments. In: Proceedings 2004 Congress on Evolutionary Computation, pp. 1751–1758. World Scientific Publishing Co. Pte Ltd., Singapore (2004) 4. John, D., Anderson, J.R.: Computational Fluid Dynamics-The Basics with Applications. Tsinghua University Press, Beijing (2002) 5. Incropera, F.P., Witt, D.P., Bergman, T.L., et al.: Fundamentals of Heat And Mass Transfer. John Wiley & Sons, New York (2007) 6. Krause, U., Schmidt, M., Lohrer, C.: Computations on the Coupled Heat and Mass Transfer during Fires in Bulk Materials, Coal Deposits and Waste Dumps. In: The Proceedings of the COMSOL Multiphysics User’s Conference, Frankfurt, pp. 1–6 (2005)

Study on Continued Industry’s Development Path of Resource-Based Cities in Heilongjiang Province* Ying Zhu∗∗ and Jiehua Lv Northeast Forestry University, College of Economics and Management, Harbin, China [email protected]

Abstract. The resource-based cities in Heilongjiang Province occupied a very important position. These cities and regions mostly faced with relative decline dilemma due to natural resources plunged. These directly affect the development of resources city. Therefore, industry transformation of resources city is realizing the sustainable development of regional economy. Keywords: sustainable development, the resource-based cities, industry development.

1 Introduction Heilongjiang province is a big resourceful province, resource-based cities in Heilongjiang province occupied a very important position. In the past these cities made significant contributions to national construction, regional economic and social development, but caused a series of "shock", recently most of the cities and regions have entered the mid-late resources exploitation. Because of natural resources plummeted, enterprise economic hand and worsening ecological environment, these result in the slower development of the cities and regions. They also faced with relative decline predicament. To choose appropriate and sustainable development’s path in resource-based cities of Heilongjiang has become one of the important strategic topics.

2 Development Conditions of Resource-Based Cities in Heilongjiang Heilongjiang province is the most provinces with the resource-based cities, there are 14, namely the resource-based cities yichun, jixi, hegang, shuangyashan, qitaihe, daqing, heihe, five dalian pool, ShangZhi, HaiLin, MuLeng, ning an, HuLin. There *

The article is subsidized by philosophy social science project of Heilongjiang province in 2010( item number:10B046) and Heilongjiang post-doctorate scientific research foundation (item number:LBH-Q09178). ∗∗ Corresponding author. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 390–395, 2011. © Springer-Verlag Berlin Heidelberg 2011

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are seven regional cities, namely, yichun, jixi, hegang, shuangyashan, qitaihe, daqing, heihe. According to the types of resources they can be divided into coal city, petroleum city and logging city: 4Coal cities: jixi, hegang, shuangyashan, qitaihe;1 petroleum city: daqing; 9 Logging cities: yichun, heihe, five dalian pool, ShangZhi, HaiLin, MuLeng, ning an, HuLin. The cities are mostly rich in mineral and forest resources exploration and exploitation, on the basis of the mining and forest by evolved, instead of natural form. Due to the need of development of mineral resources, the state in relatively short period for the number of human, financial and material related to the original injected rapidly. Only a few families in the village or a deserted place suddenly became a city. Resource-based cities in Heilongjiang province is mostly in the period of recession. Transformation problems relative to industry development in the resource-based cities is slow. Oil, coal and the forest resources declined. Natural resources relative to industrial structure is single, continuous small industrial scale, irreparable mining decline bring growth.

3 Industrial Development of Resources City Are Facing with the Problem in Heilongjiang The exposure draft has introduced that the new accounting treatment model for lesser and lesser, the related suggestion will affect the lessee and the lesser accounting treatment to the leasing contract, its revision main points as follows: 3.1 The Follow-Up Resources Reserve Is Insufficient, Worsening Ecological Environment On petroleum resources, daqing oilfield remaining recoverable reserves 5.39 million tons, with annual output of 4,500 tons and active implement protective mining, under the precondition of surplus phenomena that worldly 13 years, From the forest resources look, the greater hinggan mountains and yichun forest area significantly reduced, stand’s total volume, quality of trees and recoverable increment in volume are dropped substantially embodiment. At the aspect of coal resources, coal production of jixi, hegang, shuangyashan and qitaihe is 4 big coal cities for 68 years, existing 33 mine, already had 16 resource exhaustion. The resource-based cities for a long-term resources exploitation and environmental protection are disjointed, ecological environment were seriously damaged. Divide common "three wastes" besides, different types of cities would have different pollution. For example, the coal city ground subsidence, coal mining take up a lot of land, blocking river discharge dust, is causing serious pollution of environment. Because of oil separation vegetation destroyed with soil desertification, serious solemnization in the plain region. Because a long-term excessive cut trees, forest coverage rate drops, forest shelter-zone role weakened gradually. Ecological environment destruction, not only affects the local residents’ body health and quality of life, but also have largely restricted urban canvass business success rate.

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3.2 Simple Industrial Structure, to Resources Dependence is Strong Economic development in resource-based cities of Heilongjiang rely on resources exploitation and rough machining too much, only pursues resources products production quantity expansion, and other industrial development enough, causing the resource-based cities’ leading industry is single. Economy, finance, etc rely heavily on resources industry. Four coal cities has been the main force in coal exploitation and processing, the proportion of GDP in oil industry of daqing city has been more than 80%, Logging city, the development of the basic is by eating forest capital, stay in primary processing industry, low value-added such link. The first industry, the second industry and the third industry’s structure is with imbalance. For example, in 2008, three industries in daqing city weight for 11.8%, 85.1% and 3.1%. Most resource-based cities or in the second industry as the main body, development of the first and third industry lag behind, the single industrial structure is lack of momentum in the city's economic development, with resources exhausted, economic conditions decreasing even also appears a deterioration. 3.3 Industrial Correlativeness Degree Low, and the Economic Benefit is Low The resource-based cities leading industry is mainly state-owned enterprises, these industries from investment, production and sales of by the state implements clinching, makes the resources industries and city formed a relatively independent operation system, resources industry driving the development of relative industries advantage radiation slow, diffusion effect is bad, the industrial connection low, limiting resources industry in local economy association promotes makes urban economic over-reliance on resources industry. Resources industry development, in order to obtain larger benefits, often more attention to the development of storage, they generally belongs to upstream industry, and ignore can produce larger value-added depth processing, industrial chain short, causing deformity or urban economic recession. In addition, the large asset resources industry with high specificity, including equipment, basic production facilities, this part of the assets in enterprises over time is sunk costs, difficult to be used for other purposes. Therefore, the resource-based cities industrial structure once formed with strong rigidity, then this rigid it severely city industrial structure of changeover ability. 3.4 Funds Highlights, the Contradiction between Supply and Demand Talent Resource Scarcity Due to the lack of early industrial transformation and upgrade technology and most resource-based cities is still in the primary state of processed products output resources, product low profit, lack of market competitiveness, which is lack of financial resources city basic reasons. In addition, the resource-based cities because of geographical location, natural environment and living conditions such as disenchanted, often is the talents outflows than inflows. Talent is the foundation, the regional innovation of intellectual resources shortage of affected this urban innovating capacity, the state-owned enterprise technical renovation feels embarrassed, even if a new &high-tech projects, but lack of talent, good project also reach the good benefit, the new project cannot be started.

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4 Analysis on Resource-Based Cites Continued Industry Development Path in Heilongjiang 4.1 Guarantee in the Original Leading Industry Development A city development can not give up its fundamental, resource-based cities to ensure the sustainable development of resources industry must be original dominance of dominant industry as a prerequisite is the sustained and healthy development of the urban steady economic smooth forceful guarantee. Oil industry has been supporting daqing economic development of important farmar, so daqing petrochemical enterprise should fully support the construction of large base, strive to ready to petrochemical, daqing petrochemical industrial construction to become the biggest pigtail industry. Deforestation is ownership economy development is the most important pillar, future should continue to promote forest, lumbering, processing such a complete industrial system. The coal city in huaibei coal resources exploitation and may at the same time actively expand coal, coal turn electric industry. 4.2 Actively Developing Green Industry The green industry development can not only bring new economic growth point, and can reduce the damage to the natural environment, remove the deterioration of the environment, the greatest hazard. Cows, pigs in daqing city can develop, beef, mutton and big goose green food industry; etc. Focus on the development of wetland landscape, green hot spring tourism projects. Ownership should be actively developed wild fruit drinks, fresh edible, fruit milk, mineral water, quick-frozen brown wait for a variety of products and pollution-free rice green food; etc. Use of abundant tourism resources development has the characteristics of forest tourism in heilongjiang province north coal city in huaibei also should make xingkai lake, wusuli river WanDaShan forests, rivers, ZhenBaoDao wetland, longjiang gorges, WeiHe wetland, montefiore meters city tourism projects. 4.3 Focus on the Development of High-Tech Industries Science and technology is the first productivity, the sustainable development of resources city make good use of the weapon. Hi-tech industry with high content of technology, market competition quality is outstanding, the development potential, high return, high-risk characteristics. The resource-based cities should strive to using high-new technology instead of resources consumption, make economic growth from extensive to intensive evolution. The development of high-tech industry will accelerate the future economic into low consumption, high efficiency and nonpollution the pace of The Times. Daqing city in practice should focus on developing biological pharmaceutical, chemical, pharmaceutical, Efforts to develop energysaving, environmental protection, special new building materials. Ownership can be further development in Chinese medicine, western medicine, giving priority to the pills, tablets, capsules, plugs, oral liquid dosage form complete medical industry. Coal city can take high-tech forms, develop the hydropower development pithead coal chemical, coal -- -- --, metallurgy, building materials industries such as coal, used limited resources in search of higher value returns, extend the industrial chain.

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4.4 To Develop the Service Industry Service industry development level is the measure of a city's economic development level, but also an important symbol of the degree of civilization and judge the important basis. Long-term since Heilongjiang resource-based cities service lagging development, and the economic development and improve the requirements, compared to life still exist in the very big disparity. Actively develop the service industry, promote the proportion of service industry has become the urgent matter. Daqing constantly improve the third industries, thus taking emerging third industry instead of traditional third industry, by "using oil raise city" into "by city raise city". 4.5 Provide the Resource-Based Cities Continued Industry Development of Government Guarantee The government is the resource-based cities strategic development of the continued industry in the organizer, also responsibility subject. First, provide the system guarantee. The government can for the development of the continued industry in the laws and regulations, formulate specific investment policies, investment policy and industrial policy has articles inclining policy. Secondly, the government can provide some of the financial aid. To realize the industrial structure adjustment and upgrading, realize substituted industry and pigtail industry gradually entered the, must spend a lot of money. Lack of money problems rely solely on the market mechanism is difficult to fully solve, the central government and local government financial intervention become inevitable. Third, the government can provide for resources city planning and guidance. The resource-based cities for the development of our national economy has made great contribution to countries to this kind of urban planning and guidance in their development plays a stable and directional function. Of course, planning and guidance is a phased, it is just the resource-based cities developing a period of requirements.

References 1. Bhattacharjee, Y.: Industry Shrinks Academic Support. Science 312, 671 (2006) 2. Fritsch, M., Brixy, U., Falck, O.: The Effect of Industry, Region, and Time on New Business Survival – A Multi-Dimensional Analysis. Review of Industrial Organization 28(3), 285–306 (2006) 3. Bale, H.E.: Industry, innovation and social values. Science and Engineering Ethics 11(1), 31–40 (2005) 4. Wang, S., Jiang, L.: Economic transformation capacities and developmental countermeasures of coal-resource-based counties of China. Chinese Geographical Science 20(2), 184–192 (2010) 5. Pichon, C.L., Gorges, G., Boët, P., Baudry, J., Goreaud, F., et al.: A Spatially Explicit Resource-Based Approach for Managing Stream Fishes in Riverscapes. Environmental Management 37(3), 322–335 (2006)

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6. West, G.P., Bamford, C.E.: Creating a Technology-Based Entrepreneurial Economy: A Resource Based Theory Perspective. The Journal of Technology Transfer 30(4), 433–451 (2004) 7. Wang, S., Jiang, L.: Economic transformation capacities and developmental countermeasures of coal-resource-based counties of China. Chinese Geographical Science 20(2), 184–192 (2010) 8. Yang, X., Ho, E.Y.-H., Chang, A.: Integrating the resource-based view and transaction cost economics in immigrant business performance. Asia Pacific Journal of Management, Online FirstTM (October 16, 2010)

Cable Length Measurement Systems Based on Time Domain Reflectometry Jianhui Song*, Yang Yu, and Hongwei Gao School of Information Science and Engineering, Shenyang Ligong University, Shenyang, 110159, P.R. China [email protected] Abstract. Based on the principle of time domain reflectometry(TDR) cable length measurement, the principle error of the TDR cable length measurement is analyzed. Methods for reducing cable length measurement error are analyzed. Two cable length measurement systems based on the TDR principle are designed. The high-precision time interval measurement module is the core of the first measurement system. The sampling oscilloscope with a computer is the core of the second measurement system. The experimental results show that the measurement systems developed in this paper can achieve high cable length measuring precision. Keywords: TDR, time interval measurement, measurement system.

1 Introduction The issue of measuring precision in the wire and cable market becomes more and more prominent. It is significant to measure the cable length precisely, rapidly and economically. Compared with the traditional measurement methods, time domain reflectometry (TDR) technology has an advantage of non-destruction, portability and high-precision, which is an ideal cable length measurement method[1~3]. In order to achieve high cable length measuring precision and study the key technologies of the cable length measurement based on TDR, two cable length measurement systems based on different platforms are developed.

2 The TDR Cable Length Measurement Theory TDR is a very useful measuring technology based on high-speed pulse technology. The cable length measuring principle is very simple. The test voltage pulse is injected into one end of the cable, and the pulse will be reflected at the end of the cable. By measuring the time interval between the injection pulse and the reflection pulse, the cable length can be obtained by assuming the velocity as constant[4,5]. The formula for length measurement is v ⋅ Δt (1) l= 2 *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 396–401, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Where, l —cable length, v —signal propagating velocity, Δt —time interval between the injection pulse and the reflection pulse. According to the linear superposition law of error propagation, the cable length error can be expressed as formula (2) 1 2

δ l = (t ⋅ δ v + v ⋅ δ t )

(2)

Where, v ——signal propagating velocity in cable t ——time interval between the injection pulse and the reflection pulse δ v ——propagation velocity error δ t ——time interval measuring error. The direct pulse counting method is the most basic method of time interval measurement and it is almost the basic of all time interval measurement methods. Many methods combine the direct pulse counting method with other methods to achieve high precision measurement. Therefore, the TDR cable length measuring accuracy based on the principle of direct pulse counting time interval measurement are analyzed. According to the principle of direct pulse counting, δ t can be expressed as formula (3)

1 N ⋅δ N − 2 ⋅δ f f f

δt =

(3)

Where, f ——count pulse frequency N ——count pulse number δ f ——count pulse frequency error δ N ——count pulse number error. Therefore, formula (2) can be expressed as formula (4)

δl = l ⋅

δv v

+l⋅

δN N

−l ⋅

δf f

(4)

The cable length is measured n times. Taking into account of the random measuring errors and according to the of random error accumulation, the average measuring error can be calculated by formula (5):

δl = l ⋅

δv v

+

l n 1 δf ⋅ ∑ ⋅δ N − l ⋅ n i =1 N i f

(5)

The ±1 quantization error can be expressed as:

1 1 1 1 = = ... = ( ) = N1 N 2 Nn N

(6)

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At present, the crystal oscillator temperature stability is better than 10−9 , therefore the count pulse frequency error can be ignored. At this point the TDR cable length measuring uncertainty ul can be expressed as ul = (l ⋅

uv 2 v 2 ) +( ) v 2f n

(7)

Where, uv ——propagation velocity standard uncertainty u f ——reference frequency standard uncertainty n ——number of measurements.

It can be seen from formula (7) that when the velocity is constant, the count pulse frequency and number of measurements are the key factors to the TDR cable length measuring uncertainty.

3 The TDR Cable Length Measurement Systems In order to achieve high cable length measuring precision and study the key technologies of the cable length measurement based on TDR, two cable length measurement systems based on different platforms are developed. The schematic diagram and photo of measurement system I and II are shown in Fig. 1 and Fig. 2. The first measurement system is composed of signal transmitting and receiving modules, the high precision time interval measurement module, temperature measurement module, display circuit, control panel and microprocessor. Different amplitude and different pulse width signal is transmitted into the cable under test based on the actual measurement situation. Then the time interval between the transmitted pulse and reflected pulse is shaped into the gate signal and measured by high precision time interval measurement module. The time interval measurement result is sent into the microprocessor and filtered to eliminate the gross errors. According to the ambient temperature measured by the temperature measurement module, the propagation velocity is compensated. Finally the length of the cable under test is calculated and sent to the display circuit to display.

Fig. 1. Schematic diagram and photo of measurement system I

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399

computer

sampling oscilloscopes

signal generator

temperature measurement module

Cable under test

Fig. 2. Photograph of measurement system II

The second measurement system is composed of signal generator, sampling oscilloscopes temperature measurement module and computer. Different amplitude and different pulse width signal generated by signal generator is transmitted into the cable under test based on the actual measurement situation. The waveform data of the transmitted pulse and reflected pulse is collected by the sampling oscilloscope and sent into the computer processing. Firstly, the measurement data is filtered by the system software. Then the reflected wave is identified and detected by the reflected wave recognition algorithm. According to the ambient temperature measured by the temperature measurement module, the propagation velocity is compensated. Finally the length of the cable under test is calculated.

4 Experiment and Analysis A length of 105.00m RVV 300/300V PVC sheathed flexible cable is measured by measurement system I. The count frequency of the high precision time interval measurement module is 1.2GHz. The cable length is measured 256 times. The propagation velocity is 2 × 108 m/s. The measurement data are analyzed. There are nine measurement results. The histogram is shown in figure 3. The standard deviation of the TDR cable length measurement system is 256

sl =

∑l i =1

2

i

N −1

= 0.12 ( m )

(8)

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The standard deviation of the cable length measurement arithmetic mean is

( )

s Δl =

lt N

= 0.01( m )

(9)

The coverage factor k is 2, then the expanded uncertainty of the cable length measurement is

＝

U l = ks (Δl ) 2× s (Δl ) = 0.02 ( m )

(10)

Occurrences number of measurement results

It can be seen from formula (8) to (10) that the measurement system developed in this paper can achieve high precision cable length measurement. 80

60

40

20

0

103.25 103.33 103.42 103.50 103.58 103.67 103.75 103.83 103.92 Cable length(m)

Fig. 3. Random error of cable length measurement system

5 Conclusions Based on the principle of time domain reflectometry(TDR) cable length measurement, Two cable length measurement systems based on the TDR principle are designed. The high-precision time interval measurement module is the core of the first measurement system. The sampling oscilloscope with a computer is the core of the second measurement system. The experimental results show that the measurement systems developed in this paper can achieve high cable length measuring precision.

References 1. Dodds, D.E., Shafique, M., Celaya, B.: TDR and FDR Identification of Bad Splices in Telephone Cables. In: 2006 Canadian Conference on Electrical and Computer Engineering, pp. 838–841 (2007) 2. Du, Z.F.: Performance Limits of PD Location Based on Time-Domain Reflectometry. IEEE Transactions on Dielectrics and Electrical Insulation 4(2), 182–188 (1997)

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3. Pan, T.W., Hsue, C.W., Huang, J.F.: Time-Domain Reflectometry Using Arbitrary Incident Waveforms. IEEE Transactions on Microwave Theory and Techniques 50(11), 2558–2563 (2002) 4. Langston, W.L., Williams, J.T., Jackson, D.R.: Time-Domain Pulse Propagation on a Microstrip Transmission Line Excited by a Gap Voltage Source. In: IEEE MTT-S International Microwave Symposium Digest, pp. 1311–1314 (2006) 5. Buccella, C., Feliziani, M., Manzi, G.: Detection and Localization of Defects in Shielded Cables by Time-Domain Measurements with UWB Pulse Injection and Clean Algorithm Postprocessing. IEEE Transactions on Electromagnetic Compatibility 46(4), 597–605 (2004)

The Cable Crimp Levels Effect on TDR Cable Length Measurement System Jianhui Song*, Yang Yu, and Hongwei Gao School of Information Science and Engineering, Shenyang Ligong University, Shenyang, 110159, P.R. China [email protected]

Abstract. Time domain reflectometry (TDR) technology is an ideal cable length measurement method. The traveling wave propagation velocity is the key to the measuring accuracy of the TDR cable length measurement system. The cable crimp levels effect on traveling wave propagation velocity is analyzed theoretically, and the corresponding experiment is done. The experimental results are match to the theoretical analysis. The experimental results show that the law of the traveling wave propagation velocity influenced by cable crimp levels is different for different types of cable, however, as long as the cable state under test is uniformed, the velocity error can be controlled in a small range. Therefore the measuring accuracy of the TDR cable length measurement system is ensured. Keywords: TDR, propagation velocity, cable crimp level.

1 Introduction All kinds of wires and cables have been widely used with the rapid development of the national economy. The wire and cable industry have developed rapidly, and gradually expanded the production scale and market share. Cable is an important commodity, and its length measurement precision is strictly formulated in the national standard. However, the issue of measuring precision in the wire and cable market becomes more and more prominent. It is significant to measure the cable length precisely, rapidly and economically. Compared with the traditional measurement methods, time domain reflectometry (TDR) technology has an advantage of nondestruction, portability and high-precision, which is an ideal cable length measurement method[1~3]. It is found in practice that the measuring accuracy of the TDR cable length measurement system can be influenced by the cable crimp levels. In order to reduce the cable crimp levels effect on the measuring accuracy of the TDR cable length measurement system, the cable crimp levels effect on traveling wave propagation velocity is analyzed theoretically, and the corresponding experiment is done.

2 Relationship between Velocity and Distributed Capacitance of Cable According to the theoretical knowledge of the capacitor plates, the capacity of the capacitor plates can be calculated as formula (1): S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 402–407, 2011. © Springer-Verlag Berlin Heidelberg 2011

The Cable Crimp Levels Effect on TDR Cable Length Measurement System

C=

ε × D×l d

403

(1)

Where, D is the width of the capacitor plates, l is the length of the capacitor plates, d is the distance between the two plates of the capacitor, ε is the dielectric constant. According to the cable length measurement principle of capacity conversion of capacitor, an open end cable is regarded as a capacitor. Two cores of the cable is regarded as two plates of the capacitor. The effective width of the cable core can be approximately interpreted as D in formula (1). The length of the cable can be regarded as l in formula (1). The distance of the cable cores can be interpreted as d in formula (1). For the two core wire cable whose internal structure, ε , D and d is fixed, the capacitances between the two wires of the cable are proportional to the cable length. That is

C1 l1 = C2 l 2

(2)

The cable length can be obtained by measuring the cable capacitance per unit length[4]. At high frequencies, the propagation velocity of the electromagnetic waves can be calculated as formula (3)[5~7].

v=

1 L0 C0

(3)

Where, L0 is the distributed inductance per unit cable length. C0 is the distributed capacitance per unit cable length. It can be seen from formula (3) that the wave velocity is inversely proportional to the square root of the distributed capacitance per unit length. The relationship between the velocity and distributed capacitance can be expressed as follow v ∝ 1/ C0

(4)

The distance between the adjacent insulated core decreases and the distribution capacitance of the cable increases as the cable is curled. Therefore the velocity decreases as the cable is curled. However, as long as the cable state under test is uniformed, the distribution capacitance of the cable is also uniformed; therefore, the velocity can be controlled in a small range.

3 Experiment and Analysis In order to further study the law of the traveling wave propagation velocity influenced by cable crimp levels, the measurements were performed on RVV 300/300V PVC insulated cable. The equivalent capacitances and distributed capacitances of different cable length in state of curl and straighten is shown in table 1.

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Table 1. Equivalent capacitances and distributed capacitance of different cable length in state of curl and straighten Curl

Cable under

Straighten Equivalent

Equivalent

Distributed

capacitances(nF)

capacitances(pF)

30.00

1.5183

50.610

1.4615

48.717

86.75

4.3892

50.595

4.2257

48.711

test(m)

Distributed

capacitances

capacitances(pF)

(nF)

Table 2. Equivalent capacitance ratio and length radio of with 86.75m and 30.00m cable length in state of curl and straighten Curl

Straighten

Capacitance ratio

Length ratio

Capacitance ratio

Length ratio

2.8909

2.8917

2.8913

2.8917

Table 3. Velocity and relative error of different cable length and different cable crimp degree Cable under test(m) 30.00

Cable state

velocity(m/s)

Straighten

1.9234 × 10

Curl

1.8886 × 108

Straighten

1.9258 × 108

Curl

1.8892 × 108

86.75

Relative error(%)

8

1.84

1.94

The equivalent capacitance ratio and length radio of 86.75m and 30.00m cable length in state of curl and straighten is shown in table 2. The ambient temperature is 17.0 . It can be seen from table 2 that although the values of the equivalent capacitance of the cable are different under different conditions, the capacitances between the two wires of the cable are still proportional to the cable length. In the same state, the equivalent capacitance of the cable is greater as the cable length is longer. But the distributed capacitance per unit cable length is always the same. The comparison of the distributed capacitance in state of curl and straighten, it can be found that the equivalent capacitance and distributed capacitance in state of curl is bigger than the equivalent capacitance and distributed capacitance in state of straighten. It is because the distance between the adjacent insulated wire cores decreases as the cable is curled, therefore the equivalent capacitance and distributed capacitance in state of curl is bigger. The velocity and relative error of different cable length and different cable crimp degree is shown in table 3. It can be seen form table 3 that the relative error of velocity in state of curl and straighten is big. The velocity relative error of the same cable crimp degree with 86.75m and 30.00m cable length is shown in table 4. It can be seen form table 3 and table 4 that the cable crimp degree of RVV 300/300V PVC

℃

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sheathed cable has a great impact on the velocity. However, as long as the cable state under test is uniformed, the velocity can be controlled in a small range. The measurements were performed on RVVP multi-core shielded cable. The length of three cores is 40.73m. The length of seven cores is 41.57m. The length of eight cores is 43.18m. The ambient temperature is 18.0 The equivalent capacitances and distributed capacitance of different cable cores in state of curl and straighten is shown in table 5. The velocity relative error is shown in table 6. It can be seen form table 5 and table 6 that the cable crimp degree of RVVP multicore shielded cable has little impact on the velocity. However, the cable state under test is better to be uniformed to control the velocity error in a small range. The measurements were performed on SYV75-5-1 coaxial cable. The length is 156.06m. The ambient temperature is 18.0 . The equivalent capacitances and distributed capacitance of coaxial cable in state of curl and straighten is shown in table 7. The coaxial cable velocity relative error in state of curl and straighten is shown in table 8.

℃。

℃

Table 4. Velocity relative error of the same cable crimp degree with 86.75m and 30.00m cable length Cable state

Velocity relative error(%)

Straighten

0.1

Curl

0.03

Table 5. Equivalent capacitances and distributed capacitance of different cable cores in state of curl and straighten Straighten

Curl

Cable under

Equivalent

Distributed

Equivalent

Distributed

test

capacitances

capacitance

capacitances

capacitance

(nF)

(pF)

(nF)

(pF)

Three cores

5.7440

141.03

5.7890

142.14

Seven cores

4.4257

106.46

4.4891

107.99

Eight cores

4.7321

109.60

4.7709

110.50

Table 6. Velocity relative error of different cable crimp degree

Cable under test

velocity(×108m/s) Relative error(%)

Three cores

Seven cores

Eight cores

Straighten

Curl

Straighten

Curl

Straighten

Curl

1.7098

1.7071

1.7463

1.7440

1.7030

1.6997

0.16

0.13

0.19

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Table 7. Equivalent capacitances and distributed capacitance of coaxial cable in state of curl and straighten Straighten

Curl

Cable

Equivalent

Distributed

Equivalent

Distributed

under test

capacitances

capacitance

capacitances

capacitance

(nF)

(pF)

(nF)

(pF)

11.993

76.848

12.022

77.034

Coaxial cabel

Table 8. Coaxial cable velocity relative error of different cable crimp degree Cable under test

Straighten

Curl

velocity(m/s)

1.9815 × 108

1.9811 × 108

Relative error(%)

0.02

It can be seen form table 7 and table 8 that the cable crimp degree of SYV75-5-1 coaxial cable has very little impact on the velocity. However, the cable state under test is better to be uniformed to control the velocity error in a small range.

4 Conclusions The cable crimp levels effect on traveling wave propagation velocity is studied. The experiment results show that the cable crimp degree of RVV 300/300V PVC sheathed cable has a great impact on the velocity. The cable crimp degree of RVVP multi-core shielded cable has little impact on the velocity. The cable crimp degree of SYV75-5-1 coaxial cable has very little impact on the velocity.

References 1. Dodds, D.E., Shafique, M., Celaya, B.: TDR and FDR Identification of Bad Splices in Telephone Cables. In: 2006 Canadian Conference on Electrical and Computer Engineering, pp. 838–841 (2007) 2. Du, Z.F.: Performance Limits of PD Location Based on Time-Domain Reflectometry. IEEE Transactions on Dielectrics and Electrical Insulation 4(2), 182–188 (1997) 3. Pan, T.W., Hsue, C.W., Huang, J.F.: Time-Domain Reflectometry Using Arbitrary Incident Waveforms. IEEE Transactions on Microwave Theory and Techniques 50(11), 2558–2563 (2002)

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4. Shan, L.D., Meng, W.S., Zhang, L.H., Wang, Y.M.: Apply the Principle of Capacity Conversion of Capacitor and Quick Determination the Inside Break Point of Cable. Metal World (4), 46–48 (2006) 5. Mugala, G., Eriksson, R.: Measurement Technique for High Frequency Characterization of Semi-Conducting Materials in Extruded Cables. IEEE Transactions on Dielectrics and Electrical Insulation 11(3), 471–480 (2004) 6. Oussalah, N., Zebboudj, Y.: Analytic Solutions for Pulse Propagation in Shielded Power Cable for Symmetric and Asymmetric PD Pulses. IEEE Transactions on Dielectrics and Electrical Insulation 14(5), 1264–1270 (2007) 7. Oussalah, N., Zebboudj, Y., Boggs, S.A.: Partial Discharge Pulse Propagation in Shielded Power Cable and Implications for Detection Sensitivity. IEEE Electrical Insulation Magazine 23(6), 5–10 (2007)

The Clustering Algorithm Based on the Most Similar Relation Diagram Wei Hong Xu1, Min Zhu1, Ya Ruo Jiang1, Yu Shan Bai2, and Yan Yu2 1

College of Computer Science, Sichuan University, Chengdu, China College of Education, Tianjin Normal University, Tianjin, China [email protected] [email protected]

2

Abstract. The MSRD (Most Similar Relation Diagram) of a dataset is a weighted undirected graph constructed from an initial dataset. In the MSRD, each datum represented by a vertex, is connected with its MSD (Most Similar Data), and each MSRG (Most Similar Relation Group), represented by a subgraph, is connected with its MSG (most similar group) through connecting the most similar pairs of data between the two sub-graph. The clustering algorithm based on the MSRD involves two stages: constructing the MSRD of the dataset and cutting the diagram into sub-graphs (clusters). In this paper, we developed a package of methods for the later stage and applied them to some synthesized and real datasets. The performance verified the validity of these methods and demonstrated that the MSRD based clustering is a universal and rich algorithm. Keywords: data mining, clustering algorithm, weighted graph, the most similar relation diagram (MSRD), the most similar data (MSD), the most similar group (MSG).

1 Introduction In recent years, cluster analysis has become an important tool in data mining, and has been extensively studied and applied to many fields such as pattern recognition, customer segmentation, similarity search and trend analysis. Though thousands of clustering algorithms have been presented, some new algorithms still continue to appear [1] due to the demand in practice and theory. Some algorithms of recent trend e.g. ensemble methods [2], semi-supervised method [3], methods for clustering largescale datasets, Multi-way clustering method [4] as well as kernel and spectral methods [5] are developed notably. Recently, Yan Yu et al. published a clustering algorithm based on the MSRD (Most Similar Relation Diagram) [6]. This algorithm consists of two stages: constructing the MSRD of the dataset and cutting the MSRD into clusters. In literature [6], the first stage has been presented in detail, but the second stage seems to have not been explored sufficiently. In this paper we develop a package of methods of cutting the diagram into clusters and apply some of the methods on some synthesized and real dataset. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 408–415, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Terms and Definitions

…

Definition 1. Let G=G (V, E) is a graph. V={Vn| n=1, ,N} is the set of vertexes. Then vh is the Most Similar vertex (MSV) of vi if h=arg minj {dij}; dij is the dissimilarity between vi and vj; vi, vj V; j=1, 2, , h, , N; j≠i. A vertex vi and one of its MSV vj is called the most similar pair (MSP) of vertexes and is denoted by vi j. According to definition 1, each vertex has at least one MSV in a graph, but it is not true that a vertex must be the MSV of another vertex. Some vertexes are not the MSV of any vertex. The edge connecting a vertex and its MSV is called the 1st level edges, denote by (1) eij . Suppose Gi =Gi(Vi, Ei) is a sub-graph of G(V,E); Ei={eij(1)| j=1, ,J}, J is the number of the edges of Gi. Then, Gi is called a 1st level sub-graph, which is denoted by Gi(1).

，

∈

∽v

… …

…

…

Definition 2. Let (1) G is cut into M sub-graphs, G={Gm|m=1, ,M} (2) Gi∩Gj =Φ, (Gi, Gj G; i, j=1, 2, , M; i≠j); (3)Vi={vip|p=1, ,P}; Vj={vjq|q=1, ,Q} (Vi Gi; Vj Gj). Then, Gl is the most similar graph (MSG) of Gi. vlh Gl and vik Gj is the most similar pair (MSP) of vertexes between Gl and Gi, if l,h,k=arg minj,p,qwpq (wpq is the weight of e(vlp, viq)); j=1, ,l, , M; p=1, , h, , P; q=1, , k, , Q; j≠i). The edge between the two vertexes of a MSP, vik and vlh, in 1st level sub-graphs is called the 2nd level edge, denoted by eij(2). According to definition 2, any sub-graph has at least one MSG in a partition, but sometimes sub-graph is not the MSG of any sub-graph.

∈

∈

…

…

… …

… …

… ∈ ∈ … …

∈

…

Definition 3. Suppose there is a sub graph Gi(l)=Gi(Vi(l), Ei(l)), l=2,3, , L; (l) (1) (l-1) th Ei ={eij , , eik | j=1, 2, , J; k=1, 2, , K}. Then, Gi is a m level sub-graph and is denoted by Gi(m) if m=argl max l.

…

…

…

Definition 4. Suppose there is a graph G=(V, E), V={Vn|n=1,…,N}, E=E(eij); eij is the edge between vi and vj(i,j=1, 2, …, N; i≠j). Then, G is called the Most Similar Relation Graph (MSRG) if vi vj.

∽

3 The Clustering Algorithm Based on the MSRD The clustering algorithm based on the MSRD involves two stages: (1) constructing the MSRD of the dataset; (2) cutting the MSRD into clusters. 3.1 Constructing the MSRD of the Dataset The procedure of constructing the MSRD of a dataset is as follows: Define and compute the dissimilarities of each vertex with others and find the MSVs of every vertex following the definition 1. In this paper we use the Euclidean distance to measure the dissimilarity between a pair of vertexes.

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(a)

(b)

(d)

(c)

(e)

Fig. 1. (a) The coordinate graph of dataset 1; (b) The four 1st level MSRG of dataset 1; (c) The 2nd level MSRG of dataset 1; (d)The MSRD of dataset 1; (e) The r-MSRD of dataset 1

Connect every vertex (or node) to its MSV by an edge. By doing so, a certain number of sub-graphs are composed. Following the definitions above, these subgraphs are all 1st level MSRGs, and all the edges are the 1st level edges. According to the definition 2, find the MSGs of every 1st level sub graph and the MSP of vertexes between the two sub-graphs. Connect the two vertexes of every MSP so that each 1st level sub-graph will be connected to its MSGs to form a certain number of 2nd level sub-graphs. Following the definitions above, these sub-graphs are 2nd level MSRGs.Iterate such process to merge the lower level sub-graphs into higher level sub-graphs until all MSRGs are aggregated into one graph, the MSRD of the dataset.At last, assign the weight value to every edge beside it. By now the construction of the MSRD is accomplished. As an example, we synthesized a simple two-dimension dataset including 20 data called dataset 1. Fig.1 (a) is the coordinate graph of dataset 1. Fig. 1 (b) shows the four 1st level sub-graphs and Fig. 1 (c) shows the 2nd level sub-graphs of dataset 1. The numerals in Fig.1 (b) and (c) are the IDs of some data. The MSRD of dataset 1 constructed following the procedure above is shown in Fig.1 (d). Comparing Fig.1 (a) with (d), the relation between a dataset and its MSRD can be seen. From Fig.1 (b) it can be seen that 20 vertexes are connected together by 1st level edges to construct four 1st level sub-graphs: G1(1){1, 2, 3, 4, 5, 6, 7,8}, G2(1){9, 10, 11, 12, 13, 14,15, 16}, G3(1){17,18} and G4(1){19,20}. Then, G1(1) and G2(1)are connected by the 2nd level edge e14,17 , to form a 2nd level MSRG G1(2). G1(2){ G1(1), G2(1), G3(1) , G4(1)} is the highest level “sub-graph” and is also the MSRD of dataset 1. 3.2 Cutting the MSRD into Clusters By cutting off a certain number of edges in the MSRD, a partition of the dataset can be generated. Usually the edges with the highest weights in the MSRD should be chosen to cut off if the Euclidean distance is the measure of the dissimilarity. Therefore if the different approaches are adopted in weighting the edges, the different edges will be selected to cut off and different partitions will be generated. There may be variety of methods for weighting the edges relying on the factors being taken into account such as the number of the clusters, the similarity between the clusters, the densities of the

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data, the shape of the clusters, the uniformity of the partition, the size or volume of the clusters etc. Suppose the weight of an edge eij is wij, we propose a package of methods for weighting the edges of the MSRD: The d-MSRD. wij=dij. dij is the dissimilarity between xi and xj (or between vi and vj). The l-MSRD. wij=lij. lij is the level of eij. The r-MSRD. wij=rij.

—

The fragments contain vi vj in a MSRD can be one of the three cases in Fig. 2. In any case, the rij of eij is calculated according to formula (1). The case of (a) is the normal one and the formula (1) can be used directly. In the case of (b), take djk=∞; in the case of (c), take djk=( djm+djl)/2, the rij is also calculated according to formula (1).

(a)

(b)

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Fig. 2. The fragment cases in MSRD

(dij-dhi)+(dij-djk) if (dij-dhi)>0 and (dij-djk) >0 rij=

(dij-dhi) 0

≦0 if (d -dh )≦0 and (d -d )≦0 if (dij-dhi)>0 and (dij-djk) ij

i

ij

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The u-MSRD. wij=uij.The uniformity uij of Eij is calculated according to formula (2) uij=( N ij N ij )/( N ij + N ij )

(2)

N ij and N ij are the number of data in the two clusters respectively generated if Eij is cut off. The double factor methods. such as the ld-MSRD, ud-MSRD, lr-MSRD, ur-MSRD, the wij is defined by wij=lijdij,, wij=uijdij, wij=lijrij, wij=uijrij. The triple factor methods. such as the uld-MSRD and ulr-MSRD, the wij is defined by wij=uijlijdij and wij=uijlijrij respectively. Obviously, partitions with different features can be obtained by selecting different methods.For example, the d-method can generate such partitions that the gaps between the clusters are as big as possible. So it favors partitions containing isolated nodes. See Fig.3 (a). It is interesting to notice that the partition generated by d-method is all the same with that generated by Hierarchical simple method. For instance, the partition in Fig.3 (a) is generated by Hierarchical simple method also. The l-method cut the high level edges off to prevent the lower level MSRG from dividing. Therefore, the partition produced by l-method is more uniform than that produced by d-method. See Fig.3 (b). The u-method can generate partition with high uniformity. Partition in Fig. 3 (c) demonstrates this conclusion. The r-method can guarantee the data points in a manifold to be in the same cluster. See Fig.3 (b).

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(a) by d-method

(b) by l-, r-, lr- ur- and ulr- methods (c) by u-method

(d) by ud-method

Fig. 3. The partitions generated by different methods of MSRD

The double or triple factor methods take multiple factors into account so that it can generate partitions with multi-features. Fig. 3 (d) is the partition based on the udmethod, it is more uniform than (a), but the gaps between some clusters are narrower than that of (a). These arguments support that the MSRD method is a rich clustering method for it can generate variety of partitions with different features, some of which are not be able to generate by K-means or Hierarchical, such as the partition in Fig.3 (b). The partition in Fig. 3 (b) is generated by l-, r-, u-, lr- ur- and ulr- methods of MSRD does not mean that these methods always generate the same partitions for any dataset. Whether the different methods generate different partitions vary with the characteristics of the datasets.

4 The Clustering of the Synthesized Dataset Tow artificial datasets called dataset 2 and dataset 3 are used in testing our algorithm respectively. The coordinate graph of it is shown in Fig. 4 (a) and 4 (b). It is no doubt that when the weight of e(v1, v13) is larger than that of e(v1, v2) (see Fig. 4 (a)), it is an easy task for many existing algorithms to separate the two ellipses from each other. But when the weight of e(v1, v13) is smaller than that of e(v1, v2) (see Fig. 4 (b)), many existing algorithms can not separate the two ellipses. The partitions generated by k-means and the 7 methods of Hierarchical shown in Fig.4 (c), (d), (e), (f) and (g) demonstrate this argument. However the r-, u- and the ur-method of MSRD can generate the partition as shown in Fig.4 (h).

(a) d(1,2)
(e) by single

(b) d(1,2)>d(1,13)

(c) by ward

(f)by weighted and median

(d) by complete, average and centroid

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Fig. 4. (a) and (b) the coordinate graph; (c), (d) ,(e), (f), (g) the partitions of dataset 3 by different methods; (h) the partitions of dataset 3 by the r-MSRD methods

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The partitions of dataset 4 generated by k-means, the 7 methods of Hierarchical and MSRD are shown in Fig.5. Only MSRD can separate the two ellipses (see Fig. 5 (d)). Fig. 6 shows the coordinate graph and the partitions of dataset 5 by different methods. It is clear that the partition generated by MSRD is more reasonable and receivable than the others. This example demonstrates that the MSRD can detect clusters with different size, shape and density simultaneously. What we must address is that the partitions generated by k-means and Hierarchical in Fig. 4, 5 and 6 can also be generated by our MSRD method. This shows universality of our Method. But some partitions generated by our MSRD methods, such as the partitions in Fig. 3 (d), Fig. 4 (h) and Fig. 5 (d), are not able to generate by k-means and Hierarchical. This suggests the richness of our mathod.

（a）

(b)

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Fig. 5. The partitions of dataset 4 generated by k-means (a), by single of Hierarchical (b), by the oher 6 methods of Hierarchical (c), by r-MSRD (d).

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Fig. 6. The coordinate graph (a), and the four-cluster partitions of dataset 5 by k-means (b), single of Hierarchical (c), word of Hierarchical (d) and ulr-MSRD (e)

5 The Clustering of the Real Dataset In this section we test our methods in clustering real datasets, Breast-cancer and Wine, and compare the performance with K-means and Hierarchical. The clustering results of Iris and Wine by the ulr-MSRD method are given in Table 1 and Table 2 together with the clustering results obtained by K-means, Single and Ward method of Hierarchical for comparison. In the tables, Ni is the number of the data in the cluster i; Nj is the number of the data in the category or class j labelled by the dataset provider; Nij is the number of the data belong to the category j or class j being partitioned into cluster i. It can be seen from Table 1 and 2 that the partition of Iris

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Dataset Categories 1 2 3

Nj 50 50 50

K-means Nj Ni,j 50 50 62 48 38 36

Single Nj Ni,j 50 50 1 0 99 49

Ni 50 64 36

Ward Ni,j 50 49 35

ulr-MSRD Ni Ni,j 50 50 47 46 53 49

Table 2. The clustering results of Wine by four methods Dataset Class 1 2 3

Nj 59 71 48

K-means Ni Ni,j 62 59 65 59 51 48

Single Ni Ni,j 174 59 3 3 1 0

Ward Ni 64 58 56

Ni,j 59 58 48

ulr-MSRD Ni Ni,j 69 59 55 55 54 48

generated by ulr-method of MSRD is better than that generated by K-means and Word of Hierarchical. However, the performance of ulr-MSRD, K-means and Hierarchical ward in clustering the Wine are not much different.

6 Conclusion In this paper we developed a package of clustering methods based on the MSRD and applied them to some real and synthesized datasets. The performance verified the validity of these methods and demonstrated that the clustering based on the MSRD can detect both the spherical and non-spherical clusters simultaneously, and has the capacity to distinguish the clusters of different size, with different density, having different shape, or belong to the different manifolds. Therefore, it is more universal and richer than K-means and Hierarchical. Acknowledgments. The authors would like to thank Professor Pilian He in advance for his helpful suggestion to improve this paper. We are grateful to the editors and anonymous reviewers for their constructive comments. This work is supported by the Science and Technology Department Sichuan Provence, China (2009JY0038).

References 1. Jain, A.K.: Data clustering: 50 years beyond K-means. Pattern Recognition Letters 31, 651– 666 (2010) 2. Fred, A., Jain, A.K.: Data clustering using evidence accumulation. In: Proc. Internat. Conf. Pattern Recognition, ICPR (2002) 3. Chapelle, O., Schölkopf, B., Zien, A. (eds.): Semi-Supervised Learning. MIT Press, Cambridge (2006)

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4. Bekkerman, R., El-Yaniv, R., McCallum, A.: Multi-way distributional clustering via pairwise interactions. In: Proc. 22nd Internat. Conf. Machine Learning, pp. 41–48 (2005) 5. Filippone, M., Camastrab, F., Masulli, F., Rovetta, S.: A survey of kernel and spectral methods for clustering. Pattern Recognition 41, 176–190 (2008) 6. Yu, Y., Bai, Y.S., Xu., W.H., et al.: A Clustering Method Based on the Most Similar Relation Diagram of Datasets. In: 2010 IEEE International Conference on Granular Computing, San Jose, California, August 14-16, pp. 598–603 (2010)

Study of Infrared Image Enhancement Algorithm in Front End Rongtian Zheng, Jingxin Hong, and Qingwei Liao The Advanced Digital Processing Laboratory, Xiamen University, Xiamen, Fujian, China, 361005 [email protected]

Abstract. In this paper, we propose a linear enhancement algorithm for original infrared images. The algorithm which is choosing the transform threshold based on infrared detector’s features, that is a majority of normal pixels locate in an aiguille, minority non-operating pixels and some noise locate some other places in histogram, needs little space resource and time. The experimental results show that the image details can be revealed effectively by this algorithm. There is a problem that grayscale range of the target is not much enough when we use common linear enhancement to process the image while the sky and earth appear in one infrared image, it leads to low contrast of the target, since, we propose a improved algorithm—segmentation enhancement. The results show the improving algorithm is better than the common linear enhancement method. Keywords: original infrared image, infrared detector, linear enhancement, Front End process, grayscale.

1 Introduction Original infrared image collected from infrared detector has some features, which are existing non-operating pixels, low contrast, gray concentrating on a small grayscale range in the histogram, and the contrast of target is too low to see the image details. In order to see the infrared image details and improve image quality, enhancing the original infrared image in front end is necessary. The remainder of the paper is organized as follows: in section 2, traditional infrared image enhancement methods are briefly exposed. In section 3, the proposed method is introduced. In section 4, we present the improved algorithm. In section 5, we give details of the experiment results. In section 6, we present our conclusions.

2 Traditional Algorithm Traditional infrared image enhancement usually uses Histogram equalization (HE). This method smoothes the histogram through specific gray-level transforming function and then revises the original image according to new histogram. The essential of HE is to expand those pixels that have large gray quantity probabilities to neighboring gay-level pixels and compress those pixels whose quantity gray S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 416–422, 2011. © Springer-Verlag Berlin Heidelberg 2011

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probabilities are small [1]. According to the features of infrared image, which is the target in the original image has small grayscale, when HE is used in infrared image processing, the image quality will worsen much and we can't recognize the target from the background, so the traditional HE method doesn't suit in these conditions . Linear enhancement algorithm can expand those target pixels in original infrared image and compress, even denoise the noise, and its key is to choose gray-level transforming threshold. Such as using histogram statistics obtain 1/32 and 31/32 mean value of the histogram as the transform threshold [2], intensify image contrast using segmented histogram nonlinear extension [3], A kind of infrared image contrast enhancement algorithm based on discrete stationary wavelet transform (DSWT) and non-linear gain operator [4], A conventional piecewise linear grey transformation based self-adaptive contrast enhancement algorithm [5]. These methods could achieve good performance in back-end processing for original infrared image, but it does not suit for front-end enhancement.

3 Infrared Image Linear Enhancement Base on Features of Infrared Detector In this paper, we use infrared detector named UL04171 Produced by ULIS[6], its measurement is settled from -10°C to 50°C,output voltage swing between 1.0v and 4.2v,responsivity value is 3mv/k, so we need 14bit for voltage dynamic range. Generally, computer screen’s resolution is form 0 to 255 for gray level image, and human resolution is much lower. Original infrared image collected from objects which temperature is normal by infrared detector can’t be seen. The essential of the linear enhancement is to remove redundant pixels from histogram of original infrared image, then transfer grayscale to another gray level range that is between 0 and 255. Linear transform formula is as follow:

⎧ 0 ⎪ ⎪ Y − Ymin Xout = ⎨ max X in ⎪ X 2 − X1 ⎪⎩ Ymax

Xin < X1 X 2 ≤ Xin ≤ X1

(1)

Xin > X 2

Where Xout, Xin is the output and input of the function, Ymax,Ymin is the largest and smallest grayscale of result image, X2,X1 is the max and min transform threshold chosen from original infrared image’s histogram, choosing X2,X1 is the algorithm that proposed in this paper. The linear enhancement function is illustrated in Fig.1. We suppose there is no non-operating pixel in infrared detector, we have histogram of original infrared image like Fig.2.Here, we just regard the beginning and the end of the aiguille as the X1 X2 in formula 1 to enhance the image, the result will be perfect. But, actually, infrared detector has some non-operating pixels, UL04171 has about 2% .Real-time histogram of original infrared image consist of a main aiguille and some small aiguilles. The main aiguille is from a majority of normal pixels, these small aiguilles result from non-operating pixel and noises.

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X2 255

X1

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Fig. 1. The linear enhancement function

Number

X2

X1

Grayscale

Fig. 2. Ideal histogram

Data of original infrared image Calculate the histogram Remove nonoperating pixels from the histogram, obtain the X1 X2

Result image

Transform the original image According to the formula 1

Fig. 3. Linear enhancement algorithm flowchart

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Base on this phenomenon, we propose the linear enhancement based on features of infrared detector as follow: (1). Calculate the histogram of the original infrared image. (2). According to the sum pixels and ratio of non-operating pixels, calculate the number of non-operating pixels. (3). Remove 1/2 non-operating pixels calculated in step 1 from two sides of the histogram, obtain the transform threshold X1 X2 as in formula 1. (4). According to the formula 1, transform the original image. The algorithm illustrated in Fig.3

4 A Improved Algorithm - Segmentation Enhancement Base on Linear Enhancement Generally, the performance of the Linear enhancement proposed above is good enough, but, when the sky and earth appear in one infrared image at the same time, use commom linear enhancement to process the image will result low contrast of the target. Through a series of experiment, we find that when there are two main aiguilles which are consisted by target and sky in one image, grayscale of target in result image enhanced by Linear method is not much enough, that leads to lowly contrast of result image. This paper, we use improved algorithm based on the enhancement algorithm proposed by Chen Zheng [7] to segment the image into the sky section and the earth section, then enhance the two parts by Linear enhancement method separately, its steps as follow: (1). Calculate the histogram of the original infrared image. (2). According to the sum pixels and ratio of non-operating pixels, calculate the number of non-operating pixels. (3). Remove 1/2 non-operating pixels from two sides of the histogram calculated in step 1, obtain the transform threshold X1 X2 as in formula 1. (4). Divide the histogram data which between X1 and X2 into two segment using Otus at threshold T. (5). Enhance the two parts by linear enhancement method separately. Enhance the original infrared image by the method above, the grayscale of target in result image can reach the maximum, the sky have the same grayscale with the target, it leads to a boundary between the target and sky. If we use an unfair distribution about the grayscale, such as in process step, distribute all grayscale to the target and little even no grayscale to the sky, there is no the boundary in result image, and the quality of the result image is better than the commom linear enhancement.

5 Experiment Result Fig. 4 shows the original infrared image transformed to grayscale 0-255 and the histogram of original infrared image. From this figure, we can’t see any image information if the original infrared image is not taken any enhancement. On the histogram of original infrared image, a majority of pixels locate in a main aiguille.

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Fig. 5 is the result image enhanced by the proposed method. From this figure, we can see the image details appearing.

Fig. 4. Original infrared image and the histogram of original infrared image

Fig. 5. The result image enhanced by the proposed method

Fig. 6 is the result image enhanced by the linear enhancement method when the sky and earth appear in one infrared image at the same time, we can see the contrast of earth in result image is low.

Fig. 6. The result image enhanced by the linear enhancement method

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Fig. 7 are the result images enhanced by the linear enhancement algorithm and its improved algorithm. Fig.7(a) is the result image enhanced by the commom linear algorithm, the image is too white and the earth contrast is lowly; Fig.7(b) is enhanced by improved linear algorithm with the earth and sky are distributed the same grayscale 0-255,compared with (a),the image’s details are increased greatly and arrangement of the image is better; Fig.7(c) is enhanced by improved linear algorithm with the earth is distributed grayscale 0 to 255 but the sky is distributed no grayscale(0),the image’s details are as good as Fig. 6 (b),however, there are no pitting and the boundary between the target and sky, so the vision effects are improved ; Fig.7(d) is enhanced by improved linear algorithm with the earth is distributed grayscale between 0 and 255 and the key is distributed grayscale range 0 to 100,its details is the best in these four result images, there are no pitting, no boundary between the target and sky, and keeping the sky information.

(a)

(c)

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Fig. 7. The result images enhanced by the the linear enhancement algorithm and its improved algorithm

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6 Conclusion This paper proposes a algorithm of choosing transform threshold for linear enhancement based on the features of infrared detector, The algorithm is easily implementable and fast, The experimental results show that the image details can be revealed effectively by this algorithm. Since grayscale of target is not much enough in result image enhanced by linear method when the sky and earth appear in one infrared image at the same time, that leads to low contrast of result image, we propose an improved algorithm, by which enhance the original infrared image both keeping background information and enlarging the grayscale of target, the result images show this improved algorithm achieve a good performance. Acknowledgment. This work was supported by the Major Science and Technology special project of Fujian Province, P.R.China (No.2009HZ0003-1).

References 1. Zhang, Y.: Image Processing, 2nd edn. Tsinghua University Press, Beijing (2006) 2. Wang, Y.H., Wang, D., Hu, Y.M., Zhang, T.: The FPGA-based Real-Time Image Linear Contrast Enhancement Algorithm. Microcomputer Information, China (2007) 3. Wu, Z., Wang, Y.: An Image Enhancement Algorithm Based on Histogram Nonlinear Transform. Acta Phot On Ica Sinica, China (2010) 4. Zhang, C.-J., Yang, F., Wang, X.-D., Zhang, H.-R.: An Efficient Not–Linear Algorithm for Contrast Enhancement of Infrared Image. In: Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, August 18-21 (2005) 5. Li, Y., Zhou, J., Ding, W.: A Novel Contrast Enhancement Algorithm for Infrared Laser Images. IEEE, Los Alamitos (2009) 6. Chen, Z., Ji, S.: Enhancement Algorithm of Infrared Images based on Otsu and Plateau Histogram Equalization. Laser& Infrared, China (2010) 7. UL 04 17 1 NTC05011-1 Issue 1 640 x 480 LWIR 29 11 05.pdf

Influence of Milling Conditions on the Surface Quality in High-Speed Milling of Titanium Alloy Xiaolong Shen, Laixi Zhang, and Chenggao Ren Hunan Industry Polytechnic, Changsha, 410208, China [email protected], [email protected], [email protected]

Abstract. The study was focused on the machined surface quality of titanium alloy under different milling conditions, including milling speed, tool rake angle and cooling method. The surface quality was investigated in terms of residual stress and surface roughness. The results show that the compressive residual stresses are generated on the machined surface under all milling conditions. The compressive residual stresses in both directions decreased and the surface roughness increased with the milling speed increasing. The compressive residual stresses increased with the tool rake angle increasing. The lowest surface roughness was obtained when the rake angle was 8º. Under the condition of dry milling, the highest compressive residual stresses were obtained, approximately 350 MPa. The highest surface roughness was obtained when the oil mist coolant was used. Water cooling was the best cooling method with uncoated cemented carbide tool in high-speed milling of titanium alloy. Keywords: High-speed milling, Titanium alloy, Milling condition, Surface roughness, Residual stress.

1 Introduction Titanium alloys have been widely used in aerospace and other industrial applications because of their elevated mechanical resistance having a low density and their excellent corrosion resistance, even at high temperatures. However, titanium alloys are difficult to machine due to their high temperature strength, relatively low modulus of elasticity, low thermal conductivity and high chemical reactivity [1-2].Conventional milling speeds range from 30 to 100 m min-1 when sintered carbide tools were used in the machining of titanium alloys, resulting in low productivity [3]. High speed machining is widely appreciated in industry for its high material removal rate, low milling force, high machining accuracy and high surface quality. All these advantages have led to the application of high-speed machining technology in the machining of titanium alloys [4]. Many researchers have researched on surface quality of milling of titanium alloy. Che-Haron [5] carried on the research on surface quality of rough turning of titanium alloy Ti–6Al–4V with uncoated carbide. The results showed that the machined surface experienced microstructure alteration and increment in microhardness on the top white layer of the surface. Machined surfaces have shown severe plastic deformation and hardening after prolonged machining time with worn tools, especially when machining S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 423–429, 2011. © Springer-Verlag Berlin Heidelberg 2011

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under dry milling condition. A metallurgical analysis on chip obtained from high speed machining of titanium alloy Ti–6Al–4V was performed by Puerta Velásquez [6].The titanium β phase was observed in all chips for any tested milling speeds. No evidence of phase transformation was found in the shear bands. Ezugwu [7] investigated the effect of machining parameters on residual stress of titanium alloy IMI-834 by milling. The residual stresses were found to be compressive in nature at the milling speed of 11~56m min-1 and a linear relationship could not explain the variation of the residual stresses with respect to the milling parameters. Ge [8] reported experimental evidence that the surface roughness was less than Ra 0.44μm when milling gamma titanium aluminide alloy at speeds of 60~240m min-1. Workpiece surface has a maximum microhardness of approximately 600HV (0.100), and the depth of maximum hardened layer was confined to 180μm below the surface. Che-Haron’s study showed that surface roughness values recorded were typically less than 1.5µm Ra when milling gamma titanium aluminide alloy at high speed. Microhardness evaluation of the subsurface indicated a hardened layer to a depth of 300µm. Initial residual stresses analysis showed that the surface contained compressive stresses more than 500MPa. Tool flank wear and milling speed have the greatest effect on residual stress. Ezugwu investigated the chip formation mechanism and surface quality as well as milling process characteristics of titanium alloy in high speed milling. The high milling speed with much more milling tooth will be beneficial to reduction of milling forces, enlarge machining stability region, depression of temperature increment, auti-fatigability as well as surface roughness. The aim of this paper is to investigate the influence of milling speed, tool rake angle and cooling method on surface quality in high-speed milling of titanium alloy. The paper will provide experimental and theoretical basis for optimizing high-speed milling parameters and controlling surface quality of titanium alloy. Consequently, it will lead to the generation of counteractive machining procedures to improve component fatigue life and machinability.

2 Experimental Procedure 2.1 Experimental Material The workpiece material used in all the experiments was an alpha-beta titanium alloy TC11. The nominal chemical composition of the workpiece material confirms to the following specification (wt.%): 6.42 Al; 3.29 Mo; 1.79 Zr; 0.23 Si; 0.025 C; 0.096 O; 0.003 H; 0.077 Fe; 0.004 N; allowance Ti. The mechanical properties of tested material at room temperature and high temperature are shown in Table 1. The workpiece dimension was 80mm×50mm×30 mm. Table 1. Mechanical properties of TC11 titanium alloy

，

Room temperature mechanical properties ≥ Tensile strength σb/MPa Yield strength σ0.2/Mpa Elongation δ/% Shrinkage ψ/% Impact value аk/J•cm-2

1128 1030 12 35 44.1

High temperature mechanical properties 500 Test temperature/ Tensile strength σb/MPa 765 Rupture strength σ100/MPa 667

℃

，≥

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2.2 Milling Conditions All the machining experiments were carried out on a three-axis Mikron HSM 800 high speed milling center with an ITNC 530 controller. The milling tools used were K44 uncoated cemented carbide milling cutter with four teeth. The diameter of the cutter was 10 mm, the helix angle and relief angle were 30°, 10°, respectively. The milling mode was down milling. Three different milling speeds were selected as 376.8 m/min, 471 m/min and 565.2 m/min, and feed per tooth, milling depth and milling width were maintained constant at 0.05 mm/tooth, 0.2 mm and 10 mm, respectively. Meanwhile the tool rake angle used was 14 º. The water coolant was used. The three tool rake angles used were 4º, 8 º and 14 º to investigate the influences of rake angle on surface quality. Meanwhile the milling speed, feed per tooth, milling depth and milling width were maintained constant at 251 m/min, 0.05 mm/tooth, 0.2 mm and 10 mm, respectively. The coolant used was oil mist. In addition, three different cooling methods including dry, water and oil mist were selected. 2.3 Measurement of Surface Quality After each processing step, the surface residual stress was measured by X-ray diffraction. The residual stress was measured at three locations both in the feed and stepover directions, and then the average value is calculated. The surface roughness of the machined surface after each test was measured using a contact type profilometer instrument (Taylor Hobson Form Talysurf 120). The evaluation length was set at 5.6 mm and the sampling length was fixed at 0.8 mm. The instrument was calibrated using a standard calibration block prior to the measurements. The surface roughness was measured by positioning the stylus in the feed direction. The surface roughness was taken at five locations and repeated twice at each point on the face of the machined surface, and then the average value is gained.

3 Results and Discussion 3.1 Influence of Milling Speed on Surface Quality Fig. 1 shows the influence of milling speed on surface residual stresses. It is observed that all surface residual stresses are compressive, and increasing the milling speed tends to decrease the compressive residual stresses on the surface in both directions. The results show the trend of the residual stresses is from compression to tensile with the milling speed increasing. This trend is expected because as milling speed increases, machining becomes more adiabatic, so the temperature rise softens the metal and thus reducing the milling forces. Fig. 2 shows the influence of milling speed on surface roughness. It can be seen that an increase of milling speed causes an increase of surface roughness. This was probably due to rapid tool wear at the milling edge closer to the nose.

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350 0

400

Milling speed vc/m min 450

500

550

600

-50

Residual stress/MPa

-100 -150 -200 -250 -300

σx

-350

σy

-400

Fig. 1. The influence of milling speed on residual stress 1.20 1.15

Surface roughness Ra/μm

1.10 1.05 1.00 0.95 0.90 0.85 0.80 0.75 350

400

450

500

550

600

-1

Milling speed vc/m min

Fig. 2. The influence of milling speed on surface roughness

3.2 Influence of Rake Angle on Surface Quality Fig. 3 shows the influence of rake angle on surface residual stresses. It is observed that all the surface residual stresses are compressive, and the magnitude of the compressive stresses increased on the surface in both directions with the rake angle increasing. Fig. 4 shows the influence of rake angle on surface roughness. It can be seen that the surface roughness decreases slightly when the rake angle is changed from 4 º to 8 º. However, the surface roughness increases remarkably when the rake angle is increased from 8 º to 14 º.

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Rake angle γ /degree 0 4

6

8

10

12

14

σx

-50

Residual stress/MPa

σy -100

-150

-200

-250

-300

Fig. 3. The influence of rake angle on residual stress

Surface roughness Ra/μm

0.8

0.7

0.6

0.5

0.4

0.3 4

6

8

10

12

14

Rake angle γ/degree

Fig. 4. The influence of rake angle on surface roughness

3.3 Influence of Cooling Method on Surface Quality Fig. 5 shows the influence of cooling methods on surface residual stresses. It is observed that all the surface residual stresses are compressive, and the highest compressive stresses on the surface in both directions appeared under dry milling condition. The magnitude of the highest compressive stress is about 350 MPa in feed direction. The lowest compressive stresses on the surface appeared in both directions under water cooling condition. Fig. 6 shows the influence of cooling methods on surface roughness. It can be seen that the highest surface roughness appeared under oil mist cooling condition. The lowest surface roughness appeared under water cooling condition, and the value of that surface roughness is only about 0.271μm. By comprehensive consideration of residual stresses and surface roughness, the best cooling method is water cooling.

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Water

Oil mist

0

-50

Residual stress/MPa

-100

-150

-200

-250

-300

σx σy

-350

Fig. 5. The influence of cooling method on residual stress 0.8

Surface roughness Ra/μm

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Dry

Water

Oil mist

Fig. 6. The influence of cooling method on surface roughness

4 Conclusion Experimental investigation of the influence of milling conditions, involving milling speed, tool rake angle and cooling methods, on the surface quality in terms of residual stress and surface roughness in high-speed milling titanium alloy with uncoated cemented carbide tool, were carried out. The results show the milling speed, rake angle and cooling method have important influence on residual stress and surface roughness. Compressive residual stresses are higher in the feed direction than in the stepover direction. The best surface quality can be obtained when the rake angle is 8º. Water cooling is the best cooling method. Acknowledgements. This project is supported by Scientific Research Fund of Hunan Provincial Education Department (No. 10C0113) and 2010 College Research Project of Hunan Industry Polytechnic Grant (No. GYKYZ201004).

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References [1] Shen, X.L., Zhang, L.X., Ren, C.G., Zhou, Z.X.: Research on Design and Application of Control System in Machine Tool Modification. Adv. Mater. Res. 97-101, 2053–2057 (2010) [2] Shen, X.L., Luo, Y.X., Zhang, L.X., Long, H.: Natural frequency computation method of nonlocal elastic beam. Adv. Mater. Res. 156-157, 1582–1585 (2011) [3] Su, Y., He, N., Li, L., et al.: An experimental investigation of effects of cooling/lubrication conditions on tool wear in high-speed end milling of Ti-6Al-4V. Wear 261, 760–766 (2006) [4] Shen, X.L., Zhang, L.X., Long, H., Zhou, Z.X.: Analysis and Experimental Investigation of Chatter Suppression in High-speed Cylindrical Grinding. Appl. Mech. Mater. 34-35, 1936–1940 (2010) [5] Che-Haron, C.H., Jawaid, A.: The effect of machining on surface integrity of titanium alloy Ti-6% Al-4% V. J. Mater. Proc. Technol. 166, 188–192 (2005) [6] Puerta Velásquez, J.D., Bolle, B., Chevrier, P., et al.: Metallurgical study on chips obtained by high speed machining of a Ti-6 wt.% Al-4 wt.% V alloy. Mater. Sci. Eng. A. 452-453, 469–474 (2007) [7] Ezugwu, E.O., Wang, Z.M.: Titanium alloys and their machinability–a review. J. Mater. Proc. Technol. 68, 262–274 (1997) [8] Ge, Y.F., Fu, Y.C., Xu, J.H.: Experimental Study on High Speed Milling of γ-TiAl Alloy. Key Eng. Mater. 339, 6–10 (2007)

Molecular Dynamics Simulation Study on the Microscopic Structure and the Diffusion Behavior of Methanol in Confined Carbon Nanotubes Hua Liu, Xiaofeng Yang*, Chunyan Li, and Jianchao Chen Department of Physics North University of China Taiyuan, Shanxi Province 030051 People’s Republic of China Mobile: 13453153691 [email protected], [email protected]

Abstract. Molecular dynamics simulation was performed to study the conformation and diffusion properties of the methanol molecules in the (8, 8) (9, 9) and (10, 10) single-walled carbon nanotubes under an ambient environment. We present the results of the radial distribution functions and the diffusion of methanol in different pipe diameters. The result shows that the methanol molecules confined inside the (10, 10) carbon nanotubes are observed to have extremely highly ordered structure. The methanol molecules confined in smaller pipe diameter are mostly clustered near the central axis. The diffusion of the methanol molecules that are located in the carbon nanotubes show a strong dependence on the different pipe diameters are Knudsen diffusion. Keywords: confined, carbon nanotubes, methanol molecules, molecular dynamics simulation.

1 Introduction In recent years, the technique of the molecular dynamics(MD) simulation plays an important role in studying the properties of the restricted molecules[1,2].The limited water molecule in carbon nanotubes (CNTs) has become the focus of research [3,4].Especially, the hydrogen bond has a crucial influence on the physical and chemical properties of the water molecules[5,6]. As water molecules, methanol molecules can form hydrogen bond. Yu, LM et al [7]investigated the micro-structural and the dynamic properties of the methanol by MD simulation, and showed that the average distance increasing as temperature. The distance between the molecules and the diffusion coefficients show an increase trend with temperature. The randomness of the molecular distribution also increases in the carbon nanotube (CNT). Sun, W et al [8] also deliberated the microstructure of the methanol. The result shows that each methanol molecule form the average number of hydrogen bond is approximately equal to 2, which suggests that there is not only one preferred orientation of methanol molecules with respect to each other. In this paper, we explore the dependence of the microscopic *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 430–436, 2011. © Springer-Verlag Berlin Heidelberg 2011

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structure of the methanol on the nanotube diameters, to observe the distribution of whether can appear similar phenomena. We study the RDF and diffusion properties of methanol in different diameters of the CNTs by MD simulation.

2 Methods We use arm-chair mode of rolling the graphite sheet to construct the different nanotubes in diameter [9,10]. The (8, 8) (9, 9), and (10, 10) single-walled CNT have been chosen and their diameters are 1.08 nm, 1.22 nm, and 1.356 nm respectively, according to the formula d = a 3(m2 +mn+n2) , Where a is the C-C distance fixed at π 0.142nm. The lengths of the CNT in which contains 16 methanol molecules are 7.739nm thought out our simulations. A considerable number of potential models have been developed so far to describe methanol molecules interactions, namely, TIPS [11], OPLS [12], Haugney rigid threesite model [13], flexible model [14], and polarizable model [15]. The OPLS model can accurately predict the properties of methanol molecule at ambient temperature. The intermolecular interaction between a pair of methanol molecules is given by

u(ri , rj ) =

⎡ σ ij σ ij ⎤ + 4ε ij ⎢( )12 − ( )6 ⎥ rij rij ⎥⎦ ⎢⎣ rij

qi q j

Here i and j are the label sites in methanol molecule.

(1)

ε ij And σ ij are Lennard-Jones

energy and radius, respectively. rij Is the distance between sites i and j in methanol,

qi is the charge at site i in methanol. The Lennard-Jones interaction energy and radius parameters of the cross-terms are calculated on the basis of the Lorentz-Berthelot 1

combining rules: σ = 1 (σ +σ ) , ε ij = ( ε iε j ) 2 . The force field parameters are listed in ij i j 2

Table 1. In the model of methanol the O-H and O-Me distances are 0.912×10-10and 1.430×10-10m, respectively, and the H-O-Me angle is 108.5º. The simulations were conducted in the canonical ensemble (NVT) at temperature of 298K with a Nose-Hoover thermostat. The long-range electrostatic interactions were treated with the Ewald summation method. All simulations are carried out with an integration time step of 0.5fs and a cutoff distance is 1.0nm for the short-range interactions. The various equilibrium and dynamical properties were calculated over a period of 360 ps, after the systems were equilibrated for 140 ps. Table 1. Potential model parameters

Atom symbol C CNT CH3 O H

（ ）

ε/(kj.mol-1) 0.293 0.866 0.711 0

σ/nm 0.355 0.376 0.307 0

Partial charge (e) 0.000 0.4246 -1.1215 0.6969

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3 Results and Discussion The radial distribution function (RDF) can well depict the microscopic structure of a system. The O-H and O-O radial distribution functions gO-H(r) and gO-O(r) for the different diameters at 298K are shown in Fig.1and Fig.2

4.5

4.0

d=1.085nm d=1.22nm d=1.356nm

4.0

d=1.085nm d=1.22nm d=1.356nm

3.5

3.5

3.0

3.0 2.5

g(r)

g(r)

2.5 2.0

2.0 1.5

1.5 1.0

1.0

0.5

0.5 0.0 0.0

0.2

0.4

0.6

0.8

0.0 0.0

1.0

r/nm

0.2

0.4

0.6

0.8

1.0

r/nm

Fig. 1. O-H radial distribution functions

Fig. 2. O-O radial distribution functions

As can be seen from Fig1 and Fig2, the first peaks in the O-H radial distribution functions show a similar trend to that of the O-O radial distribution functions. Furthermore, the first peak height of the radial distribution functions increases and that of the first minimum decreases with the larger diameters. The positions of the first peaks almost remain unchanged by the sizes of the diameters, but the positions of the first minimum are shifted to right with the increasing diameters. This result indicates that the hydrogen bonding structure of methanol is enhanced significantly by increasing diameter. The aggregation densities of oxygen-hydrogen bond and the oxygen-oxygen bond increase with the larger diameters. The density of the largest region for the O-H radial distribution functions and the O-O radial distribution functions are respectively gathered at 0.20nm and 0.29nm. It is possible to figure out that the architecture graduate closely regular to change the loose disorder. One of the most important curves is the O-H radial distribution functions. In this section the influence of the different diameters on the hydrogen bond structure will be investigated by calculating the average number of coordination numbers. We have used the following geometric definition of the hydrogen bond that can be formed among methanol molecules if the oxygen-oxygen distance is less than 0.35nm; the hydrogen-oxygen distance is less than 0.245nm and the oxygen-oxygen-hydrogen angleθis less than 30º. The number of the hydrogen bonds and the coordination numbers have relation with each other. The coordination numbers ( nOH (r) ) are obtained by integrating the corresponding O-H pair distribution function ( gOH (r) )

nOH ( r ) = 4πρ ∫

rmin

0

g OH ( r )r 2 dr

(2)

In eq (2), ρ is the macroscopic number density of the methanol molecule. The integration is usually restricted by the position of the first minimum in the pair distribution function. Both H-O radial distribution functions have the first wave

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trough at 0.284nm. MD simulation was performed to explore the water in confined CNTs by Gordillo and Marti [16].It is seen that the hydrogen bonds of the confined water were damaged owing to restriction. It is attributed to the decrease of the average number of hydrogen bonds and the coordination numbers among waters. The methanol molecules have the same structure to be observed whether appear this kind of phenomenon. Table 2. Coordination numbers in different diameters of carbon nanotubes d(nm) NOH

1.085 2.28

1.22 2.32

1.356 2.56

The diameters of the CNTs and the corresponding coordination numbers are listed in table2. The tendency of the coordination numbers indicate the axial dispersion coefficient increasing with the larger diameters, the number of the hydrogen bonds also follows this law. 2.5

Wall of CNT 2.0

1.5

<ρ> 1.0

0.5

0.0 0.0

0.2

0.4

0.6

0.8

r/nm

Fig. 3. The radial density distributions of sites of methanol molecules in the (10, 10) CNTs gained from MD simulation, illustration shows the longitudinal section of the methanol molecules in CNT

Coordinate origin represents the center axis of carbon nanotube in Fig 3.The position of the maximum is away from the pipe wall at a distance of 0.36nm. The limited effect of the methanol weakens with the larger diameters of the CNT. More and more methanol molecules which connect to form a ring tend to locate near the tube wall. However, there are little molecules near the tube axis and keeping away from the wall. In eq. (1), the Lennard-Jones energy and radius parameters of the cross-interactions are calculated on the basis of the Lorentz-Berthlot combining rules. Electrostatic interactions can be ignored on account of low-energy. The derivative of 6 the Lennard-Jones energy reach conclusion: r = 2σ .According to the potential model parameters of the methanol molecule: σ = 0.331nm. The value of the radius is 0.36nm.The consequence corresponds with the simulated result (Fig 3). We can conclude that the interaction energy of the methanol molecule which is away from the wall at a distance of 0.36nm is lowest. The molecules which locate in a relatively stable state are gathered here. Inner layer represents methanol and outer layer indicates CNTs as shown in the illustration of Fig 3.The methanol in (8, 8) (9, 9)

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CNTs gathered near the central axis of the rube due to the strength of the LennardJones energy. The limited effect of molecules obvious which appear mission-shaped or liner arrangement As can be seen from Fig 4, the first characteristic peak is monotonically decreasing on the CH3-CNT, O-CNT, and H-CNT radial distribution. The first characteristic peak of the CH3-CNT radial distribution function is the maximum, the corresponding minimum is the H-CNT radial distribution function. It can probably be attributed to the space factor of the restricted pipe diameter. The characteristic peak of the (10, 10) CNTs is lower than the corresponding characteristic peak of the (8, 8) (9, 9) CNTs. This means that the former orderly degree is generally lower than the later. This is due to the tube space increasing and the limited effect weakens. In order to make a better understanding of the relationship between diffusion coefficient and the channel diameters, MD simulation was explored to solve the diffusion coefficient by two kinds of methods. 1.16 1.14

300

CH3-CNT O-CNT H-CNT

1.12 1.10

d=1.085nm d=1.22nm d=1.356nm

250

1.08 1.06

200 2

MSD/nm

g(r)

1.04 1.02 1.00 0.98

150

100

0.96 0.94

50

0.92 0.90 0.88 1.05

0

1.10

1.15

1.20

1.25

1.30

1.35

1.40

0

100

200

300

400

500

t/ps

r/nm

Fig. 4. The diagram of the first characteristic peak on the CH3-CNT, O- CNT, H-CNT radial distribution functions with the different diameters

Fig. 5. The mean square distance (MSD) of methanol molecules on the axial direction in CNTs

The diffusion coefficient can be obtained either from axial velocity autocorrelation via the Green-Kubo relations or from mean square displacement via the Einstein expression for the MD simulation. We take advantage of the Einstein formula and Green-Kubo relations to calculate the self-diffusion coefficient. The self diffusivity is conveniently defined using the Einstein expression [17] D S = lim i→ ∞

1 6N ⋅t

N

∑ i =1

ri ( t ) − ri (0)

2

(3)

Or, equivalently, using the generalized Green-Kubo relations , D =

Here,

1 3N

N

∞

∑∫ i =1 0

u i (t ) u i (0 ) d t

(4)

ri (t ) and ui (t ) are the position and velocity of the tagged particle, respectively.

The velocity autocorrelation function reach null point in a short time while adopt the Green-Kubo equation. However, with the time passing, the numerical instability leads to the curve waves. The eq. (3) is without this phenomenon. In this paper, it

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would be best to adopt the eq. (3) to calculate the diffusion coefficients of the methanol. The methanol has particle-wall collisions, and the rate is lower than the particle-to-particle collisions. This diffusion which is calculated with the following formula called Knudsen diffusion. DK =

2 r 3

8RT πM

(5)

Where r denotes the pore radius and R denotes gas constant; M denotes molecular diffusion components. Table 3. Using Einstein method and Knudsen equation separately calculate the diffusion coefficient of the methanol

d/nm -9

2 -1

DS/10 m s DK/10-9m2s-1

1.085 4.63 4.88

1.22 5.61 5.73

1.356 6.3 6.34

Table 3 exhibits the diffusion coefficients of the methanol molecules increase gradually by this two approaches. This result suggests that the diameter is smaller; the diffusion coefficient is less obvious. The methanol molecules in the CNT form orderly structure in respect that the methanol-methanol interaction and the methanolwall interaction. These reasons block the spread of methanol molecules in the CNT. Diffusion coefficients increase when the collision frequency of the methanol and the pipe wall decrease with the larger diameter. Using eq. (3) ermittelt the average of the diffusion coefficient is 5.513×10-9m2/s. By eq. (5) calculating the average of the diffusion coefficient is 5.65×10-9 m2/s.The relative errors of the results of the two methods are 2.43%.Therefore, the diffusion of the methanol molecules in different diameters of the CNTs are Knudsen diffusion.

4 Conclusions We have carried out extensive research on the diffusion of methanol molecules in CNTs by molecular dynamics simulation, offering a microscopic description of the relevant static and dynamic properties. It is found that the limited effect plays a critical role in the RDF and the diffusion coefficient of the methanol. An enhancement of the numbers of the hydrogen bonds and the coordination numbers of the methanol molecules with increasing diameters have been deduced from the RDFs. The coordination numbers of the methanol are shown in table2.Thus, it is seen that the diffusion of the methanol molecules that are located in the carbon nanotubes show a strong dependence on the different pipe diameters are Knudsen diffusion.

References 1. Zhang, X.R., Wang, W.C.: Journal of Chemistry 60, 1396 (2002) 2. Lv, L.H., Wang, Q., Li, Y.C.: Journal of Chemistry 61, 1232 (2003)

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3. Hummer, G., Rasaiah, J.C., Noworyta, J.P.: Nature 414, 188 (2001) 4. Wang, J., Zhu, Y., Zhou, J., Lu, X.H.: Journal of Chemistry 61, 1891 (2003) 5. Netz, P.A., Starr, F.W., Stanley, H.E., et al.: Static and dynamic properties of stretched water. J. Chem. Phys. 115, 344–348 (2001) 6. Netz, P.A., Starr, F.W., Stanley, H.E., et al.: Relation between structural and dynamical anomalies in super cooled water. J. Physical A. 314, 470–476 (2002) 7. Yu, L., Tang, Y., Liu, J., Liu, J.: Molecular Dynamics Simulation of liquid Methanol. Chemical Industry and Engineering 7(26), 338–341 (2009) 8. Sun, W., Chen, Z., Huang, S.Y.: Liquid methanol microstructure of molecular dynamics simulation. 11(33), 51–53 (2005) 9. Ayappa, K.G.: Langmuir 14, 880 (1998) 10. Zhang, F.J.: Chem. Phys. 111, 9082 (1999) 11. Jorgensen, W.L.: Microstructure and Diffusive Properties of Liquid Methanol. J. Am. Chem. Soc. 102, 543–549 (1980) 12. Jorgensen, W.L.: Optimized intermolecular potential functions for liquid alcohols. Phys. Chem. 90, 1276–1284 (1986) 13. Haughney, M., Ferrario, M., McDonald, I.R.: Molecular dynamics simulation of liquid methanol. J. Phys. Chem. 91, 4934–4940 (1987) 14. Haughney, M., Ferrario, M., McDonald, I.R.: Molecular dynamics simulation of liquid methanol with a flexible threesite model. J. Phys. Chem. 91, 4334–4341 (1987) 15. Skaf, M.S., Fonseca, T., Ladanyi, B.M.: Wave vector dependent dielectric relaxation in hydrogen-bonding liquids: a molecular dynamics study of methanol. J. Chem. Phys. 98, 8929–8945 (1993) 16. Gordillo, M.C., Marti, J.: Chem. Phys. Let. J. 329, 341 (2000) 17. Allen, M.P., Tildesley, D.J.: Computer simulation of liquids Methanol. Oxford University Press, Oxford (1987)

Spoken Emotion Recognition Using Radial Basis Function Neural Network Shiqing Zhang1, Xiaoming Zhao2, and Bicheng Lei1 1

School of Physics and Electronic Engineering, Taizhou University, 318000 Taizhou, China 2 Department of Computer Science, Taizhou University, 318000 Taizhou, China {tzczsq,tzxyzxm,leibicheng}@163.com

Abstract. Recognizing human emotion from speech signals, i.e., spoken emotion recognition, is a new and interesting subject in artificial intelligence field. In this paper we present a new method of spoken emotion recognition based on radial basis function neutral networks (RBFNN). The acoustic features related to human emotion expression are extracted from speech signals and then fed into RBFNN for emotion classification. The performance of RBFNN on spoken emotion recognition task is compared with several existing methods including linear discriminant classifiers (LDC), K-nearest-neighbor (KNN), and C4.5 decision tree. The experimental results on emotional Chinese speech corpus demonstrate the promising performance of RBFNN. Keywords: Spoken emotion recognition, Feature extraction, Radial basis function neutral networks.

1 Introduction Affective computing [1], which aims at understanding and modeling human emotions, is currently a very active topic within the engineering community. Speech is one of the most powerful, natural and immediate means for human beings to communicate their emotions, speech is thus a main vehicle of human emotion expressions. Recognizing human emotions from speech signals, called spoken emotion recognition, has attracted extensive research interests within artificial intelligence field due to its important applications to human-computer interaction [2], call centers [3], and so on. A typical spoken emotion recognition system comprises of two parts: feature extraction and emotion classification. Feature extraction involves in extracting the relevant features from speech signals with respect to emotions. Emotion classification maps feature vectors onto emotion classes through a classifier’s learning by data examples. After feature extraction, the accuracy of emotion recognition relies heavily on the use of a good pattern classifier. So far, the widely used emotion classification methods, such as linear discriminant classifiers (LDC), K-nearest-neighbor (KNN), C4.5 decision tree, have been applied for spoken emotion recognition [4-7]. Radial basis function neural networks (RBFNN) [8, 9] as representative neural networks has S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 437–442, 2011. © Springer-Verlag Berlin Heidelberg 2011

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became a well-known method for classification since its main advantages are computational simplicity, supported by well-developed mathematical theory, and robust generalization, powerful enough for real-time real-life tasks. Motivated by little attention to explore the performance of RBFNN on spoken emotion recognition task, in this study we employ RBFNN to conduct emotion recognition experiments in Chinese speech. This paper is structured as follows. The basic principle of RBFNN for classification is reviewed briefly in Section 2. The emotional speech corpus and feature extraction are described in Section 3. Section 4 analyzes the experiment results. Finally, the conclusions are given in Section 5.

2 Radial Basis Function Neural Networks for Classification When using radial basis function neural networks (RBFNN) for classification, the RBFNN is a three layer feed-forward network that consists of one input layer, one hidden layer and one output layer, as shown in Fig. 1. The input layer receives input data. Each input neuron of the input layer corresponds to a component of an input vector x .The hidden layer is used to cluster the input data and extract features. The hidden layer consists of n neurons and one bias neuron. Each input neuron is fully connected to the hidden layer neurons except the bias one. Each hidden layer neuron computes a kernel function. A Gaussian Radial Basis Function could be a good choice for the hidden layer.

Fig. 1. The basic framework of RBFNN

The used Gaussian Radial Basis Function for the hidden layer is defined as

⎧ x − ci ), ⎪exp( − yi = ⎨ 2σ i2 ⎪ 1, ⎩

i = 1, 2, ", n i=0

(1)

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where ci and σ i represent the center and the width of the neuron, respectively, and the symbol

denotes the Euclidean distance. The weight vector between the input

layer and the i -th hidden layer neuron corresponds to the center ci . The closer x is to ci , the higher the value the Gaussian function will produce. The output layer consists of m neurons corresponding to the possible classes of the problem. Each output layer neuron is fully connected to the hidden layer and computes a linear weighted sum of the outputs of the hidden neurons as follows: n

z j = ∑ yi wij , j = 1, 2, ", m

(2)

i =0

where wij is the weight between the i -th hidden layer neuron and the j -th output layer neuron.

3 Experiment Setup 3.1 Emotional Speech Corpus

The emotional speech Chinese corpus reported in our present study [10] was used for experiments. The Chinese corpus was collected from 20 different Chinese dialogue episodes from a talk-show on TV. In each talk-show, two or three persons discuss the problems such as social typical issues, family conflict, inspiring deeds, etc. Due to the spontaneous and unscripted manner of the episodes, the emotional expressions can be considered authentic. Because of the limited topics, the speech corpus consists of four kinds of common emotion including angry, happy, sad and neutral. This corpus collected in total contains 800 emotional utterances from 53 different speakers (16 male /37 female), speaker-independent, each of four emotion for about 200 utterances. All utterances recorded at a sample rate of 16 kHz and 16 bits resolution with mono-phonic Windows WAV format stored in computer. 3.2 Feature Extraction

It has been found speech prosody and voice quality features are closely related to the expression of human emotion in speech [3, 10]. The popular prosody features contain pitch, intensity and duration. And the representative voice quality features include the first three formants (F1, F2, F3), spectral energy distribution, harmonics-to-noise-ratio (HNR), pitch irregularity (jitter) and amplitude irregularity (shimmer). The popular prosody and voice quality features are extracted for each utterance from the Berlin emotional speech database. Some typical statistical parameters such as mean, standard derivations (std), median, quartiles, and so on, are computed for each extracted feature. These extracted acoustic features, 48 in total, are presented as follows. ♦Prosody features:

(1-10)Pitch: maximum, minimum, range, mean, std (standard deviation), first quartile, median, third quartile, inter-quartile range, mean-absolute-slope. (11-19)Intensity: maximum, minimum, range, mean, std, first quartile, median, third quartile, inter-quartile range.

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(20-25)Duration: total-frames, voiced-frames, unvoiced-frames, ratio of voiced to unvoiced frames, ratio of voiced-frames to total-frames, ratio of unvoiced-frames to total-frames (20ms/ frame). ♦Voice quality features:

(26-37)First three formants F1-F3: mean of F1, std of F1, median of F1, bandwidth of median of F1, mean of F2, std of F2, median of F2, bandwidth of median of F2, mean of F3, std of F3, median of F3, bandwidth of median of F3. (38-41)Spectral energy distribution in 4 different frequency bands: band energy from 0 Hz to 500 Hz, band energy from 500 Hz to 1000 Hz, band energy from 2500 Hz to 4000 Hz, band energy from 4000 Hz to 5000 Hz. (42-46)Harmonics-to-noise-ratio: maximum, minimum, range, mean, std. (47)Jitter: pitch perturbation in vocal chords vibration Jitter is calculated with the following equation (3), in which Ti is the i -th peak-topeak interval and N is the number of intervals: N −1

Jitter (%) = ∑ (2Ti − Ti −1 − Ti +1 ) i =2

N −1

∑T i=2

(3)

i

(48)Shimmer: perturbation cycle to cycle of the energy Shimmer is calculated similarly to Jitter as shown in equation (4), in which Ei is the i -th peak-to-peak energy values and N is the number of intervals: N −1

Shimmer (%) = ∑ (2 Ei − Ei −1 − Ei +1 ) i =2

N −1

∑E i =2

i

(4)

4 Experiment Results All extracted different acoustic features were normalized by a mapping to [0, 1] before anything else. Three typical classification methods, i.e., linear discriminant classifiers (LDC), K-nearest-neighbor (KNN) and C4.5 decision tree were used for emotion recognition and compared their performance with RBFNN. Note that the number of nearest neighbor for KNN method is set to 1 due to its best performance. For all emotion classification experiments, we performed 10-fold stratified cross validations over the data sets so as to achieve more reliable experiment results. In other words, each classification model is trained on nine tenths of the total data and tested on the remaining tenth. This process is repeated ten times, each with a different partitioning seed, in order to account for variance between the partitions. The different emotion recognition results of four classification methods, including LDC, KNN, C4.5 and RBFNN, are presented in Table 1. From the results in Table 1, we can observe that RBFNN performs best with the highest accuracy of 83.3%, outperforming the other used methods including LDC, KNN and C4.5. This demonstrates that RBFNN has the best generalization ability among all used four classification methods. Note that LDC and KNN get an accuracy of about 75%, indicating that LDC is highly close to KNN on classification task. Additionally, C4.5 performs better than LDC and KNN, and gets a recognition accuracy of 80%. To further explore the recognition results of different kinds of emotions when using RBFNN classifier, Table 2 gives the confusion matrix of emotion recognition

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results obtained with RBFNN. As shown in Table 2, we can see that that neutral is best classified with an accuracy of 91.2%, and angry is discriminated with an accuracy of 85.6%. While other two emotions, happy and sad, only could be classified with relatively lower accuracies, in detail 80% for happy and 76.4% for sad. This can be explained to that happy is highly confused to angry and sad for each other since they have confused acoustic parameters to a great extent. Table 1. Emotion recognition results for different classification methods Methods

LDC

KNN

C4.5

RBFNN

Accuracy (%)

75.2

75.1

80.0

83.3

Table 2. Confusion matrix of emotion recognition results with RBFNN Emotion

Angry

Happy

Sad

Neutral

Angry

85.6

10.3

4.1

0

Happy

13.7

80.0

5.2

1.1

Sad

2.8

13.6

76.4

7.2

Neutral

0

6.5

2.3

91.2

5 Conclusions In this paper, a new method based on RBFNN is presented for spoken emotion recognition. To effectively compare the performance of RBFNN on spoken emotion recognition task, three well-known emotion classification methods, i.e., LDC, KNN, and C4.5, were used. From the experiment results on emotional Chinese speech corpus, we can conclude that RBFNN performs best with an average recognition accuracy of 83.3%, due to its good generalization ability. It’s worth pointing out that in this study we focus on recognizing only four emotions such as angry, happy, sad and neutral. However, in real world scenery some other common emotions such as disgust, fear and surprise also existed. Therefore, in the future it’s an interesting subject to extend our emotional speech Chinese corpus and identify more other different emotion categories such as disgust, fear, surprise and so on. Acknowledgments. This work is supported by Zhejiang Provincial Natural Science Foundation of China (Grant No.Z1101048, No. Y1111058).

References 1. Picard, R.: Affective computing. MIT Press, Cambridge (1997) 2. Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., Taylor, J.G.: Emotion Recognition in Human-Computer Interaction. IEEE Signal Processing Magazine 18(01), 32–80 (2001)

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3. Lee, C.M., Narayanan, S.S.: Toward Detecting Emotions in Spoken Dialogs. IEEE Transactions on Speech and Audio Processing 13(2), 293–303 (2005) 4. Dellaert, F., Polzin, T., Waibel, A.: Recognizing emotion in speech. In: Proceedings of 4th International Conference on Spoken Language Processing, Philadelphia, PA, USA, pp. 1970–1973 (1996) 5. Petrushin, V.: Emotion in speech: recognition and application to call centers. In: Proceedings of 1999 Artificial Neural Networks in Engineering, New York, pp. 7–10 (1999) 6. Yacoub, S., Simske, S., Lin, X., Burns, J.: Recognition of emotions in interactive voice response systems. In: Proceedings of EUROSPEECH 2003, Geneva, Switzerland, pp. 729–732 (2003) 7. Lee, C.C., Mower, E., Busso, C., Lee, S., Narayanan, S.S.: Emotion recognition using a hierarchical binary decision tree approach. In: Proceedings of INTERSPEECH 2009, Brighton, United Kingdom, pp. 320–323 (2009) 8. Park, J., Sandberg, I.W.: Universal approximation using radial-basis-function networks. Neural Computation 3(2), 246–257 (1991) 9. Er, M.J., Wu, S., Lu, J., Toh, H.L.: Face recognition with radial basis function (RBF) neural networks. IEEE Transactions on Neural Networks 13(3), 697–710 (2002) 10. Zhang, S.: Emotion Recognition in Chinese Natural Speech by Combining Prosody and Voice Quality Features. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds.) ISNN 2008, Part II. LNCS, vol. 5264, pp. 457–464. Springer, Heidelberg (2008)

Facial Expression Recognition Using Local Fisher Discriminant Analysis Shiqing Zhang1, Xiaoming Zhao2, and Bicheng Lei1 1

School of Physics and Electronic Engineering, Taizhou University, 318000 Taizhou, China 2 Department of Computer Science, Taizhou University, 318000 Taizhou, China {tzczsq,tzxyzxm,leibicheng}@163.com

Abstract. In this paper a new facial expression recognition method based on Local Fisher Discriminant Analysis (LFDA) is proposed. LFDA is used to extract the low-dimensional discriminant embedded data representations from the original high-dimensional local binary patterns (LBP) features. The Knearest-neighbor (KNN) classifier with the Euclidean distance is adopted for facial expression classification. The experimental results on the popular JAFFE facial expression database demonstrate that the best accuracy based on LFDA is up to 85.71%, outperforming the used Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA). Keywords: Facial expression recognition, Local binary patterns, Local Fisher discriminant analysis.

1 Introduction Facial Expression is one of the most powerful, nature, and immediate means for human beings to communicate their emotions and intentions. Automatic facial expression recognition has attracted much attention over two decades due to its important applications to human-computer interaction, data driven animation, video indexing, etc. An automatic facial expression recognition system involves two crucial parts: facial feature representation and classifier design. Facial feature representation is to extract a set of appropriate features from original face images for describing faces. Mainly two types of approaches to extract facial features are found: geometry-based methods and appearance-based methods [1]. In geometric feature extraction system, the shape and location of various face components are considered. The geometrybased methods require accurate and reliable facial feature detection, which is difficult to achieve in real time applications. In contrast, the appearance-based methods, image filters are applied to either the whole face image known as holistic feature or some specific region of the face known as local feature to extract the appearance change in the face image. Up to now, Principal Component Analysis (PCA) [2], Linear Discriminant Analysis (LDA) [3], and Gabor wavelet analysis [4] have been applied to either the whole-face or specific face regions to extract the facial appearance S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 443–448, 2011. © Springer-Verlag Berlin Heidelberg 2011

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changes. Recently, Local Binary Patterns (LBP) [5], originally proposed for texture analysis [6] has been successfully applied as a local feature extraction method in facial expression recognition [7, 8]. No matter which kind of facial features is used, the dimensionality of facial features is still high-dimensional. Therefore, it’s desirable to perform dimensionality reduction on high-dimensional facial features in purpose of extracting the low-dimensional embedded data representations for facial expression recognition. In recent years, a new supervised dimensionality reduction method called Local Fisher Discriminant Analysis (LFDA) [9] has been proposed to overcome the limitation of LDA. LFDA effectively combines the ideas of LDA and locality preserving projection (LPP) [10], that is, LFDA maximizes between-class separability and preserves within-class local structure at the same time. Thus, LFDA is capable of extracting the low-dimensional discriminant embedded data representations. Motivated by the deficiency of studies about LFDA for facial expression recognition, in this work we use LFDA to extract the low-dimensional discriminant embedded data representations from high-dimensional LBP features on facial expression recognition task. We compare LFDA with PCA and LDA to verify the effectiveness of LFDA for facial expression recognition. We conduct facial expression recognition experiments on the popular JAFFE [11] facial expression database. The remainder of this paper is organized as follows. In Section 2 Local Fisher Discriminant Analysis (LFDA) is reviewed briefly. The popular JAFFE facial expression database is introduced in Section 3. Section 4 presents the experiment results. Finally, the conclusions are given in Section 5.

2 Local Fisher Discriminant Analysis Let xi ∈ R D (i = 1, 2," , n) be D -dimensional samples and li ∈ {1, 2," , c} be associated class labels, where n is the number of samples and c is the number of classes. Let nl be the number of samples in class l : c

∑n l =1

l

=n

(1)

Let yi ∈ R d (1 ≤ d ≤ D ) be the low-dimensional data representation of a sample

xi , where d is the dimension of the embedding space. Local Fisher Discriminant Analysis (LFDA) [9] finds a transformation matrix Τ such that an embedded representation yi of a sample xi is given by yi = T T xi

(2)

where T T denotes the transpose of a matrix Τ . Let S (lw) and S ( lb ) be the local within-class scatter matrix and the local betweenclass scatter matrix: 1 n S (lw) = ∑ Wi (, lwj ) ( xi − x j )( xi − x j )T (3) 2 i , j =1

Facial Expression Recognition Using Local Fisher Discriminant Analysis

S ( lb ) =

445

1 n Wi ,(lbj ) ( xi − x j )( xi − x j )T ∑ 2 i , j =1

⎧⎪ Ai , j / nl Wi ,(lwj ) = ⎨ ⎪⎩0

(4)

if li = l j

(5)

if li ≠ l j

⎧⎪ Ai , j (1/ n − 1/ nl ) Wi ,(lbj ) = ⎨ ⎪⎩1/ n

if li = l j

(6)

if li ≠ l j

where A is a affinity matrix between xi and x j . Using the local scaling heuristic, A is defined as

Ai , j = exp(− xi − x j

2

/ σ iσ j )

(7)

where σ i is the local scaling around xi and defined by σ i = xi − x

(k ) i

(k ) i

, and x

is the

k-th nearest neighbor of xi . A heuristic choice of k=7 has shown to be the best performance. The LFDA transformation matrix TLFDA is defines as

TLFDA = arg max[tr (T T S (lb )T (T T S (lw)T )−1 )] T ∈R D×d

(8)

3 Facial Expression Database The popular JAFFE facial expression database [11] used in this study contains 213 images of female facial expressions. Each image has a resolution of 256×256 pixels. The head is almost in frontal pose. The number of images corresponding to each of the 7 categories of expression (neutral, happiness, sadness, surprise, anger, disgust and fear) is almost the same. A few of them are shown in Fig.1.

Fig. 1. Examples of facial images from JAFFE database

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As done in [12], we normalized the faces to a fixed distance of 55 pixels between the two eyes. Automatic face registration can be achieved by a robust real-time face detector based on a set of rectangle haar-like features [13]. From the results of automatic face detection, such as face location, face width and face height, two square bounding boxes for left eye and right eye are created respectively. Then, two eyes location can be quickly worked out in terms of the centers of two square bounding boxes for left eye and right eye. Based on the two eyes location, facial images of 110×150 pixels were cropped from original frames. Fig.2 shows the process of two eyes location and the final cropped image. No further alignment of facial features such as alignment of mouth was performed in our work.

Fig. 2. (a) Two eyes location (b) the final cropped image of 110×150 pixels

4 Experimental Results Since LBP has a predominant characteristic, that is, LBP tolerates against illumination changes and operates with its computational simplicity, we adopted LBP for facial image representations for facial expression recognition. The K-nearest-neighbor (KNN) classifier with the Euclidean distance was used to conduct facial expression recognition experiments owing to its simplicity. And the parameter K for KNN was set to 1 for its best performance. To compare with LFDA, PCA and LDA was used for dimensionality reduction. The reduced feature dimension is limited to the range [2, 20]. For all facial expression recognition experiments, a 10-fold stratified cross validation scheme was performed and the average recognition results were reported. Table 1. The best accuracy for different methods with corresponding reduced dimension Methods

Baseline

PCA

LDA

LFDA

Dimension

2478

17

6

11

Accuracy (%)

80.95

78.57

83.81

85.71

The different recognition results of three used dimension reduction methods, i.e., PCA, LDA and LFDA, are given in Fig.3. It should be pointing out that the reduced feature number of LDA is set to the range [2, 6] because LDA can find at most 6 (less than 7 categories of expression) meaningful embedded features due to the rank

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deficiency of the between-class scatter matrix [3]. The best accuracy for different methods with corresponding reduced dimension is presented in Table 1. Note that the “Baseline” method denotes that the result is obtained on the original 2478dimensional LBP features without any dimensionality reduction. As shown in Fig.3 and Table 1, we can see that LFDA obtains the highest accuracy of 85.71% with 11 embedded features, outperforming PCA, LDA and Baseline. This indicates that LFDA is capable of extracting the most discriminant low-dimensional embedded representations for facial expression recognition. In addition, LDA performs better than PCA, since LDA is a supervised reduction method and can extract the lowdimensional embedded data representations with higher discriminating power than PCA. 100

Recognition accuracy / %

90 80 70 60 50 LDA PCA LFDA

40 30 20 2

4

6

8

10

12

14

16

18

20

Reduced dimension

Fig. 3. Performance comparisons of different used dimension reduction methods

5 Conclusions In this paper, we presented a new method of facial expression recognition based on LFDA for. To testify the effectiveness of LFDA, two well-known dimensionality reduction methods including PCA and LDA, were used to compare with LFDA. The experiment results on the popular JAFFE facial expression database indicate that LFDA performs best and obtains the highest accuracy of 85.71% with 11 embedded features. This is attributed to that LFDA has the better ability than PCA and LDA to extract the low-dimensional embedded data representations for facial expression recognition. Acknowledgments. This work is supported by Zhejiang Provincial Natural Science Foundation of China (Grant No.Z1101048, No. Y1111058).

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References 1. Tian, Y., Kanade, T., Cohn, J.: Facial expression analysis. In: Handbook of Face Recognition, pp. 247–275 (2005) 2. Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Maui, USA, pp. 586–591 (1991) 3. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997) 4. Lyons, M.J., Budynek, J., Akamatsu, S.: Automatic classification of single facial images. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(12), 1357–1362 (1999) 5. Ojala, T., Pietikinen, M., Menp, T.: Multiresolution gray scale and rotation invariant texture analysis with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002) 6. Ojala, T., Pietikinen, M., Harwood, D.: A comparative study of texture measures with classification based on featured distributions. Pattern Recognition 29(1), 51–59 (1996) 7. Shan, C., Gong, S., McOwan, P.: Robust facial expression recognition using local binary patterns. In: IEEE International Conference on Image Processing (ICIP), Genoa, pp. 370–373 (2005) 8. Shan, C., Gong, S., McOwan, P.: Facial expression recognition based on Local Binary Patterns: A comprehensive study. Image and Vision Computing 27(6), 803–816 (2009) 9. Sugiyama, M.: Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis. Journal of Machine Learning Research 8, 1027–1061 (2007) 10. He, X., Niyogi, P.: Locality preserving projections. In: Advances in Neural Information Processing Systems (NIPS), pp. 153–160. MIT Press, Cambridge (2003) 11. Lyons, M., Akamatsu, S., Kamachi, M., Gyoba, J.: Coding facial expressions with Gabor wavelets. In: Third IEEE International Conference on Automatic Face and Gesture Recognition, Nara, Japan, pp. 200–205 (1998) 12. Tian, Y.: Evaluation of face resolution for expression analysis. In: First IEEE Workshop on Face Processing in Video, Washington, USA, pp. 82–82 (2004) 13. Viola, P., Jones, M.: Robust real-time face detection. International Journal of Computer Vision 57(2), 137–154 (2004)

Improving Tracking Performance of PLL Based on Wavelet Packet De-noising Technology YinYin Li*, XiaoSu Xu, and Tao Zhang Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University, Nanjing 210096, China [email protected], [email protected], [email protected]

Abstract. The Phase-Locked Loop is used to track an incoming signal and provide accurate carrier phase measurements on GPS receivers. However, the PLL performance is affected by the thermal noise and dynamic stress. In order to resolve the conflict between reducing PLL noise and overcoming the dynamic stress, some compromises must be taken in PLL design. This paper proposes a wavelet packet de-noising technology to resolve this conflict. The wavelet packet de-noising technique effectively eliminates the effect of the noise and allows broadening the PLL bandwidth. The performance is evaluated by real signals test. The results show that this method outperforms the ordinary method in terms of Signal-to-Noise Ratios (SNR) and Relative Mean-Square Error (RMSE). Keywords: GPS, Software Receiver, PLL, wavelet packet, soft-threshold, de-noising.

1 Introduction The robustness of GPS receivers has gained more and more attention in recent years. For GPS receivers, a phase-locked loop provides the carrier phase measurement for accurate positioning. Unfortunately, the PLL tracking performance is often affected by many errors, mainly the thermal noise and dynamic stress [1]. To tolerate dynamic stress, the conventional method is to broaden PLL bandwidth and reduce the preintegration time. However, in order to reduce the thermal noise, a narrow bandwidth and longer pre-integration time are required. Actually, some compromise must be made to resolve this conflict [2]. This paper proposed an algorithm based on wavelet packet de-noising technology to improve the tracking performance of PLL. Due to their flexibility, software receivers are quite valuable and convenient in executing and evaluating the algorithm. The proposed algorithm was implemented in a GPS software receiver developed in C/C++ language. The paper’s frame are as follows: firstly, the basic structure of software GPS receiver is illustrated; Secondly, some basic concepts of PLL and *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 449–456, 2011. © Springer-Verlag Berlin Heidelberg 2011

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wavelet packet de-noising are introduced as well as a detailed introduction of how to implement the wavelet packet de-noising technology in a PLL; And lastly, test results and conclusions are demonstrated.

2 Software GPS Receiver Structure The structure of the software receiver used in this paper is shown as Fig.1. GPS Software receiver realizes base-band signal processing and navigation solution by the way of software, through a generalized and modularized hardware platform, viz., front-end [3]. Achieving the functions by software makes the software receiver have characteristics of good compatibility and flexibility. Different algorithms can be executed and evaluated in the receiver. IF signal input

Signal Acquisition

Signal Tracking

Bit synchronization Frame synchronization Parity check

Decode Navigation message

Position Solution

Fig. 1. The Structure of a Software GPS Receiver

The principle of a software receiver is as follows: firstly, the receiver should read the IF data. Secondly the acquisition module is used to acquire the rough code phase and Doppler frequency from each satellite. Thirdly the tracking module is used to implement carrier tracking and code tracking based on the parameters from the second step. Then, synchronization, parity and decoding are implemented in sequence [4]. As a result, the position message is then calculated. The carrier tracking is accomplished by PLL to synthesize the replica carrier frequency and phase with the one of the satellite signals. The performance of PLL plays an important role to the GPS receiver.

3 Basic Principle of PLL A PLL is a control loop which synchronizes its output signal uo (t ) (generated by a

voltage controlled oscillator) with a reference or input signal ui (t ) in frequency as well as in phase. The PLL generates a control signal which is related to the phase error to control VCO to generate the signal frequency which will be closer to the input signal, until the output frequency of a PLL is exactly same as the input signal and the error signal ud (t ) between the oscillator’s output signal and the reference signal is zero, or remains constant. In such a control mechanism, the PLL always adjusts the phase of the output signal to lock to the phase of the reference signal [5]. A typical PLL block diagram is shown in Figure 2. It consists of three basic functional components: a discriminator or a phase detector (PD), a loop filter (LF)

Improving Tracking Performance of PLL

451

and a voltage controlled oscillator (VCO). LF is used to filter the result from the PD and generate the control signal u f (t ) to control the VCO to generate the output signal.

ui (t)

ud (t)

uf (t)

uo (t)

Fig. 2. A Typical PLL Block Diagram

4 Principle of Wavelet Packet De-noising Signal f (t ) can be decomposed into coefficients { α λ (t ) } which are on another space based on the wavelet packet basis. The signal f (t ) can be expressed by the linear superposition of these coefficients:

f (t ) = ∑ aλ β λ (t ) . λ ∈Λ

(1)

Where { βλ (t ) } are the basis of the other space. We can abstract the characteristic of the signal from the coefficients aλ . So the processing of the signal can be replaced by the processing of aλ [6]. In this paper, the wavelet packet decomposition was used. The wavelet packets transform the signal in time domain into the coefficients in the inner product space of wavelet packet. Define the following notation: ϕ ( x ) is an scaling function and φ ( x) is the corresponding wavelet function, {Vk } is a multiresolution space, also called scale space generated by ϕ ( x ) .{Wk } is a wavelet space generated by φ ( x) , Wk −1 is an fill space differences between Vk −1 and Vk , so Lévesque space L2 ( R ) can be decomposed as [7]: L2 ( R ) = L ⊕ W−2 ⊕ W−1 ⊕ W0 ⊕ W1 ⊕ W2 ⊕ L

(2)

And {2k / 2 φ (2k t − l ) : l ∈ Z } is a group of bases of Wk .Wavelet packet transform can be carried out by followed ways: Define a sequence of functions as follows [8]:

⎧ ϕ 2 n ( x) = 2 j / 2 ∑ hk ϕn (2 j / 2 − k ) ⎪ k ⎨ j/2 = ϕ ( x ) 2 g k ϕ n (2 j / 2 − k ) ∑ ⎪ 2 n +1 ⎩ k

(3)

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Where j , k ∈ Z (Z is an integer set) and j is a scale parameter, k is time or location parameter, n ∈ N (N is a non-negative integer set), hk is a low-pass filter coefficient, g k is a high-pass filter coefficient. Moreover {hk } and{g k } are a group of conjugate mirror filters. Their relationships are as followed:

∑h n∈Z

h

n − 2 k n − 2l

= δ k ,l ∑ hn = 2 g k = (−1) k hl − k . n∈Z

(4)

Then two-scale equations of wavelet packet transform can be achieved: ⎧ϕ 2 n ( x ) = 2 ∑ hk ϕ n (2 x − k ) ⎪ k ⎨ ⎪φ2 n ( x) = 2 ∑ g k ϕn (2 x − k ) k ⎩

(5)

The signal can be expressed by the following wavelet packet bases function: f (t ) = ∑ Cnj (k )2k / 2 φn (2k / 2 t − j ) .

(6)

Cnj (k ) = 2 k / 2 ∫ f (t )φn (2k / 2 t − j )dt .

(7)

n, j

Where

R

Based on the theory of local maxima value of the wavelet transformation, the characteristic information is concentrated in a few coefficients. So, de-noising process can be done by saving the character coefficients and threshold other coefficients. After threshold, the modified coefficients can be used to reconstruction of signal. The reconstruction formulation of a discrete signal is done by [8]: Cmj ( k ) = ∑ hk − 2 n C2jm+1 ( n) + ∑ g k − 2 n C2jm+1+1 ( n) . n

n

(8)

hk − 2 n and g k − 2 n can be obtained by reversing order of hk − 2 n and g k − 2 n . Wavelet packet decomposition can decompose the signal to different frequency bands in different levels. If we have sufficient decomposed levels and data samples, the beginning and the ending of a frequency band can be acquired [6]. In general, wavelet packet de-noising is done in the following steps: Firstly, decompose the signal based on the selected wavelet packet basis. The signal is decomposed into several layers of wavelet packet coefficients as a tree [6]. The structure of the tree is as figure 3:

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453

Fig. 3. The structure of the wavelet packet tree

Secondly, compute the best tree based on the entropy of Shannon, which is computing the best wavelet packet basis. Thirdly, a threshold is computed and then a soft-threshold is applied to the coefficients. The threshold can be calculated as follows [8]:

λ = σ 2 * log 2 N .

(9)

There are two kings of threshold functions, hard threshold and soft threshold functions. In this paper, soft threshold function was selected. It is defined as [8]:

⎧⎪ sign(W j , k )( W j , k − λ ), W j , k ≥ λ ) W j,k = ⎨ . 0 , W j ,k < λ ⎪⎩

(10)

Fourthly, signal reconstruction is performed using the modified detail coefficients. The reconstruction algorithm is as formula (8).

5 Applying Wavelet De-noising Technique for PLL The purpose of applying the wavelet packet de-noising technique in the PLL is to reduce the noise level before the loop filter. The block diagram is as figure 4:

uI (k) SI (k)

uO(k)

ud (k) uf (k)

ui (k)

,

uO (k)

SQ (k)

uQ(k) Fig. 4. Applying Wavelet De-noising Technique in the PLL

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The main function of the wavelet packet de-noising is to reduce the noise level within the bandwidth of the loop filter. The loop filter could filter out the noise beyond the bandwidth of the loop filter, but the noise within the bandwidth still could pass through and affect the NCO tracking performance. It should be noted that the wavelet packet de-noising technique can only reduce the noise level rather than eliminate the noise totally. The remaining noise still can affect the NCO tracking performance but at a lower level [2]. The wavelet packet de-noising technique may cut off some useful signals which are smaller than the threshold. This disadvantage will make the PLL spend more time to lock due to the loss of some control signals and the output from PLL distorted. However the decrease of the noise will produce smaller phase error that will help the PLL to maintain locked and smooth the output [6].

6 Test Results The performance of the proposed algorithm is assessed by using real IF data acquired by RF front-end. The front-end’s parameters are as follows: IF (intermediate frequency) is 4.123968 MHz and sampling frequency is 16.367667MHz. The software receiver is simulated based on VC++6.0. The algorithm processed the outputs from the discriminator. The performance is evaluated in terms of signal-to-noise (SNR) ratios and Relative Mean-Square Error (RMSE). The formulas of SNR and RMSE are as follows [9]: N

S N R = − 1 0 • lo g 10

∑

i =1

( I (i) − I d (i)) 2 N

∑

.

(11)

2

I (i)

i=1

RM S =

N

[∑ ( I (i) − I d (i)) 2 ] i =1

N

∑

i =1

I

2 d

(i) .

(12)

I (i ) and I d (i ) denote the original signal and the de-noised signal separately. Doppler frequencies from the ordinary PLL and the modified PLL are compared in figure5 and figure 6. The tested data is 36000ms long, parts of which are selected to display for briefness. Both figures show that the data from the proposed algorithms has less noise than the ordinary PLL , but with a little offset. The results comply with the theory above. The slope of the curves stands for change rate of Doppler frequency.

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Fig. 5. The difference of Doppler frequency between modified PLL and ordinary PLL for satellite 9

Fig. 6. The difference of Doppler frequency between modified PLL and ordinary PLL for satellite 18

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The SNR and RMSE improvements of the proposed algorithm are depicted in table 1. In general, the results comply with the results from the figures. The waveletde-noising algorithm provides some improvement in SNR and RMSE. Table 1. Doppler frequency improvement in SNR and RMSE

Satellite number

SNR(dB)

RMSE

9 18

64.3340 72.5939

0.00060687 0.00023459

7 Conclusion The wavelet de-noising technique in the PLL can reduce the noise within the bandwidth of the loop filter and therefore, a less noisy tracking output can be obtained from the NCO. So this proposed method is effective to improve the PLL tracking performance. However, the bias between the de-noised signal and the original signal are related to the soft-threshold function and will still affect the performance of the PLL. How to improve the threshold function will be the focus of the future work. Besides, operating the software in real time instead of post-processing is also a key issue to be considered in later research.

References 1. Ward, P.W., Betz, J.W., Hegarty, C.J.: Satellite Signal Acquisition, Tracking, and Data Demodulation. In: Understanding GPS Principles and Applications, pp. 153–241. Artech House, Inc., Norwood 2. Lian, P., Lachapelle, G., Ma, C.L.: Improving tracking performance of PLL in high dynamics applications. ION. NTM, 1042–1052 (2005) 3. Tsui, James, B.Y.: Fundamentals of Global Positioning System Receivers: A Software Approach. John Wiley & Sons Inc., Chichester (2000) 4. Cai, B.-G., Shang, G.W., Wang, J., Liu, H.-C.: Design and Realization of Software Receiver Based on GPS Positioning Algorithm. In: International Conference on Information Science and Engineering, pp. 2030–2033. IEEE, Los Alamitos (2009) 5. Gardner, F.M.: Phase Lock Techniques, 3rd edn. John Wiley & Sons, Inc., USA (2005) 6. Qian, H.-m., Ma, J.-c., Li, Z.-y.: Fiber optical gyro de-noising based-on wavelet packet soft-threshold algorithm. Journal of Chinese Inertial Technology 15(5), 602–605 (2007) 7. Daubechies, I.: Orthonormal bases of compactly supported wavelets. Commun. Pure Appl. 41, 909–996 (1998) 8. Peng, Y., Weng, X.H.: Thresholding-based Wavelet Packet Methods for Doppler Ultrasound Signal Denoising. In: IFMBE Proceedings, APCMBE 2008, vol. 19, pp. 408–412 (2008) 9. Yu, W.X., Zhang, Q.: Signal De-noising in Wavelet Packet Based on An Improvedthreshold Function. Communications Technology 43(6), 7–9 (2010)

Appendix: Springer-Author Discount This project was supported by the National Natural Science Foundation of China (No. 60874092, 50575042, 60904088).

Improved Algorithm of LED Display Image Based on Composed Correction Xi-jia Song1,2, Xi-qiang Ma1,2, Wei-ya Liu1, and Xi-feng Zheng1 1

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 130033 Changchun, China 2 Graduate School of the Chinese Academy of Sciences, 100039 Beijing, China [email protected]

Abstract. In order to enhance the display result of the LED display image, an improved algorithm of LED display image based on composed correction is proposed. Firstly, the correction principle and the development status of the current correction technologies of the LED display image is introduced, and the two main correction technologies are analyzed. Secondly, the theory of composed correction is proposed by constructing a mathematical model. Thirdly, this algorithm is achieved in VHDL which is one of hardware description language, and verified in an experimental platform. Experimental results show that this algorithm is able to enhance the display result of the LED display image significantly. Keywords: Improved algorithm; LED display image; composed correction.

1 Introduction LED display panel has been used widely in various occasions such as stage background, traffic guidance, sports events living and so on. The reason that the LED display panel is widespread attention and development rapidly is that it itself has many advantages. The reason why widespread attention to LED, and rapid development, is that it itself has many advantages. The sums of these advantages are: high brightness, low voltage, low power consumption, and long life. Although the LED display panel has so many advantages, its development is still constrained by some unfavorable factors. One of them is the non-uniformity among pixels after the LED display panel works a period of time, because different pixels have different length of working [1-6]. In order to solve the above problem, there are two main correction technologies which are correction based on CCD and correction based on dedicated video processor. The correction based on CCD has been used in the LED display panel many years and this technology is already mature. The correction based on video processor is only in recent years developing. The cost of this technology is high because the dedicated video processor is expensive. Therefore, an improved algorithm of LED display image based on composed correction is proposed [7-10]. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 457–463, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Mathematical Model of LED Display Image A two-dimensional function is used to denote the LED display image. In particular coordinates (x, y), for the monochromatic LED display panel, the value of f(x, y) represents the grayscale level of the pixel in (x, y); for the full color LED display panel, f(x, y) is combined with three parts which are fR(x, y), fG(x, y) and fB (x, y) because one pixel is composed of three sub-pixels which are red, green and blue. So the value of fR(x, y), fG(x, y) and fB (x, y) represents the grayscale level of these subpixels respectively. In the back, the pixel is composed of three sub-pixels in the absence of special circumstances statement, because the focus of this paper is the full color LED display panel and the monochromatic LED display panel can be viewed as one of special circumstance of the full color LED display panel. We can see from the LED light-emitting principle that f(x, y) is proportional to the luminous intensity of LED. Therefore, f(x, y) must be bounded and non-negative, that is expressed in (1).

⎧0 ≤ f R ( x, y ) ≤ Lmax ⎪ ⎨0 ≤ f G ( x, y ) ≤ Lmax ⎪ 0 ≤ f ( x, y ) ≤ L ⎩ B max

(1)

In (1), Lmax denotes the highst grayscale level of the pixel. The coordinates of the LED display image should be agreed the constants shown in Fig. 1.

Fig. 1. Coordinate constraints of the LED display image. ● denotes one pixel and (0, 0) denotes the pixel which in the first row and the first column. The resolution of the LED display panel is V×H. It means that the LED display panel has the number of H rows and V columns pixels.

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3 Mathematical Description of LED Display Image

，

The LED display image can be described as a matrix F because it itself is digital array. Each pixel of the LED display panel is the corresponding element of the matrix F. It should be note that the size of the matrix F is not V×H but (3×V)×H. F is combined with three sub-matrixes which are FR, FG and FB.

F = [ FR : FG : FB ]

(2)

In (2), FR, FG and FB is expresses in (3), (4) and (5) respectively.

⎡ f R (0, 0) ⎢ f (1, 0) FR = ⎢ R ⎢ # ⎢ ⎣ f R ( H − 1, 0)

⎡ fG (0, V ) ⎢ f (1,V ) FG = ⎢ G ⎢ # ⎢ ⎣ fG ( H − 1,V )

f R (0,1)

"

f R (1,1)

"

f R (0,V − 1) ⎤ f R (1, V − 1) ⎥ ⎥ ⎥ # ⎥ f R ( H − 1, V − 1) ⎦

# % f R ( H − 1,1) "

f G (0, V + 1)

"

f G (1,V + 1) #

" %

fG ( H − 1,V + 1) "

⎡ f B (0, 2V ) ⎢ f (1, 2V ) FB = ⎢ B ⎢ # ⎢ ⎣ f B ( H − 1, 2V )

f B (0, 2V + 1) f B (1, 2V + 1)

(3)

f G (0, 2V − 1) ⎤ f G (1, 2V − 1) ⎥⎥ ⎥ # ⎥ fG ( H − 1, 2V − 1) ⎦

(4)

f B (0,3V − 1) ⎤ f B (1,3V − 1) ⎥⎥ ⎥ # ⎥ f B ( H − 1, 3V − 1) ⎦

(5)

" "

# % f B ( H − 1, 2V + 1) "

In addition to the abobe representation, the LED display image can be described as a vector shown as in (6).

f = [ fR

fG

fB ]

(6)

In (6), fR, fG and fB is expressed in (7), (8) and (9) respectively.

f R = [ f0

f1 "

f G = [ fV

fV +1 "

f B = [ f 2V

f 2V +1 "

fV −1 ]

(7)

f 2V −1 ]

(8)

f 3V −1 ]

Each emement in vector fR, fG or fB can be expresssed in (10).

(9)

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⎡ f (0, i ) ⎤ ⎢ f (1, i ) ⎥ ⎥ fi = ⎢ ⎢ ⎥ # ⎢ ⎥ ⎣ f ( H − 1, i ) ⎦

(i = 0,1,"3V − 2,3V − 1)

(10)

4 Experiments Results This algorithm is achieved in VHDL which is one of hardware description language. This program has four modules which are data_in, data_pro, data_driv and correction_end. Data_in is a module which receive the data from the data sources such as display card, video processor and so on. Date_pro is a module which processes the data provided by data_in based on composed coreection. Data_driv is a module which transfores the data to the LED display panel. Correction_end is module which controls the processing of correction. The main code of this program is Library ieee; Use ieee.std_logic_1164.all; Use ieee.std_logic_unsigned.all; Entity Composed_Correction is Generic(M:integer:=8; N:integer:=8; K:integer:=16; L:integer:=8); Port(pr,pg,pb:in std_logic_vector(M-1 downto 0); ctr:in std_logic_vector(N-1 downto 0); qr,qg,qb:out std_logic_vector(K-1 downto 0); ena:out std_logic_vecor(L-1 downto 0)); End Composed_Correction; Architecture a of Composed_Correction is Signal mr,mg,mb: std_logic_vector(M-1 downto 0); Signal nr,ng,nb: std_logic_vector(N-1 downto 0); Begin U1: data_in port map(pr,pg,pb,mr,mg,mb); U2: data_pro port map(mr,mg,mb,ctr,nr,ng,nb); U3: data_driv port map(nr,ng,nb,qr,qg,qb); U4: correction_end port map(ctr,ena) End a; This program is verified in an experimental platform. The algorithm based on composed correction has been applied in the projects, and the following figures, Fig.3, Fig.4, Fig.5 and Fig.6 are the LED display result before and after using this algorithm.

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display unit

data transform unit drive unit

control unit

Fig. 2. The experimental platform is combined with the data transform unit, the control unit, the drive unit and the display unit

(a)

(b)

Fig. 3. (a) is the LED dispplay result in red before correcint and (b) is after correcting

(a)

(b)

Fig. 4. (a) is the LED dispplay result in green before correcint and (b) is after correcting

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(a)

(b)

Fig. 5. (a) is the LED dispplay result in write before correcint and (b) is after correcting

(a)

(b)

Fig. 6. (a) is the LED dispplay result in write before correcint and (b) is after correcting

5 Conclusion The improved algorithm of LED display image based on composed correction is able to reduce the non-uniformity among pixels after the LED display panel works a period of time. The experimental results show that this algorithm is able to enhance the display result of the LED display image significantly.

References 1. Goh, J.C., Chung, H.J., Jang, J., et al.: A new pixel circuit for active matrix organic light emitting diodes. IEEE Transactions on Electron Device, 544–546 (2002) 2. Critchley, B.R., Blaxtan, W.P., Eckersley, B.: Picture quality in large-screen projectors using the digital micro-mirror. Society for Information Display, 199–202 (2008) 3. Winkler, S.: Issues in vision modeling for perceptual video quality assessment. Signal Processing, 231–252 (1999) 4. Cheng, W.S., Zhao, J.: Correction method for pixel response non-uniformity of CCD. Opt. Precision Eng., 103–108 (2008) 5. Chang, F., Wang, R.-g., Zheng, X.-f., et al.: Algorithm of reducing the non-uniformity of images in LED display panel. IEEE Transactions on Power Electronics, 169–172 (2010)

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6. Vovk, U., Likar, B.: A Review of Methodsfor Correction of Intensity Inhomogeneity in MR. IEEE Transactions on Medical Imaging, 405–411 (2007) 7. Leemput, K.V., Maes, F., Vandermeulen, D., et al.: Automated model -based bias field correction of MR images of the brain. IEEE Transactions on Medical Imaging, 885–889 (1999) 8. Pinson, M.H.: A New Standardized Method for Objectively Measuring Video Quality. IEEE Transactions on Broadcasting, 135–139 (2004) 9. Peter, J., Burt, E.H.: The Laplacian pyramid as a compact image code. IEEE Transactions on Communication, 532–540 (1983) 10. Ro, Y.M., Huh, Y., Kim, M.: Visual content adaptation according to user perception characteristics. IEEE Transactions on Multimedia, 435–445 (2005)

The Development Process of Multimedia Courseware Using Authoware and Analysis of Common Problem LiMei Fu DaLian Neusoft Institute of Information DaLian, China Abstract. With the rapid development of modern education technology, Multimedia courseware in teaching shows its advantage role. Based on author’s some experiences in developing multimedia courseware, this paper systematically introduced the principle of multimedia courseware ,the development tools of multimedia courseware and the development process of courseware. Meanwhile This paper also introduced some common problems encountered when we develop multimedia courseware. Finally for these common problems we make specific analysis. Actual teaching result shows that using the multimedia courseware can stimulate the learning interest of the students, and achieved good teaching effect. Keywords: Authoware, Multimedia Courseware, The process of development, The analysis of Common Problem.

1 Introduction With the rapid development of modern education technology,which put computer technology and network technology as the core, The schools pay more and more attention to use computers to develop multimedia courseware .Multimedia courseware in teaching shows its advantage role. A multimedia courseware can be considered as a teaching system ,which constitute by six basic part.The six part Respectively is cover introduction, knowledge content, exercises part, jump relations, navigation strategy and the interface, combining author actual experience in developing C programming courseware,This paper introduced the development process of courseware using Authoware, and summarized some problems encountered on the development process.Finally this paper presents some solution of these problems.

2 The Development Principles of Courseware The design of multimedia courseware should follow education teaching regularity and reflect specialized training goal. Meanwhile the courseware should combine teaching science with practicality.It also should have distinct characteristics and spread value,as in [1]. (1) Teaching.Firstly, the design of courseware should visual in image .It is also beneficial for students to understand knowledge. Secondly, the embodiment of the content should be lively and interesting. Finally, the courseware should also have practical applicability, and it can be apply to daily learning.of most students. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 464–469, 2011. © Springer-Verlag Berlin Heidelberg 2011

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(2) Scientific.The content of courseware should be science. At the same time the materials of courseware should be tightly arould of syllabus.The content of courseware should also adapt to the needs of teaching object. (3) Technical.Courseware can run in independent environment with quick speed and continuous animation.It also should have ability of fault-tolerant and trouble-free. The interface of courseware should have characteristic of friendly and strong interactivity. (4) Artistic.The picture of courseware should be concise, artistically and unification. Iit also should be reasonable for applying of image, animation and text font.The size of font should be easily identified.

3 The Introduction of Developing Tools Authorware Authorware is the product of the Macromedia company. As a kind of multimedia developing tools, it provides intuitive creation environment based on flow chart and design icon for developers. Developers can easily organize various multimedia material together and specify their respective forms.which can make developers completely control the flow of program .Using Authoware the users can develop complex multimedia application system with strong ability to interact.

4 The Development Process of C Programming Courseware Any courseware's success depends on perfect plans .The development of a good couserware generally is divided into four stages,as in [2]. (1) The collection of related materialst. (2) The development of courseware.Using multimedia production tools organize all kinds of material and develop courseware. (3) The testing and debugging of courseware. After completion in order to make corrections,courseware must be thorough examination. Before developing C programming courseware, it should be designed good hierarchical relationships firstly,as in [3]. According to the characteristics and content of C programming course we designed the hierarchical relationships of couseware as figure 1 shows. As an example figure 1 only lists the part of array,others is omited. Firsly we should bulid the overall framework of programe.The process as follows, Draging a group icon to follow line as couseware beginning. According to figure 1, we should firstly set framework of the the overall program. Building process as follows, draging a group icons to flow line, as whole courseware beginning. In group icons a AVI files is included.To prevent the illegal use of courseware,we set passoword for entering the courseware.If you want to use couseware you must input the right password. Then again drag a group icon as the whole procedure of the core part.This group icon contains all conten of courseware, including lecturing. Figure 2 shows the basic structure of courseware.

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Fig. 1. The hierarchical relationships of courseware

Fig. 2. The framework of courseware

The second step is to design the core part of courseware . Based on the framework of courseware and function, we determine the main menu, submenu and corresponding button of courseware.The design should be convenient to swith between one part and another part.At the same time the design should have some buttons which can return home page and exit the courseware system. In order to make courseware more beautiful, the main menu and submenu of chapters all use flash production. The design process of main menu as follows, first insert a flash animation into flow line, and then drag an interactive icon to flow line.In the following of the interactive icon, it can drag many group icons. there are many types of interactive response .We choose "hotspots response" as interaction.In those group icons,we can make use of all kinds of icon to finish the development of courseware.Such as “display icon” to display the content of courseware and all kinds of pictures,“audio icon”to play sounds,“move icon” to play movies. “Return button” and “exit button” use “caculate icon” to finish return main menu and exit system. In order to jump rightly,each icons are shall be named accurately in the whole process. Each icon should not have the same name.If have the same name, during execution of program jumping command would be caused wong runnig. Program flow see figure 3 shows. Initial interface displays each big chapter of the main menu, the submenu display the menu of chapters.Click the main menu can enter submenu interface.

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5 Fig. 3. The t structure of core courseware

Fig. 4. The structure of statements parts

Third step, each part of teaching contents is refined and divided into several independent unit of knowledge .Meanwhile it should be clear for every knowledge unit. According to different knowledge unit, the design gives the corresponding interface. Pages can be connected through “the next page button”. If submenus have been the last page, it should be return the main meun of this chapter by“return button”.In various state of sub menu, it can exit courseware by pressing "exit button” at anytime. Figure 5 is the structure chart of “statements”. In order to complete the corresponding function, you can drag different types of icon to the “group icon”. Fourth step is to complete the tests of each unit. Using Authorware“ knowledge object”can be done quickly. There are two kinds of question which respectively is choice and judgment.The feedback function is very important for the testing,when students do right,it should be design a encorage feedback,such as a “smiling face”.or an encouraging expression etc.When students answer wrong ,the test system should explain the reasonsts. In order to record the lerning situation of student every time,the system provids the function of “learning diary”.Finally the system also provide more resources of learning by “course resource” part.

5 The Analysis of Common Problem Encounted on the Development Process In the development process of courseware using Authoware,we offen encounter many questions.It maybe appear on the phase of development ,or on the phase of package,as in [4].

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5.1 The Analysis of Common Problem during the Development Phase (1) Import other formats file To make a excellent multimedia courseware, it usually need to import other file which generated by other software file into Authoware. Such as the main menu and various submenu,we use Flash file that can make interfaces more beautiful. Sometimes it also needs to insert some executable file, such as we can make an executable file through Flash to display the execution process of “for circulation” .It is a little difficulty if we want to realize it by using Authoware itself.In Authoware if you want to insert a excutable file ,you can do it by using JumpOutReturn."JumpOutReturn" function format is “JumpOutReturn("program", ["document"][,"creator"]).This function can begin to run a excutable file ,after finishing running it will return to Authorware environment.In addition, using the function might well connect Authorware with other applications, such as the applications.of notebook etc. PPT is a common file format of courseware.If you want to run PPT, you can click "insert" menu,then insert a "OLE object" . After inserting the PPT,you can set some attributes by demo manuscripts“OLE object" menu which is under "edit" menu. (2) The connection of material Whatever picture or vide or sound ,materials both have two ways to built-in Authoware.It is “external links” and “embedded in”. If the picture is not very big, “embedded in “ will be show quickly, in this way, it's best to put these pictures into the library after completion.If you use “external links”, it will be convenient to modify material and reduce data quantity of the application which will be improve efficiency of operation. (3) The use of interaction icon The most powerful function of development courseware using Authorware is interactive. It has rich control mode of interactive, besides the usual button, dropdown menus, hotspots, hot objects object outside, Authorware still can provide the conditions, moving objects, text, press the keys and limited interactive.These interactions enable convenient to develop courseware.so it is a good way to attract students to study by using all sorts of interactive when you develop multimedia courseware. 5.2 The Analysis of Common Problem during the Packaged Stage (1) lack of DLL file error After completion of Package,when you run excutable file you may find error which appear "lacks the DLL" message. This is because that Authorware has been adopted an open program structure which make all program function exists by hanging outside. such as Xtra, UCD etc. Therefore, all kinds of external support files must be released accompanying production together. Solution is to find these files which is under the installation directory of Authorware and then copy these files to pack directory. Other similar situation can be solved according to the method.

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(2) lack of Xtra error In order to run the pack files normallly,it still need to copy the Xtra file which have been used in courseware to pack folder. Otherwise it will cause that some materials can not be shown normally. Xtra file is some external files which can use to strengthen Authorware function. The solution of this error can be solved by copying all Xtras files which is under the installation directory folder of Authoware to Packaged directory. (3) When running package file it appears error message.which is “Where is movie name. Avi attention?” The cause of this error is that the program calls avi animation. files .These avi files are usually bigger, Authorware can not put these files included automatically when packed. The solution of these problems is copy avi file to packaged directory.

6 Conclusion This paper expounds the development process of a multimedia courseware using Authoware,based on author’s some experiences in developing the courseware of C programming.Meanwhile this paper also analysed common problem encountered on thedevelopment process of courseware. Practical teaching effect shows that using multimedia courseware teaching has achieved good teaching effect.

References 1. Koper, E.J.R.: A method for the development of multimedia courseware. The British Journal of Educational Technology 26(2) (May 1995) 2. Flori, R.E.: Computer-Aided Instruction in Dynamics: Does it Improve Learning? In: Session 3D1 77-81, Proceedings Frontiers in Education, 24th Annual Conference, San Jose, CA, November 2-6 (1994) 3. Ning, J.X.: How to make the multimedia courseware for teaching. Education Teaching BBS (March 2011) 4. Zhou, D.: The analysis of common problem using Authoware. Natural Sciences Journal of Harbin Normal University 17(2) (2001)

Design of Ship Main Engine Speed Controller Based on Expert Active Disturbance Rejection Technique Weigang Pan1, Guiyong Yang2, Changshun Wang1, and Yingbing Zhou1 1

Department of Information Engineering, Shandong Jiaotong University, Jinan, Shandong Province, China [email protected] 2 Beyond the NC Electronics Co., Ltd. Inspur Group, Jinan City, Shandong Province China [email protected]

Abstract. Applying mathematics model of nonlinear ship main engine control and the wave disturbances to the design of electronic governor, and considering the uncertainty of model parameters and the characteristics of servo-system makes the model have the unmatched uncertainty correspondingly. In order to solve the difficulty, an active disturbance rejection nonlinear control strategy is proposed, and the expert system is used to modify parameters of ADRC online which improve the ADRC's adaptive capacity. A ship main engine genetic algorithm ADRC controller is designed. The simulation results of ship main engine (ME) speed tracking and keeping show that the controller has good adaptabilities on the system nonlinearity and strong robustness to parameter perturbations of the ship and environmental disturbances. And the speed switching is fast and smooth, thus achieved high-accurate ship ME speed control. Keywords: Ship main engine, Expert, Active disturbance rejection controller.

1 Introduction Ship's main engine performance and service life depends very much on the performance of the speed adjust. At home and abroad most of the advanced speed control system of ship used digital governor, which used mainly PID algorithm. For the ship ME speed control processes are nonlinear, time-varying as well as the uncertainty of environment, it is very difficult to meet the requirements which obtain optimal control system performance index by depending on the traditional PID algorithm, because PID algorithm is usually used in the control system for constant coefficients and little environmental interference, otherwise, the control system can not guarantee optimal performance, or even become unstable.This paper design a new type of ship ME speed controller using expert ADRC technique and simulation study indicate that it achieves good results when parameter perturbations of the ship and environmental disturbances.

2 Ship ME Model Main Engine speed control system structure is shown in Fig.1. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 470–475, 2011. © Springer-Verlag Berlin Heidelberg 2011

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In this paper, MAN B&W S60M large low-speed diesel engine is used, its mathematical model as follows: kT1 n f (t ) + kn f (t ) = s (t − τ )

(1)

Fig. 1. ME Block diagram of speed control system

DC servo motor is used as Implementing agencies, its model as follows: T22 s(t ) + 2ξT2 s(t ) + s (t ) = ns (t )

(2)

Measurement results of speed detection unit directly affect the system's regulation accuracy, commonly magnetic sensor is used on board, whose mathematical model can be regarded as the proportion of links. Ship main engine used pure delay one order inertia model in the actual design, which is in (3).It not only simplifies the design work, but also achieve satisfactory results. G (s) =

ke −τs Ts + 1

(3)

In addition, the disturbance problem about ship ME control is very complex, which relative to water depth, load, wind, current, wave and so on. If the ship at sea in the rough, it sometimes make the propeller out of the water, suddenly the engine load will decrease. if the fuel pump can not be reduced in time, the engine speed will suddenly rise high, and even vehicles, the other hand, when the load suddenly increased, particularly in the case of low speed operation, if the fuel supply can not increase in time, may cause stop the engine. These disturbances of the navigation of the ship which has a large influence in the design of the controller must be considered.

3 Design of Expert ADRC Controller for Ship ME For the system which can be expressed as a series formation illustrated in Fig.3, it can be controlled by designing two ADRC controllers, which constitute a double closed loop control system as shown in Fig.2. Where, ADRC1 is the controllers of the ship ME system (two-order) and the ship sevo-system(one-order).

Fig. 2. Double rings ship ME controller based on ADRC

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Fig. 3. Single ring ship ME controller based on ADRC

A ship ME system showed in Fig.2, according to conventional design methods, generally is designed as shown in Fig.2 Double-ADRC ship ME system. Where, ADRC1 is the controllers of the ship ME system(two-order) and the ship sevosystem(one-order), ns for the expectations of the ME speed, sc is the expectations of displacement of servo mechanism, nf is the actual speed of the ME, s is the actual displacement of the servo. In accordance with the order from the inner to the outer tuning controller parameters, respectively, which ADRC2 11 parameters, ADRC1 15 parameters. Parametric design is difficult. The ultimate goal for designed the ship ME controller is to maintain the accuracy and tracking to speed, so the servo mechanism and the ship ME mathematical model can be considered as a whole, and thus greatly simplify the controller design, this design is shown in Fig.3, where ADRC is the two-order.

4 Parameter Setting of Expert ADRC Controller for Ship ME Speed Tracking For other parameters are easy to designed, the expert system is used to optimal

{k p , k d , β 01 , β 02 , β 03 } five parameters. It is easy to select the parameters compare with other manual adjustment based on experience. 1) The design of the expert ADRC Controller must be self-tuning parameters before operation. In the controller parameter tuning stage, based on analysis approximate model of the controlled object, the inference mechanism of expert system select the best set of ADRC parameters from the knowledge base and embed into the ADRC technology Control system, the final aim is achieved which control the uncertain object (Fig.4).

Fig. 4. expert system parameter self-tuning schematic

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2) Knowledge acquisition The basic task of knowledge acquisition are get knowledge and create sound, complete and effective knowledge base for expert systems to meet the needs of the field of problem solving, which is the key to the controller design, correct or not of knowledge base directly affect the control accuracy of the controller. The system has two main methods of knowledge acquisition. The first is by knowledge engineers, in the process of acquiring knowledge, the knowledge engineers Coordinate knowledge experts in the field, generating expert knowledge base. ADRC controller has strong robustness, and can be said to have "universal" in a certain type of object, but the ADRC controller of fixed parameters is not able to control all of the objects.Through research on some controlled objects which have pure delay one order inertia model found that: the constant of proportionality is 1 (it can be implemented by software), the time constant is generally 1 ~ 1000s, the delay time is generally 0 ~ 800s; Controller designed ten sets of ADRC parameters (Tab.1) to control the object.Parameter selection criteria are: the uncertain objects can be controlled always by a set of knowledge base parameters of ADRC, and control accuracy can meet the requirements (with a good fast, less than 15% overshoot); for the short delay objects, the knowledge base in the ADRC parameters should be as little as possible; for the long delay, big inertia objects, the knowledge base in the ADRC parameters should be as much as possible in order to meet the requirements of high-precision control . The second method for failure to control, the user should manually adjust the intelligent controller parameters, and improve the content of the knowledge base. Table 1. Ten sets of second-order ADRC parameter table

No.

kp

kd

β01

β 02

β 03

1 2 3 4 5 6 7 8 9 10

0.1 0.5 1.0 1.5 2.0 3 4 5 6 8

80 90 50 30 40 60 70 30 80 20

5 10 15 20 25 30 35 40 45 50

25 30 25 25 30 30 30 25 25 30

80 40 70 30 50 10 20 40 80 30

3) Knowledge base All ADRC parameters (Tab.1) and the controlled object similar model are stored in knowledge base. 4) Inference mechanism Inference mechanism is the core of the controller design which equivalent the brain of experts. It analysis approximate mathematical model of controlled object, use square

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error integral indicators ISE = e 2 (t )dt as a basis for parameter selection, and ∫ 0

simulate online by the parameters of knowledge base, then, the best performance index which obtained through online simulation embedded in the ADRC control system to achieve control of an uncertain object.

5 Simulation Results Simulating experiment is carried out on a ship which the ME is used MAN B&W S60M, nominal parameters are: T =12.4s, k=98.5, τ =0.0656s. The parameters of ADRC by tuning principle of the ADRC parameters are:

r =100, h =30, δ 01 =0.02, δ 02 =0.04, α1 =0.5, α 2 =0.25, δ1 =0.05, δ 2 =0.1. By expert system, the fourth sets of parameters in expert database is used. The parameters are:

k p =1.5, k d =30, β 01 =20, β 02 =25, β 03 =30. Set the periodic sample time as 0.1s, simulation time as 500s. Due to limited space, there are just some simulation results under typical conditions described in Fig.5-6. 120 100 n i m80 / n o i 60 t u l o v e r40

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Fig. 6. Simulation result of unload 25% load

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From which we can see that: 1) In nominal model, the speed response of Expert ADRC controller is fast and smooth than PID controller. 2) When load changed caused by disturbance, the speed response is still smooth and accurate relatively. These results indicate that Expert ADRC controller has a powerful robustness on the severe nonlinearity, parameter and condition uncertainties of ship ME and under the ADRC control. The speed switching is fast and smooth, thus achieves the goal of high-accurate ship ME speed.

6 Conclusion and Prospect This paper presents a design of the Expert ADRC for ship ME non-linear control. Simulation results show that this controller appears to be strictly robust to the nonlinear characteristic of the ship, and system disturbances, and the system uncertainty. The process of speed switching is fast and smooth. So it works perfectly as a ship ME speed controller. Acknowledgements. This work is supported by Natural Science Foundation of Shandong Province (Project Number: 2009ZRB019B2), Natural Science Foundation of Shandong Province (Project Number: ZR2009FL013), Natural Science Foundation of Shandong Province (Project Number: ZR2010FL014), Shandong Jiaotong College Research and Innovation Teams.

References 1. Han, J.Q.: From PID technique to active disturbance rejection control technique. Control Engineering of China 9(3), 13–18 (2002) 2. Han, J.Q.: Auto disturbances rejection control technique. Frontier Science 1, 24–31 (2007) 3. Zhao, X.R., Zheng, Y., Hou, Y.H.: The rational spectrum modeling of the ocean wave and its simulation method. Journal of System Simulation 4(2), 33–39 (1992) 4. Hu, Y.H., Jia, X.L.: Theory and Application of Predictive Control of Ships Subject to State Constraints. Control and Decision 17(4), 542–547 (2000) 5. Cheng, Q.M., Wan, D.J.: Overview on the development and comparison of the control techniques on ship maneuvering. Journal of Southeast University 29(1), 14–19 (1999) 6. Pan, W.G., Zhou, Y.B., Han, Y.Z.: Design of Ship Main Engine Speed Controller Based on Optimal Active Disturbance Rejection Technique. In: 2010 International Conference on Automation and Logistics, vol. 1, pp. 528–532 (2010)

Design of Ship Course Controller Based on Genetic Algorithm Active Disturbance Rejection Technique Hairong Xiao1,2, Weigang Pan1, and Yaozhen Han1 1 Department of Information Engineering, Shandong Jiaotong University, Jinan, Shandong Province, China [email protected] 2 School of Control Science and Engineering, Shandong University, Jinan, Shandong Province, China

Abstract. Because of the strong non-linearity and uncertainty, the dynamics restraints of autopilots, as well as the effects of wave disturbances, designing a high performance ship course controller is always a difficult work. In order to solve the difficulty, an active disturbance rejection nonlinear control strategy is proposed, and the genetic algorithm is used to modify parameters of ADRC online which improve the ADRC's adaptive capacity. A ship course genetic algorithm ADRC controller is designed. The simulation results of ship course tracking and keeping show that the controller has good adaptabilities on the system nonlinearity and strong robustness to parameter perturbations of the ship and environmental disturbances. Keywords: Ship course, Genetic algorithm, Active disturbance rejection controller.

1 Introduction Ship autopilot will navigate through the designed optimal course, saving lots of energy, time and manpower. Since 1920s, PID based autopilot, has been designed and used in the field of ship course control. In 1970s, some modern control methods, such as the self-adaptive control, are introduced to ship course control. However, the traditional PID controller is so sensitive to high frequency disturbance that it will cause steering operation frequently, lacking sufficient adaptability to dynamic condition of ship and sea. Furthermore, the self-adaptive steer, with a high cost and the difficulty of parameters regulating, in addition to ship's nonlinearity, can't make sure that there will be a good control effect.This paper design a new type of ship course controller using genetic algorithm ADRC technique and simulation study indicate that it achieves good results when parameter perturbations of the ship and environmental disturbances.

2 Ship Steering Model and Disturbance Model 2.1 Ship Motion Mathematical Model and Rudder Model Ship motion can be described by state space model and input-output model. The former description can handle the problem of ship multi-parameter and has accurate S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 476–481, 2011. © Springer-Verlag Berlin Heidelberg 2011

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reflection of the wind, wave disturbances, but its calculation is very complex. The latter is called responding ship model method. The method, having eliminated the transverse excursion, is mainly based on the ship dynamic condition-the relation of δ → ψ → ψ . However, the differential equation can still include the nonlinear disturbances and even can reflect the wind and wave disturbance as an equivalent rudder angle δ d which together with rudder angle δ is taken into the ship model. The linear Nomoto responding ship model is: Tψ + ψ = K δ . Ship course motion is essentially nonlinear, whose model parameters are perturbed with changes of water depth, navigation speed, loading weight and also wind and wave disturbances. Besides, auto-rudder is a dynamic system, which is restrained by the maximum rudder angle and the maximum rudder angular velocity. Taking all of the above into account, the ship course motion model is usually based on improved two-dimension Nomoto model which includes uncertain items. The model is described as follows:

⎧(T + ΔT )ψ + ( K + ΔK ) H (ψ ) = ( K + ΔK )(δ + δ d ) ⎪ H (ψ ) = (α + Δα )ψ + ( β + Δβ )ψ 3 ⎪ ⎪(T + ΔT )δ + δ = ( K + ΔK )δ E E c ⎨ E ⎪ δ ≤ δ max ⎪ ⎪⎩ δ ≤ δmax

(1)

Where, ψ,ψ : ship course angular acceleration (rad/s2) and angular velocity (rad/s). δ, δ : steering autopilot angular velocity (rad/s) and angle (rad).

δ c , δ d : steering autopilot control angle (rad) and disturbance equivalent angle (rad). T , ΔT , TE , ΔTE : ship time constant(s) and steering autopilot time constant(s) and their perturbation. K , ΔK , K E , ΔK E : ship course control gain (s-1) and rudder control gain (dimensionless) and their perturbation. α , Δα , β , Δβ : nonlinear coefficient and their perturbation (s2/rad2) . δ , δ : maximum rudder angular velocity (rad/s) and maximum rudder angle max

max

(rad). 2.2 Disturbance Model

There are different methods in different literatures, but in this paper, uniform stochastic wave disturbance is used only which is shown as follows:

ω = (4.58H 3 + 3.44 H 4 ) °

(2)

Where H3 and H4 are two independent pseudo-stochastic-variable which submit to uniform distribution U(0,1).

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3 Design of Genetic Algorithm ADRC Controller for Ship Course Tracking 3.1 The Ship Course ADRC Controller Design

The ultimate goal for designed the ship course controller is to maintain the course, so the servo mechanism and the ship course mathematical model can be considered as a whole, and thus greatly simplify the controller design, this design is shown in Fig.1, where ADRC. is the two-order.

ADRC

rudder

ship

Fig. 1. Single ring ship course controller based on ADRC

3.2 Design Design of Genetic Algorithm ADRC

The performance of the ADRC is heavily related with the selection of its parameters which is mainly confirmed by experiments. Large numbers of simulation research shows that ADRC controller can completely be designed by “separability” principle, namely to individually design TD, ESO and error feedback part and combine into complete ADRC. Among them, α 1 , α 2 , δ 1 , δ 2 , δ 01 , δ 02 are invariable parameter, and three parameter of ESO can be generate automatically, only k p and k d need be setting manually. So it is not convenient when actually operating and parameters change. Using the Genetic Algorithm control, a kind of method called Genetic Algorithm control is proposed. In this method, k p and k d can be adjusted automatically. In this paper, a Genetic Algorithm controller is designed, which can optimally approximate k p and k d automatically according to e1 and e2 . In this design, e1 and e2 are considered as input. The adaptive disturbance rejection parameters are modified on-line under the Genetic Algorithm control rules in order to satisfy the requirements of different time and improve the control performances of ADRC. With the analysis above, the structure of Genetic Algorithm ADRC designed is shown as Fig.2. For solving optimization problems by used genetic algorithms, the encoding schem genetic methods of operation and setting the fitness function are very important, because it is not only the judge criteria of individual's adaptive capacity, but also the optimal solution key to ensure the best individual optimization problem. Fitness function is closely related to the specific research question, it should not only reflect the essence of the problem under study, but also easy to compute.

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Genetic Algorithm kp kd v2 v1

ω

e2

-

e1

NLSEF

479

u0

- 1/b

-

u

Object

y

b z3 z2 z1

E S O

Fig. 2. Genetic Algorithm ADRC

1) Determination of optimal objective function According to optimization problem for the ADRC, for comprehensive evaluation about the dynamic performance, static performance of control systems (eg. response time, settling time, overshoot and steady-state error, etc.), and according to the minimum energy principle, this objective function is selected as the error absolute time integral performance index ITAE and the absolute value of the control volume, namely: t

J (e) = ∫ (τ | y (τ − v0 ) | + | u |) dτ

(3)

0

It’s reciprocal is fitness function. Optimal control parameters are the corresponding controller parameters when the fitness function is the largest. 2) Encoding and genetic manipulation Encoding: the individual coding forms use real number coding, so it avoid the trouble of common binary encoding and decoding. {k p , k d } are selected as the individual expression which is composed by ADRC parameters. Genetic manipulation: a simple single point crossover fashion. Variation use adaptive mutation way. When the fitness is high, the mutation rate reduce; When fitness is low, the mutation rate increase. The common proportion and the optimal retention policies are choosen. The implementation of the optimal retention policy can guarantee the optimal individual obtained so far will not be destroyed by cross and mutation, it cooperating with the other selection methods is an important guarantee of the optimal value.

4 Simulation Results Simulating experiment is carried out on a ship which nominal parameters of Nomoto ship non-linear motion model are : K=0.48s-1, T=216.58s, α=9.16s2/rad2, β=10814.30 s2/rad2, TE=2.5s, KE=1s-1; δmax = 0.052356 rad/s (3D /s) , δ max = 0.61082 rad (35D ) .

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The parameters of ADRC by tuning principle of the ADRC parameters are:

r =100, h =30, δ 01 =0.02, δ 02 =0.04, α1 =0.5, α 2 =0.25, δ1 =0.05, δ 2 =0.1, β01 =20,

β 02 =26, β 03 =28.

The scope of the optimization parameters are: k p =0.1~10,

k d =5~100. By genetic algorithms, the optimal parameters which are evolved after 16 generations are as follows: k p =1.7, k d =28.

Rudder Angle(°)

Set the periodic sample time as 0.1s, simulation time as 500s. Due to limited space, there are just some simulation results under typical conditions described in Fig.3-4. 10 5 0

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Fig. 3. Simulation results of expected course change from 4o to 8o (nominal parameters)

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Fig. 4. Simulation results of expected course 6o(rational spectrum method disturbance)

From which we can see that: 1) Both the dynamic accuracy (switching course) and static accuracy of course control (keeping course) are very high when course conversion angle is small. 2) In nominal model, the course response has a high accuracy and the auto-rudder response is very smooth with a small rudder turning volume. When disturbance is put, the auto-rudder response is frequent, but still smooth and very accurate. 3) Parameter's stochastic perturbation and control object's unmodeled dynamics almost have no much influence on auto-rudder and ship course response.

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5 Conclusion and Prospect This paper presents a design of the optimal ADRC for ship course non-linear control. Simulation results show that this controller appears to be strictly robust to the nonlinear characteristic of the ship, and the parameters perturbation, system disturbances, and the system uncertainty, such as unmodeled dynamics. The process of course switching is fast and smooth, and the rudder operation is keeping at a high precision and with very low energy consumption. So it works perfectly as a ship course controller. Acknowledgements. This work is supported by Natural Science Foundation of Shandong Province (Project Number: 2009ZRB019B2), Natural Science Foundation of Shandong Province (Project Number: ZR2009FL013), Natural Science Foundation of Shandong Province (Project Number: ZR2010FL014), Shandong Jiaotong College Research and Innovation Teams.

References 1. Han, J.Q.: From PID technique to active disturbance rejection control technique. Control Engineering of China 9(3), 13–18 (2002) 2. Han, J.Q.: Auto disturbances rejection control technique. Frontier Science 1, 24–31 (2007) 3. Zhao, X.R., Zheng, Y., Hou, Y.H.: The rational spectrum modeling of the ocean wave and its simulation method. Journal of System Simulation 4(2), 33–39 (1992) 4. Hu, Y.H., Jia, X.L.: Theory and Application of Predictive Control of Ships Subject to State Constraints. Control and Decision 17(4), 542–547 (2000) 5. Zhou, Y.B., Pan, W.G., Xiao, H.R.: Design of Ship Course Controller Based on Fuzzy Adaptive Active Disturbance Rejection Technique. In: 2010 International Conference on Automation and Logistics, vol. 1, pp. 232–236 (2010)

A CD-ROM Management Device with Free Storage, Automatic Disk Check Functions Daohe Chen1,2, Xiaohong Wang1,3, and Wenze Li1,2 1 Science and Technology Projects in Guangdong Province Department of Computer Science and Information Management, Shengda Economics Trade & Management College of Zhengzhou, Zhengzhou, China [email protected] 2 College of Automation Science and Technology, South China University of Technology, Guangzhou, China [email protected] 2

Abstract. With the development of information resources, there are more and more CD-ROM resources. The traditional disc management, storage and search methods can not meet the current requirements of the fast-paced CD-ROM management infomationization and standardization. Based on the demand, we studied a distributed intelligence disc management system with random access, fuzzy search and automatic pop-up functions. Keywords: intelligence disc management system, random access, fuzzy search, automatic pop-up.

0 Introduction With the development of information resources, there are more and more CD-ROM resources in libraries, archives, television stations, radio stations, hospitals, schools, military units, enterprises and institutions. A large number of discs need to use special storage systems. The original manually manage and storage search methods by number in CD case / box / drawer / cabinet can not meet the current requirements of the fast-paced CD-ROM management infomationization and standardization. Therefore, designing an intelligent CD-ROM management device is increasingly becoming a pressing need.

1 The Overall Structure of CD-ROM Management Device The system consists of two parts, the first is to design disc storage mechanism to achieve free CD-ROM disc storage and automatic access functions; second part is the disc's information management and sharing system.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 482–488, 2011. © Springer-Verlag Berlin Heidelberg 2011

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CD storage organization is divided into mechanical and electrical control part. Electrical control part can scan disc storage location, accurately locate stepper motor, and communicate with the outside world through the Internet. CD information management system mainly to complete the disc information collection, editing, publishing, and so on. The system holds the conventional CD-ROM information, but also scans and stores the discs directory structure information, provides users with the fuzzy find function of the directory and file header keywords. Another important part of the Information management system is network share. We can achieve the preview contents of the disc, scan the CD directory structure, upload CD information and share with others. Shown in figure 1.

Fig. 1. Overall structure of CD-ROM management device

2 Design of CD-ROM Management Hardware 2.1 Design of Mechanical Parts in Modular Unit Storage Structure Actually, the discs number of different users needs to storage and manage are great different. Starting from the universal, to design a program of convenient expansion is necessary. This device uses a modular unit storage structure to achieve. Each modular unit storage structure is mainly composed of axial motor, screw, dial, dial drive motor, rail and bracket components. Axial motor is stepper motor. It is connected with the screw. By controlling the stepper motor turn, the screw rotates in accordance with the direction of rotation, drive motor and dial dial to achieve axial movement. Then the dial can drive the motor and run in the axial movement. The dial drive motor (which is low power stepper motor) and the dial taken together make up the check disk body. When it arrived at the designated location, it would drive the dial to release the disc through the dial drive motor. Why the axial motor and the dial drive motor using stepper motors? Compared to DC motors and AC motor, the stepper, the biggest advantage is that the stepper motor control is simple. In the case of not losing steps, it can be used for open-loop control. In the case of a short trip ,it is with high accuracy. Using stepper motor control is not only simple but also can avoid the more

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complicated position detection device, such as rotary transformers, inductosyn, grating, etc., simplifying the system, so greatly reduces the interference of other electrical systems. CD storage grid is designed with "W". The dial just need to push the disc from the storage stowed position to the taken disc stowed position. In order to reduce the load screw, dial drive motor and dial stuck in a rail through the bracket. Rail ends are bracket fixed. Axial motor and dial drive motor are controlled by the main control circuit. Shown in figure 2.

Fig. 2. Mechanical design of modular unit storage structure

2.2 The Detection Circuit Design of Random Deposition The disc management device specially designed the detection circuit of random deposition. When the user needs to deposit a disc, can choose an empty position at random according to the prompt light position. The circuit consists of two main parts: storage position detection and light. We use optical test tube to achieve storage position detection, which is installed at the entrance of each disc storage grid. When the optical test tube is blocked by disc, it will produce transitions to identify the stored position. The main control circuit can get optocoupler level signal through Parallel-in/ Serial-out Shift Register. The optical test tube uses the spatial arrangement of delta shape . This reduces the limitations that the launch tube and receiver tube thickness have for disc storage grid size. Indication lamp uses ultra bright LED. The main control circuit can control indication lamp through Serial-in/Parallel-out Shift Register, respectively. Shown in figure 3.

Fig. 3. Deposition detection circuit

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2.3 Hardware Structure of the Main Control Circuit From the perspective of actual use, the system uses two control program. The first one is distributed control unit which consists of embedded control system. They can either be a separate system, and can be combined with a general server into a network-based large-scale systems. The second one consists of the total servers, and can complete the information system management and external network communications. In order to achieve the stepper motor control, human-computer interaction, network communications in various functions, Availability and scalability from the start, the distributed control unit uses embedded computer, the industry PC of PC / 104 bus as the control center. PC104 single board computer can be used as the core processors and the bottom control panel communication, but also as a user interface, complete the Human–computer interaction, and communicate with the background master server through the network. PC104 single board computer uses compact stack connected structure which is suitable for embedded applications, with small, low power consumption, good seismic performance, high reliability and flexible configuration, etc., in the field of industrial control has been widely used. In the system design process, the stepper motor control is a key part. In program choice, we abandon the complex hardware design, but mainly focus on the interface circuit and control software design. In the interface circuit, we use CPLD (Complex Pro-grammableLogic Device) as the key device. The computer connects interface circuit through PC104 standard interfaces. The interface board consists of CPLD and peripheral circuits necessary. It can receive action command send by CPU , and convert these instructions into a corresponding pulse, direction signals, direct stepper motor movement through stepper motor driver. At the same time, it receives the signal from the field, and send part of the signal to the CPU, complete control of the whole system. Here, Altera Corporation EPM7128 using the CPLD, developing software using the MAX + plus . Shown in figure 4.

Ⅱ

Fig. 4. Control unit structure

The control of the system uses software and hardware combination. The computer only to send pulses and pulse direction instruction to the interface circuit. Software takes very little storage unit. Program development is no time limit , computer can perform other tasks freely between each step of the motor to achieve more motion control of stepper motor. As the core of the interface circuit, pulse generating circuit shown in Figure 5. The circuit consists of the data latch circuits, counters, data comparators and necessary logic circuit. “Pulse input” in figure is continuous pulse signal send by pulse source. It is

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controlled by the "start " signal and "send end " signal, that is only when the "start" signal starts, and the pulse "send end " signal is invalid (for 1), pulse signal send by pulse resource can enter the counter and output to the stepper motor drive.

Fig. 5. Pulse circuit

Pulse send flow chart shown in Figure 6. First, the CPU send clear signal to the counter, through the expansion port of the CPLD. Then send the data latch again the number of pulses planned in advance. After the data latch, the latch output showing the number of pulses in hexadecimal. For data comparison of two data input device, the latch input is the number of pulses, and counter input zero, so the data is not equal to comparison. Data comparator ouput is zero, after negated, is sent to AND gate, and then send pulses "start" signal through the expansion port. In this case, pulse signal sent by the pulse source can send the pulse signal to pulse output port and counter pulse input port , through the AND gate. With pulse output, the counter starts counting. When the number of pulses is the same as the data in data latch, data comparator output is 1, after nagated, through the AND gate, the output pulse blockade, thus, the sending pulse process is over.

Fig. 6. Pulse flow

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When the CPU detects the end of the signal pulse, it can repeat the above process, the next pulse transmission. If it send a large number of pulses, it can send through multiple cycles, or add CPLD latches, counters, width of the data comparator to resolve.

Fig. 7. Block diagram of lifting-speed circuit

When the stepper motor start and stop with a higher frequency or speed of mutation, they will appear out of step or even the phenomenon of stepping motor can not start, so the program functions must have a lifting-speed. Many are mentioned in the literature on the lifting-speed curve, lifting-speed circuit block diagram shown in Figure 7. This part of the circuit consists of frequency divider, frequency synthesizer circuit, data latch, the data selector. After the crystal pulse signal passed through the frequency divider and pulse synthesis circuit, it will produce several frequency pulse signals. These pulse signals are sent to data selector data input port. CPU send the corresponding control signal to the data selector , through the data latch, then the output port will send pulses of different frequencies. The pulse signal, as a pulse source, is provided to the pulse circuit before. About process control, in pulse flow chart, only need to set the pulse frequency in any step before the “start” signal send signal.

3 Software Design of CD-ROM Management Device The main achievement of the information management system is disc information input, edit update, delete, and CD-ROM information network share. The system is mainly two parts - general view and system administrators. The management procedures is also divided into three parts: user management, admin and other management. User Management provides some of the major user registration, registration information changes, data browsing and query, data download. Back section includes system settings, data storage and modification, user management, announcement and the administrator password changes, student issues and message processing. Other management, including counting, statistics, user messages, user requests, provides and manages personal CD data. System use ASP + C #. net + SQL

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Server as development tool, taking into account the needs of actual use, the use of C / S (Client / Server) and B / S (Browser / Server) structure combined. Large amount of information data is to use C / S implementation, including the image file to upload and so on. Small amount of data is to use B / S implementation, such as add, modify, and delete the disc information, the user management. The distributed uni uses the Wince operating system, through writing low-level driver functions of ISA bus, to achieve the communication between the control unit and the lower control board. A small embedded database is installed on the Wince system, which with the total server composes of the network database structure, with the total server synchronization. When the server has modified the information, it can notify the distributed unit, to trigger a database update event.

4 Experimental Results The project has successfully developed a multi-layer disc management unit pilot prototype, realized accessing CD-ROM through the name of the disc, number, type, content , and other related information on webpage, using disc directory structure scanning functions to save disc directory structure information and automatically associate with the disc number. So as to solve the existing technology to save the information singularly, the shortcomings of low utilization of space. The modular structure is designed to achieve an unlimited level of the expansion, provides references for the design of similar products.

5 Conclusion With the increase in disc capacity, CD-ROM management will become more intelligent, humane. Future improvements will focus on network management, remote query and share information. The disc management will be more efficient, more convenient. Acknowledgment. This work was supported by Science and Technology Projects in Guangdong Province (2009B010900018).

References 1. Xia, M.: Research and Design of Library CD-ROM. SuZhou University (2002) 2. Zhen, T.: Analysis and Design of CD-ROM Electronic Records Management System Based on Disc Database. Xi’an University of Architecture Technology (2002) 3. Zha, Y.: CD-ROM Library File Cache Management System. Wu Han University (2004) 4. Xu, D.Y.: Principles of Disc Storage System. National Defence Industry Press (January 2000)

An Efficient Multiparty Quantum Secret Sharing with Pure Entangled Two Photon States* Run-hua Shi1,2 and Hong Zhong1,2 1

Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education, Anhui University, Hefei, 230039, China [email protected] 2 School of Computer Science and Technology, Anhui University, Hefei, 230039, China [email protected]

Abstract. We present an efficient multiparty quantum secret sharing scheme by using dense coding method. The implementation of this scheme only needs to utilize pure entangled two-photon pairs as quantum resources, where each pure entangled two-photon pair can carry more than one bit of classical information. Thus it obtains the higher efficiency than other schemes with pure entangled states. Keywords: quantum information, quantum cryptography, quantum secret sharing.

1 Introduction Secret sharing had been studied extensively in the classical setting and was extended to the quantum setting. The first quantum secret sharing (QSS) protocol was presented by Hillery, Bužek and Berthiaume [1] in 1999. Afterward, there were a lot of studies focused on QSS in both the theoretical [2-4] and experimental [5-6] aspects. At present, most QSS can only split a (classical or quantum) secret by quantum mechanics principles. Furthermore, these QSS can be divided into two categories: one only splits a classical secret and another shares a quantum secret (i.e., an arbitrary unknown quantum state). In this paper, we mainly focus on the former. To date, a lot of QSS schemes for sharing a classical secret have been proposed. According to the differences of using quantum resources, these QSS schemes can also be divided into three categories: QSS with single photons [7-10], QSS with the maximally entangled states [11-14] and QSS with the non-maximally entangled states (i.e., the pure entangled states) [15, 16]. For the first kind of QSS with single photons, the most difficult problem is to obtain the ideal single photons since requiring the high precision of the experimental equipments. For the second kind of QSS with the maximally entangled states, the generation and distribution of maximally entangled multi-particle states is a difficult task. For the third kind of QSS with the pure *

This work was supported by the Natural Science Foundation of Anhui Province (No. 11040606M141), Research Program of Anhui Province Education Department (No. KJ2010A009) and the 211 Project of Anhui University.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 489–495, 2011. © Springer-Verlag Berlin Heidelberg 2011

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entangled states, the advantage is easy to implement, but the drawback is the low efficiency. For example, each pure entangled states only carries one bit of classical information in References [15, 16]. In this paper, we will present an efficient multiparty quantum secret sharing scheme with pure entangled two-photon states. In our scheme, the sender takes the pure entangled two-qubit states as quantum resources, instead of the pure entangled three or multi-qubit states, which makes our scheme more convenient in a practical application than the scheme in Ref. [15], since the generation of the three or multiqubit states is more difficult than the two-qubit states. Especially, the total efficiency of our QSS scheme is higher than the existing third type of QSS schemes [15, 16].

2 Dense Coding with Pure Entangled Two-Photon States Dense coding was first proposed by Bennett and Wiesner in 1992 [17]. Utilizing entanglement properties, dense coding can transmit more than one bit of information by manipulating only one of the two particles in an entangled state. In this section, we present a dense coding method with pure entangled two-photon states, in which the receiver uses the projective measurement first and then applies the generalized measurement to order to discriminate the senders’ unitary operators with some probability. Suppose that the sender Alice and the receiver Bob each obtain one photon in a pure entangled two-photon state φ ab , where Alice owns the photon a and Bob keeps the photon b with him. Without loss of generality, we assume that the twophoton pair (a , b) is in the state:

φ

ab

= α 00

ab

+ β 11

ab

,

(1)

where α + β = 1 and α ≥ β . 2

2

Alice first applies any one of the four unitary operators {U 1 , U 2 , U 3 , U 4 } on the photon a and then sends the photon a to Bob, where

U1 = I = 0 0 + 1 1 , U 2 = σ z = 0 0 − 1 1 , U 3 = σ x = 0 1 + 1 0 , U 4 = iσ y = 0 1 − 1 0 .

(2)

After receiving the photon a from Alice, the state of Bob’s two-photon pair ( a, b ) is one of the following four cases: (I ⊗ I ) φ

ab

= α 00

ab

+ β 11

ab

= φ

(σ z ⊗ I ) φ

ab

= α 00

ab

− β 11

ab

= φ'

(

x

I)

ab

(i

y

I)

ab

10 10

ab

ab

01 01

ab

,

ab

,

ab ' ab

(3)

, ab ab

.

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Obviously, the above four states are not mutually orthogonal, so these states cannot be distinguished with certainty. But, they can be distinguished with some probability of success. In order to distinguish the four states, Bob first performs a projection onto the subspaces spanned by the basis states { 00 , 11 } and { 01 , 10 } with projection operators: P1 = 00 00 + 11 11 and P2 = 01 01 + 10 10 . It is obvious that P1 and P2 are mutually orthogonal, and there exist the following equations: ab

ϕ P1 ϕ

= 0,

ab

ab

ϕ ' P1 ϕ '

ab

=0,

ab

φ P2 φ

ab

=0,

ab

φ ' P2 φ '

ab

= 0.

(4)

That is, if Bob obtains P1 , then he knows that the state of the two-photon pair ( a, b ) will be either φ

ab

or φ '

ab

; if he gets P2 , the state will be either ϕ

ab

or ϕ '

ab

.

Without loss of generality, we assume that Bob obtains P1 . Thus, Bob knows that the state of the two-photon pair ( a, b ) will be either φ with certainty that the state is φ state is in φ

ab

or φ '

ab

ab

or φ '

ab

ab

or φ '

ab

, but he cannot know

. Furthermore, in order to known that the

, Bob performs a generalized measurement on his two-

photon entangled states with the corresponding POVM elements in the subspace { 00 , 11 }

M1 =

1 ⎛β2 ⎜ 2α 2 ⎜⎝ αβ

αβ ⎞ 1 ⎟ , M2 = 2α 2 α 2 ⎟⎠

⎛ β2 ⎜ ⎜ − αβ ⎝

β 2 ⎛ − αβ ⎞ ⎜1 − ( ) ⎟ , M = α 3 ⎜ α 2 ⎟⎠ 0 ⎝

⎞ 0⎟ . ⎟ 0⎠

(5)

3

Here ∑ M i = I . If Bob obtains M 1 then his two-photon state is φ i =1

ab

φ ' M1 φ '

ab

φ M2 φ

ab ab

= 0 ; if he gets M 2 then the state is

φ'

ab

ab

because of because of

= 0 . However, if he gets M 3 the state is completely indecisive and Bob

cannot obtain any information. Obviously, the success probability of distinguishing

φ

ab

and φ '

ab

is 2 β 2 [18]. Similarly, for the case of P2 one can show that the

success probability is also 2 β 2 . So, the average amount of information transmitted from Alice to Bob should be expressed as 1 + 1 × 2 β 2 = 1 + 2 β 2 . Thus, if Alice codes the four unitary operators U 1 , U 2 , U 3 and U 4 to 00, 01, 10 and 11, respectively, Bob will obtain the coding information is {00, 01} or {10, 11} with 100% probability by using the projection measurement, furthermore he will get the coding information is 00 (10) or 01 (11) with 2 β 2 probability of success by using the generalized measurement. Especially, he can distinguish two bits of coding information of Alice with 100% probability of success when α = β = 1 / 2 .

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3 Multiparty Quantum Secret Sharing with Pure Entangled Two-Photon States In this section, we will propose an efficient multiparty quantum secret sharing with pure entangled two-photon states by using the dense coding method above. We first consider three-party case. Suppose that there are three parties, say, Alice, Bob and Charlie, where Alice is the sender and Bob and Charlie are the two agents. Alice first prepares a pure entangled two-photon pair (h, t ) , which is in either

φ

ht

= α 00 + β 11 or ψ

= α 01 + β 10 , where α + β 2

ht

2

= 1 (suppose that

α ≥ β ). Then Alice holds the photon h in hand and sends the photon t to Bob. After receiving the photon t , Bob randomly chooses a unitary operation U i ( i = 1, 2, 3 or 4) and applies it on the photon t . Furthermore, Bob transmits the photon t to Charlie. After receiving the photon t , Charlie also does the same things as Bob, that is, he encodes his secret on the photon t by applying the unitary operation U i ( i = 1, 2, 3 or 4), and sends back the photon t to Alice. After receiving the photon t sent by Charlie, Alice performs the projective measurement and the generalized measurement described in the above section in order to distinguish the state of the entangled twophoton pair (h, t ) . By the measured outcomes of Alice, she can extract the secret information shared among all agents. That is, she can build a secret key shared among all agents. Now, let us describe the principle of our three-party QSS scheme in detail as follows: (1) Alice, Bob and Charlie first agree on that the four unitary operations U 1 , U 2 , U 3 and U 4 represent the two bits of information 00, 01, 10 and 11, respectively. (2) Alice prepares an ordered N photon pairs. Each photon pair ( h, t ) is randomly in one of the two pure entangled states φ ht or ψ ht ( φ ht = α 00 ht + β 11 ht and

ψ

ht

= α 01

ht

+ β 10

ht

). Then she divides the photons into two sequences:

[ P1 ( h ), P2 (h ),..., PN ( h )] and [ P1 (t ), P2 (t ),..., PN (t )] , which are denoted as S h and St , respectively. Furthermore, Alice prepares 3k ( k << N ) decoy photons by measuring the photons x in some pure photon pairs (x, y) and operating the remaining photons y with the two unitary operations U i ( i = 1,3 ) and the H operation as the references [15, 16], inserts randomly these decoy photons into the sequence St and makes a record of the insertion positions and the measurement basis of the decoy photons. (3) Alice sends the new sequence St (including N + 3k photons) to Bob over the quantum channel and retains the remaining sequence S h . Alice has to confirm that Bob has actually received the sequence St via classical communication. (4) After being notified that Bob has received the sequences St , Alice performs an eavesdropping check of this transmission: Alice announces the positions of k photons of all decoy photons and their corresponding measurement basis. Bob

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measures these decoy photons according to Alice’s announcements and tells Alice his measurement outcomes. Alice compares the measurement outcomes of Bob with the initial states of these decoy photons and analyzes the security of the transmissions. If the error rate is higher than the threshold determined by the channel noise, Alice cancels this protocol and restarts; or else they continue to the next step. (5) Bob randomly chooses one of the four local unitary operations U i ( i = 1,2,3,4 ) to encrypt each of the remaining photons in the sequence St , say U b , and then he sends the new sequence St (including N + 2k photons) to Charlie over the quantum channel. Alice has to confirm that Charlie has actually received the sequence St via classical communication. (6) After being notified that Charlie has received the sequences St , Alice performs an eavesdropping check of this transmission with the help of Bob. If the error rate is higher than the threshold determined by the channel noise, Alice cancels this protocol and restarts; or else they continue to the next step. (7) Charlie randomly chooses one of the four local unitary operations U i ( i = 1,2,3,4 ) to encrypt each of the remaining photons in the sequence St , say U c , and then sends back the new sequence St (including N + k photons) to Alice over the quantum channel. (8) After receiving the sequence St from Charlie, Alice performs an eavesdropping check of this transmission with the help of Bob and Charlie. If the error rate is higher than the threshold determined by the channel noise, Alice cancels this protocol and restarts; or else they continue to the next step. (9) Alice performs a projection measurement with the corresponding projection operations { P1 , P2 } first and then a generalized measurement with the corresponding POVM operations { M 1 , M 2 and M 3 } on the photon pair ( Pi (h ) , Pi (t ) ) in two sequences S h and St for i = 1,2,..., N , respectively. By the measured outcomes of each entangled-photon pair, Alice can infer one bit or two bits of coded information shared between Bob and Charlie. If he gets M 3 in the stage of performing the generalized measurements, Alice announces one bit of classical information ‘0’ to Bob and Charlie, which shows that only the first bit ~ ~ ~ ~ of U b ⊕ U c will be the sharing secret information, where U b and U c denote the coding information of the corresponding local unitary operations of Bob and Charlie, respectively; otherwise, Alice announces one bit of classical information ~ ~ ‘1’ to Bob and Charlie, which shows that the whole two bits of U b ⊕ U c will be the sharing secret information. Alice transforms her measured outcome sequences to the classical bit strings K A . By Alice’s announcements, Bob and Charlie can transforms their local unitary operation sequences to the classical bit strings K B and K C . In this three-party QSS scheme, Bob and Charlie can collaborate to infer the shared secret key of Alice since K A , K B and K C satisfy the relationship: K A = K B ⊕ K C ,

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where the average bit length of K A is N (1 + 2β 2 ) . The generalization of this threeparty QSS scheme to the case with n agents can be implemented in a simple way by modifying the processes in the case with two agents. We describe it after the step 5 discussed above. (6') Charlie randomly chooses one of the four local unitary operations U i ( i = 1,2,3,4 ) to encrypt each of the remaining photons in the sequence St , say U c , and then sends the sequence St to the next agent, Dick. (7') Then Alice and Dick complete the eavesdropping check of this transmission, same as that between Alice and Charlie. If the transmission is secure, Dick performs one of the four local unitary operations U i ( i = 1,2,3,4 ) to encrypt each of the remaining photons in the sequence St , say U d , and then sends the sequence St to the next agent. (8') After repeating the step 7` n − 2 times, the sequence St is received securely by Alice from the last agent, say Zach. Then Alice and Zach complete the eavesdropping check of this transmission. (9') After the eavesdropping check, Alice extracts the secret key K A by the same procedures in step 8 discussed above.

4 Discussion and Summary Like that in Ref. [16], our QSS protocol is secure against the intercept-resend attack and the collusion attack. Furthermore, the security of the proposed protocol still depends on the process for setting up the quantum channels. To set up the secure quantum channels, we use the decoy-photon technique as the references [15, 16]. In Addition, the total efficiency for QSS can be calculated as η t = bs /( qt + bt ) , where bs is the number of bits that consist of the secret information to be shared, qt is the number of qubits that is transmitted and used as the quantum channel (except for those chosen for security checking) and bt is the public classical bits. In our QSS scheme, bs = N (1 + 2 β 2 ) , q t = N and bt = N , so η t = (1 + 2 β 2 ) / 2 . However, in Zhou et al.’s scheme [15], bs = N , qt = mN and bt = 0 , so ηt = 1 / m , where m is the number of the agents ( m ≥ 2 ). It is obvious that the total efficiency of our QSS scheme is higher than their scheme. In summary, we have presented a secure multiparty quantum secret sharing scheme. The implementation of the scheme only needs to exploit the pure entangled two-photon pairs as quantum resources, where each photon transmitted can carry more than one bit of information by the dense coding method (the average amount of information is 1 + 2 β 2 bits). With the present techniques, the pure entangled twophoton pairs may be one of the optimal entangled quantum resources. Thus, we can deduce that this scheme is feasible.

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References 1. Hillery, M., Buzek, V., Berthiaume, A.: Quantum secret sharing. Phys. Rev. A 59(3), 11834–18229 (1999) 2. Cleve, R., Gottesman, D., Lo, H.K.: How to share a quantum secret. Phys. Rev. Lett. 83(3), 648–651 (1999) 3. Gottesman, D.: Theory of quantum secret sharing. Phys. Rev. A. 61(4), 042311(1-8) (2000) 4. Sudhir, K.S., Srikanth, R.: Generalized quantum secret sharing. Phys. Rev. A. 71(1), 012328(1-6) (2005) 5. Tittel, W., Zbinden, H., Gisin, N.: Experimental demonstration of quantum secret sharing. Phys. Rev. A 63(4), 042301(1-6) (2001) 6. Lance, A.M., Symul, T., Bowen, W.P., et al.: Tripartite quantum state sharing. Phys. Rev. Lett. 92(17), 177903(1-4) (2004) 7. Zhang, Z.J.: Multiparty quantum secret sharing of secure direct communication. Phys. Lett. A 34(1-2, 4), 60–66 (2005) 8. Zhang, Z.J., Li, Y., Man, Z.X.: Multiparty quantum secret sharing. Phys. Rev. A 71(4), 044301(1-4) (2005) 9. Deng, F.G., Zhou, H.Y., Long, G.L.: Bidirectional quantum secret sharing and secret splitting with polarized single photons. Phys. Lett. A 337(4-6), 329–334 (2005) 10. Wang, T.Y., Wen, Q.Y., Chen, X.B., et al.: An efficient and secure multiparty quantum secret sharing scheme based on single photons. Opt. Commun. 281(24), 6130–6134 (2008) 11. Zhang, Z.J., Man, Z.X.: Multiparty quantum secret sharing of classical messages based on entanglement swapping. Phys. Rev. A 72(2), 022303(1-4) (2005) 12. Deng, F.G., Long, G.L., Zhou, H.Y.: An efficient quantum secret sharing scheme with Einstein-Podolsky-Rosen pairs. Phys. Lett. A 340(1-4, 6), 43–50 (2005) 13. Deng, F.G., Li, X.H., Li, C.Y., et al.: Multiparty quantum secret splitting and quantum state sharing. Phys. Lett. A. 354(3), 190–195 (2006) 14. Shi, R.H., Huang, L.S., Yang, W., Zhong, H.: Quantum secret sharing between multiparty and multiparty with Bell states and Bell measurements. Sci. Chain Phys. Mech. Astron. 53, 2238–2244 (2010) 15. Zhou, P., Li, X.H., Liang, Y.J., et al.: Multiparty quantum secret sharing with pure entangled states and decoy photons. Physica A 381(15), 164–169 (2007) 16. Shi, R.H., Zhong, H.: Multiparty quantum secret sharring with the pure entangled twophoton states. Quantum Information Processing (2011), doi:10.1007/s11128-011-0239-9 17. Bennett, C.H., Wiesner, S.J.: Communication via one- and two-particle operators on Einstein-Podolsky-Rosen states. Phys. Rev. Lett. 69, 2881–2884 (1992) 18. Luo, C.L., Ouyang, X.F.: Controlled dense coding via generalized measurement. International Journal of Quantum Information 7(1), 365–372 (2009)

Problems and Countermeasures of Educational Informationization Construction in Colleges and Universities Jiaguo Luo1 and Jie Yu2 1

Faculty of Liberal Arts and Law, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China [email protected] 2 Faculty of Foreign Studies, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China [email protected]

Abstract. Setting up a digital, intelligentized and networking platform based on modern information technology is of great importance and will be beneficial to the building of learning community in which abounds in information and the students are available to the information and will be cultivated into creative talents. After the detail analysis of the technical characteristics and developing tendency of educational informationization, this paper puts forward some suggestions on the problems of the informationization construction. Keywords: higher education, educational modernization, informationization construction.

1 Introduction Promoting the educational modernization by the educational informationization and changing traditional education pattern by information technology have become the inevitable trend of education development. The standard of the educational informationization has become an important mark of national educational level.

2 The Promoting Effects of Educational Informationization on Educational Modernization 2.1 The Connotation of Educational Informationization Educational informationization, which refers to setting up a digital, intelligentized and networking platform based on modern information technology, is the process of promoting the development and reform of education with modern information technology deeply being used in educational domain. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 496–500, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2.2 The Technical Features of Educational Informationization (1) The Multimedia of the Teaching Content and the Intelligent Teaching Process By integrating text, figure, image and sound together, it deals with various kinds of media information and then makes the teaching content structural, dynamic and graphic. Meanwhile, the combination of IT and cognitive science bring about the automation of Computer Thinking and Mental Labor. For instance, through the intelligent teaching system, the students can study, review, and take stimulated test and self assessment test by Self Assessment Test. (2) The Network and Virtualization of Information Transmission It makes the information transmission based on the NET and virtualization, connecting the global educational resources as a whole for the large number of learners. Meanwhile, the virtual world made by computer simulation set up a new teaching pattern for net teaching, distance learning, and virtual laboratory. The learners perceive the objective world and acquire the relative skill through Virtual Reality. (3) The Digitalization of the Learning Resources and the Variety of the Teaching Pattern Reforms The digitalization of the information processing and transmission enables the net collect a plenty of teaching resources, such as Multimedia Resources Database, Library Information Database, Dynamic Comprehensive Information Database and etc. Learners can choose relevant learning resources according to the different conditions, purposes and phases, breaking the limitation of time, spaces and the teaching management of the traditional Class Education System. It will promote a mass, global and lifelong education.

3 Problems and Countermeasures of Information Technology Construction for Higher Education 3.1 Educational Information Technology Construction Focusing on Quality-Developed Education (1) Establish Curricula System Adapting to Information Economy Society Curricula compose an implementation blueprint for the construction of training objectives, which would be the most important basis for carrying out quality-developed education. Therefore, the construction of educational informationization should focus on the reform of curricula to establish a curricula system for quality-developed education adapting to the information economy society. (2) Construct Educational Informationization Conducive to Reform of Personnel Training Modes. Quality-developed education aims to guiding students to change from their traditional passive receiving, understanding and grasping of knowledge to initiative acquiring, processing and applying knowledge by making full use of information networks for their exploration of knowledge along with increasingly stronger self-learning capability. Therefore, during the construction process of educational informationization, it should be strongly strengthened to train students from learning Internet knowledge into the grasping of their learning capability through Internet while teaching functions of a school should be expanded into being

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an open learning community so that the new personnel training modes of lifelong learning, learning organization, etc., can be formed under the circumstances of educational informationization. 3.2 Campus Network in Close Connection with Teaching to Highlight Various Characteristics 3.2.1 Functions of Campus Network Curricula (1) Regarding the functions of campus network curricula, it should pay attention to interactive features and the creation of learning circumstances. Although, in respect to the functions of campus network, there are basically sectors of teaching, research, management, information exchange and distance teaching & learning. Nevertheless, most of the existing functions of campus networked would be presented with more in information exchange and management (some of the fast developed schools have realized their OA office automation). Therefore, much of the benefits of their teaching capabilities have not yet been maximized, especially in their network curricula. Network multimedia curricula can be applied to sharing resources of equipment, teachers, and research & development conditions. Therefore, while establishing the functions of campus network curricula, it should pay attention to interactive features and the creation of learning environmental circumstances so that, when satisfying the basic requirements of the traditional curricula, teaching objectives, a complete system of knowledge can be clearly reflected, students can be guided to consciously and effectively conduct their operations and exercises while reasonably assessing their self-learning results. Besides, network curricula should be presented while reflecting the “learning” as the core by stressing students’ independent learning and designing as well as inspiration and mobilization of their learning motivation. (2) Campus Network Curricula Playing an Important Role in School’s Teaching System. Based on some certain educational purposes, network curricula should be a combined sum demonstrating some content and implementing the related teaching activities through the Internet. At present, the campus network curricula is spread basically using face to face oriented mode which is an education dissemination form carried out under a school’s educational circumstances based on the campus platform applying teacher-led instruction supplemented by network curricula, whose goal aims at students’ systematic learning of curricula knowledge. It is precisely because it is a supplement to classroom teaching, colleges and universities, on the one hand, generally put not enough importance to campus network curricula and; on the other hand, most of them can only provide theoretical study or practical simulation currently, which can not be a substitute for experiment, practice and other practical aspects. Therefore, we believe that, during the construction of higher educational network, the curricula network platform should be enhanced to play its role in the construction of campus network. (3) The campus curricula network should be constructed in a combination along with the construction of campus network, the quality courses and the item pool. Due to the status that currently both the computer multimedia technology and network technology are very mature already, it is entirely achievable that, based on the integrated use of B/S-modeled Web application development technology, JavaSeript, vbSript, ASP and other technologies, the establishment of campus network, the

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construction of quality courses, multimedia curricula and item pool can be constructed in a combination base. In this way, it can not only solve the problems regarding the fragmented nature of separate functional modules, the disintegrated application and disunion interfaces, but also significantly save the construction cost of educational informationization. Currently, a number of principal universities which are featured by richer financial resources and stronger scientific R & D strength have mostly developed their campus information platform subject to their own actual circumstances while some of the weaker institutions would generally purchase from software companies, which have often resulted in the disjoint between their development party and user and hence increasing their cost later on. Therefore, we recommend these schools to have strategic cooperation with some companies, by which their original separate functional modules can be fully integrated to achieve a comprehensive upgrade of their campus network, such as constructing their campus one-card-through by mutual benefit cooperation with some banks or some companies. Besides, a united campus network construction can be implemented in relation to multiple universities to reduce cost, to improve resource utilization, and to achieve resource sharing among university communities. 3.2.2 Constructing Campus Network by Considering Both Future and Real Circumstances and being Implemented in Phases or Blocks (1) Establish information centers, digital libraries and multimedia information database; (2) Build an electronic classrooms, electronic lesson-preparation rooms and educational teaching resource pools in every school; (3) Construct office automation, distance teaching & learning and external access (Establishing close combination of regional education networks and campus network) and so on. 3.2.3 Highlighting Every University's Own Characteristics, in Particular to Be Constructed Along with the Campus E-commerce Network Along with the increasing growth of information network technology, campus network construction becomes mature and the campus e-commerce activities have become pretty natural rising in the campus, which has increasingly shown its charm since it has promoted the campus network construction and provided enriched and convenient service to campus life of students and teachers, thus enhancing the understanding capability of students majored in business, economics and management. Therefore, utilizing the existing conditions to accelerate the development of campus e-commerce, promote the construction of e-learning platform, and create learning atmosphere for developing e-business talent has become the key research subject of digital campus construction. 3.3 The Fund and Management Problems of Information Construction (1) Strive for financial support from higher levels and receive donations from social communities to increase funds used. Colleges and universities can set up resourcesearching groups responsible for collecting all kinds of outstanding teaching materials

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available from the market according to teaching needs. For example, regular contracts can be signed with Internet companies, such as Teaching Resources Networks of Chinese Universities and others of such kind to buy network teaching materials and resources. (2) Virtuous cycles of educational cooperation can be created with enterprises, educational institutions and financial institutions, such as mirror-image using some Internet’s high level and high-quality educational resource libraries to establish all or part of images so as to obtain newer and more specialized resources and links. A school’s WWW server and a number of Internet’s free educational teaching resources sites can be linked to directly achieve sharing of teaching resources. (3)Try to Gain the Non-stated Donation and Achieve the Replacement of the Equipment with the Manufacturers

4 Conclusion The Process of educational informationization is that of continuous application of informational science, in which a lot of problems and phenomena will necessarily occurs and leave us to recognize and solve which will in hence promote the development of the educational informationization theories.

References [1] Cai, Y.: The Connotation of the Concept of Educational Informationization: from a Perspective of Sociology. Journal of Educational Science of Hunan Normal University 4(1), 18–22 (2005) [2] Lu, P., Ge, N., Liu, Q.: The Gateway to the Future of China—the Process of Informationization in China. Nan Jing University Press, Nan Jing (1998) [3] Wang, H., et al.: The Modern Distant Learning which Adapting to the Knowledge Economy. Higher Education Research (5) (1999) [4] Fu, D.: The Purpose, Content and Significance of Educational Informationization. The Study of Educational Technology (4) (2000) [5] Luo, J., Yang, J., et al.: Construct the Platform of Campus Network Course and Accelerate the Construction of Course. Heilongjiang Researches on Higher Education (10), 146–147 (2006) [6] Zhang, B., Luo, J.: The study of Multimedia Courseware Resource Database Based on the Campus Network. Journal of Jiangxi University of Science and Technology (3), 36–38 (2007) [7] Luo, J., Yang, J., et al.: Several Problems in the Network Construction of Campus Electronic Commerce. Market Modernization, 11-3518/TS (20), 122–123 (2006) [8] Chen, F.: Introduction Remarks on the Socialization of Technology—a Sociology Study of Technology. Renmin University of China Press, Peking (1995)

Synthesis and Characterization of Eco-friendly Composite: Poly(Ethylene Glycol)-Grafted Expanded Graphite/Polyaniline Mincong Zhu1, Xin Qing1, Kanzhu Li1, Wei Qi1, Ruijing Su1, Jun Xiao2, Qianqian Zhang2, Dengxin Li1,*, Yingchen Zhang1,2,3, and Ailian Liu3 1

College of Environmental Science and Engineering, Donghua University, Shanghai 201620, P.R. China 2 College of Textiles, Zhongyuan University of Technology, Henan 450007, P.R. China 3 Langsha Holding Group Co., LTD, Zhejiang 322000, P.R. China [email protected], [email protected]

Abstract. In this paper, synthesis and characterization of poly(ethylene glycol)grafted expanded graphite/polyaniline (PEG-grafted EG/PANi) as a novel ecofriendly composite material was reported. EG as substrate prepared from expandable graphite was firstly synthesized by in-situ polymerization at the presence of aniline (An) to obtain EG/PANi, and then graft polymerization with as-prepared PEG-grafted PANi (PEG-g-PANi) composite under no tough conditions. Structural characteristics of the products were evaluated by infrared spectrum (IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. The experimental results have shown that the product of PEGgrafted EG/PANi composite were synthesized by facile method. Keywords: expanded graphite, PANi, PEG, EG/PANi, PEG-g-PANi, PEGgrafted EG/PANi, eco-friendly composite.

1 Introduction Expanded graphite (EG), a kind of modified graphite contains abundant multi nanoand micro-pore structure, is an important raw material for the production of flexible graphite sheets, which have been widely used as gaskets, thermal insulators, fireresistant composites, etc.[1-3] EG keeps a layered structure similar to natural graphite flakes but with larger interlayer spacing, and has a higher specific surface area than carbon powder and carbon nanotubes.[4,5] Therefore EG nanosheets can easily grafted the polymer on the surface. Polyaniline (PANi) is a well-known and preferred conducting polymer, its synthesis route is straightforward since it simply involves only one step of oxidation of aniline (An), and most of all, its monomer is quite inexpensive. Due to its easy synthesis, environmental stability and simple doping/dedoping chemistry, PANi has been subjected to extensive use in most commercial application such as lightweight *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 501–506, 2011. © Springer-Verlag Berlin Heidelberg 2011

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battery electrodes, sensors, electromagnetic shielding devices, and anticorrosion coatings.[6,7] Polyethylene glycol, a synthesized long-chain flexible macromolecule, are both hydrophilic and hydrophobic, their dual nature leads to numerous and various interactions with very different components, which have been demonstrated to be an outstanding material on the basis of intermolecular associations aimed at either stabilizing structures in soft materials or strengthening fragile ones.[8] In the present work, we report on the synthesis and characterization of PEG-grafted EG/PANi composite under no tough conditions.

2 Experimental 2.1 Materials and Reagents Commercially available expandable graphite was purchased from Qingdao Nanshu Hongda Graphite Co., Ltd. Dodecylbenzenesulfonic acid (DBSA) was bought from TCI (Shanghai) Development CO., Ltd (China) and isophorone diisocyanate (IPDI) was obtained from Shanghai Spring Chemical Technology Co., Ltd (China). Another reagents used, such as aniline (An), ammonium persulfate (APS), NaOH, HCl, N, Ndimethylform amide (DMF), thionyl chloride (SOCl2), tetrabutyl ammonium bromide (TBAB), 4-aminophenol and polyethylene glycol (PEG) with molecular weight (MW = 1000) were all of analytical grade and bought from Sinopharm Chemical Reagent Company (Shanghai, China). All reagents were used without any further purification and all solutions were prepared with distilled water. 2.2 Synthesis of PEG-Grafted EG/PANi Composite Firstly, EG was prepared in our laboratory after microwave irradiation treatment of the commercial expandable graphite at 1000 W for 60 s in a EM-3011EB1 microwave oven (Sanyo Inc., China) according to the method reported by B. Tryba et al [9]. Secondly, in the previous work [10], EG/PANi composite with the mass ratio of EG/An (mEG/An)=1.0 was synthesized according to the method reported by C. Xiang et al [11]. Thirdly, synthetic method used to prepare PEG-grafted PANi in our laboratory is based on, but modified from the reported method by P. Wang and K.L. Tan [12]. Thus, 50 g PEG-1000, 0.6 mL DMF and 8 mL SOCl2 were mixed and added into the bottom flask. The reaction was carried out in water-bath for 6 h at 80 ℃. Then, 16 g NaOH, 11 g 4-aminophenol and 0.54 g TBAB were mixed and poured into the upper mixture. The slurry reaction mixture was carried out in water-bath for 48 h at 60 ℃. The product marked PEG-g-PANi was filtered, washed with distilled water, and dried under vacuum. The PEG-g-PANi was dissolved into 1 M HCl solution. The mixture solution was mark HCl/PEG-g-PANi. Finally, 1.0 g EG/PANi, 60 mL HCl /PEG-g-PANi solution, 60 mL An-HCl (0.01 mol An dissolving with 1 M HCl solution) was mixed and placed into beaker with an ice-bath at 0 ℃. The mixture was kept by mechanical raking for 1 h. Subsequently, 60 mL APS solution was dropwise added into the emulsion. The reaction mixture was carried out in an ice-bath for another 72 h at 0 ℃. The suspension was filtered, washed with distilled water, and dried under vacuum. Then, the resultant product was obtained and marked as mark PEG-grafted EG/PANi composite.

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2.3 Characterization Infrared spectra (IR) were recorded on a Tensor 27 infrared spectrophotometer (Bruker Inc., Germany) over the wave number range from 4000 to 500 cm-1. Samples were prepared as KBr pellet. The studies on the crystal structure of products were carried out using a D/max–2550PC X-ray diffractometer (Rigaku Inc., Japan) with Cu anode (Cu/K-alpha1 radiation λ= 1.54056Å) in the range of 20o ≤ 2θ ≤ 80o at 40 kV. Scanning electron micrographs of products were obtained using a JSM-5600LV scanning electron microscopy (JEOL Inc., Japan).

3 Results and Discussion 3.1 IR Spectra Fig. 1 shows the IR spectra of (a) EG and (b) EG/PANi ((mEG/An)=1.0), (c) EG-gPEG, (d) PEG-grafted EG/PANi. The IR spectrum in Fig. 1a and Fig. 1c show that the same broad absorption peak at 3448.6 cm-1 is of hydrogen bonded O-H stretching vibration. After in-situ polymerization of PANi, the new peaks appeared in spectra. Fig. 1b shows the spectra of EG/PANi in which the news peaks appeared at a lower wave number side in between 500 and 1000 cm-1. The peak at 3498.7 cm-1 is attributed to O-H stretching vibration. The PANi gave absorption bands at 1573.8, 1386.7, 1186.1, 1124.4, 1070.4 and 1008.7 cm-1, as shown in Fig. 1b. There were some peaks which appeared both in the spectra of PEG-grafted EG (Fig. 1c) and PEG-grafted EG/PANi (Fig. 1d): the broad peak at 3448.6 cm-1 was attributed to O-H bond; the peak at 2925.9 cm-1 corresponded to saturated C-H stretching absorption; the absorption at 1451.2 cm-1 was attributed to the vibration absorption of CH2 group in PEG.

Fig. 1. IR spectra for products: (a) EG and (b) EG/PANi ((mEG/An)=1.0), (c) EG-g-PEG, (d) PEG-grafted EG/PANi

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3.2 XRD Analysis The XRD patterns of (a) EG and (b) EG/PANi ((mEG/An)=1.0), (c) EG-g-PEG, (d) PEG-grafted EG/PANi are shown in Fig. 2, respectively. As shown in Fig. 2a, all the patterns can be easily indexed as graphite materials, which is in good agreement with the literature value (JCPDS Card number 75-2078). Fig. 2b shows the diffraction patterns of as-prepared EG/PANi composite, in which there is one diffraction peak of located at 18.78º. Fig. 2c shows the diffraction patterns of as-prepared PEG-g-EG composite, in which there is one diffraction peak of located at 21.08º, and there is a broad band centered at 2θ = 14 24 , which reveal the sample are partially crystallized.

－ ℃

Fig. 2. X-ray diffraction patterns of products: (a) EG, (b) EG/PANi ((mEG/An)=1.0), (c) EG-gPEG, (d) PEG-grafted EG/PANi

3.3 Morphology Observation Fig. 3 shows SEM images of (a) EG and (b) EG/PANi ((mEG/An)=1.0), (c) EG-g-PEG and (d) PEG-grafted EG/PANi. The micrographs depicting the EG, as shown in Fig. 3a, revealed that in graphite flakes interlayer spacing is separated by increased distance and leads into highly porous structure and high surface area. PANi is not only grafted on the surface, but also in the interspace of EG. As shown in Fig. 3b, significant changes in morphology are seen in the EG/PANi composite synthesized by in-situ polymerization. PANi are absorbed into the pores of EG which gives the composites without distinguishing individual phase. As shown in Fig. 3c, PEG is not only grafted on the surface, but also in the interspace of EG. As shown in Fig. 3d, the PEG-grafted EG composite showed a good dispersion, which indicated that PEG chains could reduce Van der Waals force between composite flakes.

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Fig. 3. SEM images of products: (a) EG×50.0k, (b) EG/PANi ((mEG/An)=1.0)×50.0k, (c) EG-gPEG×50.0k, (d) PEG-grafted EG/PANi×5.0k

4 Conclusions In this work, EG was modified by the in-situ polymerization with the presence of An to prepare the EG/PANi composite. Subsequently, EG/PANi composite was graft polymerization with the as-prepared PEG-g-PANi under routine conditions. The SEM, IR and XRD observation well demonstrated that the surface of EG flakes was successfully modified by both PANI and PEG-g-PANi. PEG-grafted EG/PANi composite was prepared successfully. Acknowledgement. This work was supported by Innovation Foundation of Donghua University for Doctoral Candidates (BC20101217) and Shanghai Leading Academic Discipline Project (B604). The financial support of the China Postdoctoral Science Foundation (20100480569) and the Postdoctoral Science Foundation of Langsha are also gratefully acknowledged.

References 1. Chung, D.D.L.: Exfoliation of graphite. J. Mater. Sci. 22, 4190–4198 (1987) 2. Furdin, G.: Exfoliation process and elaboration of new carbonaceous materials. Fuel 77, 479–485 (1998)

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3. Inagaki, M., Tashiro, R., Washino, Y., Toyoda, M.: Exfoliation process of graphite via intercalation compounds with sulfuric acid. J. Phys. Chem. Solids 65, 133–137 (2004) 4. Celzard, A., Mareche, J.F., Furdin, G., Puricelli, S.: Electrical conductivity of anisotropic expanded graphite-based monoliths. J. Phys. D Appl. Phys. 33, 3094–3101 (2000) 5. Chen, G.H., Weng, W.G., Wu, D.J., Wu, C.L.: PMMA/graphite nanosheets composite and its conducting properties. Eur. Polym. J. 39, 2329–2335 (2003) 6. Shimano, J.Y., MacDiarmid, A.G.: Polyaniline, a dynamic block copolymer: key to attaining its intrinsic conductivity. Synth. Met. 123, 251–262 (2001) 7. Ahmad, R., Kumar, R.: Conducting Polyaniline/Iron Oxide Composite: A Novel Adsorbent for the Removal of Amido Black 10B. J. Chem. Eng. Data 55(9), 3489–3493 (2010) 8. Chawla, K., Lee, S., Lee, B.P., Dalsin, J.L., Messersmith, P.B., Spencer, N.D.: A novel low-friction surface for biomedical applications: Modification of poly(dimethylsiloxane) (PDMS) with polyethylene glycol(PEG)-DOPA-lysine. J. Biomed. Mater. Res. 90, 742– 749 (2008) 9. Tryba, B., Morawski, A.W., Inagaki, M.: Preparation of exfoliated graphite by microwave irradiation. Carbon 43, 2417–2419 (2005) 10. Zhu, M.C., Qi, W., Mao, Y.J., Hu, Y., Qing, X., Li, K.Z., Yang, T., Zhang, Y.C., Li, D.X., Chai, H.M.: Synthesis, characterization and adsorption property of expanded graphiteconducting polymer composite. Accepted by Adv. Mater. Res. (2011) 11. Xiang, C., Li, L.C., Jin, S.Y., Zhang, B.Q., Qian, H.S., Tong, G.X.: Expanded graphite/polyaniline electrical conducting composites_ Synthesis, conductive and dielectric properties. Mater. Lett. 64, 1313–1315 (2010) 12. Wang, P., Tan, K.L.: Synthesis and Characterization of Poly(ethylene glycol)-Grafted Polyaniline. Chem. Mater. 13(2), 581–587 (2001)

The Features of a Sort of Five-Variant Wavelet Packet Bases in Sobolev Space* Yujuan Hu1, Qingjiang Chen2,**, and Lang Zhao2 1

School of Education, Nanyang Institute of Technology, Nanyang 473000, P.R. China [email protected] 2 School of Science, Xi'an University of Architecture and Technology, Xi'an 710055, China [email protected]

Abstract. Wavelet packets have been the focus of active research for twenty years, both in theory and applications. In this work, the notion of orthogonal nonseparable five-variantl wavelet packets is introduced. A new approach for de-signing them is presented by iteration method. We proved that the fivevariant wavelet packets are of the orthogonality trait. We give three orthogonality formulas regarding the wavelet packets. We show how to construct nonseparable five-variant wavelet packet bases. The orthogonal fivedimensional wavelet packets may have arbitrayily high regularities. Keywords: Nonseparable, five-variant wavelet packets, Sobolev space, iterative method, bracket product, time-frequency representions.

1 Introduction The concept of wavelet packets have received much research attention and evidence has shown that they can be used to improve the localization of the frequency field of wavelet bases. Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. The main feature of the wavelet transform is to hierarchically decompose general functions, as a signal or a process, into a set of approximation functions with different scales. Wavelet packets[1], owing to their good properties, have attracted considerable attention. They can be widely applied in science and engineering [2,3]. Coifman R. R. and Meyer Y. firstly introduced the notion for orthogonal wavelet packets. Chui C K. and Li Chun [4] generalized the concept of orthogonal wavelet packets to the case of nonorthogonal wavelet packets so that wavelet packets can be employed in the case of the spline wavelets and so on. The introduction for biorthogonal wavelet packs attributes *

Foundation item: The research is supported by the Natural Science Foundation of Shaanxi Province (Grant No: 2009J M1002), and by the Science Research Foundation of Education Department of Shaanxi Provincial Government (Grant No:11JK0468). ** Corresponding author. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 507–512, 2011. © Springer-Verlag Berlin Heidelberg 2011

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to Cohen and Daubechies [5]. The introduction for the notion of nontensor product wavelet packets attributes to Shen [6]. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. The classical method for constructing multivariate wavelets is obtained by means of the tensor product of some univariate wavelets. But, there exist a lot of obvious defects in this method, such as, scarcity of designing freedom. The objective of this paper is to generalize the concept of univariate orthogonal wavelet packets to orthogonal five-variate wavelet packets.

2 Notations and Preliminaries We start from the following notations. Z and N stand for integers and nonnegative n integers, respectively. Let R be the set of all real numbers. R denotes the n 2 n dimensional Euclidean space. By L (R ), we denote the square integrable function n n , vn ), ϖ = (ω1 , ω2 , space on R . Set x = ( x1 , x2 , , xn ) ∈ R , v = (v1 , v2 , , ωn ), zι = e− iωι 2 , where ι = 1, 2, , n and n ∈ N , n ≥ 2 . The inner product 2 n for arbitrary g ( x ), ϕ ( x ) ∈ L (R ) and the Fourier transform of ϕ ( x ) are defined as, respectively

g , ϕ := ∫ n g ( x ) ϕ ( x) dx , ϕ (ω ) := ∫ n ϕ ( x) e −ix⋅ω dx , R

R

where ω ⋅ x = ω1 x1 + ω2 x2 + + ωn xn and ϕ ( x) denotes the conjugate of ϕ ( x ) . The space H λ ( R n ) is a Hilbert space equipped with the inner product given by h, ϕ

H λ ( Rn )

:=

1 (2π )

n

∫

2λ

Rn

h(ω ) ϕ (ω ) (1+ | ω | ) d ω , h, ϕ ∈ L ( R ). 2

The bracket product of compactly supported functions g ( x ), ϕ ( x ) ∈ L (R 2

n

n

)

(1)

is given by

[ g , ϕ ](ω ) := ∑ u∈Z n g , ϕ (⋅ − u ) e − iuω = ∑ u∈Z n g (ω + 2uπ )ϕ (ω + 2uπ ) .

(2)

We are interested in wavelet bases for the Sobolev space H λ ( R n ) , where λ is a positive integer. In this case, we obtain h, ϕ

H λ ( Rn )

= h, ϕ + h( λ ) , ϕ ( λ ) , h, ϕ ∈ L2 ( R n ) .

(3)

By algebra theory, it is obvious that there are 2 elements μ0 , μ1 , , μ2n −1 in space n Z + = {(k1 , k2 , , k2 ) : k s ∈ Z + , s = 1, 2, , n − 1, n} such that Z = ∪ ( μ + 2 Z ) ; ( μ1 + 2Z 5 ) ∩ ( μ 2 + 2Z 5 ) = φ , where Γ0 = {μ0 , μ1 , , μ2n −1} denotes the aggregate of all the different representative elements in the quotient group Z n /(2 Z n ) and order μ0 = {0} where {0} is the null element of Z and μ1 , μ 2 denote two arbitrary distinct elements in Λ 0 .Let Λ = Λ 0 − {0} and Λ, Λ 0 to be two index sets. n

n

n

d ∈Ω 0

n

+

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Definition 1. A sequence {ϕ k ( x)}k∈Z n ⊂ L2 ( R n ) is called an orthonormal set, if

〈ϕu , ϕv 〉 = δ n ,v , u, v ∈ Z n ,

(4)

where I s stands for the s × s identity matrix and δ n ,v , is generalized Kronecker symbol, i.e., δ n ,v = 1 as n = v and δ n ,v = 0 , otherwise. Definition 2. A sequence {ξv : v ∈ Z } ⊆ W is a frame for H if there exist two positive real numbers C , D such that ∀ η ∈W , C η

2

≤ ∑ v∈Λ | η , ξ v | ≤ D η 2

2

,

(5)

where W be a separable Hilbert space and Λ is an index set. A sequence {ξv : v ∈ Z } ⊆ W is a Bessel sequence if (only) the upper inequality of (6) holds. If only for all ∈ Ω ⊂ W , the upper inequality of (6) holds, the sequence {ξ v } ⊆ W is a Bessel sequence with respect to (w.r.t.) Ω . For a sequence c = {c(v)} ∈ 2 ( Z n ) , we define its discrete-time Fourier transform as the function in L2 (0,1) n by

Fc (ω ) = C (ω ) = ∑ v∈Z n c(v) e −2π ixω dx

，

(6)

Note that the discrete-time Fourier transform is Z -periodic. Let Tvφ ( x ) stand for integer translations of a function φ ( x) ∈ L2 ( R n ) , i.e., (Tvφ )( x) = φ ( x − v) , and φ j ,v = 2 nj / 2 φ (2 j x − v) , where a is a positive real constant number. Let ( x) ∈ L ( R ) and let V0 = span{Tv : v ∈ Z n } be a closed subspace of L2 ( R n ) . n

2

n

3 Five-Dimensional Multiresolution Analysis The multiresolution analysis method is an important approach to obtaining wavelets and wavelet packs. We introduce the notion of multiresolution analysis of L2 (R 5 ) . Set n = 5, ( x ) ∈ L2 (R 5 ) satisfy the refinement equation:

( x) = 32 ⋅ ∑ v∈Z 5 b(v) (2 x − v) ,

(7)

where { b(v)}u∈Z 5 is a real number sequence and ( x) is called a scaling function. Taking the Fourier transform for the both sides of refinement equation (1), we have

(ω ) = B ( z1 , z2 , z3 , z4 , z5 ) (ω 2). B( z1 , z2 , z3 , z4 , z5 ) =

∑ b(v ) z

v1 v2 v3 v4 v5 1 2 3 4 5

z z z z .

(8) (9)

v∈Z 5

Define a subspace U l

⊂ L2 (R 5 ) ( l ∈ Z ) by

U l = closL2

(R ) 5

2l (2l ⋅ −n) : n ∈ Z 5 ,

(10)

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We say that ( x ) in (8) generates a multiresolution analysis {U j } j∈Z of L2 (R 5 ), if the sequence {U j } j∈Z , defined in (4) satisfies the below: (a) U l ⊂ U l +1 , ∀ l ∈ Z ; (b) ∩ U = {0} ; ∪ U is dense in L2 (R 5 ) ; (c) ( x ) ∈ U l ⇔ (2 x ) ∈ U l +1 , ∀ l ∈ Z ; (d) the family {2l (2l ⋅ − n) : n ∈ Z 5 } is a Riesz basis for U l ( l ∈ Z ). Let Wl (l ∈ Z ) denote the orthogonal complementary subspace of U l in U l +1 and assume that there exists a vector-valued function Ψ ( x ) = (ψ 1 ( x ),ψ 2 ( x) , ⋅⋅⋅, ψ 31 ( x))T (see [7]) forms a Riesz basis for Wl , i.e., l ∈Z

l ∈Z

l

l

Wl = closL2 ( R5 ) ψ ν (2l ⋅ −u ) : ν = 1, 2, ⋅⋅⋅, 31; u ∈ Z 5 , l ∈ Z .

(11)

By (5), it is clear that ψ 1 ( x) , ψ 2 ( x ) , ⋅⋅⋅ , ψ 31 ( x ) ∈ W0 ⊂ U1 . Therefore, there exist fifteen real sequences { b(ι ) (v)} (ι = 1, 2, ⋅⋅⋅31, v ∈ Z 5 ) such that

ψ ι ( x) = 32 ⋅ ∑ v∈Z d (ι ) (v) (2 x − v), ι ∈ Γ , 5

where

Γ = { 1, 2,3

(12)

,30,31 } , Γ 0 = Γ ∪ {0} . Formula(6) can be written in

frequency domain as follows:

ψ ι ( ω ) = D(ι ) ( z1 , z2 , z3 , z4 , z5 ) where the symbol of the real sequence

(ω 2 ) , ι ∈ Γ ,

(13)

{d (ι ) (v)} (ι ∈ Γ , u ∈ Z 5 ) is

B (ι ) ( z1 , z2 , z3 , z4 , z5 ) =

∑ d (ι ) (n) z

n1 n2 n3 n4 n5 1 2 3 4 5

n∈Z

z z z z .

(14)

5

A five-variant scaling function ( x ) ∈ L2 (R 5 ) ∈ is orthogonal one, if

(⋅), (⋅ − u ) = δ 0,u , u ∈ Z 5 .

(15)

We say that ψ 1 ( x ),ψ 2 ( x ), ⋅⋅⋅,ψ 31 ( x ) are orthogonal five-dimensional wavelets associated with the scaling function

( x) , if they satisfy:

(⋅), ψ ι (⋅ − v) = 0 , ι ∈ Γ, v ∈ Z 5 ,

ψ ι (⋅),ψ τ (⋅ − u ) = δι ,τ δ 0,v , ι , τ ∈ Γ, v ∈ Z 5

(16) (17)

4 The Traits of Nonseparable Five-Variant Wavelet Packets We are now ready to introduce the below notations: Λ 0 ( x) = ( x), Λι ( x) = ψ ι ( x) , 5 ( ) d ( v ) = b(v ) , ι ∈ Γ u ∈ Z . We are now in a position discuss the traits of orthogonal nonseparable five-variant wavelet packets. 0

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Definition 3. A family of five-variant functions { Λ 32 n +ν ( x) : n = 0,1, 2, ⋅⋅⋅, ν = 0, 1, 2, ⋅⋅⋅, 31} is called a nonseparable five-dimensional wavelet packs with respect to the orthogonal scaling function ( x ) , where Γ 0 = {0,1, 2, ⋅⋅⋅,31} and

Λ 32 n +ι ( x) = ∑ v∈Z 5 d (ι ) (v) Λ n (2 x − v), ι ∈ Γ 0 ,

(18)

Taking the Fourier transform for the both sides of (19) yields

Λ 32 n +ι (ω ) = D (ι ) ( z1 , z2 , z3 , z4 , z5 ) Λ n (ω 2 ) .

(19)

where ι ∈ Γ 0 , D (ι ) ( z1 , z2 , z3 , z4 , z5 ) = D (ι ) (ω / 2) = ∑ v∈Z 5 d (ι ) (v) z1v1 z2v2 z33 z4v4 z5v5 . v

Lemma 1[6]. Assuming that ( x ) is an orthogonal five-variant scaling function and P( z1 , z2 , z3 , z4 , z5 ) is the symbol of the sequence {b(v)} . Then we have

P ( z1 , z2 , z3 , z4 , z5 ) + P ( − z1 , z2 , z3 , z4 , z5 ) + P ( z1 , − z2 , z3 , z4 , z5 ) 2

2

2

2

+ P( z1 , z2 , − z3 , z4 , z5 ) + P( z1 , z2 , z3 , − z4, , z5 ) + P ( z1 , z2 , z3 , z4 , − z5 ) 2

+ P (− z1 , − z2 , z3 , z4 , z5 ) + P( − z1 , z2 , − z3 , z4 , z5 ) + 2

2

2

+

+ P(− z1 , z2 , − z3 , − z4 , − z5 ) + P( z1 , − z2 , − z3 , − z4 , − z5 ) + P (− z1 , − z2 , − z3 , − z4 , − z5 ) = 1 . 2

2

2

Lemma 3[6]. Ifψ ν ( x ) (ν = 0,1, ⋅⋅⋅, 31 ) are orthogonal wavelet functions associa j ted with ( x ) . Denoting by yι = (−1) zι , ι = 1, 2, 3, 4,5, then we have

Ξλ ,μ =

∑ {D 1

j =0

(λ )

( y1 , y2 , y3 , y4 , y5 ) D (ν ) ( y1 , y2 , (−1) j z3 ,(−1) j z4 , (−1) j z5 )

+ D ( λ ) ((−1) j +1 z1 , y2 , y3 , y4 , y5 ) ⋅ D (ν ) ((−1) j +1 z1 ,(−1) j z2 , y3 , y5 ,(−1) j z5 )

+ D ( λ ) ((−1) j z1 , (−1) j +1 z2 , y3 , y4 , (−1) j z5 ) ⋅ D (ν ) ( y1 , − y2 , y3 , y4 , y5 ) + D ( λ ) ((−1) j z1 , (−1) j z2 , (−1) j +1 z3 , y4 , (−1) j z5 ) ⋅ D (ν ) ( y1 , y2 , − y3 , y4 , y5 ) + D ( λ ) ( y1 , y2 , y3 , − y4 , y5 ) ⋅ D (ν ) ((−1) j z1 , (−1) j z2 , y3 , − y4 , (−1) j z5 ) + D ( λ ) ( y1 , y2 , y3 , y4 , − y5 ) ⋅ D (ν ) (( −1) j z1 , ( −1) j z2 , ( −1) j z3 , ( −1) j z 4 , ( −1) j +1 z5 )

+ D ( λ ) ( − y1 , − y2 , y3 , y4 , y5 ) ⋅ D (ν ) ( − y1 , − y2 , ( −1) j z3 , ( −1) j z4 , (−1) j z5 ) + D ( λ ) ( − y1 , y2 , − y3 , y4 , y5 ) ⋅ D (ν ) (− y1 , y2 , − y3 , (−1) j z4 , (−1) j +1 z5 )

+

= δ λ ,ν , λ ,ν ∈ {0,1, 2, ⋅⋅⋅,31}.

Theorem 1[6]. For every

u ∈ Z 5 and n ∈ Z + , ι ∈ {0,1, 2, ⋅⋅⋅, 30, 31} , we have

Λ 32 n (⋅), Λ 32 n +ν (⋅ − u ) = δ 0,ν δ 0,u . Theorem 2. For every

(20)

u ∈ Z 5 and m, n ∈ Z + , we have

(21)

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Λ m (⋅), Λ n (⋅ − k ) = δ m, nδ 0,k .

，

(22)

Proof. For the case of m = n (22) follows from Theorem 1. As m ≠ n and m, n ∈ Γ 0 , (22) can be established from Theorem 1. Assuming that m is not equal to n and at least one of {m, n} doesn’t belong to Γ0 , rewrite m , n as m = 32m1 + λ1 , n = 32n1 + μ1 , where m1 , n1 ∈ Z + , and λ1 , μ1 ∈ Γ 0 . Case 1. If m1 = n1 , then λ1 ≠ μ1 . By (14), (16) and (18), (22) holds, since

(2π )5 Λ m (⋅), Λ n (⋅ − k ) = ∫ R5 Λ 32 m1 + λ1 (ω )Λ 32 n1 + μ1 (ω ) ⋅ exp{ikω}dω = ∫ R5 D ( λ1 ) ( z1 , z2 , z3 , z4 , z5 ) Λ m1 (ω 2) ⋅ Λ n1 (ω 2) D ( μ1 ) ( z1 , z2 , z3 , z4 , z5 ) ⋅ eikω d ω

= ∫ [0,2π ]5 Ξ λ1 , μ1 ⋅ exp{ikω} d ω = O.

m1 ≠ n1 , we set m1 = 32m2 + λ2 , n1 = 32n2 + μ 2 , where m2 , n2 ∈ Z + , and λ2 , μ2 ∈ Γ 0 . If m2 = n2 , then λ2 ≠ μ2 . Similar to Case 1, we have Λ m (⋅), Λ n (⋅ − k ) = O. That is to say, the proposition follows in such case. As m2 ≠ n2 , we order m2 = 32m3 + λ3 , n2 = 32n3 + μ3 , once more, where m3 , n3 ∈ Z + , and λ3 , μ3 ∈ Γ 0 . Thus, after taking finite steps (denoted by r ),we obtain that mr , nr ∈ Γ 0 , and λr , μr ∈ Ω0 . If α r = β r , then λr ≠ μ r . Similar to Case 1, (22) follows. If α r ≠ β r , Similar to Lemma 1, we conclude that Case 2. If

Λ m (⋅), Λ n (⋅ − k )

= 1

((2π ) ) ∫ 5

r

[0,2

Corollary 1. For

r +1

π]

5

{∏ B ( λι ) ( ι =1

ω

r

ω

)} ⋅ O ⋅ {∏ B ( μι ) ( ι )} ⋅ eikω d ω = O. 2ι 2 ι =1

n ∈ Z + , v ∈ Z 5 , we have Λ n (⋅), Λ n (⋅ − v) = δ 0,v .

References 1. Telesca, L., et al.: Multiresolution wavelet analysis of earthquakes. Chaos, Solitons & Fractals 22(3), 741–748 (2004) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis:Nature of Cantorian spacetime. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Li, S., et al.: A theory of generalized multiresolution structure and pseudoframes of translates. Fourier Anal. Appl. 7(1), 23–40 (2001) 4. Chen, Q., et al.: Existence and characterization of orthogonal multiple vector-valued wavelets with three-scale. Chaos, Solitons & Fractals 42(4), 2484–2493 (2009) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal., 26(4), 1061--1074 (1995) 6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Wei, Z.: The characteristics of orthogonal trivariate wavelet packets. Information Technology Journal 8(8), 1275–1280 (2009) 8. Chen, Q., Huo, A.: The research of a class of biorthogonal compactly supported vectorvalued wavelets. Chaos, Solitons & Fractals 41(2), 951–961 (2009)

The Features of Multiple Affine Fuzzy Quarternary Frames in Sobolev Space Hongwei Gao Department of Mathematics, Yulin University, Yulin 719000, P.R. China [email protected]

Abstract. The concept of a generalized quarternary multiresolution struccture (GQMS) of space is formulated. A class of multiple affine quarternary pseudoframes for subspaces of L2 ( R 4 ) are introduced. The construction of a GQMS of Paley-Wiener subspaces of L2 ( R 4 ) is studied. The sufficient condition for the existence of pyramid decomposition scheme is presented based on such a GQMS. A sort of affine quarternary frames are constructed by virtue of the pyramid decomsition scheme and Fourier transform. We show how to draw new orthonormal bases for space L2 ( R 4 ) from these wavelet wraps. Keywords: Sobolev space, separable Hilbert space, explicit frame bounds, projection operator, quarternary, wavelet frames, frame analysis.

1 Introduction and Notations The frame theory plays an important role in the modern time-frequency analysis.It has been developed very fast over the last twenty years, especially in the context of wavelets and Gabor systems. In her celebrated paper[1], Daubechies constructed a family of compactly supported univariate orthogonal scaling functions and their corresponding orthogonal wavelets with the dilation factor 2. Since then wavelets with compact support have been widely and successfully used in various applications such as image compression and signal processing. he frame theory has been one of powerful tools for researching into wavelets. To study some deep problems in nonharmonic Fourier series, Duffin and Schaeffer[2] introduce the notion of frames for a separable Hilbert space in 1952. Basically, Duffin and Schaeffer abstracted the fundamental notion of Gabor for studying signal processing [3]. These ideas did not seem to generate much general interest outside of nonharmonic Fourier series however (see Young's [4]) until the landmark paper of Daubechies, Grossmann, and Meyer [5] in 1986. After this ground breaking work, the theory of frames began to be more widely studied both in theory and in applications [6-8], such as signal processing, image processing, data compression and sampling theory. The notion of Frame Multiresolution Analysis (FMRA) as described by [6] generalizes the notion of MRA by allowing non-exact affine frames. However, subspaccs at different resolutions in a FMRA are still generated by a frame formed by translares and dilates of a single bivariate function. Inspired by [5] and [7], we introduce the norion of a Generalized Quarternary Multiresolution Structure (GQMS) of L ( R ) generated by several 2

4

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 513–518, 2011. © Springer-Verlag Berlin Heidelberg 2011

514

H. Gao 2

4

functions of integer translates L ( R ) . We demonstrate that the GQMS has a pyramid decomposition scheme and obiain a frame-like decomposition based on such a 2 4 GQMS.It also lead to new constructions of affine of L ( R ) . Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multi-variate wavelet theory. The classical method for constructing multi-variate wavelets is that separable multivariate wavelets may be obtained by means of the tensor product of some univariate wavelet frames. It is significant to investigate nonseparable multivariate wavelet frames and pseudoframes. Let Ω be a separable Hilbert space .We recall that a sequence {η v }v∈Z 4 ⊆ Ω is a frame for Ω , if there exist positive real numbers L, M such that ∀ ℘∈ Ω, L ℘ ≤ ∑ v∈Λ | ℘,ηv | ≤ M ℘ , 2

2

2

(1)

A sequence {ηv }v∈Z 4 ⊆ Ω is called a Bessel sequence if only the upper inequality of (1) follows. If only for all element g ∈ Q ⊆ Ω , the upper inequality of (1) holds, the sequence {ηv }v∈Z 4 ⊆ Ω is a Bessel sequence with respect to (w.r.t.) Q .If {ηv } is a * frame, there exist a dual frame {η v } such that ∀ h ∈ Ω, h = ∑ h,ηv η v∗ = ∑ h,η v∗ η v . v

(2)

v

The Fourier transform of an integrable function h( x ) ∈ L ( R ) is defined by 2

4

Fh(ω ) = h(ω ) = ∫ 4 h( x)e−2π ixω dx, ω ∈ R 4 .

(3)

R

For a sequence c = {c(k )} ∈

2

( Z 4 ), we define the discrete-time Fourier tramsform

as the function in L2 (0,1)4 given by Fk (ω ) = K (ω ) = ∑ v∈Z 4 k (v) ⋅ e −2π ivω .

(4)

For s > 0, we denote by H ( R ) the Sobolev space of all quarternary functions s

4

h( x ) ∈ H s ( R 4 ) such that

∫

Rn

| h(γ ) |(1+ || γ ||2 s ) d γ < +∞.

The space H λ ( R n ) is a Hilbert space equipped with the inner product given by

h, g

H λ (R4 )

:=

1 (2π )

4

∫

R4

2λ

h(γ ) g (γ ) (1+ | γ | ) d γ , h, g ∈ L ( R ). 2

4

(5)

We are interested in wavelet bases for the Sobolev space H λ ( R n ) , where λ is a positive integer. In this case, we obtain h, g

= h , g + h ( λ ) , g ( λ ) , h, g ∈ L ( R ) . 2

H λ ( R4 )

4

(6)

Suppose that h( x) is a function in the Sbolev space H λ ( R n ) . For j ∈ Z , k ∈ Z n , setting h j ,u ( x ) = 4 j h (2 j x − u ) , we have || h j , k

||H λ ( R4 ) = || h j , k || L2 ( R 4 ) = 4 (s )

jλ

|| h ( s )

||L2 ( R 4 ) .

The Features of Multiple Affine Fuzzy Quarternary Frames in Sobolev Space

515

Note that the discrere-time Fourier transform is Z 4 -periodic.Let r be a fixed positive integer,and J be a finite index set, i.e., J = {1, 2, , r}. We consider the case of multiple generators, which yield multiple pseudoframes for subspaces. Definition 1. Let {Tk

j

} and {Tk

j

subspace M ⊂ L2 ( R 4 ) , We say that {Tk

} ( j ∈ J , k ∈ Z 4 ) be two sequences in j

} forms a multiple pseudoframe for V0 with

respect to (w.r.t.) ( j ∈ J , k ∈ Z ) if 4

∀ ϒ ∈ M , ϒ = ∑ ∑4 ϒ, Tv

j

j∈J v∈Z

Tv

(7)

j

where we define a translate operator, (Tvφ )( x) = φ ( x − v), v ∈ Z

φ ( x) ∈ L ( R ) . It is important to note that {Tk 2

4

j

} and {Tk

j

4

， for a function

} ( j ∈ J , k ∈ Z 2 ) need not

be contained in M . The above example is such case. Consequently, the position of {Tk j } and {Tk j } are not generally commutable, i.e., there exists ϒ ∈ M such that

∑ ∑ ϒ, Tv

j

j∈J v∈Z 2

Tv h j ≠ ∑ ∑2 ϒ, Tv j∈ J v∈Z

j

Tv

j

= ϒ.

Definition 2. A generalized multiresolution structure (GQMS) {V j ,

} is a sequence of closed linear subspaces {V j } j∈Z of L ( R ) and 2r elements h j , j ∈ L2 ( R 4 ), j ∈ J such that (a) V j ⊂ V j +1 ∀ j ∈ Z ; (b) ∩ j∈Z V j = {0}; ∪ j∈Z V j 4 is dense in L2 ( R 4 ) ; (c) h( x) ∈ V j if and only if Dh( x) ∈V j +1 , ∀j ∈ Z ,where Dφ ( x) = φ (2 x) , for ∀φ ( x) ∈ L2 ( R 4 ) ; (d) g ( x) ∈ V0 implies Tv g ( x) ∈ V0 ,for all v ∈ Ζ 4 ; (e) {Tv h j , j ∈ J , v ∈ Z 4 } forms a multiple pseudoframe for V0 with 4 respect to Tv j , j ∈ J , v ∈ Z . 2

j

,

j

4

2 Construction of GQMS of Paley-Wiener Subspace A necessary and sufficient condition for the construction of multiple pseudoframe for Paley-Wiener subspaces of L2 ( R 4 ) is presented as follow.

h j ∈ L2 ( R 4 ) ( j ∈ J ) be such that ˆ j > 0 a.e. on a connected nei4 ghbourhood of 0 in [− 12 , 21 ) ,and ˆ = 0 a.e. otherwise. Define Λ ≡ ∩ j∈J { γ ∈ R : | ˆ j |≥ c > 0, j ∈ J } and Theorem 1. Let

j

V0 = PWΛ = { f ∈ L2 ( R 4 ) : supp ( f ) ⊆ Λ} .

(8)

Vn ≡ {ϒ( x) ∈ L ( R ) : ϒ( x / 2 ) ∈ V }

(9)

2

4

n

，n∈Z ,

Then, for h j ∈ L ( R ), {Tv h j : j ∈ J , k ∈ Z } is a multiple pseudoframe for V0 with 2

4

respect to {Tv h j , j ∈ J , v ∈ Z } if and only if 2

516

H. Gao

∑ j∈J hˆ j (γ ) h(γ ).χ Λ (γ ) = χ Λ (γ ) a.e.,

χ Λ is the characteristic function on Λ .

where

Proof. For all

ϒ ∈ PWΛ consider

F ( ∑ j∈J ∑ v∈Z 2 ϒ, Tv

= ( ∑ ∑ 4 ∫ R4 ϒˆ ( μ ) j∈ J v∈Z

j

j

Tv

j∈J v∈Z

=∑ j∈J

j

j

= ( ∑ j∈J ∑ v∈Z 2 ϒ, Tv

0 n∈Z

j

( μ + n ).e

2 π ivμ

F (Tv

j

)

d μ ˆ j (γ )e −2π jvγ

(γ ) ∑ ϒ (γ + n ) j ( γ + n ) = ∑ j∈J ϒ (γ ) j (γ ) j (γ ). n∈Ζ 4

where we have used the fact that n∈Ζ2

j

( μ ).e 2π ivμ d μ ˆ j (γ )e −2π jvγ

1 ˆ = ∑ ∑4 ∫ ∑4 ϒˆ ( μ + n)

∑

(10)

| |≠ 0 only on [ − 12 , 21 ) 4 and that

ϒ ( ω + n ) (ω + n), j ∈ J is 1-periodic function. Therefore

∑

j∈J

j

j

⋅ χΛ = χΛ ,

is a neccssary and sufficient condition for {Tk pseudoframe for V0 with respect to {Tk

j

j

a.e.,

, j ∈ J , k ∈ Ζ} to be a multiple

, j ∈ J , k ∈ Ζ4} .

, j ∈ L2 ( R 4 ) have the properties specified in Theorem 1 such that (6) is satisfied. Assume V is defined by (9). Then {V , j , j } forms a GQMS. Theorem 2. Let

j

Proof. We need to prove four axioms in Definition 2. The inclusion Ve ⊆ Ve +1 follows from the fact that Ve defined by (9) is equivalent to PW2 A .Condition (b) is satisficd bccause the set of all band- limited signals is dense in L2 ( R 4 ) .On the other hand ,the intersection of all band-limited signals is the trivial function. Condition (c) is an immediate consequence of (9). For condition (d) to be prooved, if f ∈V0 , ~ then f = ∑ j∈ J ∑ k ∈Z f , Tk j Tk j ⋅ By taking variable substitution, for ∀n ∈ Z 4 , f (t − n ) = ∑ j∈J ∑ v∈Z 4 f (⋅),

j

(⋅ − v )

j

(t − v − n ) = ∑ j∈J ∑ v∈Z 4 f (⋅ − n ),

That is, Tn f = ∑ j∈J ∑ v∈Z 4 Tn f ⋅ Tv j Tv j ⋅ Or, it is a fact f (Tv in Ω for arbitrary k ∈ Z . Therefore, Tn f ∈ V0 . Example 1. Let

(⋅ − v )

j

(x − v)

j ) has support

∈ L ( R ) be such that 2

j

j

4

，

a.e., || ω ||≤ 18 ⎧ 1/ r ⎪ 1 3 j (γ ) = ⎨(3 − 16 || γ ||)1/ r , a.c., 8 <|| γ ||< 16 , ⎪0, otherwise. ⎩

|| γ ||≤ 18 , ⎧1, a.e., ⎪ (ω ) = ⎨5 − 16 || ω ||, a.e., 18 <|| γ ||< 165 , ⎪0. otherwise. ⎩

j ∈ J . Choose Λ = {ω ∈ R :| (ω ) |≥ 1r } = [ − 1 4 , 1 4 ] , and define V0 = PWΛ ,

The Features of Multiple Affine Fuzzy Quarternary Frames in Sobolev Space

select

j

∈ L2 ( R 4 ) such thatThen, since

Theorem 1, { Tk

j

} and { Tk

~ j

∑ j∈J

j

517

(γ ) h j (γ ) = 1 a.e. on Λ , by

} form a pair of pseudoframes for V0 = PWA .

3 The Characters of Nonseparable Quarternary Wavelet Packs To construct wavelet packs, we introduce the following notation: a = 2, Λ 0 ( x) = h( x), Λν ( x ) = ψ ν ( x), b( 0) (k ) = b(k ), b(ν ) (k ) = q (ν ) (k ), where ν ∈ Δ = {0,1, 2, ,15} We are now in a position of introducing orthogonal trivariate nonseparable wavelet packs. Definition 3. A family of functions { Λ16 n +ν ( x) : n = 0,1, 2, 3, ⋅⋅⋅, ν ∈ Δ } is called a nonseparable quarternary wavelet packs with respect to the orthogonal quarternary scaling function Λ 0 ( x) , where Λ16 n +ν ( x) = ∑ k∈Z 4 b(ν ) (k ) Λ n (2 x − k ), (11) whereν

∈ Δ. By taaking the Fourier transform for the both sides of (13), we have Theorem 3[6]. If { Λ16 n +ν ( x) : n = 0,1, 2, 3, ⋅⋅⋅, ν ∈ Δ } is called a nonseparable quarternary wavelet packs with respect to the orthogonal scaling function Λ 0 ( x) , we have

Λ m (⋅), Λ n (⋅ − k ) = δ m , nδ 0, k ,

m, n ∈ Z + ,

k ∈ Z 4.

(12)

4 The Multiple Affine Fuzzy Quarternary Frames We begin with introducing the concept of pseudoframes of translates. Definition 4. Let {Tv f , v ∈ Z 4 } and {Tv f , v ∈ Z 4 } be two sequences in L2 ( R 4 ) . Let U be a closed subspace of L2 ( R 4 ) . We say {Tv f , v ∈ Z 4 } forms an affine pseudoframe for U with respect to {Tv f , v ∈ Z 4 } if

∀ ϒ( x) ∈ U , ϒ( x) = ∑ v∈Z ϒ, Tv f Tv f ( x) 4

Define an operator K : U →

2

∀ ϒ( x) ∈ U , and define another operator S :

2

(13)

4

( Z ) by K ϒ = { ϒ, Tv f } ,

(14)

( Z 4 ) → W such that

∀ c = {c(k )} ∈ 2 ( Z 4 ) , S{c(k )} = ∑ v∈Z c(v) Tv f . 4

(15)

Theorem 4. Let {Tv f }v∈Z 4 ⊂ L2 ( R 4 ) be a Bessel sequence with respect to the subspace U ⊂ L2 ( R 4 ) , and {Tv f }v∈Z 4 is a Bessel sequence in L2 ( R 4 ) . Assume that K be defined by (14), and S be defined by (15). Assume P is a projection from L2 ( R 4 ) onto U . Then {Tv ϒ}v∈Z 4 is pseudoframes of translates for U with respect to {Tv ϒ}v∈Z 4 if and only if

KSP = P .

(16)

518

H. Gao

Proof. The convergence of all summations of (7) and (8) follows from the assumptions that the family {Tv ϒ}v∈Z 4 is a Bessel sequence with respect to the subspace Ω , and he family {Tv ϒ}v∈Z 4 is a Bessel sequence in L2 ( R 4 ) with which the proof of the theorem is direct forward. Theorem 5[8]. Let φ ( x ) , φ ( x ) ,ψ ι ( x ) and ψ ι ( x) , ι ∈ Λ be functions in L ( R ) . 2 4 Assume conditions in Theorem 1 are satisfied. Then, for any ∈ L ( R ) , and n ∈ Z , 2

∑

k ∈Z

4

15

n −1

, φ n , k φn , k ( x ) = ∑ ∑

∑

ι =1 v =−∞ k ∈Z 4

15

∞

( x) = ∑ ∑ ∑ ι =1 v =−∞ k ∈Z

,ψ ι :v ,k ψ ι :v ,k ( x ) .

,ψ ι :v , k ψ ι:v , k ( x ) . ∀ ( s ) ∈ L2 ( R 4 )

4

(17)

(18)

4

Consequently, if {ψ ι :v , k } and {ψ ι :v , k } , (ι ∈ Λ, v ∈ Z , k ∈ Z ) are also Bessel sequences, they are a pair of affine frames for L2 ( R 4 ) . 4

References 1. Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inform. Theory 39, 961–1005 (1990) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis:Nature of ε ∞  Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Zhang, N., Wu, X.: Lossless Compression of Color Mosaic Images. IEEE Trans. Image Processing 15(16), 1379–1388 (2006) 4. Chen, Q., Wei, Z.: The characteristics of orthogonal trivariate wavelet packets. Information Technology Journal 8(8), 1275–1280 (2009) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal. 26(4), 1061– 1074 (1995) 6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Huo, A.: The research of a class of biorthogonal compactly supported vectorvalued wavelets. Chaos, Solitons & Fractals 41(2), 951–961 (2009) 8. Li, S., et al.: A theory of generalized multiresolution structure and pseudoframes of translates. Fourier Anal. Appl. 7(1), 23–40 (2001)

Characters of Orthogonal Nontensor Product Trivariate Wavelet Wraps in Three-Dimensional Besov Space* Jiantang Zhao1,** and Qingjiang Chen2 1 College of Math. & Inform. Science, Xianyang Normal University, Xianyang 712000, China [email protected] 2 School of Science, Xi’an University of Architecture and Technology, Xi’an 710055, China [email protected]

Abstract. Compactly supported wavelet bases for Sobolev spaces is investigated. Steming from a pair of compactly supported refinale functions with multiscale dilation factor in space L2 ( R 3 ) meeting a very mild condition, we provide a general approach for constructing wavelet bases, which is the generalization of univariate wavelets in Hilbert space. The notion of orthogonal non-tensor product trivariate wavelet wraps is proposed by virtue of iteration method. Their orthogonality characters are researched by using time-frequency analysis method. Three orthogonality formulas concerning these wavelet wraps are obtained. It is necessary to draw new orthonormal bases of space L2 ( R 3 ) from these wavelet wraps. A procedure for designing a class of orthogonal vector-valued compactly supported wavelet functions. Keywords: Besov space, nontensor product, subdivision operator, trivariate wavelet wraps, Bessel sequence, orthonormal bases, functional analysis method.

1 Introduction Although the Fourier transform has been a major tool in analysis for over a century, it has a serious laking for signal analysis in that it hides in its phases information concerning the moment of emission and duration of a signal. In her celebrated paper[1], Daubechies constructed a family of compactly supported univariate orthogonal scaling functions and their corresponding orthogonal wavelets with the dilation factor 2. Since then wavelets with compact support have been widely and successfully used in various applications such as image compression and signal processing. Scaling biorthogonal wavelets in both univariate case and multtivariate case have been extensively studies in literature. With symmetry and many other desired properties, *

**

Foundation item: This work is supported by the Science Research Foundation of Education Department of Shaanxi Provincial Government (Grant No: 11JK0513 and Grant No:11JK0468). Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 519–524, 2011. © Springer-Verlag Berlin Heidelberg 2011

520

J. Zhao and Q. Chen

scaling biorththogonal wavelets have been found to be more efficient and useful in many applications than the orthogonal ones. Wavelet analysis has been developed a new branch for over twenty years. Its applications involve in many areas in natural science and engineering technology. The main advantage of wavelets is their timefrequency localization property. Many signals in areas like music, speech, images, and video images can be efficiently represented by wavelets that are translations and dilations of a single function called mother wavelet with bandpass property. Wavelet packets, owing to their good properties, have attracted considerable attention. They can be widely applied in science and engineering [2,3]. Coifman and Meyer firstly introduced the notion for orthogonal wavelet packets which were used to decompose wavelet components. Chui and Li Chun [4] generalized the concept of orthogonal wavelet packets to the case of non-orthogonal wavelet packets so that wavelet packets can be employed in the case of the spline wavelets and so on. Tensor product multivariate wavelet packs has been constructed by Coifman and Meyer. The introduction for the notion on nontensor product wavelet packs attributes to Shen Z [5]. Since the majority of information is multidimensional information, many researchers interest themselves in the investigation into multivariate wavelet theory. There exist a lot of obvious defects in this method, such as, scarcity of designing freedom. Therefore, it is significant to investigate nonseparable multivariate wavelet theory. Nowadays, since there is little literature on biorthogonal wavelet packs, it is necessary to investigate biorth-ogonal wavelet packs. In the following, we introduce some notations. Z and Z + denote all integers and all nonnegative integers, respectively. R denotes all real numbers. R 3 denotes the 3dimentional Euclidean space. L2 ( R3 ) denotes the square integrable function space. 3 Let x = ( x1 , x2 , x3 ) ∈ R , γ = (γ 1 , γ 2 , γ 3 ) ∈ R 3 , k = ( k1 , k2 , k3 ) ∈ Z 3 , yι = e − iγι a , w here 3 2 ≤ a ∈ Z , ι = 1, 2,3, , a − 1. In the following γ ⋅ x = γ 1 x1 + γ 2 x2 + γ 3 x3 . For any ( x ) ∈ L2 ( R 3 ) , the Fourier transform of ( x) is defined by

(γ ) = ∫

R3

( x ) e − iγ ⋅ x dx.

(1)

2 The Trivariate Multiresolution Analysis Firstly, we introduce multiresolution analysis of space L2 ( R3 ) Wavelets can be constructed by means of multiresolution analysis. In particular, the existence theorem[8] for higher-dimentional wavelets with arbitrary dilation matrice has been given. Let g ( x) ∈ L2 ( R3 ) satisfy the following refinement equation:

g ( x) = a 3 ⋅ ∑ n∈Z bn ⋅ g ( ax − n), 3

(2)

where {bn }n∈Z 3 is real number sequence which has only finite terms.and g ( x ) is called scaling function. Formula (1) is said to be two-scale refinement equation. The frequency form of formula (1) can be written as

Characters of Orthogonal Nontensor Product Trivariate Wavelet Wraps

521

g (γ ) = B( y1 , y2 , y3 ) g (γ a),

(3)

where

B ( y1 , y2 , y2 ) = ∑ bn ⋅ y1n ⋅ y2 n ⋅ y3 . 1

n∈ Z

n3

2

(4)

3

Define a subspace X j ⊂ L2 ( R 3 ) ( j ∈ Z ) by

X j = closL2 ( R3 ) a 3 j / 2 g (a j ⋅ −u ) : λ = 1, 2, Definition 2. We say that 2

, a 3 − 1; u ∈ Z 3 .

(5)

g ( x) in (2) generate a multiresolution analysis { X

j

} j∈Z of

3

L ( R ) , if the sequence { X j } j∈Z defined in (5) satisfy the following properties:

(i) X j ⊂ X j +1 ,

∀ j ∈ Z ; (ii) ∩ X j = {0}; ∪ X j is dense in j∈Z

j∈Z

L2 ( R 3 ) ; (iii)

f ( x) ∈ X k ⇔ f (ax) ∈ X k +1 , ∀ k ∈ Z ; (iv) the family {g ( a x − u ) : u ∈ Z 3 } forms a j

Riesz basis for the space X j .

Let Yk ( k ∈ Z ) denote the complementary subspace of X j in X j +1 , and assume

that there exist a vector-valued function Ψ ( x) = {ψ 1 ( x),ψ 2 ( x),ψ 3 ( x),

, ψ a3 −1 ( x )}

constitutes a Riesz basis for Yk , i.e.,

Y j = closL2 ( R3 ) ψ λ: j ,u : λ = 1, 2,

, a 3 − 1; u ∈ Z 3 ,

where j ∈ Z , and ψ λ: j ,u ( x ) = a 3 j / 2ψ λ ( a j x − u ), λ = 1, 2,

(6)

, a 3 − 1; u ∈ Z 3 . Form

,ψ a3 −1 ( x) are in Y0 ⊂ X 1. Hence there

condition (5), it is obvious that ψ 1 ( x),ψ 2 ( x ), (λ ) n

3 , a − 1}, n ∈ Z 3 ) such that

exist three real number sequences {q }(λ ∈ Δ = {1, 2,

ψ λ ( x) = a 3 ⋅ ∑ qn( λ ) g (ax − n),

(7)

n∈Z 3

Formula (7) in frequency domain can be written as

ψˆ λ (γ ) = Q ( λ ) ( y1 , y2 , y3 ) g (γ a), λ = 1, 2, , a3 − 1. where the signal of sequence {qk( λ ) }(λ = 1, 2,

Q ( λ ) ( y1 , y2 , y3 ) =

∑q

n∈Z

(8)

, a 3 − 1, k ∈ Z 3 ) is (λ ) n

⋅ y1n ⋅ y2 n ⋅ y3 n . 1

2

3

(9)

3

A trivariate scaling function g ( x ) ∈ L (R ) is called an orthogonal one, if 2

3

g (⋅), g (⋅ − n) = δ 0,n , n ∈ Z 3 .

(10)

We say Ψ ( x) = (ψ 1 ( x),ψ 2 ( x),ψ 3 ( x), ,ψ a3 −1 ( x ))T is a orthogonal trivariate vectorvalued wavelets associated with the scaling function g ( x ) , if they satisfy:

g (⋅), ψ ι (⋅ − u ) = 0 , ι ∈ Δ, u ∈ Z 3 ,

(11)

ψ λ (⋅),ψ ι (⋅ − u ) = δ λ ,ιδ 0,u , λ , ι ∈ Δ, u ∈ Z 3

(12)

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J. Zhao and Q. Chen

3 The Characters of Nontensor Product Trivariate Wavelet Wraps To construct wavelet wraps, we introduce the follow-ing notations: Λ 0 ( x) = g ( x), Λν ( x) = ψ ν ( x), b( 0) (k ) = b( k ), b(ν ) (k ) = q (ν ) (k ), whereν ∈ Δ . We are now in a posisition of introducing orthogonal nontensor product trivariate wavelet wraps. Definition 3. A family of functions { Λ a3 n +ν ( x ) : n = 0,1, 2,

3, ⋅⋅⋅, ν ∈ Δ } is called a

nontensor product trivariate wavelet wraps with respect to the orthogonal scaling function Λ 0 ( x) , where Λ a3 n +ν ( x) = ∑ k∈Z 3 b (ν ) (k ) Λ n (ax − k ), whereν yields

(13)

= 0,1, 2, , a 3 − 1. Taking the Fourier transform for the both sides of (13) Λ a 3n +ν (γ ) = B (ν ) ( y1 , y2 , y3 ) ⋅ Λ n (γ a ),

(14)

where B (ν ) ( y1 , y2 , y3 ) = B (ν ) ( γ / a ) = Lemma 1[6]. Let

∑ bν

( )

k ∈Z

( k ) y1k1 y2k2 y3k3 .

(15)

3

( x) ∈ L2 (R 3 ). Then ( x) is an orthogonal one if and only if ˆ (γ + 2kπ ) |2 = 1. . (16) 3

∑

k∈Z

Lemma 2 [6]. Assuming that g ( x ) is an semiorthogonal scaling function. B( y1 , y2 , y3 ) is the symbol of the sequence {b( k )} defined in (3) and set a = 2 . Then we have 2

2

2

2

Π = B( y1 , y2 , y3 ) + B(− y1 , y2 , y3 ) + B( y1 , − y2 , y3 ) + B( y1 , y2 , − y3 ) + B(− y1 , y2 , − y3 ) + B (− y1 , − y2 , y3 ) + B( y1 , − y2 , − y3 ) + B (− y1 , − y2 , − y3 ) = 1. (17) 2

2

2

2

Lemma 3 [6]. If ψ ν ( x ) (ν

= 0,1, ⋅⋅⋅7 ) are orthogonal wavelet functions associated with g ( x ) . Then for a = 2 , λ ,ν ∈ {0,1, ⋅⋅⋅7}, we have Ξλ ,μ =

∑ {B 1

j =0

(λ )

(( −1) j y1 , ( −1) j y2 , ( −1) j y3 ) B (ν ) (( −1) j y1 , ( −1) j y2 , ( −1) j y3 )

+ B ( λ ) (( −1) j +1 y1 , ( −1) j y2 , ( −1) j y3 ) ⋅ B (ν ) (( −1) j +1 y1 , ( −1) j y2 , ( −1) j y3 ) + B ( λ ) (( −1) j y1 , (−1) j +1 y2 , ( −1) j y3 ) ⋅ B (ν ) (( −1) j y1 , (−1) j +1 y2 , ( −1) j y3 )

+ B ( λ ) ((−1) j y1 ,(−1) j y2 ,(−1) j +1 y3 ) ⋅ B (ν ) ((−1) j y1 ,(−1) j y2 ,(−1) j +1 y3 )} = δ λ ,ν . (18) For an arbitrary positive integer

n = ∑ j =1ν j 8 j −1 , ∞

n ∈ Z + , expand it by .

ν j ∈ Δ = {0,1, 2,3,

, 7} .

(19)

Characters of Orthogonal Nontensor Product Trivariate Wavelet Wraps

523

Lemma 4[7]. Let n ∈ Z + and n be expanded as (19). Then we have ∞

Λn (γ ) = ∏ B

(ν j )

− iγ 1

(e

2j

− iγ 2

,e

2j

− iγ 3

,e

j =1

Theorem 1[8]. For

2j

)Λ 0 ( 0 ) .

n ∈ Z + , k ∈ Z 3 , we have Λ n (⋅), Λ n (⋅ − k ) = δ 0,k .

(20)

m, n ∈ Z + , we have

Theorem 2. For every k ∈ Z and 3

Λ m (⋅), Λ n (⋅ − k ) = δ m, nδ 0,k .

(21)

m = n , (22) follows from Theorem 1. As m ≠ n and

Proof. For the case of

m, n ∈ Ω 0 , the result (21) can be established from Theorem 1, where Ω 0 = {0,1, ⋅⋅⋅, 7} .

m is not equal to n and at least one of {m, n} doesn’t belong to Ω0 , rewrite m , n as m = 8m1 + λ1 , n = 8n1 + μ1 , where m1 , n1 ∈ Z + , and λ1 , μ1 ∈ Ω0 . Case 1 If m1 = n1 , then λ1 ≠ μ1. By (14), (16) In what follows, assuming that

and 18), (21) follows, since (2π ) 3 Λ m (⋅), Λ n (⋅ − k ) = ∫ R3 Λ 8 m1 + λ1 (ω )Λ 8 n1 + μ1 (ω ) eikω dω = ∫ R3 B (λ1 ) ( z1 , z2 , z3 ) Λ m1 (ω 2) ⋅ Λ n1 (ω 2) B ( μ1 ) ( z1 , z2 , z3 ) ⋅ exp{ikω}d ω = ∫ [0,4π ]3 B

( λ1 )

( z1 , z2 , z3 ) ⋅ ∑ Λ m (ω 1

s∈Z

2 + 2 sπ ) ⋅ Λ m1 (ω 2 + 2 sπ ) B

( μ1 )

( z1 , z2 , z3 ) ⋅ eikω dω

3

= ∫ [0,2π ]3 Ξ λ1 , μ1 ⋅ exp{ikω} dω = O. m1 ≠ n1 , we order m1 = 8m2 + λ2 , n1 = 8n2 + μ 2 , where m2 , n2 ∈ Z + , and λ2 , μ2 ∈ Ω 0 . If m2 = n2 , then λ2 ≠ μ2 . Similar to Case 1, it

Case 2. Provided that

holds that Λ m (⋅), Λ n (⋅ − k ) = O. That is to say, the proposition follows in such

m2 ≠ n2 , then order m2 = 2m3 + λ3, n2 = 2n3 + μ3 , n2 = 2n3 + μ3 once more, where m3 , n3 ∈ Z + , and λ3 , μ3 ∈ Ω 0 . Thus, after taking finite steps (denoted by r ), we obtain mr , nr ∈ Ω0 , and λr , μr ∈ Ω 0 . If α r = β r , then λr ≠ μ r . Similar to Case 1, (3.11) follows. If α r ≠ β r , Similar to Lemma 1, we case. Sin -ce

conclude that

Λ m (⋅), Λ n (⋅ − k ) = =

(2π )3 r

1

∫ (2π ) 3 [0,2

1

r +1

π]

3

∫R

3

{∏ B ( λι ) ( ι =1

Λ8 m1 + λ1 (ω )Λ8n1 + μ1 (ω ) ⋅ eikω dω

ω ι

2

r

)} ⋅ O ⋅ {∏ B ( μι ) ( ι =1

ω 2

ι

)} ⋅ e ik ω d ω = O .

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J. Zhao and Q. Chen

For simplicity, we introduce a dilation operator ( DΦ )( x ) = Φ (2 x ), where Φ ( x) ∈ L2 ( R 3 ) and set D

Γ = { DΦ( x) : Φ ( x) ∈ Γ }, where Γ ⊂ L2 ( R 3 ). For any

β ∈ Z +3 , define Γ β = {Φ ( x) : Φ ( x) = ∑ k∈Z 3 Ck Λ β ( x − k ),{Ck } ∈

2

( Z 3 )}.

(22)

where the family {Λ β ( x ), β ∈ Z +3 } are trivariate wavelet packets with respect to the orthogonal function g ( x ) . Then

For arbitrary

β ∈ Z +3 , the

space DΓ β can be

orthogonally decomposed into spaces Γ 2 β + λ , λ ∈ Ω0 , i.e., DΓ β = ⊕λ∈Ω0 Γ 2 β + λ . For arbitrary j ∈ Z + , define the set

j Δ = {α = (α1 , a2 , α 3 ) ∈ Z +3 − {0}:2 j −1 ≤ α l ≤ 2 j − 1,

l = 1, 2,3}.

Theorem 3[6]. The family { Λα (⋅ − k ), α ∈ j Δ, k ∈ Z 3 } form an orthogonal basis of

DjW0. In particular, {Λα (⋅ − k ), α ∈ Z + , k ∈ Z } constitutes an orthogonal basis of 3

3

space L2 ( R3 ) .

References 1. Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inform. Theory 39, 961–1005 (1990) 2. Iovane, G., Giordano, P.: Wavelet and multiresolution analysis:Nature of ε ∞ Cantorian space-time. Chaos, Solitons & Fractals 32(4), 896–910 (2007) 3. Zhang, N., Wu, X.: Lossless Compression of Color Mosaic Images. IEEE Trans. Image Processing 15(16), 1379–1388 (2006) 4. Chen, Q., et al.: Existence and characterization of orthogonal multiple vector-valued wavelets with three-scale. Chaos, Solitons & Fractals 42(4), 2484–2493 (2009) s 5. Shen, Z.: Nontensor product wavelet packets in L2 ( R ) . SIAM Math. Anal. 26(4), 1061–1074 (1995) 6. Chen, Q., Qu, X.: Characteristics of a class of vector-valued nonseparable higherdimensional wavelet packet bases. Chaos, Solitons & Fractals 41(4), 1676–1683 (2009) 7. Chen, Q., Cao, H., Shi, Z.: Construction and decomposition of biorthogonal vector-valued wavelets with compact support. Chaos, Solitons & Fractals 42(5), 2765–2778 (2009) 8. Chen, Q., Huo, A.: The research of a class of biorthogonal compactly supported vectorvalued wavelets. Chaos, Solitons & Fractals 41(2), 951–961 (2009) 9. Yang, S., Cheng, Z., Wang, H.: Construction of biorthogonal multiwavelets. J. Math. Anal. Appl. 276(1), 1–12 (2002)

Research on Computer Education and Education Reform Based on a Case Study* Jianhong Sun1,**, Qin Xu2, Yingjiang Li1, and JunSheng Li1 1

Engineering College of Honghe University, Yunnan Mengzi, 661100, China {Sparkhonghe,hhlijsh}@gmail.com 2 Faculty of Medicine, Chu Xiong Medical and Pharmaceutical College, Yunnan Chu Xiong, 675005, China

Abstract. Currently, the education reform is a widespread concerning issue in China. As the education model has been unchanged for dozens of years, some disadvantage that improper to the present era had become gradually apparent. For keep abreast of new technology, the computer science as one of the fastest developing disciplines and itself also impacts on modern education deeply needs education reform timely more than others. In this paper, we analysis the issues exist in computer education based on a case study research, and the countermeasures contributing to these issues also are presented. Keywords: education, computer education, education reform, teaching method.

1 Introduction Nowadays, there is a widespread concern over the issue that China education is a success or not. In fact, the opinion concerning this hot topic varies from person to person. Some people hold the optimistic idea that China education is successful. Because that many Chinese students can get offer from top universities of Britain, America or other country on full scholarships and can achieved the highest test scores in the world in reading comprehension, writing, math, and science with the second language, English. However, some people doubt that why the schools of China have not cultivated some world’s leading scientists with creativity. Anyway, China education has been unchanged for dozens of years, some disadvantage that improper to the present era has become gradually apparent. It is a consensus to both sides about the education needs reform. It is not a long time since the computer as an independent discipline into education. Therefore, “computer science education research is an emergent area and is still giving rise to a literature [1].” However, for keep abreast of new technology, the computer science as one of the fastest developing disciplines and itself also impacts *

Pecuniary aid of Honghe University Discipline Construction Fund (081203). Pecuniary aid of Honghe University Bilingual Course Construction Fund (SYKC0802). ** Corresponding author. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 525–529, 2011. © Springer-Verlag Berlin Heidelberg 2011

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on modern education deeply needs education reform timely more than others. In this paper, we analysis the issues exist in computer education based on a case study research, and the countermeasures contributing to these issues also are presented.

2 Background and the Exist Problems Honghe University (HU) is a developing university which upgrade from a normal specialized postsecondary college upgrade to a university since 2003. It is one of 1090 universities1 of China. HU serves a diverse population of full- and part-time, national and international students. In 2009~2010 academic year, more than ten thousand students enrolled in 12 undergraduate colleges with 36 undergraduate specialties [2]. Cultivating applied talents for society is the goal of HU and for this HU’s administration is promoting instructional technology as a crucial part of higher education for faculty and students same as other universities. Especially, as one of the most rapidly developing disciplines, the education revolution of computer must be able to keep up with development of the discipline. According to our statistics, there are more than 80% students to develop a relatively unsophisticated website as their diplomas project every year. Only a few outstanding students can develop an application software with more complicated. Anyway, the computer education of HU is facing some crucial issues during developing as follows: z

z

z

Weak sense of responsibility and teamwork spirit; these students as potential programmers, it is a horrible thing if without teamwork spirit. It is well known that a good team can excel at producing high-quality work, boosting productivity, and inspiring company loyalty. Therefore, strong teamwork spirit is a primary requirement of any company recruiting followers. It is widely believed that one person can not finish a big project such as Windows Operating System, even the person is a talent. In addition, sense of responsibility is a part of requirement of teamwork spirit; every team member should be responsible for his work with strong sense of responsibility. Lack of initiative and capability of self-study and hands-on; obviously, most students have already used to do their jobs with absolute fixed pattern of behavior learning from the teachers. It is fairly rigid just like the computer executes the program, step by step. These students usually feel flummoxed when they meet a new question and do not know how to find a solution by self-study. However, they usually can get a good score from examination, because the examination is limited to out of the scope of outline. Narrow focus on, most students attain knowledge only from classes, from teachers, can not make a better use of the Internet to extend the range of their knowledge; Limited by the scope of outline and time, students acquired knowledge from the classroom is fairly limited. They still retain the thinking mode of the phase of primary and middle school on study that it is just study the knowledge the teacher teaching in class and gets a good result from exam that is enough. Few of them are aware of the importance of extra-curricular learning.

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3 Issues and Solutions Analysis For change this situation, we feel obliged to deal with these problems for guaranteeing the quality of education. Then what are the major causes of the previous problems? After cautious research, some causation has been found out as follows: 3.1 The Textbook Issue As a contrast, a textbook in class of China, the impact on teaching is much larger than in class of the United States. Because the role of the textbook is significantly different as follows: in China, teachers usually carry out the teaching plan in strict accordance with a textbook, do not advocate mentioning other knowledge out of the book scope; in America, the textbooks only works as reference books, and not only limited to one book [3]. In another words, most teachers of China have been used to teaching on textbook-directed instead of on knowledge-oriented. A textbook will narrow a student’s focus on if he lack of initiative and capability of self-study to extend the range of his knowledge by the Internet or other books. Therefore, we should change the traditional way, try to select a couple valuable reference books for the students. It will be better if the teachers offer guidance for reading at the same time. 3.2 Teaching Methods and Examination Forms Reform The teacher as an important role is thought to be an important risk factor in education. The teaching method, examination forms, professional skills and knowledge and other personal characters of teachers such as pursuing spirits, communication and presentation skills, all of these factors are fairly important in teaching activity. Among of these factors, the opinions on the teaching method, examination forms and professional skills and knowledge should be able to reach a consensus and worth to discuss. Not only just we hold the idea that traditional teaching method based on textbook-directed and examination-oriented should be reformed. Reference [4] [5] [6] have already discussed the disadvantages of the traditional teaching method and have respectively offered their own suggestion for teaching reform. Based on our case study research, some proposals in our opinion are presented as follows: To start with, the teachers should keeping update their professional skills and knowledge. Teaching in a subject, the teacher should master related skills and knowledge concerning this subject: the development history, the current technology, achievement and hot discussed topics, even the future trends of development. The computer science is one of the fastest developing subjects. To be a better teacher in computer, up to date in professional skills and knowledge must be. Next, as proverb says, “Give a man a fish and you feed him for a day. Teach a man to fish and you feed him for a lifetime.” As a teacher, it is important to understand that teaching student how to solve a question is much better than just tell them the answer of a question. In addition, a teacher must understand he/she is a leader to guide students how to learn, how to solve problems, not just a knowledge transfer between textbooks and

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students in class. Teaching students how to use the Internet resource and reference books to extend professional knowledge will make a better use of the limited class time. Finally, improve the form of teaching, the form and content of examinations and make them serve their purpose better. Panel discussion, group projects are useful for training teamwork spirit and communication skills of students. Presentation is helpful for training students to express their opinions. And the examination should consider every phase of previous teaching forms. The content of homework, projects and examination should be related with the practice application. This will help enhance the sense of accomplishment and interest of students in learning. 3.3 Understand the Program Objectives of Computer Clearly Since 2003, as HU upgrade from a normal specialized postsecondary college upgrade to a university, the new program objectives was proposed as, “The Bachelor of Engineering (Engineering in Computer Science and Technology) program aims to prepare graduates for gain a professional qualification in the field of computer and entry-level positions as IT professionals. The program provides a broad and thorough study of the essential knowledge and practical skills required by graduates preparing for a career in the IT profession.” Every teacher should understand the program objectives clearly, because it is guidance for designing the outline and teaching plan for their responsible courses. It is well known that the computer can be used in literally any field, limited only by the imagination of its programmers and the ingenuity of its associated hardware engineers. And the experiments and projects related various practical applications will ensure the students understand this point as well. Therefore, a teacher should attempt to design more experiments and projects related more practical applications for his/her responsible courses. This way also can be able to enhance the sense of accomplishment and interest of students in learning.

4 Some Difficulties Exist The traditional teaching methods and educational concepts are still stamped upon the minds of people that were formed over the years. It is not easy to be changed. Furthermore, to make better implement of these new concepts to reform education, it is need superior departments support. Therefore, some difficulties are unavoidable. They are: Firstly, the administration department of HU expects standardized instruction: standard examination, standard handout format, etc.; it is for pass the National Evaluation of Undergraduate Teaching Quality (NEUTQ). The NEUTQ has very deep influence on the development prospects of every college or university, the administration department have to lay much stress on it. Only a few elective courses, the teacher have choice to teach in their own way. It is already beyond the scope of our capabilities to change this situation. And secondly, many teachers seem reluctant to change the existing teaching model; Education reform not only need spend much time, but also need devote more energy to it. Few teachers willing to do it except it must to be done.

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Thirdly, from primary school to college or university, the students have already used to accept the traditional teaching method. In fact, the teaching methods such as panel discussion, group projects and presentation are difficult to achieve the desired effect. This situation is not just several courses’ reform can be changed except the whole education system has a significant revolution.

5 Discussion Many well-known educationalists and scholars have realized that the Chinese traditional education model exists many problems need to be changed. Qin Xuesen, a well-known physics of China had asked a question while in his deathbed: “why Chinese schools have not nurtured outstanding elitists?” As more and more people concerning this issue, the exist problems is likely to be solved soon.

References 1. Fincher, S., Petre, M.: Computer science education research, p. 1. Taylor & Francis Group, London (2004) 2. Sun, J.H., Zhu, Y.B., Fu, J.W., Xu, H.C.: The Impact of Computer Based Education on Learning Method. In: 2010 International Conference on Education and Sport Education, ESE 2010, Wuhan, China, vol. 1, pp. 76–79 (2010) 3. Zhu, Y.X., Zhen, H.: Comparison of Choice of Textbooks in Universities between China and the United States. Igher Educational Research in Areas of Communications (6), 104–105 (2004) (in Chinese) 4. Han, H.Y.: Researching on Teaching Method of Undergraduate Education. Joural of Jilin Business and Technology College 25(3), 86–88 (2009) (in Chinese) 5. Duan, H., Wang, S.: Deepen Education Reform Innovative Teaching Modes. China University Teaching 4, 35–37 (2009) (in Chinese) 6. Deng, Y., Shang, Q.: A Comparison of Chinese and American College Textbooks, Teaching Methods and Curriculums. Journal of Zhanjiang Normal College 22(10), 34–37 (2001) (in Chinese)

The Existence and Uniqueness for a Class of Nonlinear Wave Equations with Damping Term Bo Lu and Qingshan Zhang Department of Mathematics, Henan Institute of Science and Technology, Xinxiang 453003, P.R. China [email protected],[email protected]

Abstract. In this paper the existence and uniqueness of the global generalized solution and the global classical solution are studied by the Galerkin method, The class of nonlinear wave equations describe the propagation of long waves with the viscosity in the medium with the dispersive effect. It can also be governing the problem of the longitudinal vibration of the 1-D elastic rod. Keywords: nonlinear wave equation with damping term, initial boundary value problems, global generalized solution, global classical solution.

1 Introduction In this paper we are concerned with the following initial boundary value problem

utt − 2bu xxt + α u xxxx = β (u xn ) x ,

x ∈ ( 0, 1) , t > 0,

(1.1)

u ( 0, t ) = u (1, t ) = 0, u xx ( 0, t ) = u xx (1, t ) = 0, t ≥ 0,

(1.2)

u ( x , 0 ) = φ ( x ) , ut ( x, 0 ) = ψ ( x ) , x ∈ [ 0, 1]

(1.3)

where α > 0, b > 0 are constants, u(x, t)is the unknown function. The subscripts x and t indicate the partial derivative with respect to x and t, respectively, n ∈ N, (x) and (x) are given initial value functions definite in [0, 1]. The equation (1.1) is contacted with many equations. For example, in the study of a weakly non-linear analysis of elasto-plastic-microstructure models for longitudinal motion of an elasto-plastic bar in [1] there arises the model equation

φ

ψ

utt + α u xxxx = β ( u x2 ) , x

(1.4)

where u(x, t) is the longitudinal displacement, α > 0, β = 0 are any real numbers. Moreover, the special solution of equation (1.4), its instability, and the instability of the ordinary stain solution were studied in [1]. In [2], [3], the authors studied the problem for determining solution of the generalized equation of the equation (1.4). And the authors proved the existence and uniqueness of the global generalized S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 530–533, 2011. © Springer-Verlag Berlin Heidelberg 2011

The Existence and Uniqueness for a Class of Nonlinear Wave Equations

531

solution and the global classical solution of several initial boundary value problems by the contraction mapping principle, and give the sufficient conditions of the nonexistence of the solution. Because the equation (1.4) can describe the propagation of the wave in the medium with the dispersion effect, it’s meaningful[4] to study the following nonlinear wave equations with the viscous damping term. The paper [5], [6] studied the equation with the viscous damping term proved the global existence, asymptotic property of its solution of the initial boundary value problem, gave some sufficient conditions of the blow-up of the solution. In this paper, we are going to prove the existence and uniqueness of the global generalized solution and the global classical solution of the initial boundary value problem (1.1)--(1.3) by Galerkin method.

2 Existence and Uniqueness of Global Generalized Solution of the Problem (1.1)-(1.3) We are going to prove the existence and uniqueness for the problem (1.1)-(1.3) by Galerkin method and compactness theorem in this section. First of all, we’ll study the initial boundary value problem (1.1)--(1.3). 2 Let yi ( x ) be the orthonormal bases in L [0, 1] composed of the eigenvalue

{

}

problem

y′′ + λ y = 0, x ∈ ( 0, 1) ,

(2.1)

y ( 0 ) = y (1) = 0 corresponding to eigenvalue λi (i =1, 2,

d . ), where ′ = dx

Let N

u N ( x, t ) = ∑ γ Ni ( t ) yi ( x )

(2.2)

γ

i =1

be Galerkin approximate solution of the problem (1.1)-(1.3), where Ni(t) are the undetermined functions, N is a natural number. Substituting the approximate solution uN(x, t) into Eq.(1.1) and the initial value functions, multiplying both sides by ys(x) and integrating on (0, 1), we obtain

( uNtt

− 2bu Nxxt + α u Nxxxx , ys ) =

﹒﹒

( β (u ) , y ) , n Nx x

s

s = 1, 2,

N , (2.3)

2

where ( , ) denotes the inner product of L [0, 1]. Substituting the approximate solution uN(x, t) and the approximate of the initial value functions into Eq.(1.1) and initial conditions (1.3), we get

γ Ns (0) = μ s , γ Ns (0) = ν s , s = 1, 2,

N,

(2.4)

In order to prove the existence of the global generalized solution for the problem (1.1)--(1.3), we make a series of esti- mations for the approximate solution uN(x,t) .

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Lemma 2.1[6]. Suppose that n ≥ 3 and n is an odd number. φ∈H [0,1] , ψ∈L [0,1], n+1 ψx∈L [0,1], and φ(x) and ψ(x) satisfy the boundary conditions(1.2). Then for any 2 N, the initial value problem (2.3), (2.4) has a global classical solution γNs ∈ C [0, T ] (s = 1, 2,…,N). Moreover, the following estimate holds: 2

u N (⋅, t )

2 H2

+ u Nt (⋅, t )

2

≤ C1 (T ),

2

t ∈ [0, T ],

(2.5)

where and in the sequel C1(T ) and Ci(T )( i = 2, 3,…) are constants which only depend on T . Lemma 2.2[6]. Suppose that the conditions of Lemma 2.1 hold. φ∈H [0,1] , 2 ψ∈H [0,1], then, the approximate solution of the problem (1.1)--(1.3) satisfies the following estimate: 4

u N (⋅, t )

2 H4

+ u Nt (⋅, t )

2 H2

+ u Ntt (⋅, t ) ≤ C3 (T ), 2

t ∈ [0, T ], (2.6)

Theorem 2.1. Suppose that n ≥ 3 and n is an odd number, if φ∈H [0,1], ψ∈H [0,1], and φ(x) and ψ(x) satisfy the boundary conditions(1.2), the initial boundary value problem (1.1)--(1.3) exists the unique global generalized solution 4

2

u ∈ C ([0, T ]; H 4 [0, 1] ) ∩ C1 ([0, T ]; H 2 [0, 1]) ∩ C 2 ([0, T ]; L2 [0, 1]) , (2.7) where u(x, t) satisfies the boundary value conditions (1.2) in the generalized sense, and it satisfies the initial value conditions (1.3) in the classical sense. Proof: From (2.6) we know that

u N ∈ C ([0, T ]; H 4 [0, 1] ), u Nt ∈ C1 ([0, T ]; H 2 [0, 1]), u Ntt ∈ C 2 ([0, T ]; L2 [0, 1]) . Using Sobolev imbedding theorem[7] we have

u Nxs ∈ C ([0, T ] × [0, 1] ), 0 ≤ s ≤ 3, u Ntxs ∈ C ([0, T ] × [0, 1]), 0 ≤ s ≤ 1. According to Ascoli--Arzela theorem we see that we can select a subsequence still denoted by {uN(x, t)} from {uN(x, t)}, such that there exists a function u(x, t) and when N → ∞ the subsequence {uN(x, t)} uniformly converges to the limiting function u(x, t) in [0, T ] × [0, 1]. The corresponding subsequence of the derivatives {uNx(x, t)} also uniformly converges to ux(x, t) in 0, T ] × [0, 1]. And according to the compactness principle, the subsequence {uNxs(x, t)}(0 ≤ s ≤ 4), {uNxst(x, t)}(0 ≤ s ≤ 2), and {uNtt(x, t)} 2 weakly converge to the uxs (x, t)(0 ≤ s ≤ 4), uxst(x, t)(0 ≤ s ≤ 2), and utt(x, t) in L ([0, T ] × [0, 1]), respectively. Hence, we get u(x, t) satisfies (2.7). Sense u(x, t) satisfies the boundary value conditions (1.2) in the generalized sense, and it satisfies the initial value conditions (1.3) in the classical sense. Therefore, u(x, t) is the generalized solution of the problem (1.1)--(1.3). It’s easy to prove the uniqueness of solutions of the problem (1.1)--(1.3). This completes the proof of the theorem.

The Existence and Uniqueness for a Class of Nonlinear Wave Equations

3

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Existence and Uniqueness of Global Classical Solution of the Problem (1.1)--(1.3)

Lemma 3.1[6]. Suppose that the conditions of Lemma 2.2 hold. φ∈H [0,1] , 5 ψ∈H [0,1], then, the approximate solution of the problem (1.1)--(1.3) satisfies the following estimate: 7

u N (⋅, t )

2 H7

+ u Nt (⋅, t ) + u Nttt (⋅, t )

2 H5 2 H

1

+ u Ntt (⋅, t ) ≤ C4 (T ),

2 H3

(3.1)

t ∈ [0, T ],

Theorem 3.1. Suppose that n ≥ 3 and n is an odd number, if φ∈H [0,1], ψ∈H [0,1], and φ(x) and ψ(x) satisfy the boundary conditions(1.2), the initial boundary value problem (1.1)--(1.3) exists the unique global generalized solution 7

5

u ∈ C ([0, T ]; C 4 [0, 1] ) ∩ C1 ([0, T ]; C 2 [0, 1]) ∩ C 2 ([0, T ]; C[0, 1]) , (3.2) where u(x, t) satisfies the initial boundary value conditions (1.2) and (1.3) in the classical sense.

4

Conclusion

By the method in Section 2 and Section 3, we can obtain the other initial boundary value problem of the equation.

References 1. An, L.J., Peire, A.: A weakly nonlinear analysis of elasto-plastic-microstructure models. SIAM J. Appl. Math. 55(1), 136–155 (1995) 2. Chen, G.W., Yang, Z.J.: Existence and nonexistence of global solutions for a class of nonlinear wave equations. Math. Meth. Appl. Sci. 23, 615–631 (2000) 3. Zhang, H.W., Chen, G.W.: Potential well method for a class of nonlinear wave equa-tions of fourth-order. Acta Mathematica Scientia 23A(6), 758–768 (2003) 4. Guenther, R.B., Lee, J.W.: Patial Differential Equations of Mathematical Physics and Integral Equations. Prentice Hall, NJ (1988) 5. Yang, Z.: Global existence asymptotic behavior and blow-up of solutions for a class of nonlinear wave equations with dissipative term. J. Differential Equations 187, 520–540 (2003) 6. Chen, G.W., Lu, B.: The initial C boundary value problems for a class of nonlinear wave equations with damping term. J. Math. Anal. Appl. 351, 1–15 (2009) 7. Mázja, V.G.: Sobolev Spaces. Springer, New York (1985)

Research on the Distributed Satellite Earth Measurement System Based on ICE Middleware Jun Zhou, Wenquan Feng, and Zebin Sun School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing, 100191, China [email protected]

Abstract. Satellite earth measurement is one of the crucial steps during the development of satellites, and also plays an important role in system validation and performance evaluation. This paper presents a distributed satellite earth measurement system based on ICE(Internet Communication Engine) middleware, which guarantees the high scalability and flexible configuration by decoupling the correlative relationship between the message distributers and subscribers in the system, and thereby realizes the dynamic location and loadbalance. The system implementation and test results prove that this system performs better in distributed deployment, flexibility and network wideband occupancy compared with traditional systems. Keywords: Satellite earth measurement, Internet communication engine, middleware, distributed.

1 Introduction Satellite earth measurement is one of the crucial steps during the development of satellites, and also plays an important role in system validation and performance evaluation. Satellite earth measurement system itself is a sophisticated giant system whose design and implementation process are affected by many factors. First of all, during its application, measuring units of the system have to constantly and periodically transfer all sorts of results to difference-based service units, during which information intercourse is of distributing-subscribing model. Second, different data reports’ transmission may have different requirements in transferring efficiency, safety and reliability, which requires the information intercourse to effectively support those differences. In addition, in view of the diversity of the measuring environments, the system has to be operated on multi-platforms. But in current system, the compact coupling association between measuring units and service units has severely limited the scalability of the system, so the different needs of service units cannot be meet. Meanwhile, the current system has a poor inter-operability and is hard to be practically deployed in large scale. Information subscribe/publisher system based on ICE (Internet Communication Engine) middleware provides a new solution for the above-mentioned problems. ICE middleware guarantees the system high scalability and flexible configurations by decoupling the association between publishers and subscribers, which lays a realistic foundation for the distributed design of the large satellite earth measurement system. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 534–541, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Based upon the above analysis, this paper presents a new design of distributed satellite earth measurement system based on ICE middleware. Compared with traditional one, the new system is effectively simplified, realizes the dynamic location and load-balance of the target server, and performs much better in distributed deployment, flexibility and the occupancy of network bandwidth.

2 The Distributed Design Principle Based upon ICE Middleware Middleware technology is a very important supporting technology in establishing a distributed system and widely applied in the design. But the existing middleware technology has defects in cross-platforms, performance, inter-operability and convenience of development at different degree. As an object oriented middleware platform, ICE could provide tools, general interfaces and database supports based on different operating systems and programming languages for establishing object oriented distributed application system; ICE also provides simple object model, simple but strong functional general interface, efficient and compact protocol, plentiful calldispatch mode, which puts forward a new idea for the design of satellite earth measurement system. Firstly, ICE provide subscribe/publish services, ICEStorm, which could de-couple the compact coupling association between information publishers and subscribers, therefore guarantees the system’s high scalability and flexibility. Traditional information subscribe/publish mode is shown as the Fig. 1.

subscriber

publisher

subscriber

subscriber

Fig. 1. Traditional information subscribe/publish mode

Under traditional information subscribe/publish mode, publishers periodically provide information to subscribers, which demands publishers to manage subscribers’ registration information, monitor data transmission, and recover errors. But in practical operation, there are many publishers and subscribers. When subscribers subscribe different information, publishers have to cost lots of resources to manage and maintain the above-mentioned details, which severely limited the scalability and flexibility of the system. While in ICE structure, ICEStorm plays as a agency between publishers and subscribers. When publishers are ready to publish a new message, they no longer pay attention to subscribers and just simply send a request to the ICEStorm server who is full in charge of transferring message to subscribers. On the other side, subscribers just have to interact with ICEStorm server, finish tasks like subscribing or cancelling it and obtain interested information. With this logic, publishers and subscribers could concentrate on their own application logic, which greatly simplifies the subscribe/publish process. subscribe/publish mode based on ICEStorm is shown as the Fig. 2.

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subscriber

ICEStorm

publisher

subscriber

subscriber

Fig. 2. Subscribe/publish mode based on ICEStormc

Information distribution also could be categorized by subjects. Subscribers could choose their interested subjects, and only information consistent to subjects will be publisherd to particular subscribers. Therefore this structure is especially suitable for large scale difference application environments. Moreover, ICE provides publisherd management service for locating and activating ICE application program. Fig.3 presents an example of topic federation. Topic T1 has links to T2 and T3, as indicated by the arrows. The subscribers S1 and S2 receive all messages published on T2, as well as those published on T1. Subscriber S3 receives messages only from T1, and S4 receives messages from both T3 and T1.

6 3

7

6 3

7

6 3

7

6

Fig. 3. Topic federation

The service is consist of registration positioning service and arbitrary nodes. They cooperate to manage information and service processes consisting of the application, provide redundancy for the same service running in different servers. Thus, when one of the servers cannot provide service, the other servers in the same group could provide the same service to the client.

3 Distributed Satellite Earth Measurement System Based on ICE Middleware Analyzing the demands of the system and integrating the advantages that ICE have in information subscribe/publish and publisherd management service, this paper puts forward a implementation solution for the publisherd satellite earth measurement system based on ICE middleware, which is shown as Fig.4.

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interface

interface

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interface

interface

Server Software Modules Server

Server

Server

Server

VISA-DTEA net

ICE middleware

Cosumer

Cosumer

Cosumer

Fig. 4. Distributed satellite earth measurement system based on ICE middleware

Function modules of the system are of distributed deployment and systematically integrated based on ICE middleware so as to support the system’s measurement. The front-end measuring units mainly include three types: a series of intelligent devices providing hardware interface functions, computers with specific software functions, and computer software controlling standard commercial instruments. In practical application, the system deploys one or more measuring units according to the changes of the measuring targets. The front-end measuring units measure all kinds of orders, signals and data, such as satellite remote sensing, satellite remote control and satellite position, through multiple measuring interfaces, produce data reports of various themes by digesting the measuremecnt datac, and publisher them to differences service units to process relevant tasks. Based on ICE middleware technology, the system de-couples the association between service units of the satellite earth measurement system, thereby achieves flexible configurations of the system and efficient distribution of the data, and eventually realizes the dynamic location and load-balance. In the aforesaid system, a safe and effective event message communicating mechanism plays a crucial link in the design of the satellite earth measurement system. The design of the system’s event message transfer module is shown as Fig.5. Ice general interface

Receiving thread poolt

Netword connection

Distribute thread pool

Event buffer

Qos

Memory

Fig. 5. The design of the system’s event message transfer module

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The functions of the modules are as follow: z ICE general interface: realizing standardized communications in heterogeneous environment. z Receiving thread pool management: managing the thread pool that receives events, processing concurrent events according to priorities. z Distributing thread pool management: managing thread buffer pool that publishers events. z Network connection management: limiting the number of publisherd and received concurrent events z Event buffer management: publisherrs send event messages to buffer zone which sequentially forward them to sending thread. z QoS management: managing QoS parametersc of informatcion transmission. z Memory management: unified allocation and release of cmemory Based on the aforesaid function design, the process of the event message transmission is shown as Fig.6.

Message sender

Message receive

Interface

Interface

Send command

Binding identify

Enter event buffer zone

connection

Waiting for network

Thread pool

Event buffer zone

Data decode

Waiting data

Qos management

Qos

Qos

Qos management

connection

Waiting network

Waiting network

connection

Ice general interface

ICEStorm server

Ice general interface

Fig. 6. The process of the event message transmission

In Fig. 6, before the sending end sends a message, the receiving end have to call a user interface binding to its unique identity, and establish network connection with ICEStorm to receive messages. After the connection is established, the receiving end enters waiting for data state, returns the received data to upper application through callback function. The distribution end calls for user interface to publisher message and sends event messages to event buffer zone with sequential priorities; when there is a idle thread in the distributing thread pool, the event message will be picked out of the event buffer zone, and the transfer parameters will be managed by QoS. When the data is ready, it waits for the connection management module allocates handles of network

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connection. During this period, connection management module will first decide whether there is an idle connection or a multiplexed connection, and return network connection handle when there is one. The general transmission interface publishers messages to ICEStorm server by calling for handles. After receiving an event message, ICEStorm server will first traverse subscribers relevant to the theme of the message, and sequentially forward the message to each subscriber. After receiving the event message, the receiver will wait for the receiving thread pool allocate a processing thread, correspondingly process the data after acquiring the handle of the receiving thread, and eventually send it to the callback functions that subscribers registered to receive. We take a theme T1 for example as follow, in order to briefly demonstrate the process of event messages publishe/subscribe of the satellite earth measurement system. The publisherr’s implementation process is as follow: z First acquire an agent of theme management; z Acquire an agent of T1 theme, if the theme doesn’t exist, then create one, or acquire an existing theme; z Acquire the “publisherr object” agent of theme T1; z In the end collect and publisher the event message. The subscriber’s implementation process is as follow: z z z z z z

First acquire an agent of the theme management; Create an object adapter as the host of the theme interface; Instantiate the agent and activate it by the object adapter; Subscribe theme T1; Process the message of the report until it is closed; Cancel the subscription of theme T1.

4 System Test In order to verify the validity of the design of the system and test its performances, this paper established a testing environment, shown as Fig.7.

server

73/,1. URXWHU

client

client

client

client

Fig. 7. Testing environment

The testing environment is a 100M LAN established by TP-LINK SOHO router. There are 5 computers who all have the same Windows XP Professional SP3 operation system, dual-core processor, 2G memory, 100M/1000M adaptive net card. One of the 5 computers play as a server, sending data to the others. Each of the other

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4 client computers open 4-6 clients, which makes 20 clients in all. The server will send orders to clients with a rate of 10 frames/s. The byte length of every order is 30K. The test time is 24*3 hours. The testing result is shown as table 1. Table 1. duration

Volume (K/m)

Feedback time(s)

packet rate

The 1st 24hours

10*20*60*30= 12000*30

0.00098

The 2nd 24hours

10*20*60*30= 12000*30

The 3rd 24hours

10*20*60*30= 12000*30

loss

Reported time

Qos

0.01%

<0.003

100%

0.00094

0.0089%

<0.003

100%

0.00099

0.0093%

<0.003

100%

The test results shows that the volume of the order transmission is 10*20*60=12000 frames/m; the volume of the data transferred is 12000*30K=360000K/m. After inspecting log information of the 24*3 hour test, we find the server operate normally and send orders correctly; its feedback time is less than 0.001s; packet loss rate is under 0.01%, and report in 0.003s after losing a packet; the command packets with QoS could be sent by 100%. The results are far beyond the satellite earth measurement system s performance indexes and meet the requirements of the design. In order to test the event message transmission performance under rough network environment, we limit the network speecd to 1M. The server send orders to clients with a rate of 10 frames/s. The byte length of every order is 5K. The test time is 24*3 hours. The volume of the order transmission is 10*20*60=12000frames/m; the volume of the data transferred is 12000*5K=60000K/m. The results show that the system could reach the satellite earth measurement system s performance indexes even under a relatively rough network environment and full loaded. In this paper, we use single-ended subscriber timing method to test throughput.Test case contains a publisher and a subscriber, the publisher is incessant publishing event, the subscriber continues to receive events. The number n events in time for Tn, the throughput is calculated as:

’

’

T = EVENT SIZE * n / (Tn-T1)

Fig. 8. Throughput test

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The results shown in Figure 8, when the event is small, the throughput with events increases linearly with increase in size, but due to network bandwidth and Environmental factors such as hardware constraints.The throughput increases to 9MB / S reaches the limit.

5 Conclusion Analyzing the needs of the satellite earth measurement, this paper put forward a satellite earth measurement system based on ICE middleware. Relying on the technological advantages of the ICE middleware, the system de-coupled the association between the service units of the satellite earth measurement system, accomplished the flexible configuration of the system and the hi-efficient data distribution, and realized the dynamic location and load-balance of the target server. Eventually, the system test effectively verified the validity and performances of the solution.

References 1. ZeroC. Publisherd Computing with Ice. Revision 3.4 (June 2010), http://zeroc.com/doc/index.html 2. Joseph, H.Y.D.: Space Telecommunications Systems Engineering. Plenum Press, New York (1983) 3. Chen, Y.-y.: Satellite Radio Monitoring and Control Technology. China Astronautics Publishing House (2007) 4. Tesauro, G.: Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies. IEEE Internet Computing 11, 22–30 (2007) 5. Gokul, S., Cristiana, A.: Towards end-to-end quality of service: controlling I/O interference in shared storage servers. In: Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, Springer-Verlag New York, Inc., Leuven (2008) 6. Welch, V., Siebenlist, F., Foster, I., Bresnahan, J., Czajkowski, K., Gawor, J., Kesselman, C., Meder, S., Pearlman, L., Tuecke, S.: Security for grid services. In: The Twelfth IEEE International Symposium on High Performance Distributed Computing, Seatle, Washington, pp. 48–57 (June 2003) 7. Blanquer, J.M., Batchelli, A., Schauser, K.E., Wolski, R.: Quorum: Flexible Quality of Service for Internet Services. In: Processings of Symposium on Networked Systems Design and Implementations, NSDI 2005 (2005)

The Analysis and Optimization of KNN Algorithm Space-Time Efficiency for Chinese Text Categorization Ying Cai and Xiaofei Wang Dept. of Computer Science and Technology, Beijing Information Science & Technology University Beijing, 100101, P. R. China [email protected], [email protected]

Abstract. The performance of any algorithm for text classification are reflected in the of reliability classification results and classification algorithm is high efficient. We analyze the space-time efficiency of different stages based on the traditional KNN algorithm process for Chinese text classification and ensure the reliability of classification. And we optimize efficiency of the algorithm and the feasibility in the practical application from these aspects including feature extraction, feature weighting, similarity computing etc. Keywords: KNN Algorithm, Space-Time Efficiency, Text Categorization, Feature, Feature Vector, Similarity.

1 Introduction With the Web site of resources and the popularization of electronic text, the human began to pursue an efficient and reliable method of information processing in response to the rapid development of information technology industry brought about by the explosion of knowledge and other issues. Now many scholars concern the text classification technology. Text classification will be determined by one or more pre-defined class method based on the text content [1]. The current text classification methods can be divided into general rule-based calssifying and statistical-based classifying which including Decision Tree, K-nearest neighbor (KNN), Support Vector Machine, Bayes etc.[2]. However, the performance of any classification is reflected in two aspects, namely, the reliability and high efficiency of the classification algorithm. Chinese text classification requires more reliability and efficiency because of its inherent complicated, confusing meaning of the word, language forms and other characteristics. The text classification algorithm is often optimized for the reliability of the algorithm itself and is very difficult to implement it. At the same time it is easy to ignore time and space efficiency of classification algorithms. Or efficiency for the algorithm optimization of a certain stage, the whole traditional classification algorithms advantage is dispersed weakened. Therefore we analyze the efficiency of time and space in difference stage in order to get a reasonable proportion of S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 542–550, 2011. © Springer-Verlag Berlin Heidelberg 2011

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space-time according to the process of traditional KNN algorithm. It can get high efficiency and feasible for optimization algorithm of the practical application in ensuring the reliability of classification.

2 KNN Algorithm 2.1 KNN Algorithm Overview Traditional KNN algorithm is a simple and effective non-parametric algorithm. It is outstanding in the precision and recall rate. But its main problem is a high feature dimension space[3]. KNN is a lazy learning method, the calculation of large sample similarity, classification time is nonlinear, training fast but classification slow. And KNN classifier is strongly affected by the distribution of training data in efficiency. Its computational is unbearable in the general computer environment[4]. Traditional KNN algorithm is one of the most useful classifier as a Chinese text. It is deserved to study and exploration for the performance analysis and optimization. 2.2 Traditional KNN Algorithm Process The basic idea of the traditional KNN algorithm can be expressed as: According to the traditional vector space model, text features are formalized as the weighted feature vector[5]. For a given text to be classified, calculate similarity (distance) for each text in the training set. Then select the K texts with the nearest distance between the training set of documents and text sets to be classified. Determine which categories of the new text [6] according to the above K texts category. The algorithm flow is as the Figure1.

Fig. 1. Traditional KNN Algorithm Flow

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2.3 The Principles of Traditional KNN Algorithm KNN algorithm design and implementation of the optimization process should follow a few principles to improve the space-time efficiency of algorithms. (1) Store intermediate results with a disk file. (2) Minimize the number of disk file access. (3) Hash table used as the basic storage structure.

3 KNN Algorithm Space-Time Efficiency Analysis We analyze the space-time efficiency of the traditional KNN algorithm. It will divide three stages including feature extraction, feature vector computing and similarity computing. 3.1 Feature Items Analysis The solution of feature item on the traditional KNN algorithm exists time and space both defects. First, the current widespread use of evaluation function to extraction feature items. But the evaluation function only increase in the extraction accuracy within a limited, and the time cost and the calculation cost of flat text similarity is same, timeconsuming is too high and increase the training corpus part of the burden. Secondly, feature extraction is not strictly the requirements of space resources, however, the characteristics of large-scale text feature entry will greatly increase the computational complexity of subsequent algorithms. In the calculation feature vector stage, each feature item is calculated as a dimension of vector. 3.2 Feature Vectors Analysis It is the basis in the text classification that the document was changed into the format computer can do it by using simple and accurate method [7]. Formalization of the classic text is as the feature vector with feature as following: (W1,W2,W3,…,Wn), where Wi is the ith weight of feature item. The text formalization of the feature is calculated by assigning weight and form feature vectors. Feature vectors are composition numerical by weight. Feature items weighted based on the following two main experiences [1]. (1)The more lexical item appearing in a text the more it related to the subject of it. (2)The more times appear set of lexical items in the text the worse the term discrimination between items. Traditional KNN algorithm use tfidf(term frequency–inverse document frequency), weighting formula[7], that is, feature items wk in the text t k weight is: tfidf ( w k , t k ) = # ( w k , t k ) * lg( N /# w k )

(1)

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# ( wk , t k ) is the number of the feature item wk appearing in the text t k . N is the total number of text , # wk is the number of text when appearing the feature wk . High dimension of feature vectors, is generally more than 20 World Wide Web, commonly used feature vector stored in two ways. (1) Using fixed-length dimensions to store text feature vector. It takes up a lot of storage space, easy to calculate similarity and seek fast. (2) Using variable length dimensions to store text feature vector. Saving only the characteristics of each item in the real text, need small space, not easy to calculate the similarity, a large seek time. The tfidf algorithm with weight is as follows. for(text_i=first_text to N) for(i_tag_j=i_first_tag to text_i.length) begin #t_j++; for(text_k=first_text to N) if(search i_tag_j in text_k) #w_j++; end return #t*log(N/#w); The time complexity above algorithm is O (n3) and space complexity is O(1). It costs so more time by repeatedly opening the disk file in the inner loop that it becomes the bottleneck for the weighting algorithm. Consider the separation of the inner loop, or cut down to a constant level for the inner cycle. 3.3 Similarity Analysis We calculate the similarity between the test and the training corpus to reflect how similarity and provide data support for the classification. We use cosine formula as a formula for calculating the similarity in Chinese text categorization [8]. Between the text t i and t j , the similarity is : M

sim ( t i , t j ) = ( ∑ w ik * w jk ) / k =1

⎛ M ⎞⎛ M ⎞ ⎜ ∑ w ik2 ⎟ ⎜ ∑ w 2jk ⎟ ⎝ k =1 ⎠ ⎝ k =1 ⎠

(2)

wik is the kth feature item weight in the text t i . M is the total number of feature items. Because the traditional KNN algorithm needs to calculate the similarity with each training text, and therefore simplifying the training process will cost a lot of time[9].The traditional KNN algorithm for classification is low efficiency. Testing corpus choose single text . The basic design of the similarity is replacing time with space. Traditional similarity algorithm is as follows. for(weight_i=first_weight to M) put into hashtable ha; for(text_j=first_text to N) for(j_weight_k=j_first_weight to M) if(search j_weight_k in ha) sim_j();

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The time complexity of algorithm is O(n2), space complexity is O(n). But if we use a conventional algorithm to calculate the similarity of large texts, time complexity will increase to O (n3), then control the time consumption is particularly important.

4 Optimization Scheme of KNN Algorithm and Test Then with the results of KNN algorithm space-time efficiency analysis, we design and test space-time efficiency optimization schemes according to every stages. Mainly including extraction of feature items optimization scheme, feature items weighted optimization scheme, similarity calculation optimization scheme. 4.1 Features Extraction Optimization and Test

The feature item data are the most is resources in the KNN classification algorithm. If the evaluation function is ignored, the establishment of good quality stop words can also reduce the dimension of feature vectors, and to ensure time efficiency of the algorithm. At present, stop words table is no uniform standard [10]. According to different extraction method stop words can be constructed of different tables, the space-time classification algorithm will affect the performance. Feature extraction program supports different items filter design is as follows. if(word.length()>lower_limit && word.length
Choose different word frequency, word combinations form different feature item extraction scheme. The test result is as the Table1. It includes 500 training Corpus. Table 1. Testing Result of Features

No.

Word Frequency

Speech Part

1 2 3 4 5 6 7 8 9 10

>99 >99 >499 >499 >999 >999 <1000 <1000 <500 <500

Noun noun,verb Noun noun,verb Noun noun,verb Noun noun,verb Noun noun,verb

Feature Extraction Time(ms) 3407 3250 3594 3719 3453 3609 3500 3531 3469 3578

The different test results are as the Figure 2.

Feature Storage space(KB) 416 660 205 380 154 293 265 371 214 284

Feature Vector Dimension 206846 228281 1884 3228 841 1495 212241 233114 211198 231381

The Analysis and Optimization of KNN Algorithm Space-Time Efficiency

4.2 Optimization of Feature Items with Weight and Test

We design tfidf optimization algorithm as the following. for(text_i=first_text to N) for(i_tag_j=i_first_tag to text_i.length) #t_j++; for(tag_group_i=first_tag_group to tag.group) for(text_j=first_text to N) if(search tag_group_i in text_j) #w_group_i++;

The test results are as the Table2. It includes 500 training Corpus.

Fig. 2. Feature Analysis

Table 2. Testing Result of Feature Weighting

Size of feature set 1 100 1000 10000 50000 100000 200000

Computing time (ms) 78739100 821850 110950 15953 7609 5422 5000

Auxiliary storage space 4 400 4000 40000 200000 400000 800000

Fig. 3. Analysis of Feature Weighting

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As the group size increases, the time complexity of the algorithm tends to O(n2), space complexity tends to O(n). When the block size is 1, optimization algorithm is the same to the traditional one. When the block size is greater than 100, the time cost is reduced, space is increased slightly, and the system is easy to bear. Therefore, the optimization algorithm is feasible and effective. 4.3 Optimization Scheme of Similarity Calculation

We consider to using the space instead of time if test corpus is composed of the text corpus. We send all the training feature vectors into memory, also can get the similarity. Optimized algorithm time complexity is O(n2) and space complexity increase to O(n2) but it still can withstand within the system. for(train_text_i=train_first_text to N) for(i_weight_k=i_first_weight to M) put into hashtable hash_train[]; for(test_text_j=test_first_test to N) for(j_weight_k=j_first_weight to M) if(search j_weight_k in hash_train[]) sim_j();

5 Classifier Design and Test After the optimization of traditional KNN algorithm, the space-time efficiency is improved and more reasonable. But this high efficiency must based on the ensuring of reliability. 5.1 Classifier Design Select the K Neighbors. Select the K training text with big similar as the K neighbors for the current test version. In practical problems, it is difficult to determine the K value of the selected, often only rough estimates based on experience. This method of valuation may cause a decline in the accuracy of KNN algorithm. Scoring by Category. Test the text similarity of K neighbors by accumulation, accumulated value will be scored [11]. Classification Proposed. According to the principle of the KNN algorithm, we should include the class which is in the highest scores. 5.2 Performance Indexes

Classification proposed is on the direct basis of evaluating the classification performance by Classifier. The following performance test index is generally used. 1) accuracy rate = number of correctly assigned to the particular type of the text / actual number assigned to certain types of the text. 2) the recall rate = number of correct assigned to certain types of text / text of the actual number to be assigned to certain types.

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3) Standard measure is as following formula (3), where p is the accuracy, r is the recall rate,:β the weight of precision and recall rate. F1 measure is taken when β is 1.

Fβ = (1 + β 2 ) pr /( β 2 p + r )

(3)

5.3 Classifier Testing

Sougou Corpus was selected which involve the nine categories including financial business, information technology, food hygiene, sports, tourism, education exams, employment workplace, culture arts, military weapons. There are 1990 paper in each category. Dictionary contains 275,613 words, excluding stop words 68767 words. Choose 900 test text which is 5% of total corpus. Classifier test results is as shown the Table 3. Table 3. Testing Result of Classifier

K 20

100

400

800

1500

Performance index Precision Recall F1 Precision Recall F1 Precision Recall F1 Precision Recall F1 Precision Recall F1

FB

IT

FH

SE

TV

EE

EW

CA

MW

91.1 92.0 91.5 89.3 92.0 96.5 87.3 89.0 88.1 84.0 89.0 86.4 80.9 89.0 84.8

83.7 82.0 82.8 82.7 81.0 81.8 81.8 81.0 81.4 81.1 77.0 79.0 81.5 75.0 78.1

81.0 85.0 82.9 83.3 85.0 84.2 84.2 85.0 84.6 96.5 82.0 88.7 87.1 81.0 83.9

94.1 95.0 94.5 96.0 96.0 96.0 98.0 96.0 97.0 99.0 95.0 96.9 99.0 95.0 96.9

78.0 78.0 78.0 86.1 87.0 86.6 85.3 87.0 86.1 85.3 87.0 86.1 85.2 86.0 85.6

69.9 86.0 77.1 72.7 88.0 79.6 72.1 88.0 79.3 72.9 86.0 78.9 74.1 86.0 79.6

79.8 79.0 79.4 80.8 80.0 80.4 81.2 82.0 81.6 77.0 87.0 81.7 77.2 88.0 82.2

85.3 58.0 69.1 88.6 62.0 72.9 89.6 60.0 71.9 87.0 60.0 71.0 100.0 61.0 75.8

92.4 97.0 94.6 91.5 97.0 94.2 91.7 97.0 94.3 100.0 99.0 99.5 100.0 99.0 99.5

Performance test results above are automatically statistics by the classifier without manual checking. The results show that K value has little influence on the classifier. The above implementation and testing environment for the computer is 2GHz CPU frequency, 3GB main memory, Windows XP operating system, Java Language compiler. Thus, the traditional KNN algorithm efficiency is recognized by common PC environment. The weighted average time of feature vectors are 63ms / articles, similarities average time 4043ms / articles, the traditional KNN classifier level are classified time 125ms / articles.

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6 Conclusion In this paper, we analysis time and space efficiency for the conventional KNN algorithm of Chinese text classification process. We present a set of detailed efficiency optimization scheme in ensuring the reliability of the classification including extraction of feature items optimization scheme, feature items weighted optimization scheme, similarity calculation optimization scheme. Tests results satisfied the expected results. Acknowledgment. The research is supported by the General program of science and technology development project of Beijing Municipal Education Commission under Grant No.KM201010772012, Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality Grant No.PHR201007131 and Beijing Municipal Organization Department Project talent under Grant No.2010D005007000003.

References 1. A Survey on Automated Text Categorization, http://wenku.baidu.com/view/64589a4bcf84b9d528ea7a45.html 2. Guo, G.D., Wang, H., Bell, D., Bi, Y.X., Greer, K.: An KNN Model-based Approach and Its Application in Text Categorization. J. Computer Science, 986–996 (2003) 3. Yang, Y.M., Pedersen, J.O.: A Comparative Study on Feature Selection in Text Categorization. In: 14th Int’l Conf. on Machine Learning (ICML 1997), pp. 412–420. Morgan Kaufmann Publishers, San Francisco (1997) 4. Vries, A.D., Mamoulis, N., Nes, N.: Efficient KNN search on vertically decomposed data. In: 2002 ACM SIGMOD International Conference on Management of Data, pp. 322–333. ACM Press, Madison (2002) 5. Sun, R.Z.: An Improved KNN Algorithm for Text Classification. J. Computer Knowledge and Technology. 6(1), 174–175 (2010) 6. Ma, J.B., Li, J., Teng, G.F., Wang, F., Zhao, Y.: The Comparison Studies on the Algorithm of KNN and SVM for Chinese Text Classification. Journal of Agricultural University of HeBei 31(3), 120–123 (2008) 7. Wang, X.Q.: Research of KNN Classif ication Method based on Parallel Genetic Algorithm. Journal of Southwest China Normal University 35(2), 103–106 (2010) 8. Zhu, G.H., Cheng, C.P.: An Improved k-Nearest Neighbor Classification Method. Journal of HeNan Institute of Engineer Ing., 65–67 (2008) 9. Liu, B., Yang, L., Yuan, F.: Improved KNN Method and Its Application in Chinese Text Classification. Journal of Xihua University 27(2), 33–36 (2008) 10. Zhou, Q.Q., Sun, B.D., Wang, Y.: Study on New Pretreatment Method for Chinese Text Classification System. J. Application Research of Computers (2), 85–86 (2005) 11. He, F., Lin, Y.L.: Summary of Improving KNN text classification algorithm. J. FuJian Computer (3), 33–36 (2005)

Research of Digital Character Recognition Technology Based on BP Algorithm Xianmin Wei Computer and Communication Engineering School of Weifang University Weifang, China [email protected]

Abstract. This paper describes the digital character recognition process and steps. Using artificial neural networks with momentum term and adaptive learning rate back-propagation algorithm to train and identify the ideal signal and noise signal containing the number of characters. By comparing the results to obtain that using the same network with the ideal signal and noise signal for training the network, the system can be more fault-tolerant. Keywords: Neural network, BP algorithm, a noisy digital character recognition.

1 Introduction Digital recognition technology in the field of image processing is an important research direction, and it is one of the hot areas of computer application. It consists of on-line handwriting recognition and off-line handwriting recognition. In the former system, through recording lifting pen, falling pen, on the spatial location of each pixel of handwritten figures, as well as the time between strokes and other information, in processing that information, the system extracts information characteristics by certain rules, then the recognition module compare and and identify the characteristics of the information with characteristics of library, and finally converted into computer language code. the latter compared with the former without Stroke information, it is more difficult, more widely used, such as bank notes, business reports, financial statements, statistical reports and other forms system is a focus of current research, but also a difficulty. This article describes how to use the neural network back propagation algorithm (BP algorithm) for offline handwritten digit recognition.

2 Simple Process of Hand-Written Numbers with BP Algorithm BP algorithm used in a simple digital identification process as "pre" and "BP character recognition," specifically shown in Figure 1.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 551–555, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Fig. 1. BP Number Recognition

The premise work of Digital Identification is to change the visual image into binary image with computer processing, which uses a given threshold metod to change pixels in the image into two colors according to a certain standard. However, fonts of binary images blurred in many cases, or spread appearing messy white or dark dots, causing some difficulties to identify, using gradient sharpening methods to sharpen the image, so that the blurred image becomes clear, and can play a role in removing noise. When identification Only by the characteristics of each digital character to determine, so the binary image after sharpening needs to be split into individual characters, for character refinement. Shelling algorithm commonly used, from the boundary of layer by layer to remove the black spots until you find a collection, this collection coincides with the boundary (thickness of 1 or 2.) In order to extract the characteristics of any character, also normalized the digital characters, that is the size of the character transforms into a uniform size, character position (rotation, translation) corrected. Many people believe that regulation of each character image into 5 × 9 pixels of a binary image is ideal, because the smaller size of the image, the higher the recognition rate, the faster network training. In fact, compared to identify the character images, 5 × 9-pixel map is too small. The normalized, the image information is lost a lot, when the image recognition, the accuracy is not high. Experimental results show that the regulation of a character image into 10 × 18 pixels binary image is the real ideal. Processed from the characters is split, the extract can best embody the characteristics of the character feature vectors, on behalf of the BP into the network, the network training. Then extract the sample to be identified in the generation of feature vectors into the trained BP network, the character can be identified. Commonly used method of extracting a feature vector extraction method pixel by pixel, frame feature extraction method, extraction of vertical and other statistics. This experiment uses a pixel-by-pixel extraction method.

3 BP Neural Network for Number Identification 3.1 BP Neural Network Structure and Description BP network is a multilayer feedforward networks with one-way transmission. In addition to input and output nodes in the network, there are one or more layers of hidden nodes, nodes in one layer do not couple. Input signal from the input layer nodes in turn pass through the hidden layer, then spread to the output node. The output of each layer is only under the influence of output layer. The node unit characteristics (transfer function) is usually Sigmnid type, of which, a slope parameter for the Sigmnid, by changing the parameter a, will be different slope Sigmnid function.

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The basic idea of BP algorithm is: For an input sample, after weights, thresholds, and activation function operation, get a output, and then compared it with the expectations of the sample, if any deviation, from the output began to backpropagation deviation, to adjust the right value and the threshold, and output of network gradually become the same as hope output. Thus, BP algorithm is based on the steepest descent method, the steepest descent method as the inherent disadvantages: falling into local minimum easily, slow convergence and causing oscillation effect, in adjusting the weights to use the momentum method, which accelerated convergence rate, and to some extent reduce the probability of falling into local minimum, but can not completely overcome these shortcomings. To speed up the convergence rate, also used the adaptive learning rate. 3.2 Design and Training of Neural Network The goal is to identify 10 numeric characters from 0 to 9. Each character is divided into small pieces of 5 × 7 to digitize, respectively represented by a vector. 10 input vectors which containing 35 elements is defined as an input vector matrix, vector represents a letter, the corresponding location of a data value is 1, while the other position is 0. There are two types of data such as input: one is in an ideal state of the signal; the other is to use randomly generated noisy signal. The network for fast training, learning rate, the initial value selected in 0,01 - 0, 7 between. Connection weights obtained random number between -1 and 1, the initial value of the expected distortion is a random number between 0 and1. Network through outputing a 10-element output vectors to distinguish these numeric characters, such as character 1 corresponding to the vector, the elements of its first position is 1, while the subsequent location of the element value is 0. After input and output to be determined the network structure can be designed. Layer 1 is the input layer, based on the above analysis of the data to be identified to determine the neural network input layer has 35 nodes; layer 2 is hidden layer, the conventional method for determining the contacts is twice the input layer, but to rely on experience and methods to try to determine the number of nodes, through the system error test with different structures to determine the hidden layer nodes is 10 nodes, shown in Table 1. Table 1. Signals Training and Test Error with Noise of Hidden Layer Number of hidden neurons

5 10 15

Training error

0.099121 0.098804 0.099700

Test error

0.308258 0.129052 0.225840

Layer 3 is the output layer, the target output vector which containing 10 data shows that the layer has 10 nodes. Hidden layer and output layer activation function are Sigmnid, S-type function on the network structure shown in Figure 2.

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Fig. 2. Logarithmic S-function network structure

To find a suitable training methods, and found with the increasing of samples number, training results of separate BP method or adaptive learning rate BP are not ideal, but both adaptive learning rate and momentum term of the BP training algorithm works well, Therefore using this function to train the neural network. In order to produce a certain input vector network fault tolerance, the best way is to use both with an ideal signal and noise signal to train the network. In this study, the first using 15 group ideal signal to train the network; the 2nd using 15 signals with noise first and then the ideal signal with 15 groups on the same network training. With 10 kinds of increasing noise signal, which is obtained by the ideal signal alphabet to add the average of 0, standard deviation from 0.05 to 0.5. Changes in network training error is shown in Figure 3.

Fig. 3. Error changes of the training process without noise

Observed indicators of these curves shows that training time can be quickly achieved. Meanwhile, in using different levels of noise signal case, respectively, from 0 to 9 numbers for the 10 100 tests, the network identification error rate curve with the noise signal shown in Figure 4.

Fig. 4. Recognition error rate curve

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Dotted line in Figure 4 is the error recognition rate curve without the error training network, solid line is the error recognition rate curve with the network trained by the error. It can be seen that from Figure 4 the network training error tolerance is greatly improved.

4 Experimental Results and Analysis Identification method of BP neural network, to take the whole character directly as input of neural network. 500 selected number characters, where 200 of them are training samples, the remaining samples are test data. Test results in Table 2. The results show that: character recognition based on neural network method has strong fault tolerance and a strong adaptive learning ability, it is a good recognition. Table 2. Experimental Results Item

Total samples

Training 200 samples Test 300 samples

Rejection Recognition Error Error rate recognition recognition number rate number

Rejection rate

200

0

0

100%

0%

0%

282

9

9

94%

3%

3%

Identified number

Acknowledgments. This paper is funded by 2011 Natural Science Foundation of Shandong Province, its project number is 2011ZRA07003.

References 1. Bian, Z.: Pattern recognition. Tsinghua University Press, Beijing (2002) 2. Yang, S.: Image pattern recognition technology-VC + +. Tsinghua University Press, Beijing (2005) 3. Chen, Y.: Feedforward network pattern recognition preprocessing method to handwritten digit recognition application. Chinese Academy of Sciences Semiconductors, Beijing (1995) 4. Yang, Y.: Based on Neural Network Handwritten Digit Recognition. East China Geological University 26(4), 383–386 (2003) 5. Roth, M.W.: SurveyofNeural Network Technologyfor Automatic Target Recognition. IEEE Trans. Neural Networks 1(1), 28–43 (1993)

Image Segmentation Based on D-S Evidence Theory and C-means Clustering Xianmin Wei Computer and Communication Engineering, School of Weifang University, Weifang, China [email protected]

Abstract. On the basis of the Dempster-Shafer evidence theory, this paper given the multi-source information fusion method based on Dempster-Shafer evidence theory, and applied information fusion technology of Dempster-Shafer evidence theory in the classification of bamboo image texture. The image data for the DS classification, the user need to train samples, and proposed an D-S method of automatically obtaining the training sample in accordance with image feature and C-means clustering algorithm. First, the image is divided into several regions, each region containing images using wavelet decomposition to remove the edge of the area, and then calculate the remaining energy of the mean smooth area as the feature value, use the C-means clustering algorithm to smooth the regional classification, the feature value and type of training samples labeled as DS, and finally training of the classifier to segment the image. Experimental results show that the proposed method has achieved good segmentation results. Keywords: Dempster-Shafer evidence theory, texture, C-means clustering.

1 Introduction Dempster-Shafer evidence theory is an expansion of the classical form of the probability theory, trust function of evidence is associated with upper and lower probability values, and using trust function and likelihood function to explain the multi-valued mapping, and on this basis, dealing with uncertain information to form the theory of evidence. Classification of image texture image features can not be separated on the selection and extraction, a single feature can not meet the requirements of the image target classification and recognition. To this end, the DS evidence theory based on the extracted image texture features based on the use of it for information fusion, the final decision-making strategies using the image texture classification. This paper first decomposed the full image into more detailed sub-graph by wavelet decomposition, then applied the mean center of mobile convergence to reduce the amount of data, then made the fuzzy C-means clustering on the center of the convergence, making the texture characteristics of the image more concentration. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 556–561, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Texture Feature Extraction In this paper, extraction of texture features, with wavelet analysis of the image first, then the clustering features of the image texture is more prominent. 2.1 The Multi-layer Structure of Wavelet Decomposition Wavelet decomposition of an image can be decomposed into the approximation signal and the horizontal layer by layer, vertical and diagonal detail component, and then decomposition made on the details of the components to n layers, its decomposition diagram in Figure 1.

Fig. 1. Schematic diagram of full wavelet decomposition ((a) Original, (b) wavelet decomposition, (c) wavelet frame)

2.2 Mean Shift Algorithm Mean shift algorithm is approach which based on the texture density gradient to estimate the center of the cluster, can deal with unsupervised cluster classification. Mean shift algorithm is a move in the feature space sample points close to the average, until convergence to a specific location. The location is considered the center of the texture. For any point to itself as the center and radius of a given point within the region mean shift algorithm processing in order to achieve the purpose of convergence. Shown in Figure 2. Mean shift algorithm formula is: (1) In (1), x is any point, n is the number of points, h is the window radius or bandwidth, d is the dimension of feature space, K as the core, and its calculation formula is:

(2)

Where Cd is the capacityof the d-dimensional space.

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Fig. 2. Data Convergence points diagram of mean shift algorithm

2.3 Fuzzy C-means Clustering

≦ ≦

For any finite set of data models {xm;m=1......M}, the number of clusters c (2 C M), cluster weight index w, 1 <w <∞, initialize matrix elements of the division of fuzzy clustering is , where c = 1 ..... C, m = 1 ...... M, Fuzzy C-means clustering by minimizing on the membership matrix U and cluster center V of the objective function to be achieved. Matrix U(0) formed by the C × M. Performing the following steps:

①calculated of cluster centers using ②update U(l)， apply ，where ③ if ,then the loop ends ， where

。

。

ε is the convergence

threshold, when the time to meet the objective function of the type similar to the minimum, or return to the first step to continue. The algorithm has been shown to have good convergence. Weighted index w determined the degree of fuzzy clustering , w is too small, the effect of clustering is not good, w is too large, the effect of clustering unclear, experiments show that w = 2, clustering effect is good.

3 D-S Evidence Theory Classification of Bamboo Cells 3.1 D-S Evidence Theory D-S evidence theory is proposed by Demptster in 1967, with expansion and development by Shafer, it is also known as the D-S theory. Evidence deal with the problem of uncertainty and data redundancy. It used trust function as a measure, by the probability of an event to be binding, confidence-building function, and use information in decision-making methods to eliminate uncertainty and redundancy. In this paper, the basic structure of the probability distribution function method, first choose a variety of textures under a priori categories of texture images constitute the training sub-sample model library; then be identified blocks of texture images, respectively, each feature extraction block fi , respectively with the model library to match the texture image corresponding to features, to calculate the correlation

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coefficient Pi (j), j on behalf of the texture model library classification number, and finally by Pi (j) fi structural characteristics of the basic probability assigned texture mi as fi and texture characteristics of the maximum j (j). Here's how: correlation coefficient j. (3) The distribution coefficients of characteristic i and the correlation texture; (4) It is characterized by a reliable factor. In order to use D-S combination rules, the correlation coefficient to be transformed by the basic probability function. Features i given target the basic probability value of mi (j), the Pi (j) j formed feature fi which given basic probability texture: (5) Feature i given the recognition framework Θ with the basic probability value, that is, the uncertainty of the probability characteristics: (6) It can calculate a single feature (the image gray value and GLCM entropy) of the basic probability value, and then calculate the basic probability integration features. Value from the basic probability distribution functions and confidence can be calculated likelihood function, resulting in evidence of confidence intervals, the difference between the level of ignorance expressed proposition. 3.2 Classification Rules The analysis and decision-making of basic probability distribution function, using rulebased methods to analyze significance based on probability distribution, determine the following four rules: a) target class should have a maximum value of the basic probability distribution; b) target category the basic values and other types of probability distribution of the basic difference between the value of the probability distribution must be greater than a threshold value λ1, it means that all the different types of evidence for each level of support should be kept large enough difference; c) uncertainty probability mi ( Θ) must be smaller than a certain threshold value λ2, the level of the target categories of ignorance or uncertainty of evidence can not be too big; d) the basic probability distribution of target class value must be greater than the probability of uncertainty mi (Θ), ie know very little of a target, you can not on its classification. In summary, the application basic steps of D-S evidence theory for image texture classification are as following; extract the image texture of the image gray value and GLCM entropy, and model base texture matching, calculation of correlation coefficient; each were calculated evidence of basic probability assignment function, belief function and likelihood function; use of combination rules,

②

①

③

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integration of all the evidence obtained under the basic probability assignment function of trust and the likelihood function; according to decision rule, choose the largest integrated under the assumption that the evidence.

④

4 Experimental Results This treatment targets is to select cell's horizontal bamboo screen, Figure 3 (a) is a bamboo stalk of bamboo stem cross-section of the original crystallization of vascular images, Figure 3 (b) is the application of edge detection based on phase consistency

(a) single-crystal graph of vascular

(b) segmentation based on phase coherence

(c) extraction based on shapefeature Fig. 3. The process of image segmentation

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for the initial segmentation results Figure 3 (c) is the application of the edge information based on morphological characteristics of the regional growth area of the segmentation result. By comparing the original figure of Figure 3 (a) with the processing results of Figure 3 (c), which shows that it is in general satisfactory. It not only split out of the vascular area, and loss of crystalline fibrous cap smaller amount of information, more complete information about the target area reserved for the accuracy of extracting feature information to provide a guarantee.

5 Conclusion In view of the natural features details of the image texture with rich diverse, for single-use application of D-S evidence theory and fuzzy C-means clustering in many cases can not meet the requirements of image segmentation. Segmentation method described in the text using mean shift algorithm, centralized information area. Application of D-S evidence theory and then test using the border to provide the potential for regional growth and regional models. Automatically selected using the seed point boundary information, complete the final segmentation, region segmentation analysis based on the characteristics of regions of interest. Experimental results show that the method for image texture segmentation, and has good robustness, segmentation results obtained with the human visual system to determine basically the same. Acknowledgments. This paper is funded by 2011 Natural Science Foundation of Shandong Province, its project number is 2011ZRA07003.

References 1. Ma, W.M., Chow, E., Tommy, W.S.: A new shifting grid clustering algorithm. Pattern Recognition 37(3), 503–514 (2004) 2. Pilevar, A.H., Sukumar, M.: GCHL: A grid-clustering algorithm for high-dimensional very large spatial data bases. Pattern Recognition Letters 26(7), 999–1010 (2005) 3. Nanni, M., Pedreschi, D.: Time-Focused clustering of trajectories of moving objects. Journal of Intelligent Information Systems 27(3), 267–289 (2006) 4. Birant, D., Kut, A.: An algorithm for clustering spatial-temporal data. Data & Knowledge Engineering 60(1), 208–221 (2007) 5. Cai, W.L., Chen, S.C., Zhang, D.Q.: Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation. Pattern Recognition 40(3), 825–833 (2007) 6. Sun, J., Liu, J., Zhao, L.: Clustering algorithm. Journal of Software 19(1), 48–61 (2008) 7. Ke, Y., Zhang, J., Sun, J., Zhang, Y., Zhou, X.: Combined with support vector machines and C means clustering for image segmentation. Computer Application 26(9), 2082–2083 (2006) 8. Tian, J., Li, Y., Cao, R.: A Markov process and the evidence theory based on multi-source image fusion segmentation methods. Microelectronics & Computer 23(2), 27–34 (2007) 9. Wang, Y., Han, J.: Dempster-Shafer theory of evidence based on iris image classification method. Xi’an Jiaotong University 39(8), 829–831 (2005)

Time-Delay Estimation Based on Multilayer Correlation Hua Yan, Yang Zhang, and GuanNan Chen School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China [email protected], [email protected]

Abstract. Time-delay estimation technique is a key to acoustic temperature field measurement. In order to acquire a stable acoustic time-of-flight in low SNR, a time-delay estimation method combined multilayer cross-correlation and multilayer auto-correlation (MC method for short) is proposed. Crosscorrelation method and second correlation method are described briefly for comparison. Theory analysis and simulation research in MATLAB prove that MC method can obtain highest estimation precision among these three methods when the signal to noise ratio is low. Keywords: time-delay estimation, multilayer cross-correlation, multilayer autocorrelation, low SNR.

1 Introduction Temperature field measurement based on acoustic time-of-flight (TOF) tomography [1] has been used in atmospheric monitoring and heat management. It has many advantages such as nondestructive, noncontact sensing and quick in response. Timedelay estimation technique is a key to acoustic temperature field measurement. Time-delay estimation is an important signal processing problem and has received significant amount of attentions during past decades in various applications, including radar, sonar, radio navigation, wireless communication, acoustic tomography, etc [1]. The signals received at two spatially separated microphones in the presence of noise can be modeled by

r1 (t ) = s (t ) + n1 (t ), r2 (t ) = s (t − D ) + n2 (t ), (0 ≤ t ≤ T )

(1)

where r1(t) and r2(t) are the outputs of the two microphones, s(t) is the source signal, n1(t) and n2(t)represent the additive noises, T denotes the observation interval, and D is the time-delay between the two received signals. Time-delay estimation is not an easy task because of various noises and the short observation interval. There are many algorithms to estimate the time-delay D. The cross-correlation (CC) is one of the basic algorithms. Many methods, such as second correlation (SC) method [2] and generalized correlation method [3] develop based on this algorithm. There are two forms of correlations: auto- and cross-correlations. The crosscorrelation function is a measure of the similarities or shared properties between two signals. It can be used to detect/recover signals buried in noise, for example the S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 562–567, 2011. © Springer-Verlag Berlin Heidelberg 2011

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detection of radar return signals and delay measurements. The autocorrelation function involves only one signal; it is a special form of cross-correlation function and is used in similar applications. In order to acquire a stable acoustic time-of-flight in low SNR, a time-delay estimation method combined multilayer cross-correlation and multilayer auto-correlation (MC method for short) is proposed in this paper, and compared with cross-correlation method and second correlation method.

2 The Principle of Time-Delay Estimation Based on Correlation 2.1 The Cross-Correlation (CC) Method

The CC method cross-correlates the microphone outputs r1(t) and r2(t), and considers the time argument that corresponds to the maximum peak in the output as the estimated time- delay. The CC method can be modeled by:

DCC = arg max[ Rc (τ )] τ

Rc (τ ) = E[ r1 (t ) r2 (t + τ )] = E[ s (t ) + n1 (t )][ s(t − D + τ ) + n2 (t + τ )]

(2)

= Rss (τ − D) + Rn s (τ − D) + Rsn2 (τ ) + Rn1n (τ ) 1

2

The signal and the noise are assumed to be uncorrelated. Thus Rn1 s (τ − D ) ,

Rsn2 (τ ) are zero. Also, the additive noises are assumed uncorrelated, thus Rn1n2 (τ ) is zero. However, Rn1n2 (τ ) is usually not be neglected in practice due to the existing correlation between the two noises. So we have

Rc (τ ) = Rss (τ − D) + Rn1n2 (τ ) = RS1 (τ − D) + N1 (τ )

(3)

where Rss (τ ) or RS1 (τ ) is the auto-correlation of the source signal s(t), RS1 (τ − D) reaches maximum when τ=D, Rn1n2 (τ ) or N1 (τ ) is the cross-correlation of noise n1(t) and n2(t). RS1 (τ ) and N1 (τ ) can be thought of as the signal component and noise component of Rc (τ ) , respectively. 2.2 Second Correlation (SC) Method

The auto-correlation of r2(t) can be expressed as

R1 (τ ) = E[r2 (t ) r2 (t + τ )] = E[( s (t -D) + n2 (t ))( s (t − D + τ ) + n2 (t + τ ))] =Rss (τ ) + Rn2 s (τ − D) + Rsn2 (τ − D) + Rn2 n2 (τ )

(4)

Assuming the signal and the noise to be uncorrelated, we have

R1 (τ ) = Rss (τ ) + Rn2n2 (τ ) = RS1 (τ ) + N1' (τ )

(5)

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where Rn2 n2 (τ ) or N1' (τ ) is the auto-correlation of noise n2(t). RS 1 (τ ) and N1' (τ ) can be thought of as the signal component and noise component of R1 (τ ) , respectively. The SC method cross-correlates R1 (t ) and Rc (t ) , and considers the time argument that corresponds to the maximum peak in the output as the estimated time- delay. The SC method can be modeled by:

DSC = arg max[ Rs (τ )] τ

Rs (τ ) = E[ R1 (t ) ⋅ Rc (t + τ )] = E ⎡⎣[ RS 1 (t ) + N1' (t )][ RS1 (t − D + τ ) + N1 (t + τ )]⎤⎦

(6)

Assuming the signal and the noise to be uncorrelated, we have

Rs (τ ) = E[ RS1 (t ) ⋅ RS1 (t − D + τ )] + E[ N1' (t ) ⋅ N1 (t + τ )] = RS 2 (τ − D) + N 2 (τ )

(7)

where RS 2 (τ ) is the auto-correlation of the signal RS 1 (τ )

, RS 2 (τ − D ) reaches maximum when τ=D, N 2 (τ ) is the cross-correlation of noise N1' (t ) and N1 (t ) . RS 2 (τ ) , N 2 (τ ) can be thought of as the signal component and noise component of Rs (τ ) , respectively. 2.3 Multi-Correlation (MC) Method

Correlation operation is an effective means of de-noising and increasing the signal to noise ratio. Therefore we try to estimate time-delay in low SNR by multiplayer correlation. The auto-correlation of R1 (t ) can be expressed as

R2 (τ ) = E[ R1 (t ) ⋅ R1 (t + τ )] = E ⎡⎣[ RS1 (t ) + N1' (t )][ RS 1 (t + τ ) + N1' (t + τ )]⎤⎦

(8)

Assuming the signal and the noise to be uncorrelated, we have

R2 (τ ) = E[ RS1 (t ) ⋅ RS1 (t + τ )] + E[ N1' (t ) ⋅ N1' (t + τ )] = RS 2 (τ ) + N 2' (τ ) where RS 2 (τ ) is the auto-correlation of the signal RS1 (τ )

(9)

, N 2' (τ ) is the auto-

correlation of noise N1' (t ) . RS 2 (τ ) , N 2 (τ ) can be thought of as the signal component and noise component of R2 (τ ) , respectively. The MC method cross-correlates R2 (t ) and Rs (t ) , and considers the time argument that corresponds to the maximum peak in the output as the estimated time- delay. The MC method can be modeled by:

DMC = arg max[ Rm (τ )] τ

Rm (τ ) = E[ R2 (t ) ⋅ Rs (t + τ )] = E ⎡⎣[ RS 2 (t ) + N 2' (t )][ RS 2 (t − D + τ ) + N 2 (t + τ )]⎤⎦

(10)

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Assuming the signal and the noise to be uncorrelated, we have

Rm (τ ) = E[ RS 2 (t ) ⋅ RS 2 (t − D + τ )] + E[ N 2' (t ) ⋅ N 2 (t + τ )] = RS 3 (τ − D ) + N 3 (τ ) (11) where RS 3 (τ ) is the auto-correlation of the signal RS 2 (τ )

, RS 3 (τ − D ) reaches maximum when τ=D, N 3 (τ ) is the auto-correlation of noise N 2' (t ) and N 2 (t ) . RS 3 (τ ) , N 3 (τ ) can be thought of as the signal component and noise component of Rm (τ ) , respectively.

3 Fast Implementation of CC, SC, and MC Methods Above correlation operations are implemented in discrete time. Sample r1(t) and r2(t) simultaneously, we have two data sequences r1(n) and r2(n), each containing N data. The cross-correlation R12 ( j ) between r1(n) and r2(n) can be expressed as

R12 ( j ) =

1 N

N

∑ r (n)r (n + j) 1

2

(12)

n=0

For longer data sequences, correlation operations can be speeded up by using the correlation theorem and fast Fourier transform as follows [4]. R12 ( j ) = IFFT ⎡⎣[ FFT (r1 (n)]* ⋅ FFT (r2 (n)]⎤⎦

(13)

where FFT and IFFT denote the inverse fast Fourier transform and fast Fourier transform, respectively. * is conjugate operator. The fast implementation of CC, SC and MC methods is given in Fig.1. In Fig.1, REAL means obtaining the real part and MAX means obtaining the peak position, respectively.

Fig. 1. The fast implementation of CC, SC and MC methods

4 Simulation Research In order to avoid the influence of acoustic travel-distance measuring error and so on, the acoustic travel-time estimation method based on multilayer correlation is verified

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using MATLAB simulation data. The acoustic source signal s(t) is a linear sweptfrequency cosine signal generated by chirp(t,f0,t1,f1) and the acoustic signal at receiving point can be written as s(t-τ). In this paper, f0=200Hz, f1=850Hz, t1=T/2=N/2/fs, N=25000 or 50000, fs=250kHz, τ= 0.014412 s. N is the number of samples, fs is the sample frequency. Simulation research shows that the acoustic travel-time estimation value is stable and exact if the noise is weak. But if the noise isn’t weak, the acoustic travel-time estimation value will fluctuate slightly. The standard deviation (std) and the relative root-mean-square error (R_RMSE) are used to assess the stability and accuracy of the travel-time estimation values. They are defined as follows. n

n

∑ (τ i − τ )

std =

i =1

n −1

,

τ =

∑τ i i =1

n

R _ RMSE =

1 n 2 (τ i − τ ) ∑ n i =1

τ

× 100%

(14)

where τ is the actual acoustic travel-time; τi is the ith estimation value of the acoustic travel-time; n is the number of measurement (estimation), in this paper, n=100. The estimation results when Gaussian white noises and colored noises are added are given in Table1 and Table 2, respectively. The colored noise is obtained by feeding the white noise through a band-rejection filter. The system function of the filter is

H (z) =

1− 2z

−1

2 − 1 .2 2 7 z − 2 − 0 .6 1 9 2 z − 3

(15)

Following can be found from Table 1~Table 4. 1) The stability and accuracy of time-delay estimation will decrease with the decreasing of SNR, or the decreasing of samples. 2) Among CC method, SC method and MC method, MC method has best stability and accuracy of time-delay estimation. Table 1. Estimation results when Gaussian white noise is added

SNR -5 -10 25000 -15 samples -18 -19 -5 -10 50000 -15 samples -18 -19

CC method std R-RMSE(%) 1.78e-5 0.1233 3.14e-5 0.2180 4.88e-5 0.3370 7.24e-5 0.5026 2.38e-4 1.6632 1.41e-5 0.0980 2.89e-5 0.2001 4.26e-5 0.2950 6.32e-5 0.4476 6.34e-5 0.4390

SC method std R-RMSE(%) 5.46e-6 0.0382 1.22e-5 0.0846 3.52e-5 0.2437 5.31e-5 0.3677 7.33e-5 0.5086 4.28e-6 0.0296 1.13e-5 0.0785 3.48e-5 0.2411 4.87e-5 0.3407 5.26e-5 0.3650

MC method std R-RMSE(%) 3.08e-6 0.0215 7.49e-6 0.0518 2.71e-5 0.1875 5.69e-5 0.3948 7.22e-5 0.5001 2.63e-6 0.0182 6.46e-6 0.0447 2.34e-5 0.1622 4.67e-5 0.3231 4.96e-5 0.3434

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Table 2. Estimation results when colored noise is added

SNR -5 -10 25000 -15 samples -18 -19 -5 -10 50000 -15 samples -18 -19

std 2.08e-5 2.04e-5 2.30e-5 2.10e-5 2.30e-5 1.60e-5 1.79e-5 1.77e-5 1.88e-5 1.87e-5

CC method R-RMSE(%) 0.1442 0.1411 0.1591 0.1454 0.1622 0.1106 0.1247 0.1231 0.1318 0.1304

std 1.32e-5 1.13e-5 1.06e-5 1.16e-5 1.27e-5 8.13e-6 8.84e-6 8.87e-6 8.48e-6 1.01e-5

SC method R-RMSE(%) 0.0928 0.0786 0.0736 0.0816 0.0879 0.0562 0.0611 0.0618 0.0585 0.0701

MC method std R-RMSE(%) 8.04e-6 0.0556 8.03e-6 0.0560 7.39e-6 0.0512 8.61e-6 0.0609 8.96e-6 0.0623 5.89e-6 0.0409 5.69e-6 0.0394 5.96e-6 0.0412 6.44e-6 0.0456 5.78e-6 0.0399

5 Conclusion In order to acquire a stable acoustic time-of-flight in low SNR, a time-delay estimation method combined multilayer cross-correlation and multilayer autocorrelation (MC method) is proposed and compared with cross-correlation (CC) method and second correlation (SC) method. Theory analysis and simulation research in MATLAB prove that MC method can obtain highest estimation precision these three methods when the signal to noise ratio is low. Acknowledgments. The work is supported by Natural Science Foundation of China (60772054), Specialized Research Fund for the Doctoral Program of Higher Education (20102102110003) and Shenyang Science and Technology Plan (F10213100).

References 1. Ostashev, V.E., Voronovich, A.G.: An Overview of Acoustic Travel-Time Tomography in the Atmosphere and its Potential Applications. Acta Acust. United Ac. 87, 721–730 (2001) 2. Gedalyahu, K., Eldar, Y.C.: Time-delay Estimation from Low-rate Samples: A Union of Subspaces Approach. IEEE T. Signal Proces. 58, 3017–3031 (2010) 3. Tang, J., Xing, H.Y.: Time Delay Estimation Based on Second Correlation. Computer Engineering 33, 265–269 (2007) (in Chinese) 4. Knapp, C.H., Carter, C.G.: The Generalized Correlation Method for Estimation of Time Delay. IEEE T. Acoust., Speech, Signal Processing ASSP21, 320–327 (1976) 5. Ifeachor, E.C., Jervis, B.W.: Digital Signal Processing: A Practical Approach, 2nd edn. Publishing House of Electronics Industry, Beijing (2003)

Applying HMAC to Enhance Information Security for Mobile Reader RFID System Fu-Tung Wang1, Tzong-Dar Wu2, and Yu-Chung Lu3 1

Department of Computer Science & Information Engineering, Ching Yun University, 32097 Taoyuan, Taiwan 2 Department of Electrical Engineering, National Taiwan Ocean University, 20224 Keelung, Taiwan 3 eSECURE Technology, Inc. 32068 Taoyuan, Taiwan [email protected]

Abstract. This study proposed a data protection framework to enhance information security for mobile reader RFID system. HMAC scheme was integrated to communication protocol between tag and reader under considering the security requirements, limited computation capability and memory space in passive RFID system. The system life cycle comprised initial, maintain and revoke phases. Then the security is analyzed and prototype is developed. The results demonstrate that the proposed approach meets the system security requirement and suits for mobile reader RFID system. Keywords: RFID, HMAC, weakness, security controls.

1 Introduction RFID is a contact-less automatic identification technology which combines information and communication technologies. It has become very popular and been applied in various business processes. The RFID application types of the most common are asset management, asset tracking, automated payment, access control, and supply chain management, etc[1-3]. An RFID system is comprised of tags, readers, and application systems. In system structure shown in Fig.1, the tag stores detail information of customer and the owner company. The RFID readers read or write data to tags and transfer the data to the application system by using a radio frequency interface.

Fig. 1. System structure diagram S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 568–573, 2011. © Springer-Verlag Berlin Heidelberg 2011

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The configuration of RFID system can be categorized as passive and active types. In present mobile era, active type application is more attractive to most company. However, there is a few of study, focusing at active type RFID systems, been found [4-11]. The situation what we face is that the ubiquitous computing is accompanied with new weakness which induces information attack. Moreover, owing to the wide distributed item sites in application environment, owned company could not manger assets satisfied. In general case, information attack occurs in some weakness and fails the service. The potential security controls are identified to mitigate the corresponding risks with following the Guidelines for RFID Systems [12]. The system security requirement have been highlighted in [13] as in Table.1. The remainder of this paper is presented as follows: Section 2 describes the proposed security protocol. Section 3 presents the system’s implement and discussion, Section 4 contains the conclusions. Table 1. Security requirement traceable mapping Security controls

Countermeasure scheme

Description Data stored in RFID tags are assigned 5.2.7 Non-revealing Specific security model and coded using specific format and identifier formats algorithm. Authentication techniques based on cryptography often provide integrity HMAC(password based 5.3.1 Authentication service for data included in the authentication and hash and data integrity transaction. It is used to prevent function) unauthorized reading from or writing to tags. 5.3.3 Tag data DES Include encrypting the data on tags. protection

2 Proposed Security Protocol The scope of this study is restricted in mobile reader RFID system. The back end system is assumed to be protected well because the well-defined information security infrastructure has been deployed. Since the tags were embedded in each item and the items were numerous and would be scanned at very close ranges. Passive tags made the most sense, given their low cost. Proposed system includes mobile device and server end. Mobile device provide function of operator logon, tag registration, secret key modification. The initial parts of authentication module has already included in the program. It will be inspired when reader communicate to tag. The server end does mainly the database management. It deals with the tag management. All the information of corresponding tag and operation record will be recorded by the server. Proposed framework implements the engineering aspects controls which concerned the authentication and privacy issue [14]. A two phase method to address these problems. In turn, the DES was employed to offer safer data storing and transferring. HMAC scheme and proposed protocol is used as an authentication scheme to enhance system security. The system life cycle comprises initial, maintain and revoke phases.

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F.-T. Wang, T.-D. Wu, and Y.-C. Lu

1) Initial phase: First, the tag embedded in item is carried on in factory and the secret keys belong to each tag are specified, stored in database. The related HMAC is generated and written to tags, the detail step is depicted in Fig.2. 2) Maintain phase: Third party personnel is responsible for deciding whether the tag is legal or not by checking the HMAC. Only and only if the HMAC match, maintainer can be allowed to process the next step and write the encrypted data to tag. The detail operation process is depicted in Fig.3. 3) Revoke phase: Only and only if the HMAC match, the tag could be revoked by following the same procedure as shown in Fig.3. ˦̇˴̅̇ ˖˴˿˶̈˿˴̇˸ʳ ˛ˠ˔˖ ˥˸̄̈˸̆̇ʳ̇˴˺ʳ ˷˴̇˴ ˪̅˼̇˸ʳ˛ˠ˔˖ʳ ̇̂ʳ̇˴˺ ˥˸˴˷ʳ̇˴˺ʳ˷˴̇˴ʳ ˶̂̅̅˸˶̇˿̌˒

Q

6KRZVXFFHVV PHVVDJH

\

˦˻̂̊ʳ˹˴˼˿ʳ ̀˸̆̆˴˺˸

˚˸̇ʳ̇˴̅˺˸̇ʳ ˼́˹̂̅̀˴̇˼̂́ (QG

Fig. 2. The initial phase flow chart Start

Is the right Tag?

Request tag data

n

Read tag data correctly? y

Show fail message

n

y

Write encrypted data(maintain/ revoke) to tag

Reflash the database

Get target information Show success message

Calculate HMAC End

Fig. 3. The maintain process flow chart

Show fail message

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3 Discussion and System Implement As mentioned previously, lower computation ability and limited memory space is a severe limitation of most of RFID systems, and either more efficient cryptography scheme or a more intelligent protocol design is required to improve security and system performance. The HMAC approach to RFID offers attractive factors due to its lower computing time and memory space saving compared to the digital signature scheme. Proposed mechanism achieves the two-way authentication from tag to reader. Since the tag identification number is seen as a unique number and only legal operational reader keeps the correct key to corresponding tag. Illegal reader does not have permission to read the tag information while the reader fails to pass the validation process for HMAC checking. The hash function makes the integrity of tag identification number and company’s secret key information for sure. Moreover, enhanced security is assured because the data sent from the tag takes DES encryption method. Finally, each tag has a different secret key and all keys have no any obvious relationship, hacker can not deduct keys to other tags, even thought they broke the key of a certain tag. Hackers can not reveal hardly the data stored in Tag. Based on the proposed system architecture and security framework, a patrol prototype system was developed on Microsoft Visual studio 2005. The server management interface is shown in Fig.4 and the mobile device interfaces is shown in Fig.5. The patrol related data are shown in Fig 6. After the legal tag is verified, the current time and responsible staff identification number was written to the tag.

Fig. 4. The server logon interface

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Fig. 5. The mobile device logon interface

Fig. 6. The patrol data recording interface

4 Conclusion Integrating RFID technique to asset management is an innovative application. The mobile reader based system is preferred. It can less human resources and analyzes business data in time. Then, a framework comprise HMAC authentication and DES encryption method has been proposed to protect information security. The prototype

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system demonstrates that the proposed approach can meet the system security requirement. Furthermore, the proposed method provides flexibility in spending the memory space. It is no doubt that Lower computation cost and more memory safe are two factors favoring the successful implement of the RFID. Proposed protocol is valuable for deploying a real RFID based asset management system and the security framework could also be used for other mobile reader RFID system deployment.

References 1. Chan, S.Y., Luan, S.W., Teng, J.H., Tsai, M.C.: Design and implementation of a RFIDbased power meter and outage recording system. In: IEEE International Conference on Sustainable Energy Technologie, pp. 750–754 (2008) 2. Rieback, M.R., Crispo, B., Tanenbaum, A.S.: The Evolution of RFID Security. IEEE Pervasive Computing, 62–69 (2006) 3. Wu, M.Y., Ke, C.K., Tzeng, W.L.: Applying Context-Aware RBAC to RFID Security Management for Application in Retail Business. In: IEEE Asia-Pacific Conference on Service Computing, pp. 1208–1212 (2008) 4. Ding, Z.H., Li, J.T., Feng, B.: A Taxonomy Model of RFID Security Threats. In: IEEE International Conference on Communication Technology, pp. 765–768 (2008) 5. Schaberreiter, T., Wieser, C., Sanchez, I., Riekki, J., Roning, J.: An Enumeration of RFID Related Threats. In: IEEE Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 381–389 (2008) 6. Sharif, V.P.: A Critical Analysis of RFID Security Protocols. In: IEEE International Conference on Advanced Information Networking and Applications, pp. 1357–1362 (2008) 7. Chien, H.Y.: Secure access control schemes for RFID systems with anonymity. In: 2006 International Workshop on Future Mobile and Ubiquitous Information Technologies, pp. 96–99 (May 2006) 8. Zhai, J., Park, C., Wang, G.: Hash-Based RFID Security Protocol Using Randomly KeyChanged Identification Procedure. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3983, pp. 296–305. Springer, Heidelberg (2006) 9. Avoine, G., Oechslin, P.: A scalable and Provably Secure Hash-Based RFID Protocol. In: Communications Workshops on IEEE Pervasive Computing, pp. 110–114 (2005) 10. Gao, X., Xiang, Z., Wang, H., Shen, J., Huang, J., Song, S.: An Approach To Security and Privacy of RFID System for Supply Chain. In: IEEE International Conference on E-Commerce Technology for Dynamic E-Business, pp. 164–168 (2004) 11. Kang, S., Lee, I.: A Study on New Low-Cost RFID System with Mutual Authentication Scheme in Ubiquitous. In: IEEE International Conference on Multimedia and Ubiquitous Engineering, pp. 527–530 (2008) 12. Karygiannis, T., Eydt, B., Barber, G., Bunn, L., Phillips, T.: Guidelines for Security Radio Frequency Identification (RFID) Systems. NIST: Special Publication 800-98 (2007) 13. Wang, F.-T., Wu, T.-D.: Information Security Study on RFID Based Power Meter System. In: IEEE International Conference on Information Management and Engineering, Chengdu, China, pp. 317–320 (2010) 14. Maiwald, E.: Nectwork Security, A beginner’s Guide. The McGraw-Hill Companies, New York (2003)

Analysis Based on Generalized Regression Neural Network to Oil Atomic Emission Spectrum Data of a Type Diesel Engine ChunHui Zhang, HongXiang Tian, and Tao Liu College of Naval Architecture and Power, Naval Univ. of Engineering, Wuhan Hubei 430033, China

Abstract. In order to deeply mine the information of Oil Atomic Emission Spectrum Data, a simulation model and a prediction model of Cu concentration of a type of six- cylinder diesel engine were established by applying Generalized Regression Neural Network. Seven different working conditions had been set up and sixty-nine oil samples had been taken from engine. The results show that the absolute errors of the simulation value of the 69 samples are within the acceptable accuracy indices and the absolute errors of the prediction value of the 19 samples are lower than the acceptable accuracy indices. It has been proved effective that Cu concentration can be predicted via Generalized Regression Neural Network algorithm. Keywords: Generalized Regression Neural Network (GRNN), Diesel Engine, Atomic Emission Spectrum, Wear elements.

1 Introduction Modern mechanical equipment and power plant commonly runs oil film of several microns, lubricating oil carries abundant wear information. The analysis of physics & chemistry performance target, grain and concentration of elements can reveal wear conditions, the oil quality decay and contamination of machine[1]. Oil monitor technique is a technique of obtaining information of lubricant and wear, predicting faults and ascertaining reasons, types and parts of faults through analyzing performance change of lubricant and wear debris carried of checked equipment[2]. There are many common methods of deeply mining information of oil atomic emission spectrum data, including the grey system theory[3], the Factor Analysis[4], the maximum entropy principle analysis[5], the correlation coefficient analysis[6], the regression analysis[7] and the support vector machines[8], etc. This paper aims at setting up a relation between the concentration of wearing elements of diesel engine and it’s loads, cylinders’ clearances and run-time oil renewed by applying Generalized Regression Neural Network (GRNN) to dealing with the oil atomic emission spectrum data of a 6-cylinder diesel engine. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 574–580, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 General Regression Neural Network Theory General Regression Neural Network was developed by Donald F. Specht in 1991, called GRNN for short[9]. GRNN have a strong ability of the nonlinear mapping, flexible network structure and a high degree of fault tolerance, be employed for solving nonlinear problems. GRNN have a higher advantage in approximation of function and learning speed than RBF and be convergence to optimization regression plane finally. What’s more, GRNN can deal with unstable date too. The GRNN topology consists of input layer, hidden layer (radial basis layer) and output layer, the internal structure of a GRNN is depicted in figure1[10].

Output layer

Hidden layer

Input layer

W 1 S1 × R

x1 x2

W2

dist n1

…

S1 × R

P

P

P

S1 × 1

P

xR

f1 ( x ) P

A1 S1 × 1

P

b1

Nprod P

S 2 × S1

P

n2 S 2 ×1

f 2 (x )

A2 P

S 2 ×1

P

P

P

P

S1 × 1 P

Fig. 1. Internal structure of GRNN

As show in the figure 1: X means input vector, R means dimension of input vector, S1 , S 2 means the numbers of neuron of each network. The number of neuron hidden layer equals to number of the training samples. The weight functions of hidden layer is Euclidean distance which calculates the distance from the input vector of length R to each of the Q training vectors of length R, expressed by

di st . b1 means

threshold value of the hidden layer. In general, the delivery function of the hidden layer is Gaussian function, the equation is as following:

⎛ 1 R i ( x ) = exp ⎜⎜ x − di 2 ⎝ − 2δ i

2

⎞ ⎟⎟ ⎠

(1)

x is the input sample; d i is center of the hidden layer node; δ i is smooth factor which decided basis function shape of the location of i hidden In the equation (1),

1

layer. The output of hidden layer A is as following. The output layer is a pure linear layer, the weight function of it is a normalization dot product the weight function, expressed by npord , which calculate

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C.H. Zhang, H.X. Tian, and T. Liu

A

the 1

A

1

= exp

⎡ ⎢− ⎢ ⎣

( di

st b i1 2δ

)

2

2

⎤ ⎥ ⎥ ⎦

(2)

n2 of network. The elements of n2 are quotients that dot products of which vector and each row element of weight matrix

1

W 2 and the sum of elements of vector A .

( )

The value of output of network A = purelin n2 . The trait that the learning of network depends on the samples of dates decides to extremely avoid effects of results from one’s supposition. 2

3 Date Analysis and Discussion 3.1 Experimental Date and Instrument The SPECTROIL M spectrum instrument used in experiments is a special emission spectrometer designed for analyzing lubricating oil elements. The instrument has higher precision and well repeatability and can analysis 21 elements once. This emission spectrometer is calibrated by complete normalization and daily normalization before experiments. Matlab2010a is employed in analysis Emission Spectrum Data. Emission spectrum data analyzed in this paper comes from a reference[11]. Diesel engine has seven different operating conditions arranged by updating pistons of diesel engine and altering the clearance between cylinders and new pistons. 69 oil samples taken from the engine with different loads and operating time under different operating conditions has been analyzed by the SPECTROIL M spectrum instrument. The number, the clearance Between cylinder-piston and the code of cylinder-piston is shown in Table 1 [12]: Table 1. Seven Different Conditions of Diesel Engine No. 1 2 3 4 5 6 7

Clearance Between Cylinder-piston 0.7mm between the second cylinder-piston, 0.6mm between the fifth cylinder-piston, 0.87mm between the sixth cylinder-piston and other cylinder-pistons are normal. 0.7mm between the second cylinder-piston, 0.87mm between the sixth cylinder-piston and other cylinder-pistons are normal. 0.7mm between the second cylinder-piston and other cylinder-pistons are normal. 0.87mm between the sixth cylinder-piston and other cylinder-pistons are normal. 0.7mm between the second cylinder-piston, 0.6mm between the fifth cylinder-piston and other cylinder-pistons are normal. 0.6mm between the fifth cylinder-piston and other cylinder-pistons are normal. Normal clearance between every cylinder-piston.

Code of Cylinder-piston 0000001

0000010 0000100 0001000 0010000 0100000 1000000

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3.2 Establishing the GRNN Model According to a trait of GRNN, numbers of neuron of input layer equals to dimension of input vector, numbers of neuron of output layer equals to dimension of output vector. There are 21 elements in the oil atomic emission spectrum data. Among 21 elements, Fe, Cr, Pb, Cu and Al are related with wear of diesel engine; Na, Ca, Mg, Ba ,P, B and Zn are related with additive of lubricating oil; Mg, B, Na, Si, Ca and P are related with exotic contamination; elements of which concentration are under sensitivity of instrument are disturbing elements, such as Ag, Ti and V. component elements of lubricating oil are not commonly analyzed in experiment, such as C,H. concentration of Cu which can reflect adequately wear condition of engine is chosen as output dates of neural network, which means the node of output layer being 1. Input vector is represented by matrix composed of the Clearance between Cylinder-piston and the Code of Cylinder-piston and operating time, the node of input layer is 9. Then, a GRNN model is established by a sentence of MATLAB newgrnn(P, T , SPREAD ) .Input vector is represented by P , output vector is represented by T , the spread rate of radial basis function is represented by SPREAD . The delivery function of the hidden layer and output layer are respectively Gaussian function and pure linear function, so parameter of artificially factors of GRNN is an only SPREAD . A great deal of experiments show that approximating process from network to sample date will be smoothly and the prediction error of sample date will be minor when SPREAD equals to 10. Concentration of Cu is simulated by trained GRNN. The output of simulated concentration of Cu is show in figure 2:

Fig. 2. The predicting result of Cu by GRNN method

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3.3 Error Analysis Figure 2 shows the most of samples are simulated successfully. The SPECTROIL M spectrum instrument has prescribed the acceptable accuracy indices of Cu when the standard densities of Cu are 0, 5, 10, 30, 50, 100 and 300ppm, as shown in Table 2. Cubic function of MATLAB interp1(x, y, x i , ' cubic ') is employed for estimating accuracy indices of Cu of 69 samples. Standard concentration accuracy Indices of Table 2 are used as input vector x , y among the function. Table 2. Acceptable Accuracy Indices for Wear Metals-mean of Cu Standard concentration /ppm

0

5

10

30

50

100

300

Accuracy Indices/ppm

0.92

1.61

2.44

5.91

9.43

18.2

53.5

The absolute errors of the simulation value of Cu concentration have been obtained by comparing the simulation value with the observation value. Comparing the absolute errors with the acceptable accuracy indices obtained from cubic function can reveal the stimulating result. The result shows that all the 69 samples’ absolute errors are lower than the acceptable accuracy indices, as shown in Table 3. Table 3. Simulation Efficiency of Cu Concentration

No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Absolute Accuracy Error(ppm) Indices(ppm) -0.01 1.91 -0.08 1.9 0.36 1.83 0.48 1.9 0.1 1.96 0.54 1.91 -0.43 2.08 0.5 1.95 0.31 1.98 0.41 1.95 -0.28 2.06 0.22 1.98 -0.17 2.05 0.19 2.01 -0.4 2.12 -0.79 2.18 0.05 2.03 -0.23 2.08 0.15 2.01 -0.63 2.15 0.18 2.01 -0.15 2.12 -0.13 2.12

Overrun (Y/N) N N N N N N N N N N N N N N N N N N N N N N N

No. 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58

Absolute Error(ppm) 0.05 0.06 0.04 0.04 0.06 0.01 0 0 0.03 0.34 0.26 0.03 0.05 0 0.03 0.02 0.06 0.05 0.1 0.09 0.02 0.02 0.02

Accuracy Indices(ppm) 1.4 1.4 1.42 1.42 1.43 1.43 1.39 1.43 1.43 1.43 1.69 1.66 1.66 1.51 1.52 1.54 1.55 1.51 1.11 1.14 1.18 1.18 1.19

Overrun (Y/N) N N N N N N N N N N N N N N N N N N N N N N N

Analysis Based on GRNN to Oil Atomic Emission Spectrum Data

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Table 3. (continued) 24 25 26 27 28 29 30 31 32 33 34 35

0 0 -0.04 -0.05 -0.05 0.25 -0.14 -0.04 0.07 -0.04 0.01 -0.05

1.77 1.73 1.75 1.75 1.75 1.7 1.81 1.8 1.78 1.8 1.36 1.42

N N N N N N N N N N N N

59 60 61 62 63 64 65 66 67 68 69

0.02 0.02 0.07 0.13 0.22 0.13 0.06 0.15 0.14 0 0

1.21 1.21 1.22 1.25 1.03 1.05 1.07 1.09 1.09 1.09 1.09

N N N N N N N N N N N

3.4 Predicting and Analysis According to constantly changing parameter of operating condition (including running time and load) and machine parameter (clearance between cylinder-piston), an appropriate model is set up in terms of GRNN algorithm for predicting Cu concentration. 50 random samples were taken as the training sets. The remaining 19 samples have been predicted, results of prediction have been shown in Table 4: Table 4. Predicting Efficiency of Cu Concentration

No. 11 12 13 14 15 28 29 30 38 39 40 46 47 53 59 60 61 68 69

Observation value(ppm) 7.8 7.3 7.7 7.5 8.1 5.9 5.6 6.3 3.7 3.7 3.8 5.5 5.3 4.3 2.2 2.2 2.3 1.3 1.3

Prediction value(ppm) 7.29 7.3 7.31 7.65 7.66 5.95 5.95 6.18 3.62 3.7 3.7 5.02 5.29 4.6 2.28 2.28 2.5 1.17 1.18

Absolute Error(ppm) -0.51 0 -0.39 0.15 -0.44 0.05 0.35 -0.12 -0.08 0 -0.1 -0.48 -0.01 0.3 0.08 0.08 0.2 -0.13 -0.12

Accuracy Indices(ppm) 2.06 1.98 2.05 2.01 2.12 1.75 1.7 1.81 1.42 1.42 1.43 1.69 1.66 1.51 1.21 1.21 1.22 1.09 1.09

Overrun (Y/N) N N N N N N N N N N N N N N N N N N N

The data shown in Table 4 suggests that 19 samples’ absolute errors are lower than the acceptable accuracy indices.

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4 Conclusions Based on the Generalized Regression Neural Network algorithm, the simulation model has been set up for the relation between Cu concentration of lubricating oil of diesel engine and its loads, cylinders’ clearances and running time oil renewed. The simulation model has proved to be effective, for the absolute errors of the simulation value of the 69 samples are lower than the acceptable accuracy indices. As regards to seven working conditions, the Cu concentrations of the random 19 samples were predicted accurately through the predicting model based on the Generalized Regression Neural Network analysis.

References 1. Toms, L.A., Toms, A.M.: Machinery Oil Analysis. Society of Tribologists & Lubrication Engineers, 1–20 (2008) 2. Yan, X.: Development and think Of oil monitor technique. Lubrication Engineering 14(7), 6–8 (1999) 3. Wang, L., Li, L.: The Sampling Time Prediction of Oil Analysis for Power-shift Steering Transmission. Lubrication Engineering 35(8), 84–87 (2010) 4. Liu, T., Tian, H.X., Guo, W.Y.: Application of Factor Analysis to a Type Diesel Engine SOA. In: 2010 International Conference on Measuring Technology and Mechatronics Automation, Changsha, China, March 13-14, pp. 612–615 (2010) 5. Huo, H., Li, Z., Xia, Y.: Application of maximum entropy probability concentration estimationapproach to constituting oil monitoring diagnostic criterions. Tribology International 39, 528–532 (2006) 6. Tian, H.X., Ming, T.F., Liu, Y.: Comparison among oil SPECTRAL date of six types of marine engine. In: International Conference on Transportation Engineering, Chengdu, pp. 43–48 (2009) 7. Zhou, P., Liu, D.F., Shi, X., Li, G.: Threshold Setting of Oil Spectral Analysis Based on Robust Regression. Lubrication Engineering 35(5), 85–88 (2010) 8. Fan, H.B., Zhang, Y.T., Ren, G.Q., Luo, H.F.: Study on Prediction Model of Oil Spectrum Based on Support Vector Machines. Lubrication Engineering 183(11), 148–150 (2006) 9. Shi, F., Wang, X.C., Yu, L.: Analysis of 30 cases of MATLAB neural network, pp. 73–80. Press of Beijing University of Aeronautics and Astronautics, Beijing (2010) 10. Yan, W.J.: Research on Discrimination of Tongue Diseases with Near Infrared Spectroscopy. Infrared Technology 32(8), 487–490 (2010) 11. Liu, T.: Study in the Field of Oil Atomic Emission Spectrum Data Mining, pp. 18–20. Naval University of Engineering, Wuhan (2009) 12. Liu, T., Tian, H.X., Guo, W.Y.: Application of Factor Analysis to a Type Diesel Engine SOA. In: 2010 International Conference on Measuring Technology and Mechatronics Automation, Changsha, China, March 13-14, pp. 612–615 (2010)

Robust Face Recognition Based on KFDA-LLE and SVM Techniques GuoQiang Wang* and ChunLing Gao Department of Computer and Information Engineering, Luoyang Institute of Science and Technology, 471023 Luoyang, Henan, P.R. China {wgq2211,gclcsd}@l63.com

Abstract. Locally Linear Embedding (LLE) is a recently proposed algorithm for non-linear dimensionality reduction and manifold learning. However, it may not be optimal for classification problem. In this paper, an improved version of LLE, namely KFDA-LLE, is proposed using kernel Fisher discriminant analysis (KFDA) method, combined with SVM classifier for face recognition task. Firstly, the input training samples are projected into the low-dimensional space by LLE. Then KFDA is introduced for finding the optimal projection direction. Finally, SVM classifier is used for face recognition. Experimental results on face database demonstrate that the extended LLE method is more efficient and robust. Keywords: Face Recognition, Manifold learning, Locally Linear Embedding, Kernel Fisher Discriminant Analysis (KFDA), Support Vector Machines.

1 Introduction Face recognition has been researched extensively in the past decade due to the recent emergence of applications such as secure access control, visual surveillance, contentbased information retrieval, and advanced human and computer interaction. However, facial expression, occlusion and lighting conditions also change the overall appearance of faces. The high degree of variability in those factors makes face recognition a challenging task. To recognition human faces efficiently, dimensionality reduction is an important and necessary operation for multi-dimensional data. The objective of dimensionality reduction is to obtain a more compact representation of the original data, a representation that nonetheless captures all the information necessary for higher-level decision-making. Wang et al. [1] present four reasons for reducing the dimensionality of observation data: (1) To compress the data to reduce storage requirements; (2) To extract features from data for face recognition; (3) To eliminate noise; and (4) To project data to a lower-dimensional space so as to be able to discern data distribution. For face recognition, classical dimensionality reduction methods have includes Principal Component Analysis (PCA) [2], Independent Component Analysis [3], and Linear Discriminate Analysis [4]. *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 581–587, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Recently, neuroscientists suggested that human perceive objects in manifold ways. Manifold, to be brief, is a topological space that is locally Euclidean distance. Roweis and Saul [5] proposed a non-linear dimensionality reduction method, Locally Linear Embedding (LLE), for learning the global structure of nonlinear manifolds exploiting the local symmetries of linear reconstructions. Although the LLE has demonstrated excellent results for exploratory analysis and visualization of multivariate data. It is suboptimal from the perspective of pattern classification. In this paper, we propose method for face recognition by extending the LLE with Kernel Fisher Discriminant Analysis (KFDA). Firstly, the input training samples are projected into the lowdimensional space. Then KFDA is introduced for finding the optimal projection direction. Finally, SVM classifiers are used for face recognition. Experimental results demonstrate the effectiveness and robust of the proposed recognition approach.

2 KFDA-LLE LLE maps its inputs into a single global coordinate system of lower dimension, attempting to discover nonlinear structure in high dimensional data by exploiting the local symmetries of linear reconstructions. Its optimizations do not involve local minima though capable of generating highly nonlinear embeddings. The LLE transformation algorithm is based on simple geometric intuitions, where the input data consist of N points

xi , xi ∈ R D , i ∈ [1, N ] , each of dimensionality

D , which obtained by sampling an underlying manifold. Provide there is sufficient data (such that the manifold is well sampled), each data point and its neighbors are expected to lie on or near a locally linear patch of the manifold. Linear coefficients that reconstruct each data point from its neighbors are used to characterize the local geometry of these patches. As an output, it provides

N points y i , yi ∈ R d ,

i ∈ [1, N ] where d << D . A brief description of LLE algorithm is as follows: Stage I, the cost function to be minimized is defined as: N

N

i =1

j =1

2

ε (W ) = ∑ xi − ∑Wij xij

(1)

X = [ x1 , x2 ,..., x N ] , the dimension of xi is D . For one vector xi and weights Wij that sum up to 1, this gives a contribution: Given

ε (W ) = i

∑W j =1

where

2

K

ij

K

K

( xi − x j ) = ∑∑WijWim C ijm

(2)

j =1 m =1

C i is the K × K matrix:

C ijm = ( xi − xij )T ( xi − xim )

(3)

Robust Face Recognition Based on KFDA-LLE and SVM Techniques

Stage II, the weight matrix W is fixed and new m-dimensional vectors

583

y i are

sought which minimizes another cost function: N

N

2

ε (Y ) = ∑ yi − ∑Wij yij i =1

The

(4)

j =1

Wij can be stored in an n × n sparse matrix M, then re-writing equation (4)

gives: N

N

ε (Y ) = ∑∑ M ij yiT y j

(5)

i =1 j =1

To improve the LLE standalone classification performance, one needs to combine LLE with some discrimination criterion. The KFDA-LLE is similar to the original LLE in the first two steps. The original facial vector

x ∈ R D is transformed into the

feature vector y ∈ R with d << D . The main different between them is that in our algorithm, the feature vector y is nonlinearly mapped into a high dimensional space, and then a FLD method is utilized, globally forming a nonlinear mapping, i.e.KFDA. The computation in high dimension space can be facilitated by the Mercer kernel function. The main ideal of KFDA first maps the feature vectors y into a high dimension d

space

F by a nonlinear mapping φ . Fisher linear discriminant analysis (FLD) can

then be performed in

F . Thus, we define the within-class scatter matrix S wφ , the

between-class scatter matrix

S bφ for the mapped training samples respectively as

follows: c

ni

S wφ = ∑∑ (φ ( g j − μ iφ )(φ ( g j ) − μ iφ )T

(6)

i =1 j =1 c

S b = ∑ ni ( μ iφ − μ φ )( μ iφ − μ φ ) T φ

(7)

i =1

where

μ iφ is

mean vector of class

space respectively. If

i and μ φ is the total mean vector in the mapped

S wφ is nonsingular, the optimal projection Wopt is chosen as the

matrix with orthonormal columns which maximizes the ratio of the determinant of the between-class scatter matrix to that of the within-class scatter matrix, i.e.,

Wopt = arg max W

W T S bφW W T S wφW

(8)

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According to the theory of reproducing kernel [6], any solution space which is spanned by

{φ ( x1 ),...,φ ( x N )} , i.e,

w must lie in the

n

w = ∑ α iφ ( g i ) = Φ α

(9)

i =1

where we define

Φ as [φ ( g1 ),φ ( g 2 ),...,φ ( g n )] and a coefficient vector α as

[α1 ,α 2 ,...,α n ]T . After substituting Eq. (6), Eq. (7), Eq. (9) into Eq. (8), it follows wT S bφ w = α T K bα

(10)

wT S wφ w = α T K wα

(11)

ξ j = [k ( g1 , g j ),..., k ( g n , g j )]T

(12)

where,

c

K b = ∑ ni (mi − m)(mi − m)T

(13)

i =1

c

ni

K w = ∑∑ ni (ξ j − mi )(ξ j − m) T

(14)

i =1 j =1

n nj ⎤ 1 ⎡ j m j = ⎢∑ k ( g1 , g i ),..., ∑ k ( g n , g i )⎥ n j ⎣ i =1 i =1 ⎦

n 1⎡ n ⎤ m = ⎢∑ k ( g1 , g i ),..., ∑ k ( g n , g i ) ⎥ n ⎣ i =1 i =1 ⎦

T

(15)

T

(16)

Then, the following eigenvalues problem is obtained:

A = arg max = A

AT K b A AT K w A

= [α 1 ,...,α c −1 ]

To deal with the singularity of with-scatter matrix

(17)

K w that one often encounters in

classification problems, we can use a regulation strategy with adding a multiple of the identity matrix to the within-scatter matrix, i.e., K w = K w + εI where ε is a small

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585

number). This also makes the eigenvalue problem numerically more stable. Another viable approach for singularity problem by using PCA could also be adopted [3]. This method performs a linear dimensionality reduction removing the null space to obtain a matrix of full rank. For a new testing sample z , whose projection onto the optimal discriminant vector w of the feature F is n

n

k =1

k =1

wT φ ( z ) = ∑α k φ T ( xk )φ ( z ) = ∑α k k ( xk , z )

(18)

= α T [k ( g1 , z ),..., k ( g n , z )]T

3 Support Vector Machines SVM[6][7] perform pattern recognition for two-class problems by finding the decision surface which minimizes the structural risk of the classifier. This is equivalent to determining the separating hyperplane that has maximum distance to the closest samples of the training set. Considering the problem of separating a set of training samples belong to two separable classes, ( x1 , y1 ) ,…, ( x n , y n ) , where

xi ∈ R d , yi ∈ {−1,+1} , an optimal hyperplane can be obtained through solving a constrained optimization problem, the decision function can be written as:

f ( x) = sgn(

n

∑α

* i y i k ( xi

⋅ x) + b * )

(19)

i =1

where α i

(i = 1,..., n) and b * are the best solutions to the optimization problem, the kernel k ( x, y ) commonly used include polynomials kernel, radial basis function *

kernels and sigmoid kernel etc. The SVM approach was originally developed for binary classification problems. In many practical applications, a multi-class pattern recognition problem has to be solved. Usually there are two strategies [8] to solve multi-class problems by using binary SVM classifiers: The first one is one-against-one, in this method, for each possible pair of classification a binary classifier is calculated, each classifier is trained on a subset of the training set containing only training examples of the two involved classes. If N represents the number of total classes, all (N-1)N/2 classifiers are combined through a majority voting scheme to estimate the final classification. The other one is the one-against-rest, in this method N different classifiers are constructed, one for each class. Here the l-th classifier is trained on the whole training data set in order to classify the members of class l against the rest. In the classification stage, the

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classifier with the maximal output defines the estimated class label of the current input vector. While the former has too many computations, we adopt the latter one for our face recognition task.

4 Experimental Results We test both the original and improved LLE method against Eigenface and Fisherface methods using the face database B of the BVC’2005 [9]. This face database contains 2000 face images corresponding to 100 distinct subjects. The 2000 face images were acquired under vary illumination conditions, different facial expressions, diverse background and certain pose changes. Each subject has twenty images of size of 640x480 with RGB color. Since the database has large background, to reduce the adverse effect, original images have been cropped containing the facial contours with size 100x100. The cropped images of a few subjects in the database are shown in figure 1.

Fig. 1. Face images from database

B of the BVC’2005

In this experiment, a pre-processing stage is first applied to normalize all of the images. Illumination compensation was performed using both conventional histogram equalization and the phase-only image obtained using the FFT[10]. The samples in the database are randomly divided into two disjoint sets: ten images for training and the remaining ten images for testing. All images are projected to a reduced space and recognition is performed using SVM classifier. To reduce the fluctuation of results caused by the randomness of data sets, the experiment was performed 10 times and the results are averaged. For all methods, all samples are projected to a subspace spanned by the c-1 largest eigenvectors. The experimental result is shown in Table 1. From the Table we can see that the performance of our approach is better than other methods. As in KFDA-LLE, kernel methods could effectively extract the nonlinear feature for further classification.

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Table 1. The experimental results on test database using the different methods

Method Eigenface+SVM Fisherface+SVM LLE+SVM KFDA-LLE+SVM

Parameter NA NA K=10 K=10

Reduced Space 32 37 42 35

Face Recognition Rate 80.45% 85.02% 82.67% 91.25%

5 Conclusion In this paper, an improved version of LLE, namely KFDA-LLE, is proposed for face recognition. The KFDA-LLE is capable of identifying the underlying structure of high dimensional data and discovering the embedding space nonlinearly of the same class data set. Then KFDA is used to find an optimal projection direction for classification. In face recognition experiments, KFD-LLE serves as a feature extraction process compared with LLE, and two other well-established subspace methods combined with SVM classifier. Experimental results on face database show that KFD-LLE excels LLE and is highly competitive with those two baseline methods for face recognition.

References 1. Wang, J., Zhang, C.S., Kou, Z.B.: An Analytical Mapping for LLE and lts Application in Multi-pose Face Synthesis. In: The 14th British Machine Vision Conference (2003) 2. Turk, M.A.: pentland, A.P.: Face Recognition using Eigenfaces. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 586–591 (1991) 3. Bartlett, M.S., Movellan, J.R., Sejnowski, T.J.: Face recognition by ICA. IEEE Transactions on Neural Networks 13(6), 1450–1463 (2002) 4. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997) 5. Roweis, S.T., Saul, L.K.: Nonlinear Dimensionality Reduction by LLE. Science 290, 2323–2326 (2000) 6. Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1995) 7. Li, Y.F., Ou, Z.Y., Wang, G.Q.: Face Recognition Using Gabor Features and Support Vector Machines. In: Zhou, T.H., Bloom, T., Schaffert, J.C., Gairing, M., Atkinson, R., Moss, E., Scheifler, R. (eds.) CLU. LNCS, vol. 114, pp. 114–117. Springer, Heidelberg (1981) 8. Schwenker, F.: Hierarchical Support Vector Machines for Multi-Class Pattern Recognition. In: Fourth International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies, vol. 2, pp. 561–565 (2000) 9. The First Chinese Biometrics Verification Competition, http://www.sinobiometrics.com 10. Kovesi, P.: Symmetry and Asymmetry From Local Phase. In: The 10th Australian Joint Conf. on A.I. (1997)

An Improved Double-Threshold Cooperative Spectrum Sensing DengYin Zhang and Hui Zhang Key Lab of Broadband Wireless Communication and Sensor Network Technology, (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003, China {Zhangdy,Y001090436}@njupt.edu.cn

Abstract. Cognitive Radio is becoming a hot research topic in wireless communication field now, in which the spectrum sensing is one of the most critical technologies. In the double-threshold cooperative spectrum sensing, the fusion center collects the local decisions and observational values of the secondary users, and then makes the final decision to determine whether the primary user is presence or not. While the fusion center collects the observational values, the traditional method does not consider that the reliability of different cognitive user will be different, which will cause certain impact on detection performance. For this shortfall, we introduce the reliability factor based on the signal-to-noise ratio, and propose an improved double-threshold cooperative spectrum sensing method. Simulation results will show that the spectrum sensing performance is improved significantly under the proposed scheme compared with the conventional method. Keywords: cognitive radio, double threshold, cooperative spectrum sensing, reliability factor.

1 Introduction With the expansion of broadband multimedia services, the radio spectrum resources are becoming scarcer and scarcer, and the contradiction between supply and demand of the spectrum is becoming more and more acute. The emergence of cognitive radio alleviates the contradiction between supply and demand of the current spectrum. Spectrum sensing is one of the most critical technologies in cognitive radio. The detection of spectrum holes can improve the utilization of wireless spectrum resources. In the cognitive network (CRN), the cognitive user (Secondary User, SU) can only use the frequency band which is not used by the statutory main user (Primary User, PU). In order to limit the interference to the PU, the SU should exit the band immediately if the PU exists and can switch to other free unused spectrum to continue communicating. It is a major challenge that how SU can detect the existence of PU timely and reliably. Therefore, spectrum sensing is very important in cognitive radio technology. The existing spectrum sensing methods have single-user detection and collaborative detection [1]. Single-user detection mainly includes matched filter S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 588–594, 2011. © Springer-Verlag Berlin Heidelberg 2011

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detection, cycle stationary feature detection and energy detection. In practical applications of cognitive radio, wireless environment is very complex and changeable, in which the shadow, concealed terminal, multipath, noise uncertainty and other factors will result in negative impact for the detection performance of single-user, Cooperative spectrum sensing can reduce this impact and reduce the requirements of cognitive equipment, which has a higher detection accuracy, therefore, it is one of the hot spot which people study now. Data fusion algorithm in cooperative sensing mainly includes hard decision collaboration algorithm [2], soft decision collaboration algorithm [3] and hybrid decision collaboration algorithm. In [4], a detection method using double threshold in cooperative spectrum sensing was proposed to reduce the communication traffic. Part of the cognitive users send their energy values to fusion center by soft decision , the rest of the cognitive users send their results by hard decision to the fusion center, and the fusion center makes a final decision to determine whether the PU is absence. But this method has not considered that the channel conditions of different SU are different and the detection reliabilities also vary, which will affect the detecting performance. To solve this problem, an improved double-threshold cooperative detection which can improve the detection performance is proposed.

2 The Traditional Double-Threshold Cooperative Spectrum Sensing Method In the following model, there are two thresholds λ1 and λ2, where Yi denotes the collected energy value of the i-th SU. If energy value exceeds λ2, then this user reports H1, which means that the PU is present. If energy value is less than λ1, the decision H0 will be made, which means that there is no PU, if Yi is between λ1 and λ2, the SU send the collected energy value to the fusion center which will make the further judgments [5].

Decition H0

Energy value Yi λ1

Decition H1 λ2

Yi

Fig. 1. The double threshold detection mode

Assuming that each SU can does energy detection independently and has the identical detection threshold values for simplicity. If Yi satisfies λ1 λ2, it will report its local decision Li to the fusion center. We use Ri to denote the information that the fusion center receives from the i-th SU, then it can be given by:

otherwise

.

(1)

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and

0 1

0

.

(2)

Without loss of the generality, we assume that the fusion center receives K local decisions and N-K energy detection values among N cognitive users. Then the fusion center makes an upper decision according to N-K energy detection values, which is given by: 0 1

0 ∑

∑

.

(3)

where λ is the energy detection threshold value of the fusion center according to the proper false alarm probability. It shows that these N-K cognitive users could not distinguish between the presence and the absence of the PU, so the fusion center collects their observational values and then makes an upper decision instead of the local decision by themselves [5]. The energy values fusion that the fusion center collects follows the distribution as given below [6]:

∑

Y~

H

χ χ

2γ

H

.

(4)

∑ γ represents the sum of SNR for N-K cognitive users, we can where γ make a further decision according to energy detection [7]. The fusion center makes a final decision based on OR-rule [8]: 1 0

D

∑ 1 otherwise

H . H

(5)

In the double threshold detection, some cognitive users cannot make their local decisions directly, so they need send the detection values to the fusion center where compares their energy values fusion with the threshold value for further judgment. However, without considering that the different cognitive user will have different detection reliability caused by their different geographical location and environment, which would affect the final detection performance.

3 An Improved Double-Threshold Cooperative Spectrum Sensing Method Because the cognitive users have different environment, that is, the shadow fading they have went through is different, which finally will lead to their SNR vary, so that

An Improved Double-Threshold Cooperative Spectrum Sensing

591

the credibility of information each cognitive user detected cannot be equated, in order to solve this problem, we proposed a weighting judgment method by using reliability factor which based on SNR values in this paper. In [9], the reliability factor has been defined, and in this paper we introduce it into the double threshold cooperative detection. The basic idea of reliability factor [9] is to set weight by using the SNR value of SU received. The higher its SNR value is, the bigger its weight will be, and the lower its SNR value is, the smaller its weight will be. The contribution of each SU to the overall decision can be determined according to the detection performance, which can help to fuse detection value of each SU better and improve the accuracy of the cooperative spectrum sensing. First of all, the SU send the measured SNR value to the fusion center, and then fusion center will calculate its weight factor according to the following formula. Then the fusion center makes decision based on both the weight factor and its own detection value. γ

W

∑

γ

.

(6)

In the traditional double threshold collaborative sensing, because the channel conditions of cognitive users are different, their detection reliabilities are also different. In this paper, the fusion center is not only compute the summation of all detection values simply but makes a weighted summation according to the weight factor, and then we can know that the PU is absent or not by comparing the weighted energy summation with threshold value, finally, the decision H0 or H1 will be made. Mathematical description of weighted coordination algorithm is: ∑

Y

WY .

(7)

The energy value Yw is the summation of the product of the detected energy value Yi and the weight factor Wi , where Yi denotes the collected energy value of the i-th SU, Wi denotes the weight factor of the i-th SU, N-K is the number of cognitive users. Since Yi is an independent chi-square distribution with 2TW freedom degrees, likewise, Yw is also a Chi-square distribution the same with the Yi, then it can be given by [10]: H

χ

Y

2γ

χ

H

.

(8)

And γ

∑

Wγ .

(9)

γ is the SNR of the i-th SU, u=TW, T is the spectrum detection time, W is the bandwidth when band-pass signal performs energy detection. W1 W2 … WN-K are the weighting factors of the cognitive users respectively.

， ， ，

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To facilitate the analysis, we introduce two parameters Δ0,i and Δ1,i to represent the probability ofλ1
Pλ

λ |H

Pλ

λ |H

,

,

.

(10)

.

(11)

According the calculation method of traditional double threshold detection, we can get the probability of detection, missing and false alarm respectively for each SU:

P,

PY

λ |H

Q

P

PY

λ |H

1

,

P,

λ |H

PY

2γ , λ ∆

,

,

⁄

.

(12)

P, .

(13)

.

(14)

Using Qd·Qm and Qf to denote the cooperative probability of detection, missing and false alarm respectively, then we have: ∑

Q

∏

P

,

∑

∆ Q

Q

1

∏

1 ∆

,

P,

∑

,

1 1 ∏

Q

2γ

，√λ

∏

P

,

. (15)

Q . 1 ∆

(16) ,

P, ∑

∆

,

1

,λ

Γ Γ

. (17)

where Γ(:,:) is incomplete Gamma function, Q( ) as a general Marcum Q function.

4 Simulation Results and Analysis In the front, we have analyzed the performance of the improved double threshold spectrum sensing, and now we verify its performance by using MATLAB simulation. It can be clearly seen that this method performs better. Parameters are given as follows: AWGN channel, ∆ , =∆ , =0.1the number of users N=10 u=5, the SNR of the i-th SU γ =-15:1:-6dB， the simulation results can be shown by the follow figures:

，

An Improved Double-Threshold Cooperative Spectrum Sensing

Fig. 2. Detection probability vs. false alarm probability

593

Fig. 3. Missing probability vs. false alarm probability

In figures, it can be seen that the improved double threshold collaborative detection has a better performance compared with the traditional method, with higher detection probability and lower missing probability. In this paper, the reason that the improved double threshold collaborative detection method can improve the detection performance is due to that the cognitive users have different impact to fusion center according to their different reliability factors. Considering this situation, we introduce the reliability factors while cognitive users send their detection values to the fusion center. It can be seen that this improved method can significantly improve the cooperative spectrum sensing capability in the cognitive radio network from the simulation results.

5 Conclusions In this paper, we have proposed an improved double threshold collaborative detection method, in the traditional method, the cognitive users that need send their detection values to the fusion center have different channel conditions, which result in that their detection performance vary, the improved method fully thinks about this situation which did not in the traditional method, it can be clearly seen that the performance of the improved method is significantly better from the simulation results. Acknowledgments. Thework was partially supported by Swedish Research Links [No.348-2008-6212], the National Natural Science Foundation of China [61071093], China’s Project 863 [2010AA701202], and SRF for ROCS, SEM [NJ209002].

References 1. Akyildiz, I.F., Lee, W.-Y., Vuran, M.C., et al.: Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks 50(13), 2127–2159 (2006) 2. Zhou, X., Ma, J., Li, G.Y., Kwon, Y.H., Soong, A.C.K.: Probability based combination for cooperative spectrum sensing. IEEE Trans. Commun. 58(2), 463–466 (2010)

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3. Meng, J., Yin, W., Li, H., Hossain, E., Han, Z.: Collaborative spectrum sensing from sparse observations using matrix completion for cognitive radio networks. In: Proc. IEEE 2010 International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (March 2010) 4. Sun, C.-h., Zhang, W., Letaief, K.B.: Cooperative spectrum sensing for cognitive radios under bandwidth constraints. In: Proc. IEEEWCNC (2007) 5. Zhu, J.: Double Threshold Energy Detection of Cooperative Spectrum Sensing in Cognitive Radio. In: 3rd International Conference on Oriented Wireless Networks and Communications, CrownCom 2008, May 15-17 (2008) 6. Digham, F.F., Alouini, M.S., Simon, M.K.: On the energy detection of unknown signals over fading channels. IEEE Transactions on Communications 55(1), 21–24 (2007) 7. Urkowitz, H.: Energy Detection of Unknown Deterministic Signals. Proceedings of the IEEE 5(4), 523–531 (1967) 8. Varshney, P.K.: Distributed detection and data fusion. Springer, New York (1997) 9. Visser, F.E., Janssen, G.J.M., Pawelczak, P.: Multi node Spectrum Sensing Based on Energy Detection for Dynamic Spectrum Access. In: Vehicular Technology Conference, pp. 1394–1398 (May 2008) 10. Bin Shahid, M.I., Kamruzzaman, J.: Weighted Soft Decision for Cooperative Sensing in Cognitive Radio Networks. In: 16th IEEE International Conference Networks, pp. 1–6 (2008)

Handwritten Digit Recognition Based on Principal Component Analysis and Support Vector Machines Rui Li and Shiqing Zhang School of Physics and Electronic Engineering, Taizhou University 318000 Taizhou, China {lirui,zhangshiqing}@tzc.edu.cn

Abstract. Handwritten digit recognition has always been a challenging task in pattern recognition area. In this paper we explore the performance of support vector machines (SVM) and principal component analysis (PCA) on handwritten digits recognition. The performance of SVM on handwritten digits recognition task is compared with three typical classification methods, i.e., linear discriminant classifiers (LDC), the nearest neighbor (1-NN), and the back-propagation neural network (BPNN). The experimental results on the popular MNIST database indicate that SVM gets the best performance with an accuracy of 89.7% with 10-dimensional embedded features, outperforming the other used methods. Keywords: Handwritten digits recognition, Principal component analysis, Support vector machines.

1 Introduction Handwritten digit recognition is an active topic in pattern recognition area due to its important applications to optical character recognition, postal mail sorting, bank check processing, form data entry, and so on. The performance of character recognition largely depends on the feature extraction approach and the classifier learning scheme. For feature extraction of character recognition, various approaches, such as stroke direction feature, the statistical features and the local structural features, have been presented [1, 2]. Following feature extraction, it’s usually needed to reduce the dimensionality of features since the original features are high-dimensional. Principal component analysis [3] is a fundamental multivariate data analysis method and widely used for reducing the dimensionality of the existing data set and extracting important information. The task of classification is to partition the feature space into regions corresponding to source classes or assign class confidences to each location in the feature space. At present, the representative statistical learning techniques [4] including linear discriminant classifiers (LDC) and the nearest neighbor (1-NN), and neural network [5], have been widely used for handwritten digit recognition. Support vector machines (SVM) [6] became a popular classification tool due to its strong generalization capability, which was successfully employed in various real-world applications. In the present study we employ PCA to extract the low-dimensional embedded data representations and explore the performance of SVM for handwritten digit recognition. S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 595–599, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Principal Component Analysis Principal Component Analysis (PCA) [3] is a basis transformation to diagonalize an estimate of the covariance matrix of the data set. PCA can be applied to represent the input digit images by projecting them onto a low-dimensional space constituted by a small number of basis images derived by finding the most significant eigenvectors of the covariance matrix. In order to find a linear mapping M which maximizes the objective function ( trace( M T cov( X ) M ) ), PCA solves the following eigenproblem:

cov( X ) M = λ M

(1)

where cov( X ) is the sample covariance matrix of the data X . The d principal eigenvectors of the covariance matrix form the linear mapping M . And then the lowdimensional data representations are computed by Y = XM .

3 Support Vector Machines Support vector machines (SVM) [6] is based on the statistical learning theory of structural risk management and quadratic programming optimization. And its main idea is to transform the input vectors to a higher dimensional space by a nonlinear transform, and then an optimal hyperplane which separates the data can be found. Given training data set ( x1 , y1 ),..., ( xl , yl ), yi ∈ {−1,1} , to find the optimal

hyperplane, a nonlinear transform, Z = Φ( x) , is used to make training data become linearly dividable. A weight w and offset b satisfying the following criteria will be found: ⎧⎪ wT zi + b ≥ 1, yi = 1 (2) ⎨ T yi = −1 ⎪⎩ w zi + b ≤ −1, We can summarize the above procedure to the following: 1 (3) min Φ ( w) = ( wT w) w, b 2 Subject to yi ( wT z i +b) ≥ 1, i = 1, 2,..., n If the sample data is not linearly dividable, the following function should be minimized. l 1 Φ ( w) = wT w + C ∑ ξi (4) 2 i =1 whereas ξ can be understood as the error of the classification and C is the penalty parameter for this term. l

By using Lagrange method, the decision function of w0 = ∑ λi yi zi will be i =1

l

f = sgn[∑ λi yi ( z T zi ) + b] i =0

(5)

Handwritten Digit Recognition Based on Principal Component Analysis

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From the functional theory, a non-negative symmetrical function K (u, v) uniquely defines a Hilbert space H , where K is the rebuild kernel in the space H :

K (u , v) = ∑ αϕi (u )ϕi (v) i

(6)

This stands for an internal product of a characteristic space: ziT z = Φ( xi )T Φ( x) = K ( xi , x)

(7)

Then the decision function can be written as: l

f = sgn[∑ λi yi K ( xi , x) + b]

(8)

i =1

The development of a SVM emotion classification model depends on the selection of kernel function. There are several kernel functions, such as linear, polynomial, radial basis function (RBF) and sigmoid, that can be used in SVM models.

4 Experiment Study 4.1 MNIST Database

The popular MNIST database of handwritten digits, which has been widely used for evaluation of classification and machine learning algorithms, is used for our experiments. The MNIST database of handwritten digits, available from the web site: http://yann.lecun.com/exdb/mnist, has a training set of 60000 examples, and a test set of 10000 examples. It is a subset of a larger set available from NIST. The original black and white images from NIST were size normalized to fit in a 20×20 pixel box while preserving their aspect ratio. The images were centered in a 28×28 image by computing the center of mass of the pixels, and translating the image so as to position this point at the center of the 28×28 field. In our experiments, for computation simplicity we randomly selected 3000 training samples and 1000 testing samples for handwritten digits recognition. Some samples from the MNIST database are shown in Fig.1. 4.2 Experimental Results and Analysis

To verify the performance of SVM on handwritten digits recognition task, three typical methods, i.e., linear discriminant classifiers (LDC), the nearest neighbor (1NN) and the back-propagation neural network (BPNN) as a representative neural network were used to compare with SVM. For BPNN method, the number of the hidden layer nodes is 30. We employed the LIBSVM package, available at http://www.csie.ntu.edu.tw/cjlin/libsvm, to implement SVM algorithm with RBF kernel, kernel parameter optimization, one-versus-one strategy for multi-class classification problem. The RBF kernel was used for its better performance compared with other kernels. For simplicity, the feature dimension of the original grey image features (28×28=784) is reduced to 10 as an illustration of evaluating the performance of SVM.

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Fig. 1. Some samples from the MNIST database Table 1. Handwritten Digits Recognition Results with 10-Dimensional Embedded Features Methods

LDC

1-NN

BPNN

SVM

Accuracy (%)

77.6

82.7

84.8

89.7

Table 2. Confusion matrix of Handwritten Digits Recognition Results with SVM Digits

0

1

2

3

4

5

6

7

8

9

0

90

0

0

0

0

5

0

0

1

0

1

0

110

1

0

0

0

0

0

4

0

2

0

0

84

1

2

0

1

1

0

0

3

0

0

5

108

0

3

0

0

7

0

4

0

0

3

0

69

1

1

0

1

12

5

2

0

3

2

2

88

0

0

1

1

6

2

0

0

0

1

0

84

0

1

0

7

0

2

1

0

1

0

0

101

0

6

8

2

0

2

2

0

4

1

0

75

3

9

0

2

0

0

6

1

0

2

4

88

Handwritten Digit Recognition Based on Principal Component Analysis

599

Table 1 presents the different recognition results of four classification methods including LDC, 1-NN, BPNN as well as SVM. From the results in Table 1, we can observe that SVM performs best, and achieves the highest accuracy of 89.7% with 10dimensional embedded features, followed by BPNN, 1-NN and LDC. This demonstrates that SVM has the best generalization ability among all used four classification methods. In addition, the recognition accuracies for BPNN, 1-NN and LDC, are 84.8%, 82.7% and 77.6%, respectively. To further explore the recognition results of different handwritten digits with SVM, the confusion matrix of recognition results with SVM is presented in Table 2. As shown in Table 2, we can see that three digits, i.e., “1”, “3” and “7”, could be discriminated well, while other digits could be classified poor.

5 Conclusions In this paper, we performed reduction dimension with PCA for the grey digits image features and explored the performance of four different used classification methods, i.e., LDC, 1-NN, BPNN and SVM, for handwritten digits recognition from the popular MNIST database. The experimental results on the MNIST database demonstrate that SVM can achieve the best performance with an accuracy of 89.7% with 10-dimensional reduced features, due to its good generalization ability. In our future work, it’s an interesting task to study the performance of other more advanced dimensionality reduction techniques than PCA on handwritten digits recognition. Acknowledgments. This work is supported by Zhejiang Provincial Natural Science Foundation of China (Grant No. Y1111058).

References 1. Trier, O.D., Jain, A.K., Taxt, T.: Feature extraction methods for character recognition—a survey. Pattern Recognition 29(4), 64–662 (1996) 2. Lauer, F., Suen, C.Y., Bloch, G.: A trainable feature extractor for handwritten digit recognition. Pattern Recognition 40(6), 1816–1824 (2007) 3. Partridge, M., Calvo, R.: Fast dimensionality reduction and simple PCA. Intelligent Data Analysis 2(3), 292–298 (1998) 4. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: a review. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1), 4–37 (2000) 5. Kang, M., Palmer-Brown, D.: A modal learning adaptive function neural network applied to handwritten digit recognition. Information Sciences 178(20), 3802–3812 (2008) 6. Vapnik, V.: The nature of statistical learning theory. Springer, New York (2000)

Research on System Stability with Extended Small Gain Theory Based on Transfer Function Yuqiang Jin* and Qiang Ma Department of Training, Naval Aeronautical and Astronautical University, 264001 Yantai, China {naau301yqj,maqiang1024}@126.com

Abstract. Considering the situation that controlled object is described by linear transfer function, a extended small gain theory is proposed and applied in the analysis of system stability. Especially, a comparison between two stable systems is researched and it is useful for the controller design of linear systems. What is worthy pointing out is that this method also can be applied in some general nonlinear systems with a simple transformation. So it is still an important improvement of the small gain theory although only the linear transfer function situation is studied. Keywords: Small gain theory, Transfer function, Stability, Control.

1 Introduction Robust control is researched by many scholars in recent years because not only the stability should be concerned but also the robustness should be considered by system designers. Many control methods are integrated with robust control to solve the system uncertainties such as adaptive control, neural network control and sliding mode control[1-5]. Small gain theory is one of the most important theories on system robustness in control field. It is very revealing about the essence of robustness and stability of control systems[4-7]. It also can guide the design of controller perfectly. Especially, it has some mature and systematic conclusions for linear systems. Also, the small gain theory can be extended in nonlinear systems in some special situation. In this paper, a comparison between two stable system is researched for linear controlled objects. And an extended small gain theory is proposed and it can be extended in a large family complex systems.

2 Main Conclusion The main conclusion of this paper can be concluded as the following theorem 1. *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 600–605, 2011. © Springer-Verlag Berlin Heidelberg 2011

Research on System Stability with Extended Small Gain Theory

Theorem 1: If a controlled object described by transfer function as stable with a controlled described by transfer function as

G (s) =

H ( s) =

601

B(s ) is A( s )

D( s) , then a C (s)

G1 ( s ) = G ( s )G2 ( s ) is table with a controller k0 D( s) H1 ( s ) = , where G2 ( s ) = . (k1s + 1)(k2 s + 1) k0C ( s )

controlled object described as

3 Preliminary Knowledge To make it simple, we consider a general kind of linear system with negative feedback and the transfer function can be written as

C ( s) =

G( s) 1 + G( s) H ( s) .

(1)

Assumption 1: The controlled object is stable. It means that there is no unstable poles in A( s ) . Assumption 2: The controller is realizable. It means that there is no unstable poles in C (s) .

4 Proof of the Theorem Considering the situation that, the transfer function of close loop system can be written as

C1 ( s ) =

G1 ( s ) 1 + G1 ( s ) H1 ( s ) .

(2)

Use the analogue , assume that the system is unstable, then there is unstable pole in

C1 ( s ) as C1 ( s ) =

G1 ( s ) 1 + G1 ( s ) H1 ( s )

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Where

1 + G1 (s) H1 (s) = 1 + G(s)G2 (s) = 1+

D(s) k0C (s)

G(s) D(s) (k1s + 1)(k2 s + 1)C ( s)

.

(3)

B(s) D(s) = 1+ (k1s + 1)(k2 s + 1) A(s)C (s) = Then the equation

B(s) D(s) + (k1s + 1)(k2 s + 1) A(s)C (s) (k1s + 1)(k2 s + 1) A(s)C (s)

B( s ) D( s ) + (k1s + 1)(k 2 s + 1) A( s )C ( s ) = 0 has a root as

s = a > 0. Because

the

original

system

is

stable,

B ( s ) D ( s ) + A( s )C ( s ) = 0 has no unstable roots. Define

so

the

equation

B ( s ) D ( s ) + A( s )C ( s ) = F ( s ) ,

(4)

B( s ) D( s ) + (k1s + 1)(k2 s + 1) A( s )C ( s ) = J ( s ) ,

(5)

and

Where A( s )C ( s ) has no unstable roots, then without loss of generality , we assume that A(0)C (0) > 0 . If F (0) > 0 and for s

> 0, F ( s ) > F (0) > 0 , then it is obviously has J (0) = F (0) > 0 , s > 0, J ( s ) − F ( s ) = [(k1s + 1)(k2 s + 1) − 1] A( s )C ( s ) > 0 . If F (0) < 0 , we can write F ( s ) as

F(s) = k(τ1s +1)(τ2s +1) + (τ3s +1)(τ4s +1)(τ5s +1) .

(6)

F(s) = k(τ1s +1)(τ2s +1) + (τ3s +1)(τ4s +1)(τ5s +1) .

(7)

Then

< 0 and the order of denominator polynomial is higher than the order of numerator polynomial. So we have F (∞) > 0 . And remember that F (0) < 0 , then Because k

Research on System Stability with Extended Small Gain Theory

603

it means that there exists positive roots of this system. So we proves that the new system is stable. If we consider the general situation such as G2 ( s ) = controller as H1 ( s ) =

k0 (k3 s + 1) and (k1s + 1)(k2 s + 1)

D( s) , the denominator polynomial of close loop system can k0C ( s )

be written as

(k3 s + 1) B( s ) D( s ) + (k1s + 1)(k2 s + 1) A( s )C ( s ) = J ( s ) .

(8)

And the denominator polynomial of the original system can be written as

F ( s ) = k (τ 1s + 1)(τ 2 s + 1) + (τ 3 s + 1)(τ 4 s + 1)(τ 5 s + 1) = B( s ) D( s ) + A( s )C ( s )

(9) .

> 0 , F (0) > 0 , for any s > 0, F ( s ) > 0, A(s)C(s)>0 , B ( s ) D ( s ) , A(0)C (0) > 0 , B (0) D (0) > 0 . The J (0) = F (0) > 0 , ( k3 s + 1) B ( s ) D ( s ) + ( k1s + 1)( k 2 s + 1) A( s )C ( s ) = J ( s ) , Because the original system is stable, so we have k

J ( s ) − F ( s ) = {( k3 s + 1) − 1}B ( s ) D ( s ) + {( k1s + 1)( k2 s + 1) − 1} A( s )C ( s ) . If s > 0 , {( k1s + 1)( k2 s + 1) − 1} A( s )C ( s ) > 0 . {( k3 s + 1) − 1}B ( s ) D ( s ) means that if both the controlled object and controller itself have no unstable roots, then J ( s ) − F ( s ) > 0 , so the system is stable. If the system is a non-minimum phase system, then the small theorem is necessary to cope it. We assume a transfer function is defined as

G2 ( s ) =

k0 (k3 s + 1) (k1s + 1)(k2 s + 1) .

(10)

And because it is a non-minimum phase system, we compute its infinite norm as

G2 ( s )

∞

= γ 3 > k0

.

(11)

Assume the infinite norm of the original system as

G( s)

∞

= γ1

.

(12)

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Y. Jin and Q. Ma

For controller, solve its infinite norm as

H (s)

∞

= γ2

(13)

.

According to small gain theorem, we have

G( s)

∞

H ( s)

∞

= γ 1γ 2 < 1

(14)

.

If the new system stable, then it should satisfy the following formula

G ( s )G2 ( s )

∞

H1 ( s )

<1

∞

(15)

,

and

G( s)G2 ( s)

∞

H1 (s)

∞

= G(s)G2 ( s)

H1 ( s) ∞

∞

< G( s) ∞ G2 ( s) ∞ H1 ( s) ∞ . = G(s) ∞ γ 3 H1 (s)

∞

(16)

<1

So we can design

H1 ( s ) =

k

γ3

,

Where k < 1 . Then we have

H1 ( s )

∞

=

k

γ3

(17)

H ( s)

H (s)

(18)

∞

.

Then it means that

G ( s )G2 ( s )

∞

H1 ( s )

∞

< G ( s ) ∞ γ 3 H1 ( s ) = G( s) ∞ γ 3 = k G (s)

∞

k

γ3

∞

H ( s)

H ( s)

∞

(19)

∞

<1

.

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Obviously, the system is stable now. It means that the new system is guaranteed to be stable only if the gain of the original system is amplified properly. And for some simple situations such as solve

its

infinite

norm.

For

G2 ( s ) = example,

k0 (k3 s + 1) , it is easy to (k1s + 1)(k2 s + 1) the

infinite

norm

of

k0 G2 ( s ) = is k0 . So it is the simple situation of this theorem. (k1s + 1)(k 2 s + 1)

5 Conclusion Because H1 ( s ) is not necessary to be linear for small gain theorem, we can design a nonlinear control law for a simple system, then we multiply the corresponding gain, so a stable control law for a complex system is designed. Also, G2 ( s ) is not necessary to be linear for small gain theorem, so this theorem can be applied in some nonlinear situations. Above all, the small gain theorem is extended based on the situation that the controlled object is linear transfer function. And it can be applied in a large family of complex system with the comparison method. Also, it is pointed that the comparison method can be applied in some nonlinear situations.

References 1. Lei, J., Wang, X., Lei, Y.: How many parameters can be identified by adaptive synchronization in chaotic systems? Phys. Lett. A 373, 1249–1256 (2009) 2. Lei, J., Wang, X., Lei, Y.: A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters. Commun. Nonlinear Sci. Numer. Simul. 14, 3439–3448 (2009) 3. Wang, X., Lei, J., Lei, Y.: Trigonometric RBF Neural Robust Controller Design for a Class of Nonlinear System with Linear Input Unmodeled Dynamics. Appl. Math. Comput. 185, 989–1002 (2007) 4. Hu, M., Xu, Z., Zhang, R.: Parameters identification and adaptive full state hybrid projective synchronization of chaotic (hyper-chaotic) systems. Phys. Lett. A 361, 231–237 (2007) 5. Gao, T., Chen, Z., Yuan, Z.: Adaptive synchronization of a new hyperchaotic system with uncertain parameters. Chaos Solitons Fractals 33, 922–928 (2007) 6. Elabbasy, E.M., Agiza, H.N., El-Dessoky, M.M.: Adaptive synchronization of a hyperchaotic system with uncertain parameter. Chaos Solitons Fractals 30, 1133–1142 (2006) 7. Tang, F., Wang, L.: An adaptive active control for the modified Chua’s circuit. Phys. Lett. A 346, 342–346 (2005)

Research on the Chattering Problem with VSC of Supersonic Missiles Based on Intelligent Materials Junwei Lei*, Jianhong Shi, Guorong Zhao, and Guoqiang Liang Department of Control Engineering, Naval Aeronautical and Astronautical University, 264001 Yantai, China {leijunwei,zhaoguorong302,liangguoqiang1024}@126.com, [email protected]

Abstract. Considering pitch channel simplified model of missile control system, a VSCL(variable structure control law) is designed by using overload and angle velocity signals. Especially, an analysis is proposed for the situation of equal control with uncertainties. An integral action is introduced to compensate the uncertainties and a soft function is adopted to solve the chattering problem of VSC. Finally, an analysis for the chattering problem, the function of integral action and soft function is thoroughly studied. The conclusion shows that the dead zone of soft function is a important factor that affect the chattering phenomenon. And the relationship between the chattering problem and the system gain is revealed. Keywords: Chattering, VSC, Missile, Uncertain, Stability.

1 Introduction Because the sliding mode of VSC system is inflexible, it means that it is independent with the outer interference and system uncertainties, so the VSC method is an ideal robust control method. Many control methods are integrated with robust control to solve the system uncertainties such as adaptive control, neural network control and sliding mode control [1-5]. As the development of computer technology and automatic industry, the realization of control algorithm need to use computers, so the discrete control algorithm is used wildly. But the discrete control law can not lead to ideal sliding mode, it can only cause quasi-slide control. And because of the existence of quasi-slide mode, the chattering and accuracy problem are more prominent in discrete control field [6-9]. There are many factors caused the above problem. In this paper, a pitch channel simplified model of missile control system is researched based on the sliding mode control with overload and angle velocity signals. And the essential reason for causing the chattering problem is studied. Also the integral adaptive strategy and soft function are analyzed and adopted to reduce the chattering problem. As a side note, the chattering situations caused by discrete computer algorithm or caused by the choosing of simulation step are neglected in this paper. *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 606–611, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Model Description Taking the model of pitch channel of anti-ship missile for a example, the air dynamic of missile pitch channel system can be written as follows:

1 ( P sin α + Y − mg cosθ ) mv M m qS L ω z = z = z Jz Jz

α = ω z −

ny =

，

(1)

P sin α + Y mg

the definition of symbols can see ref[6]. A theorem in paper[6] shows that any linear feedback control law that can stabilize the linear approximate system can also stabilize the original nonlinear system only if the linear approximate system of the nonlinear system is gradual stable. So we can research the linear approximate system and then we can find a control law that can stabilize the original nonlinear system. The linear approximate system can be described as follows:

α = ω z − a34α − a35δ z ω z = a24α + a22ω z + a25δ z v v n y = a34α + a35δ z g g

.

(2)

3 Control Law Design We define a new variable as

e = n y − n yd , and consider that it is difficult to measure

the attack angle, so we choose the sliding mode as follows:

S = c1e + c2 ∫ edt + c3ω z .

(3)

Solve the derivative of the sliding mode as

S = c1e + c2 e + c3ω z = l1ω z + l2α + l3δ z + l4δz + l5 Δ1 (α , t ) + l6 Δ 2 (α , t ) + l7 e

,

(4)

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J. Lei et al.

Where parameters are defined as

l1 = (c1

g v g v − c1 a34 + c2 ) , a34 + c3 a22 ) , l2 = (c3a24 va34 g v g

(5)

va va v v a34 35 + c3 a25 − c1 a34 a35 − c3 a24 35 ) g g g ga34 ,

(6)

l3 = (c1

l4 = c1

v a35 g

，l

5

= −c1n dy − c2 n dy .

(7)

Because it is impossible to accurately remove the equal control item caused by system uncertainties, we use an integral action to remove the equal control item and compensate system uncertainties. As a side note, if we increase the gain of the system to eliminate the equal control item, then the chattering will also be increased. So we consider using a integrator to approximate the equal control item. For the standard system, we have

s = l1ω z + l2 n y + v + l5 . Design the control law as v = −l1ω z

(8)

− l2 n y − l5 − k1 sgn( s ) − k2 s , then the system

is stable. Also, if we design the control law as

v = − k1 sgn( s ) − k 2 s − k d sgn( s ), k d = max( −l1ω z − l2 n y − l5 ) .

(9)

Then we have ss ≤ 0 , also the system is stable and s → 0 .

4 System Analysis We consider to use a integrator to approximate the equal control item such that s → 0 . Then we define a new variable as

ek = k d − kˆd and design

v = − k1 sgn( s) − k2 s − kˆd sgn( s) ,

(10)

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It holds as

ss < − k1 s − k2 s 2 − kˆd s + kd s = − k1 s − k2 s 2 + ek s .

(11)

Then

ss = s (l1ω z + l2 n y + l5 − k1 sgn( s ) − k2 s − kˆd sgn( s )) = −k1 s − k2 s 2 − kˆd s + (l1ω z + l2 n y + l5 ) s ≤ − k1 s − k2 s 2 − kˆd s + kd s

.

(12)

< − k1 s − k2 s 2 + ek s kd = max( −l1ω z − l2 n y − l5 ) and because kd is bounded, then  design e = − kˆ , so we have e e = −kˆ e = −e s .Then it means design kˆd = s k d k k d k k We assume

, the system is guaranteed to be stable. Now we consider how to reduce the chattering of the system. We consider that keep the equal control item to prove a constant value in the control law as

v = − k1 sgn( s ) − k2 s − kˆd sgn( s ) + sat keq (kˆ1d ) , Where

(13)

kˆ1d = ∫ sdt is used to estimate the equal control item. Then we have

ss = s (l1ω z + l2 n y + l5 − k1 sgn( s ) − k2 s − kˆd sgn( s ) + sat keq (kˆd )) = −k1 s − k2 s 2 − kˆd s + (l1ω z + l2 n y + l5 ) s ≤ −k1 s − k2 s 2 − kˆd s + kd s + satkeq (kˆd ) s

.

(14)

< −k1 s − k2 s 2 + ek s + satkeq (kˆd ) s If we choose k1

> keq , then the equal control item can be estimated properly. Also

because of the introduce of estimation of equal control item, the chattering of the system will be reduced.

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Undoubtedly, there always exists chattering only there exists the sign function. So we use a continuous function instead of the sign function. For the standard system

s = l1ω z + l2 ny + v + l5 , we design the control law as

v = −l1ω z − l2 n y − l5 − k1 sgn( s ) − k2 s to make the system stable. A soft function is taken place of the sign function as

v = −l1ω z − l2 n y − l5 − k1

s − k2 s . s +δ

(15)

Then it holds as

ss = s (l1ω z + l2 n y + v + l5 ) = − k1

s2 − k2 s 2 < 0 . s +δ

(16)

But considering the uncertainties, Design the control law as

v = − k1 sgn( s ) − k2 s − kd sgn( s ) kd = −l1ωz − l2 n y − l5

.

(17)

So the system is stable. And considering the situation of soft function, design

s s − k2 s − k g s +δ s +δ , kd = max( −l1ω z − l2 n y − l5 )

v = − k1

(18)

Then it holds

ss = s(l1ωz + l2ny ++l5 − k1 < −k1

s s − k2s − kg ) s +δ s +δ

s2 s2 − k2s2 + kd s − kg s +δ s +δ

,

(19)

It is easy to prove that

kg s (kd − k g ) s + kd δ s2 kd s − k g = s (kd − )= s . s +δ s +δ s +δ

(20)

Research on the Chattering Problem with VSC of Supersonic Missiles

Then choose k g

611

= kd , and get kδ 1 s2 = s d ≤ kd (δ s )1/ 2 , s +δ s +δ 2

(21)

kδ s s (k1 s − kd δ ) s2 − k2 s 2 + d =− − k2 s 2 . s +δ s +δ s +δ

(22)

kd s − k g So it is easy to prove that

ss < − k1

So the stable area is solved as only if

δ

s > kd δ / k1 . And the dead zone is small enough

is small enough. Also if we increase k1 , then the dead zone will be reduced.

5 Conclusions The functions of integral equal control and soft function are researched to reduce the chattering of a class of pitch channel simplified model of missile system. And the relationship between the system gain and dead zone of soft function is analyzed.

References 1. Gao, W., Hung, J.C.: Variable Structure Control of Nonlinear systems: A New Approach. IEEE Trans. Indus. Electro. 40(1) (February 1993) 2. Polycarpou, M.M., Ioannou, P.A.: A Robust Adaptive Nonlinear Control Design. Automatic 32(3), 423–442 (1996) 3. Kim, S.-H., Kim, Y.-S., Song, C.: A robust adaptive nonlinear control approach to missile autopilot design. Contr. Engin. Prac. 12, 149–154 (2004) 4. Tang, F., Wang, L.: An adaptive active control for modified Chua’s circuit. Phys. Lett. A 346, 342–346 (2005) 5. Elabbasy, E.M., Agiza, H.N., El-Dessoky, M.M.: Adaptive synchronization of a hyperchaotic system with uncertain parameter. Chaos Solitons Fractals 30, 1133–1142 (2006) 6. Qian, X., Zhao, Y.: Flying Mechanics of Missiles. Beiing University of Engineering Press, Beijing (2000) 7. Lei, J., Wang, X., Lei, Y.: How many parameters can be identified by adaptive synchronization in chaotic systems? Phys. Lett. A 373, 1249–1256 (2009) 8. Lei, J., Wang, X., Lei, Y.: A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters. Commun. Nonlinear Sci. Numer. Simul. 14, 3439–3448 (2009) 9. Wang, X., Lei, J., Lei, Y.: Trigonometric RBF Neural Robust Controller Design for a Class of Nonlinear System with Linear Input Unmodeled Dynamics. Appl. Math. Comput. 185, 989–1002 (2007)

Research on Backstepping Nussbaum Gain Control of Missile Overload System Jianhong Shi*, Guorong Zhao, Junwei Lei, and Guoqiang Liang Department of Control Engineering, Naval Aeronautical and Astronautical University, 264001 Yantai, China [email protected], {zhaoguorong302,leijunwei,liangguoqiang1024}@126.com

Abstract. The overload control of missile system is researched under the condition that the control direction is unknown. A nussbaum gain strategy is adopted to solve the unknown control direction problem for the linear model of missile motion of pitch channel . The backstepping technology and integral action are used to cope the system uncertainty. A novel type of control law, which is only consisted of overload signal and angle velocity of missile, is constructed and the stability of whole system is guaranteed by a whole Lyapunov function. The defect of the proposed method is that the dyanmic of control fin is not considered. Keywords: Backstepping, Uncertainty, Nussbaum Gain, Supersonic Missile, Overload Control.

1 Introduction Backstepping technology is a well-known method which is widely used in the design of missile control systems[1-5]. The control system of missiles described by the differential equations have strong nonlinearities and time varying characteristics. In this paer, the linear model of missile pitch channel motion is studied basd on previous research work. The input coefficient is assumed to be unknown, which is usually satisfied in real missile flight control. And the Nussbaum gain method is used in this paper to solve the unknown control direction problem. Also uncertain linear supersonic missile system is controlled where only overload and angle velocity are necessary to be measurable. Most important of all, no aero-coefficient is necessary to be known because of the adopting of integral action.

2 Model Description Without considering the first order dynamic of actuator, the linear model for the missile motion in the pitch channel are given by *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 612–615, 2011. © Springer-Verlag Berlin Heidelberg 2011

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613

α = ωz − a34α − a35δ z ω z = a22ωz + a24α + a25δ z ny =

v v a34α + a35δ z g g

(1)

.

The control objective is to design a control u such that the overload of the system d n ( y )can track the desired value n y , where the sign of a25 is unknown. With some transformations, the above model can be written as

v v v v ny = a34ωz − a34 a34 f (ny ,δ z ) − a35 a34δ z + a35δz g g g g , ω z = a22ωz + a24 f (ny ,δz ) + a25δ z Where

(2)

f (n y , δ z ) can be solved by the above output equation.

3 Stability Analysis Considering the above subsystem, define a new variable as

e1 = ny − n dy , We define

a new variable as

f1 = − a34

v v v a34 f ( ny , δ z ) − a35 a34δ z + a35δz . g g g

Assume that there exist two parameters

d11 and d10 such that

f1 ≤ d1e1 + d0 . Then design the virtual control

(3)

(4)

ω zd as

ω zd = − k11 sign ( a34 )e1 − k12 sign ( a34 ) ∫ edt .

(5)

Then it holds

e1e1 = −

v v v a34 k11e12 − a34 k11e1 ∫ e1dt + f1e1 + a34 e2 , g g g

(6)

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Where

e2 is defined as e2 = ω z − ωzd .

Also define a new variable as

f 2 = a22ω z + a24 f (n y , δ z ) − ω zd . Similarly, also assume that there exist two parameters

(7)

d 21 and d 20 such that

f 2 ≤ d 21e2 + d 20 .

(8)

If the sign of a22 is known, so in the same way, the virtual control for this subsystem can be designed as:

δ zdd 1 = −k 21sign(a22 )e2 − k22 sign(a22 ) ∫ e2 dt .

(9)

Since the sign of a22 is unknown, a Nussbaum gain strategy is adopted to solve the unknown input coefficient proble, the virtual control can be designed as follows:

δ z = − N ( k )δ zdd 2 ,

(10)

δ zdd 2 = −k 21e2 − k22 ∫ e2 dt ,

(11)

N ( k ) = k cos( k ) ,

(12)

Where

And design

And the turning law of Nussbaum gain is designed as

k = −e2δ zdd 2 .

(13)

Also, the following equation holds

e2e2 = f2e2e2 − k21 a22 e22 − k22 a22 e2 ∫ e2dt − e2 (1 + a25 N (k ))δ zdd 2

.

(14)

Choose a Lyapunov function as

V =

1 2 1 2 e1 + e2 2 2 .

(15)

Research on Backstepping Nussbaum Gain Control of Missile Overload System

615

It is easy to prove that

V ≤ (1 + a25 N ( k )) k .

(16)

With integral computation on both side of the inequality, it holds

Vi (t ) − Vi (0) ≤ (k (t ) − k (0) + a25 ∫

k (t )

k (0)

Use the apagoge method, assume that

( N (k ))dk .

(17)

k (t ) will be unstable in finite time, so when

t → tn , k (t ) → ∞ . With the help of Nussbaum gain function characteristics, it is easy to prove the above inequality is contradict. So k (t ) is bounded in finite time and the system is stable.

4 Conclusions The main contribution of this paper can be summarized as follows. A nussbaum gain strategy is adopted to slove the unknown control direction problem for the linear model of missile motion of pitch channel . Also, the backstepping technology and integral action are applied to guarantee the whole system is stable and only overload and angle velocity are necessary to be measured. But the defect of this paper is that the dyanmic of control fin is not considered. So it will be throughtly considered in our future work.

References 1. Elabbasy, E.M., Agiza, H.N., El-Dessoky, M.M.: Adaptive synchronization of a hyperchaotic system with uncertain parameter. Chaos Solitons Fractals 30, 1133–1142 (2006) 2. Qian, X., Zhao, Y.: Flying Mechanics of Missiles. Beiing University of Engineering Press, Beijing (2000) 3. Lei, J., Wang, X., Lei, Y.: How many parameters can be identified by adaptive synchronization in chaotic systems? Phys. Lett. A 373, 1249–1256 (2009) 4. Lei, J., Wang, X., Lei, Y.: A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters. Commun. Nonlinear Sci. Numer. Simul. 14, 3439–3448 (2009) 5. Wang, X., Lei, J., Lei, Y.: Trigonometric RBF Neural Robust Controller Design for a Class of Nonlinear System with Linear Input Unmodeled Dynamics. Appl. Math. Comput. 185, 989–1002 (2007)

Adaptive Control of Supersonic Missiles with Unknown Input Coefficients Jinhua Wu*, Junwei Lei, Wenjin Gu, and Jianhong Shi Department of Control Engineering, Naval Aeronautical and Astronautical University, 264001 Yantai, China {wujinhua1024,leijunwei,guwenjin301}@126.com, [email protected]

Abstract. Based on previous work, a Nussbaum gian controller is proposed to solve the unknown input direction problem of a large family of supersonic missiles. Also considering the one order dynamic characteristic of actuator , the uncertainties of nonlinear missile system, which is assumed to satisfy the socalled bounded uncertainty condition, are coped by the adopting of integral action and backstepping technology.And the unknown control direction problem of supersonic missile is solved by adopting of the Nussbaum gain method. A novel analysis with Lyapunov function and Nussbaum gain function are completed and the stability of the whole system is guaranteed by constructing of the Lyapunov function. Keywords: Adaptive, Nussbaum Gain, Missile, Control.

1 Introduction Adaptive backstepping controllers has been researched in many papers[1-5]. The uncertainties in missile pitch plane’s model considered in [2] are consisted of uncertain parameters and unknown nonlinear functions, where the unknown functions represents the model error or the time varying of the system. But the input coefficient are assumed to be positive. In fact, the sign of input coefficient is possibly to be unknown or it will be changed unexpectly under some complex fight conditions. In this paper, a Nussbaum gain strategy is proposed to control the uncertain supersonic missile described in [2]. Comparing with the above adaptive method, the unknown control direction problom is solved by adopting the Nussbaum gain control technology.

2 Model Description The nonlinear model for the missile motion in the pitch plane is adopted by Hull & Qu[2]. Considered the first order dynamic of actuator, equations of motion in the pitch plane are given by *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 616–620, 2011. © Springer-Verlag Berlin Heidelberg 2011

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617

⎛ QS ⎞

α = ⎜ ⎟ [C z (α , M m ) + B zδ ] + q ⎝ mV ⎠ ⎛ QSd q = ⎜ ⎜ I ⎝ yy

⎞ ⎟⎟ [C m (α , M m ) + Bmδ ], δ = au − aδ ⎠

, (1)

where α , q and δ are angle of attack, pitch rate and control fin deflection angle, respectively, and

m, V , I yy , Q, S and d are mass, velocity, pitching moment of

inetia, dynamic pressure, reference area, and reference length, respectively, and M m is Mach number, u and a are control input and actuator bandwidth, respectively. The aerodynamic coefficients in Eq.(1) are represented as the function of Mach number and angle of attack, the expression of functions can see ref [1]. Taking uncertainties of the aerodynamics into consideration, we can rewrite Eq.(1) as

x1 = f1 ( x1 ) + Δf1 ( x1 ) + x2 + [ g1 + Δg1 ]x3 , x2 = f 2 ( x1 ) + Δf 2 ( x1 ) + [ g 2 + Δg 2 ]x3

(2)

x1 is α and x2 stands for q , and the defination of Δ1(x1,t) , Δf1(x1) , g1 , Δg1 , Δ 2 ( x1 , t ) , Δf 2 ( x1 ) , g 2 , Δg 2 and b2 see ref [1].

Where the defination of

With the same analysis in [1], we can get the inequalities as

Δf1 ( x1 ) < ( ΔC1 + C1 p2 + ΔC1 p2 )[ φz1 ( x1 ) + φz 2 ( x1 )Mm ] ,

(3)

Δf2 (x1) < ( ΔC2 + C2 p3 + ΔC2 p3 )[ φm1(x1) + φm2 (x1)Mm ] .

(4)

And

The main assumption of this paper is the below assumption 1. Assumption 1: The uncertainties of the system satisfies the following triangular bounds condition:

Δ i ( x, t ) ≤ ψ i pi ( x) ,where pi ( x) are unknown smooth functions

andψ i are unknown constant parameters. Definition 1: characteristics

N ( χ ) is a Nussbaum-type function, if it has the following

Δf2 ( x1) < ( ΔC2 + C2 p3 + ΔC2 p3 )[ φm1( x1) + φm2 ( x1 )Mm ] ,

(5)

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and

lim inf s →∞

1 s N ( x)dx = −∞ . s ∫0

(6)

3 Design of Nussbaum Gain Controller Considering the above subsystem, a new type Nussbaum gain controller can be designed as follows. First, define a new variable as

e1 = x1 − x1d , then the first order subsystem can be

written as

e1 = f1 ( x1 ) + Δf1 ( x1 ) + x2 + [ g1 + Δg1 ]x3 − x1d ,

(7)

Design a integral virtual controller for the first order subsystem as follows:

x2d = − f1 ( x1 ) − k1e1 − k2 ∫ e1dt .

(8)

f = Δf1 ( x1 ) + [ g1 + Δg1 ]x3 − x1d .

(9)

f ≤ d1 e1 + d 2 ,

(10)

Define

And assume

where

d1 and d 2 are positive constant.

Then we define a new variable as

e2 = x2 − x2d , then the second order subsystem

can be written as

e2 = f 2 ( x1 ) + Δf 2 ( x1 ) + [ g 2 + Δg 2 ] x3 − x2d ,

(11)

Because Δg 2 is unknown, we use a Nussbaum gain control method to solve the uncertain input coefficient problem. First, we design a virtual control as:

x3dd = − f 2 ( x1 ) − k3e2 − k4 ∫ e2 dt .

(12)

Adaptive Control of Supersonic Missiles with Unknown Input Coefficients

619

Define

g = Δf 2 ( x1 ) − x2d ,

(13)

g ≤ d3 e3 + d 4 ,

(14)

Assume

where

d3 and d 4 are positive constant. It is obviously that if [ g 2 + Δg 2 ]x3 = x3dd ,

the system is stable with big enough

di . Because of the existence of unknown input

coefficient, a Nussbaum gain is adopted to cope with it as follows. Design the control as

x3 = − N (λ ) x3dd ,

(15)

N (λ ) = λ cos(λ 2 / 4 ) ,

(16)

Where

And the adaptive turning law of Nussbaum gain is designed as

λ = −e2 x2dd .

(17)

Choose a Lyapunov function as

V=

1 2 1 2 e1 + e2 . 2 2

(18)

It is easy to prove that

V ≤ −e2 ( g 2 + Δg 2 ) N (λ )) x2dd − x2dd .

(19)

V ≤ λ[1 + ( g 2 + Δg 2 ) N (λ )] .

(20)

Then it satisfies

With integral computation on both side of the inequality, It holds as

Vi (t ) − Vi (0) ≤ (λ (t ) − λ (0) + ( g 2 + Δg 2 ) ∫

λ (t )

λ (0)

( N (λ ))d λ .

(21)

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Use the apagoge method, we assume that

λ (t ) will be unstable in finite time, so

t → tn , we have λ (t ) → ∞ . With the help of Nussbaum gain function characteristics, it is easy to prove the above inequality is contradict. So λ (t ) is when

bounded in finite time. And it is easy to prove that the system is stable.

4 Conclusions A novel adaptive controller is designed with Nussbaum gain strategy and the unknown input coefficient problem of supersonic missile is solved in this paper. Also, the uncertainties are coped by the adopting of integral action and backstepping technology. So the whole system is guaranteed to be stable with the help of the Lyapunov stability theorem.

References 1. Kim, S.-H., Kim, Y.-S., Song, C.: Contr. Eng. Prac. 12, 149–154 (2004) 2. Hull, R.A., Qu, Z.: Design and evaluation of robust nonlinear missile autopilot from a performance perspective. In: Proce. of the ACC, pp. 189–193 (1995) 3. Lei, J., Wang, X., Lei, Y.: How many parameters can be identified by adaptive synchronization in chaotic systems? Phys. Lett. A 373, 1249–1256 (2009) 4. Lei, J., Wang, X., Lei, Y.: A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters. Commun. Nonlinear Sci. Numer. Simul. 14, 3439–3448 (2009) 5. Wang, X., Lei, J., Lei, Y.: Trigonometric RBF Neural Robust Controller Design for a Class of Nonlinear System with Linear Input Unmodeled Dynamics. Appl. Math. Comput. 185, 989–1002 (2007)

The Fault Diagnostic Model Based on MHMM-SVM and Its Application FengBo Zhu*, WenQuan Wu, ShanLin Zhu, and RenYang Liu Naval University of Engineering, 717, Jiefang Road, Wuhan, China [email protected]

Abstract. A new method of incipient fault diagnosis for analog circuits based on MHMM-SVM was presented. The model of MHMM has the ability of dealing with continuous dynamic signals and is suitable to depict for the samples that are in the same kinds, the model of SVM is based on Structural Risk Minimization and is adapt in classifying the different kinds. The two models are complementary for each other, and the method made them fused. At first, the dimensions of the experimental samples were decreased and divorced easily with the LDA technology, and secondly, the MHMM-SVM model was built using the samples. Finally, from experimental results that are compared with MHMM-based and SVM-based diagnostician methods, the conclusion can be drawn that the method has certain advantages for the incipient fault diagnosis. Keywords: MHMM-SVM, analog circuit, incipient faults, LDA.

1 Introduction Because of varieties of electronics equipments faults, component bad and structure of complexity, for long time, the most of faults examination and fixed positions of electronics system are the problems of hard solution. Currently ,calculate ways ,for example of misty nerve network, inherit methods etc mostly are more effective under the circumstance that equipments take place hard faults (equipments is complete or part expiration diagnose), but for equipments incipient fault diagnosis and advance forecast as that the equipments take place soft faults(the parameter outruns permits and differs but don't make equipments complete expired), there are nothing good to report[7].However, the hard faults usually arouse a series of chain reaction, and results that the whole equipments may break down, therefore, looking for the way of incipient fault diagnosis and forecast has significance for keeping the whole equips from breaking down. The model of HMM is a kind of dual random process that extensively is applied to the signal processing and the mode to identify, and it has the ability of dealing with continuous dynamic signals, already succeed to be applied to the realm of the speech understanding and others' face to identifying[1].At home and abroad parts of experts *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 621–627, 2011. © Springer-Verlag Berlin Heidelberg 2011

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have started to apply it for faults diagnosis and positioning, the effect is better than the traditional methods such as the neural network[2,3,5].The model of SVM is machine learning method that comes from data classification statistics theory, and has high classification accuracy and well spreading ability, ,and currently at faults diagnosis realm has already got an extensive application[2,4]. MHMM model is suitable to depict for the samples that are in the same categories, SVM model is adapt in classifying the different categories[1,2]. The two merits are complementary for each other, the method of the passage made them fused to deal with the samples of incipient faults, from experimental results comparing with MHMM-based and SVM-based diagnostician methods, the conclusion can be drawn that the method has certain advantages for the incipient fault diagnosis.

2 The Model of MHMM-SVM 2.1 The Model of Gaussian of Mixture HMM(MHMM) The MHMM model is a extension of HMM when the observation sequence is a continuous density distribution signal. The HMM model which is subjected to continuous density distribution presumes that the observed feature vector distributes in a sort of probability density. The quality of this kind of model depends on physical truth of assumed probability distribution. Generally speaking, some frequently-used probability distribution functions is hard to describe the distribution of a set of data in a single way, therefore, the Gaussian of Mixture HMM is presented, which approximates the actual distribution of feature vector by using several Gaussian distributions called Gaussian Mixture Model(GMM) while each distribution have different kernel and dispersion. 2.2 Support Vector Machines(SVM) SVM is a learning technique developed by Vapnik and his team in 1959, which is based on statistical learning theory. It has remarkable advantages in dealing with small-sample, non-linear and high dimension problems and is rest on the VC dimension theory and structural risk minimization of statistical learning theory. SVM also provides the best compromise between complexity(that is ,the learning accuracy for given training samples) and leaning ability (that is, the ability to identify each samples faultlessly) of the model for limited set of sample information to obtain the best generalization ability. Structural risk minimization (SRM) denotes the minimal sum of empirical risk and belive risk. Machine learning is essentially a approximation of real model of the problem. Empirical risk denotes the error of classifier on given samples, and believe risk has a relationship with two parameters: one is the number of samples, it is obvious that the larger the number of samples and the higher the accuracy of leaning outcomes, the believe risk is littler; the other is VC dimension of a classification function (the complexity of samples), simply, the VC dimension is larger, the generalization ability is worse and the confidence risk is higher.

The Fault Diagnostic Model Based on MHMM-SVM and Its Application

623

2.3 The Major Process of SVM-MHMM Used for Fault Diagnosis Fault diagnosis based on MHMM is decided by maximum likelihood value outputted by the model. As for a data sample with tolerance, it is possible that some of its MHMM models are pretty similar. Depending on the above only to classify the samples would lead to an error. Similarly, fault diagnosis based on SVM clarifies only according to the signal features at fixed time, which ignores the sequential features, would also lead to erroneous judgment. In conclusion, fault diagnosis based on MHMM-SVM is presented. The major process of this model are as follows:

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Fig. 1. Flow char of fault diagnosis based on MHMM-SVM 7+(5(68/76

The whole process contains four parts: feature extraction, diagnosis of MHMM, diagnosis of SVM and making a judgment.

3 The Application of MHMM-SVM on Incipient Fault Diagnosis of Analog Circuits In this paper, take the typical circuit of active filter for example, the tolerances of each components are 5%: 9 & &

& 

5  



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F. Zhu et al.

If the value of a component goes beyond the normal range of 20%, it was called the incipient soft fault. A Monte Carlo analysis is conducted to one of the states of the circuit by Multisim:

Fig. 3. Analyzing based on Monte Carlo Method

As is depicted in the figure, the effect of incipient parameters' change on outputs of the circuit is more obvious in the frequency of ranging from 10KHZ to 100KHZ. The values under the following frequency are elected to compose a 9-dimentional vector which serves as original datas:8KHZ, 10KHZ, 15KHZ, 20KHZ, 30KHZ, 50KHZ, 60KHZ, 80KHZ, 100KHZ. One hundred original vectors are obtained from one hundred times' Monte Carlo analysis for each states. 3.1 The Original Data Processing Based on Linear Discriminant Analysis (LDA) The original samples collected from the circuit are pretty redundant and complex, which would not only affect the results but also increase the complexity of training when it is used for training of MHMM-SVM model directly. However, with the LDA technique, the original data could be transformed into a lower dimensional space, thus it promotes the arithmetic speed and has high accuracy LDA is a dimension reduction and supervised method used in classification, which is widely applied in face recognition at the moment. It based on Fisher criterion, searching for the best projection vector that maps a high-dimensional sample into a low-dimensional space, which obtains the maximum between-class scatter and the minimum within-class scatter of all projection samples. That is to say, samples of the same class are gathered and the different one is separated as far as possible in dimensionality reduction[6]. Through dimensionality reduction by LDA, two columns of data that has maximum eigenvalue are selected to plot the figure. As is obviously showed, not only Z R R R R R R C C C C

0 .3 0 .2 0 .1 0

C 1 1 3 3 4 4 1 1 2 2

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0 .2

0 .4

0 .6

Fig. 4. The samples dimensions-decreased by LDA

0 .8

S J S J S J S J S J

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dimensionality reduction is realized but also the data obtains preliminary classification to some extent. When R2 goes beyond the normal range of 20%, the outputs are exactly the same with the normal one's, which does not affect its results. Therefore, there are eleven states as follows: the value of R1 rises 20%, the value of R1 drops 20%, the value of R3 rises 20%, the value of R3 drops 20%, the value of C1 rises 20%,the value of C1 drops 20%, the value of C2 rises 20%,the value of C2 drops 20%, the value of R4 rises 20%, the value of R4 drops 20%, and normal state. The original feature vectors are reduced to five-dimensional ones, which are used as data samples. 3.2 The Training and Result of the Model of SVM-MHMM Fifty feature vectors of one hundred ones serve as the training samples. Five ones are chosen in random to compose a observation sequence, so fifty observation sequences are obtained. In the same way, the other fifty feature vectors are used as testing samples. Eleven models of MHMM should be trained for eleven states of the circuit. The feature vector is the mixture of three Gaussian models. The value of the states of MHMM is set as five and the structure is classed as left to right one. Initial state is normal, so the initial matrix is [1,0,0,0,0]. The state transition matrix is [0.5,0.5,0,0,0;0,0.5,0.5,0,0;0,0,0.5,0.5,0;0,0,0,0.5,0.5;0,0,0,0,1]. K-means algorithm is used to approximate the observation sequence to determine the parameters of Gaussian of Mixture HMM. The model is trained by E-M algorithm where iterations is set as 50 and fluctuation tolerance is 1e-4. Figure 5 shows the iteratin of the state of R1 rising for 20%. 9 5 0 9 0 0 8 5 0 8 0 0 7 5 0 7 0 0 6 5 0 6 0 0 5 5 0 5 0 0

0

2

4

6

8

1 0

1 2

1 4

1 6

1 8

Fig. 5. The process of log-likelihood constringed

The model of SVM is mainly used to classify the two categories whose log-likelihood values are the most similar in the judgment of MHMM. Therefore, fifty-five binary classifications should be trained, for example, fig.6 and fig.7.

Fig. 6. Binary classification of R1↑and R1↓

Fig. 7. Binary classification of R1↑and C2↑

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When a testing sequence has been judged by the model of MHMM, two states are obtained whose log-likelihood values are the most similar. Subsequently, put the above testing sequence into the SVM classification trained for the two state to compartmentalize. At last, faults diagnosis result is obtained as that the following table 1 shows: Table 1. Faults diagnosis results QRUPDO

5Ĺ

5Ļ

5Ĺ

5Ļ

5Ĺ

5Ļ

&Ĺ

&Ļ

&Ĺ

&Ļ

0+00



 



















690























0+006  90



  







 



It can be seen from table 1 that the fault detection rate of MHMM-SVM is higher than the single model of MHMM or SVM, and MHMM is better than SVM in a certain extent. As for high separation samples, the three model all have good fault detection rate such as the normal state. But for the extreme overlapping samples such as the change of R1 and C2, the results are different widely. The sample separation of R1↑ and R1↓ is larger from fig.4, so it is good to the classification of SVM, but the log-likelihood values of MHMM are -612.02 and -612.86 that are almost the same; On the contrary, the sample separation of R1↑ and C2↑ is lower, which does bad to the classification of SVM, but the log-likelihood values of MHMM are -612.02 and -630.66, and the classification can be carried out easily. Therefore, the combination of two models has better results of classification for extreme overlapping samples.

4 Conclusion The method based on MHMM-SVM for the incipient fault diagnosis of electronic device has better advantages than ones based on the single model of MHMM or SVM. Based on comprehensive analysis of the advantages of both models, that is, the abilities of MHMM describing related sequences and the abilities of SVM depicting the between-class most distance, this paper bears out the practicability and feasibility of the combination of two models.

References 1. Shi, D.C., Han, L.Y., Yu, M.H.: Automatic audio stream classigication based on hidden markov model and support vector machine. Journal of Changchun University of Technology (Natural Science Edition) 29(2), 178–182 (2008) 2. Liu, X.M., Qiu, J., Liu, G.J.: HMM-SVM Based Mixed Diagnostic Model and Its Application. Acta Aeronautica et Astronautica Sinica 26(4), 497–500 (2005) 3. Xu, L., Wang, H.J.: Study on Fault Prognostic and Health Management for Electronic System. University of Electronic Science and Technology of China, Chengdu (2009)

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4. Chen, S.J., Lian, K., Wang, H.J.: Method for Analog Circuit Fault Diagnosis Based on GA Optimized SVM. Journal of University of Electronic Science and Technology of China 38(4), 554–558 (2009) 5. Alpaydin, E.: The Grid: Introduction to Machine Learning. China Machine Press, Beijing (2009) 6. Zhang, A.N., Zhuang, Z.M.: A Study on the Method of Face Recognition Based on Optimized LDA and RBF Neural Network. Shantou University (2007) 7. Yang, S., Hu, M., Wang, H.: Study on Soft Fault Diagnosis of Analog Circuits. The Electronics and Computer 25(1), 1–8 (2008)

Analysis of a Novel Electromagnetic Bandgap Structure for Simultaneous Switching Noise Suppression Hua Yang*, ShaoChang Chen, Qiang Zhang, and WenTing Zheng Naval University of Engineering, 717, Jiefang Road.Wuhan, China [email protected]

Abstract. Electromagnetic Bandgap (EBG) structures have been successfully applied for suppressing the Simultaneous Switching Noise (SSN) between the power and ground planes. Aimed at the relative narrow bandwidth and the poor performance in low frequency of the conventional Uniplanar-Compact EBG (UC-EBG) structure, a novel EBG structure formed by adding spiral-shaped metal strips on the conventional UC-EBG is proposed. This new EBG structure significantly enhance the equivalent inductance between the neighboring nuit cells, as well as change the character of the stop-band. Simulation results show that the new EBG structure can achieve a bandwidth reach 4.35GHz.This stop-band is 47.5% wider than the conventional UC-EBG structure, and 17.5% wider than the reference EBG structure in literature. The excellent SSN suppression is achieved between 0.18-4.53GHz in the depth of -40dB. Keywords: PCB, Electromagnetic Bandgap (EBG), Simultaneous Switching Noise(SSN), power /ground plane.

1 Introduction Today, the reliability of digital circuit system is attend to more and more challenged with that, the ceaseless increase of the frequency of system clock, the enlarge size of the digital ICs, the sharp increase of the organ density on the Printed Circuit Board (PCB). The power layer and ground layer in multilayer PCB are actually equal to a pair of parallel-plate resonator in high frequency station. Simultaneous Switching Noise(SSN, or delta I noise) which can lead to significant Signal Integrity(SI) problems and Electromagnetic interference(EMI) issues [1-3]will came into being by the high impedance in resonance condition. But the favorable Signal Integrity and Electromagnetic compatibility (EMC) are important contents in reliable design of high speed digital circuit systems. In order to improve the reliability of digital circuit system, the SSN in power/ground plane must be suppressed effectively. A typical method for SSN suppression is to use decoupling capacitor between the power plane and ground plane[4]. However, because of the high frequency parasitic parameters in itself, the decoupling capacitor will lost its ability to suppress SSN in the frequency higher than 600MHz[5]. In order to restrain the SSN between power plane and ground plane in high frequency region, a novel concept of mitigating SSN using *

Corresponding author.

S. Lin and X. Huang (Eds.): CSEE 2011, Part I, CCIS 214, pp. 628–634, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Electromagnetic Bandgap(EBG) structures was introduced[6]. However, the stop-band of the EBG structure is too narrow to suffice the real need of the SSN suppression. There is much research focused on broaden the stop–band of the EBG structure, a multi-via mushroom EBG was proposed in literature[7], but it is so complicated to manufacture and cost-effective. Two improved uniplanar compact EBG structures were studied in literature[8],[9].The simulation results show that the EBG structure proposed in literature[8] can achieve a stop-band wider than conventional UC-EBG structure, and the SSN in stop-band is effectively suppressed in the depth of -40dB, but the SSN in the low frequency region is still ineffectively suppressed. Therefore, how to broaden the width of stop-band in order to realize the SSN suppression in wide band from low to high frequency becomes an important issue for engineers in recent years. In this paper, we focus on the wideband SSN suppression in high speed digital PCB. Based on the mechanism and equivalent circuit of the conventional UC-EBG structure, a novel UC-EBG structure which formed by adding spiral-shaped inductance is proposed for broaden the width of stop-band. To verify its performance, 3-D electromagnetic filed simulation is performed by using the commercial software of Ansoft SIwave 3.0.

2 UC-EBG Structure and Its Mechanism for SSN Suppression There are two kinds of mechanism that stop-band is formed in EBG structure: one is Bragg scattering which includes dielectric drilling and ground plane etched; And the other is local resonance which includes mushroom EBG structure and UC-EBG structure. Fig.1 is the model of the conventional UC-EBG structure. Compared with mushroom EBG, the UC-EBG structure is only consist of metal patches and metal strips[10].

(a)

(b)

Fig. 1. Conventional UC-EBG structure. (a) unit cell (b) the equivalent LC circuit in adjacent unit cells

In UC-EBG structures, the resonance of the periodic unit cells plays an important role in the stop-band forming. The unit structure can be analyzed by equivalent LC circuit, and its character of electromagnetic also can be described by equivalent inductance and equivalent capacitance.

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Fig.1 (b) shows the equivalent LC circuit in adjacent unit cells of UC-EBG structure, the equivalent capacitance which is represented by C parameter comes from gaps between the adjacent unit cells, and the equivalent inductance which is represented by L parameter comes from the current on narrow metal strips between the adjacent unit cells, the center frequency of stop-band and the 3dB bandwidth can be approximately expressed by the following formula [11]:

1 LC

ω0 = BW =

Δω

ω0

=

1

η

( 1)

L C

(2)

Parameter ω0 represents the center frequency, parameter Δω represents the width of

the stop-band, η = 120π is the wave impedance in freedom space. Actually, the UC-EBG structure is equal to a series of parallel connection LC pairs, it shows a character of high impedance around the resonance frequency of the power/ground planes. The UC-EBG structure supplies a high-impedance gateway which is equivalent to a band-stop filter for the SSN when it spreads along the power/ground plane, in this way, the SSN is restricted in the local cell and can not transmit and excitated along the power/ground pairs. As a result, the resonance between power/ground planes is minished, and the impedance around the resonance frequency is also reduced. This is the mechanism of the UC-EBG structure for SSN suppression.

Fig. 2. The 3×3 conventional UC-EBG structures

In order to describe the mechanism for SSN suppression, an example of the conventional UC-EBG structures is shown in Fig.2. The test PCB has four metal layers with the size of 90×90mm, the top layer and the bottom layer are two signal layers, the second layer is power layer, and the third layer is ground layer. 3×3 unit cells are etched in the power plane. The parameters for simulation are setted as follows: a=30mm,w=28.5mm,h=6.75mm,s=g=1.5mm, the thickness of dielectric between power and ground layer is 0.8mm, and the ports are located in (45mm,45mm) and (75mm,75mm). Fig.3 shows the simulated results of S12 parameters of the conventional UC-EBG structures in Fig.2. Based on the -40dB suppression level, the simulation results show that

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631

the conventional UC-EBG structure has an obvious stop-band ranging from 0.83GHz to 3.78GHz, and the bandwidth is 2.95GHz. Compared with the continuous plane, the conventional UC-EBG structure can suppress the SSN in the depth of -40dB in its stop-band, thus, UC-EBG structure can effectively suppress the SSN between power and ground planes. However, we can find that the SSN in the frequency lower than 0.83GHz are still ineffectively suppressed, and the relative width of the stop-band is still narrow. So, a new EBG structures are proposed to resolve these problems in section 3.

Fig. 3. S12 parameters of conventional UC-EBG and continuous plane

3 New EBG Structure Design From the formula (1) and (2), we can educe some conclusions for new UC-EBG structure design in the following: The bandwidth of the EBG structures is in direct ratio with the equivalent capacitance, as well as in inverse ratio with the equivalent inductance; So, the augmentation of the equivalent inductance can broaden the bandwidth while it also can reduce the center frequency. The typical method to increase the equivalent inductance is adding uniplanar compact spiral-shaped inductance[12]. In this paper, we use this method to enlarge the relative bandwidth of the stop-band.

(a)

(b)

Fig. 4. Improved UC-EBG unit cells. (a) new unit cell (b) unit cell in literature[8]

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Fig.4 (a) shows the new proposed EBG structure in this paper. This UC-EBG structure is consisted of metal patches and spiral-shaped metal strips, the spiral-shaped strips is in the outside of the patches. The metal strips increase the length of connection between the adjacent unit cells, as a result, the equivalent inductance of EBG structure unit cells is enlarged. This measure improves the characteristic of the stopband and enlarge the bandwidth. In order to show the excellent performance for SSN suppression of the new UC-EBG structure, we take an improved UC-EBG structure which proposed in literature [8] for comparison. The reference structure is shown in Fig.4 (b).

Fig. 5. The 3×3 New UC-EBG structures

4 Simulation Results To achieve good SSN suppression, we propose a new UC-EBG structure by adding spiral-shaped inductance. We use the commercial available software of Ansoft SIwave3.0 to verify the excellent performance of the new UC-EBG structure. The test PCB also has four metal layers with the size of 90×90mm, and 3×3 unit cells are etched in the power plane. The parameters for simulation are setted as follows: a=30mm,

Fig. 6. S12 parameters of new UC-EBG and conventional UC-EBG

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w=28.5mm, h=6.85mm, s=0.5mm, d=0.6mm, the thickness of dielectric between power and ground layer is 0.8mm, and the two ports are located in (45mm,45mm) and (75mm,75mm). Fig.6 shows the simulated results of S12 parameters of the new EBG structure in Fig.5. They show that the new UC-EBG structure has better performance than the conventional UC-EBG structure as the same size. Based on the -40dB suppression level, the stop-band of new EBG structure is ranging from 0.18GHz to 4.53GHz, it can achieve a bandwith higher than 4.35GHz,this bandwidth is 47.5% wider than the conventional UC-EBG structure. In the meanwhile, the lower corner frequency of the stop-band is 650MHz lower than the conventional UC-EBG structure, It means that the SSN in low frequency region is effectively suppressed by the new EBG structure. And the SSN suppression is very stable because it appears below -60dB in the stop-band. Because of the spiral-shaped metal slice slightly weakened the equivalent capacitance between the unit cells, the center frequency of the new EBG structure is moved about 50MHz to the high frequencay region. Despite of this, compared with the conventional UC-EBG structure, the new EBG structure proposed in this paper effectively suppress the SSN from lower to higher frequency.

Fig. 7. S12 parameters of new EBG and reference EBG in literature[8]

Fig.7 shows the simulated results of S12 parameters compared between the new EBG structure and reference EBG structure with the same size. Based on the -40dB suppression level, the reference EBG structure has a stop-band ranging from 0.42GHz to 4.12GHz, the bandwidth is 3.70GHz. Through simulations, we can find that the new UC-EBG structure proposed by adding spiral-shaped metal strips has a bandwidth which is 17.5% wider than the reference, the lower corner frequency of the stop-band is 240MHz lower than the reference structure. Therefore, compared with the reference EBG structure in literature [8], the new UC-EBG structure provides not only the lower frequency SSN suppression characteristic but also the wider stop-band SSN suppression.

5 Conclusion In this paper, based on the conventional UC-EBG structure, we proposed a new UC-EBG structure which formed by adding spiral-shaped metal strips on the metal

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patches to effectively suppress the SSN in Power/Ground planes. The -40dB stop-band of the proposed EBG structure is ranging from 0.18GHz to 4.53GHz, this stop-band is 47.5% wider than the conventional UC-EBG structure, and 17.5% wider than the reference EBG structure in literature [8]. The SSN in low frequency region is also effectively suppressed by the new EBG structure. The excellent performance of the SSN suppression is simulated by using commercially available software. Good performance is achieved. The proposed EBG structure has better performance than the reference structure in literature for SSN suppression.

References 1. Abhari, R., Eleftheriades, G.V.: Metallo-dielectric electromagnetic band-gap structures for suppression and isolation of the parallel-plate noise in high-speed circuit. IEEE Trans. Microw. Theory Tech. 51(6), 1629–1639 (2003) 2. Kamgaing, T., Ramahi, O.M.: Design and modeling of high–impedance electromagnetic surface for switching noise suppression in power planes. IEEE Trans. Electromagnetic Compatibility 47(3), 479–489 (2005) 3. Shahparnia, S., Ramahi, O.M.: Electromagnetic interference (EMI) reduction from printed circuit boards (PCB) using Electromagnetic band-gap structures. IEEE Trans. Electromagnetic Compatibility 46(4), 580–586 (2006) 4. Power Integrity and Ground Bounce Simulation of High Speed PCBs. Empowering Profitability worldwide workshop. Ansoft (2002) 5. Ricchiuti, V.: Power-Supply Decoupling on Fully Populated High-Speed Digital PCBs. IEEE Trans. Electromagnetic Compatibility 43, 671–676 (2001) 6. Chen, G., Melde, K., Prince, J.: The applications of EBG structures in power/ground plane pair SSN suppression. In: IEEE 13th Topical Meeting on Electrical Performance of Electronic Packaging and Systems, pp. 207–210. IEEE Press, Portland (2004) 7. Zhang, M.s., Li, Y.-S., Jia, C., et al.: A Power Plane With Wideband SSN Suppression Using a Multi-Via Electromagnetic Bandgap Structure. IEEE Microwave and Wireless Components Letters 17(4), 307–309 (2007) 8. Du, J.-Y., Kim, J.-M., et al.: Analysis of Separately Arranged Patterns for Suppression of Simultaneous Switching Noise. In: IEEE, Proceeding of Asia-Pacific Microwave Conference, pp. 55–58. IEEE Press, Yokohama (2006) 9. Kim, B., Kim, D.-W.: Improvement of Simultaneous Switching Noise Suppression of Power Plane using Localized Spiral-Shaped EBG Structure and λ/4 Open Stubs. In: IEEE, Proceeding of Asia-Pacific Microwave Conference, pp. 1–4. IEEE Press, Bangkok (2007) 10. Yang, F., Ma, K., Qian, Y., et al.: A uniplanar compact photonic bandgap (UC-EBG) structure and its applications for microwave circuits. IEEE Trans. Microwave Theory and Technol. 47, 1509–1514 (1999) 11. Sievenpiper, D.: High-impedance electromagnetic surface. Ph.D.dissertation. Dept. Electrical Engineering, Univ. California, Los Angeles, CA (1999) 12. Li, Y., Fan, M.Y., Feng, Z.H.: A spiral electromagnetic bandgap (EBG) structure and its application in microstrip antenna arrays. In: IEEE, Proceeding of Asia-Pacific Microwave Conference, p. 4. IEEE Press, Suzhou (2005)

Author Index

Abbas, Ammar I-290 An, Jianwei II-81 Ao, Hongyan I-131 Azmi, Atiya I-290 Bai, Lifeng IV-454 Bai, QingHua IV-288 Bai, Wanbei III-202 Bai, Yan II-102 Bai, Yu Shan I-408 Bao, Yan III-107 Bao, Yuan-lu I-302 Baqi, Abdul I-161 Bi, TingYan V-144, V-149 Bi, Weimin IV-486 Bingquan, Liu III-398 Bo, Cheng V-533 Cai, JinBao II-77, V-128 Cai, Ying I-542 Cao, Gang IV-493 Cao, Lijuan I-131 Cha, Si-Ho I-353 Chai, Baofen III-133 Chang, Bau-Jung V-112 Chang, Liwu III-36 Chang, Yung-Fu V-381 Changhua, Li III-63 Che, HongLei I-167 Chen, Bin III-112 Chen, BingWen I-55 Chen, Chih-Sheng III-333, IV-367 Chen, Chin-Pin V-309, V-381 Chen, Daohe I-482 Chen, Dezhao I-78 Chen, Fuh-Gwo V-139, V-190, V-245, V-356 Chen, Gang III-299 Chen, GuanNan I-562 Chen, Hsuan-Yu V-309 Chen, I-Ching IV-525 Chen, Jia V-175, V-543, V-548 Chen, Jia-Ling IV-376 Chen, Jianbao IV-324

Chen, Jianchao I-430 Chen, Jie IV-481 Chen, Jifei II-458 Chen, Jinpeng II-579 Chen, Jinxing I-341 Chen, Jr-Shian V-190, V-245 Chen, JunHua V-512 Chen, Kuikui III-202 Chen, Li III-303 Chen, Min V-314, V-329 Chen, Pengyun III-89 Chen, Qing V-407 Chen, Qingjiang I-29, I-507, I-519, IV-59 Chen, Rong III-299 Chen, Rongrong V-590 Chen, Ruey-Maw V-245, V-356 Chen, ShaoChang I-628 Chen, Sheng-wei III-322 Chen, Shouhui III-170, V-581 Chen, Shun-Chieh V-362 Chen, TongJi IV-106 Chen, Weiqiang V-16, V-160 Chen, Wen-Jong V-381 Chen, Xia IV-197 Chen, Xiaohong IV-444 Chen, Xiaohui II-572, II-579 Chen, Xilun II-197 Chen, Xin IV-11, IV-313, V-32 Chen, XingWen II-291 Chen, Yaqi II-611 Chen, Yi-Chun V-139 Chen, Yin-Chih V-413, V-458 Chen, Yonghui I-309 Chen, YongPing IV-160 Chen, YouRong III-545, IV-221 Chen, Yun V-496 Chen, Yuzhen II-496 Chen, Zhuo I-231 Cheng, Ching-Hsue V-190 Cheng, Fenhua III-522 Cheng, Genwei II-176 Cheng, GuanWen I-187, I-194 Cheng, JuHua IV-221

636

Author Index

Cheng, Zhongqing II-526, II-532 Chi, Yali III-436 Cho, Ying-Chieh V-335, V-348 Choi, Seung Ho II-34 Chou, Hung-Lieh V-190 Chou, Tzu-Chuan IV-279 Chu, Huiling V-123 Chu, Yuping V-227 Chun, Hung-Kuan IV-367 Chunlin, Xie III-95 Cui, JianSheng V-472 Cui, Jingjing IV-352 Cui, Yu-Xiang IV-549 da Hu, Jun I-201 Dai, Lu IV-481 Dai, Shixun IV-481 Dai, YanHui V-299 Dai, ZhiRong III-378 Deng, Pei-xi III-73 Deng, Rui V-48 Deng, YingZhen V-43 Ding, Wen V-180 Ding, Xiangqian III-57 Ding, Yingqiang V-429, V-489 Dong, Jianwei V-227 Dong, Lu I-118 Dong, Yang IV-428 Dong, Yanyan IV-454 Dong, Zaopeng III-89 Dong, Zhen III-156 Dongping, Liu V-533, V-585 Du, Qiulei IV-423 Du, Ruizhong II-466 Du, Xuan III-78 Du, Yang V-512 Du, ZhiTao V-596, V-604 Du, Zhong II-380 Duan, Li IV-1 Duan, Zhongyan II-617 Enfeng, Liu

I-316

Fan, Jihui II-176 Fan, Li Ping IV-319 Fan, LiPing IV-509 Fan, Xiaobing V-105 Fang, Fang IV-66 Fang, HaiNing II-440 Fang, Liang IV-470

Fang, WenJie IV-99 Fangyang, Zhang II-267 Feng, Junhong V-154 Feng, Ming III-373 Feng, Ruan II-267 Feng, Wenquan I-534 Fenghua, Wen III-398 Fu, Chuanyun II-211, II-284 Fu, Hong V-604 Fu, HongYuan I-187, I-194 Fu, LiMei I-464 Fu, Tsu-Hsun IV-595 Fu, Yao V-32 Fu, Zheng IV-589 Fuqiang, Yue II-586 Gan, Shuchuan I-309 Gao, Caixia IV-148, IV-175 Gao, ChunLing I-581 Gao, Dong Juan IV-165 Gao, Fuxiang I-99 Gao, Guangping III-124 Gao, Hongwei I-396, I-402, I-513 Gao, Jianming III-160 Gao, Long IV-47 Gao, Rencai II-477 Gao, Zhen IV-298 Gao, Zhongshe III-310 Ge, LingXiao III-545 Gong, Ke V-396 Gong, Li III-202 Gong, Ping II-205 Gong, Xiaoxin III-226 Gong, Yuanpeng III-57 Gong, Zheng III-11 Gou, ShuangXiao III-441 Gu, Chunmiao V-118 Gu, Huijuan IV-404 Gu, JunJie II-354 Gu, Lefeng III-402 Gu, Wenjin I-616 Gua, MeiHua V-372 Guan, Chen-zhi III-299 Guan, Yong III-214 Gui, Jiangsheng V-185 Guo, Fabin V-81 Guo, Guofa IV-554, IV-560 Guo, Honglin I-22 Guo, Jiannjong III-609 Guo, JianQiang I-375, IV-17, V-565

Author Index Guo, Lili III-138 Guo, LongFei IV-197 Guo, Ping IV-357 Guo, Qinan V-429 Guo, Tongying III-328 Guo, Xiaowei II-15 Guo, Zhenghong III-568 Guojian, Zu II-386, II-434 Guoxing, Peng II-424 Guozhen, Shen II-405 Haisheng, Liu IV-602 Han, Fengyan III-328 Han, Gangtao V-429 Han, Guiying III-293 Han, Guohua III-339 Han, Houde II-392 Han, Jianhai IV-122 Han, Juntao III-214 Han, Liang I-219 Han, Lingling I-176 Han, Qiyun II-279 Han, Ran I-49 Han, Yaozhen I-476 Han, Yumei V-442, V-452 Han, ZhiGang I-123 Hao, Chen IV-170, V-392 Hao, Hanzhou III-107 Hao, Hui III-568 Hao, Li V-273 Hao, Shangfu III-568 Haob, JinYan V-372 He, Bo IV-399 He, Jianxin IV-258 He, Jing II-572 He, Jinxin V-257 He, Lianhua V-287 He, Xingran II-222 He, Xiong II-40 He, Xuwen II-40 He, Yong II-341 He, Yongxiu III-156 He, Yueqing II-192 Hong, Bigang I-324 Hong, Cao II-446 Hong, Jingxin I-416 Hong, Qingxi III-207 Hong, Xu V-167 Hongtao, Yang V-533, V-585 Hou, Xia II-197

Hsiao, Yu-Lin V-309 Hsieh, Kai-ju IV-362 Hsu, Chien-Min III-457 Hsueh, Sung-Lin III-457 Hu, Chengyu II-131 Hu, Dongfang IV-122 Hu, Feihui I-137 Hu, Jian-Kun V-462 Hu, Jinhai V-554 Hu, Lihua IV-248 Hu, Lin III-587 Hu, Shueh-Cheng IV-525 Hu, Tao III-100 Hu, Wujin V-554 Hu, XiaoHong II-1 Hu, YangCheng II-507 Hu, Yujuan I-507 Hu, YunAn II-592 Hu, Zhongyong III-481 Hua, Qian IV-191 Huanchang, Qin II-398 Huang, Chia-Hung V-458 Huang, Chiung-En V-139 Huang, He IV-465, IV-520 Huang, Hua II-305 Huang, Jiayin I-78 Huang, Jie III-100 Huang, Jinqiao IV-554, IV-560 Huang, Liqun II-205, V-207 Huang, Min IV-418, IV-433 Huang, Ming-Yuan V-386 Huang, Ning III-532 Huang, Shih-Yen V-356 Huang, Wanwu II-611 Huang, Wun-Min IV-367 Huang, Xin I-257 Huang, Yong IV-143 Huang, Yongping II-222 Hui, Peng III-143 Hui, SaLe I-225 Huo, GuoQing V-596 Huo, XiaoJiang III-451 Ishaque, Nadia

I-290

Jaroensutasinee, Krisanadej I-244 Jaroensutasinee, Mullica I-244 Ji, ChangPeng II-348 Ji, DongYu II-560, II-566 Ji, Jun II-392

637

638

Author Index

Ji, Shen I-316 Ji, Xiang II-598 Ji, Yukun I-214 Jia, ChangQing II-253 Jia, GuangShe III-508 Jia, NianNian II-253 Jia, XiaoGe IV-393, V-559 Jia, Yue II-452 Jia, Zhi-Ping II-162 Jian, Gao IV-111 Jiang, Annan V-437 Jiang, Chaoyong V-282 Jiang, DanDan I-381 Jiang, HaiBo II-526 Jiang, Lerong IV-133 Jiang, Libo IV-444 Jiang, Nan V-267 Jiang, Wen V-484 Jiang, Wenwen III-363, III-368 Jiang, Xiaowei IV-330 Jiang, Yan I-62 Jiang, Yan-hu III-299 Jiang, Ya Ruo I-408 Jin, Shengzhen III-214 Jin, Yuqiang I-600, II-11 Jin, Yuran V-227 Jin, Yushan II-222 Jing, Shengqi I-181 Jingjing, Ma II-429 Jingmeng, Sun V-585 Jinguo, Li III-468 Jin-jie, Yao III-143 Jong, Gwo-Jia V-413, V-458 Junrui, Li III-242 Jushun, Li III-474 Kang, Cui III-516 Kang, Zhiqiang V-570 Konigsberg, Zvi Retchkiman Kuai, JiCai III-118 Kuang, Aimin IV-530

I-8

Lee, Ching-Yi V-309 Lee, In Jeong II-68 Lee, Keun-Wang I-353 Lee, Seung Eun II-150, II-169 Lei, Bangjun II-572, II-579 Lei, Bicheng I-437, I-443 Lei, Junwei I-606, I-612, I-616, II-7, II-243, II-248

Lei, Liu IV-428 Li, Caihong III-385 Li, Chaoliang I-93 Li, Chunyan I-430 Li, Dengxin I-501, II-89 Li, Dong II-482 Li, Fo-Lin IV-549 Li, GuangHai I-297 Li, Haiyan V-539 Li, Hongmei IV-243 Li, Ji III-78 Li, Jiejia III-328 Li, Jiming III-277 Li, Jing II-279, III-481, III-592 Li, Jinxiang III-445 Li, JunSheng I-525 Li, Jushun III-496 Li, Kanzhu I-501 Li, Kunming IV-324 Li, Li III-78 Li, Lulu I-131 Li, Luyi III-347 Li, Maihe II-380 Li, Min II-291 Li, Minghui IV-268, V-94 Li, Nan III-31, IV-433 Li, Ning II-197 Li, Ping IV-288, IV-335, IV-346 Li, Qiong V-262 Li, Rui I-595 Li, SanPing III-562, IV-481 Li, Shi-de V-53 Li, Shizhuan V-506 Li, Taizhou I-231 Li, Weidong V-167 Li, Wenze I-482 Li, WuZhuang I-297 Li, Xiaojuan III-214 Li, XiaoLong I-330, I-336 Li, Xiaolu III-402 Li, XiaoMin II-23 Li, Xin V-448 Li, Xiqin II-113 Li, XiZuo III-293, IV-388 Li, Xuehua V-528 Li, Xueqin III-249 Li, Yang I-149, I-302 Li, Yanru II-526, II-532 Li, Yan-Xiao II-335 Li, Yaqin III-445

Author Index Li, Ye III-89 Li, Yibin III-385 Li, Ying III-402 Li, Yingjiang I-525 Li, YinYin I-449 Li, Yong IV-143, IV-465, IV-520 Li, YongGan I-36, IV-52 Li, Yongqing II-598 Li, Zhanli I-270 Li, Zhan-ping IV-22 Li, Zheng I-263 Li, Zhongxu IV-577 Liang, Guoqiang I-606, I-612, II-7 Liang, Tsang-Lang V-335, V-348 Liang, Xiaoteng I-72 Liao, Chin-Wen V-320 Liao, Qingwei I-416 Liao, Yingjie V-543, V-548 Lijun, Cai III-468 Lili, Dong III-63 Lin, Hui II-40 Lin, Jun I-257 Lin, Sho-yen V-320 Lin, Tingting I-257 Lin, Wei-Jhih IV-367 Lin, Yaw-Ling IV-525 Lin, Ying II-77, V-128 Lin, Yong Zheng III-21 Lin, Yufei II-15 Liu, Ailian I-501 Liu, Anping III-315, V-287 Liu, BanTeng III-545, IV-221 Liu, Bin IV-554, IV-560 Liu, Bing II-113 Liu, Chang III-254 Liu, Dan IV-186 Liu, Dong III-254 Liu, Fei II-341 Liu, Haimei V-496 Liu, Haisheng V-402 Liu, Hongzhi IV-36, IV-181 Liu, Hua I-430 Liu, Huanbin IV-262 Liu, Jian V-105 Liu, June III-430 Liu, Jun-Lan II-335 Liu, Junqiu I-257 Liu, Lei II-598 Liu, LiHong V-65, V-596 Liu, LingXia II-230, II-236

Liu, Lixia I-365, I-370 Liu, Liyuan II-40 Liu, Meihua III-138 Liu, Pengtao II-131 Liu, Qiao I-99 Liu, RenYang I-621 Liu, Ruikai II-222 Liu, Ruixiang V-133 Liu, Tao I-574 Liu, TianHui IV-6 Liu, Tsung-Min V-335, V-348 Liu, Weijie IV-186 Liu, Wei-ya I-457 Liu, Wen I-201 Liu, XianHua V-22 Liu, Xiaojuan II-47, II-53 Liu, Xiaosheng I-137 Liu, XiaoYan II-125 Liu, Xingliang II-380 Liu, Xuewu I-93 Liu, Yanfei V-185 Liu, Yang V-88 Liu, Yongfang III-392 Liu, Yongqi V-133 Liu, Yunjing II-96 Liu, Yuqiang I-118 Liu, Zhenwei IV-577 Liu, Zhen-ya III-299 Liu, Zhihai IV-47 Liu, Zhihui I-83 Liu, Zhong IV-99 Liu, ZhongJing III-451 Lixia, Song IV-602 Liyuan, Yang I-316 Llinares, Manuel Bernal IV-428 Loglo, S. IV-340 Lou, Xi’an V-175 Lu, Bo I-530, II-496 Lu, GuoDan I-187, I-194 Lu, Ning-hai III-73 Lu, Quan I-78 Lu, YiRen V-22 Lu, Yu-Chung I-568 Luo, Jiaguo I-496, III-46 Luo, Min III-283 Luo, Ping I-42 Luo, Qian V-202 Luo, Ruwei IV-133 Luo, Tao III-156 Luo, Tieqing III-527

639

640

Author Index

Luo, Xiaoting IV-298 Luo, Xin II-107 Lv, HeXin IV-536 Lv, Jiehua I-390 Lv, TingJie IV-197

Peng, Lingyi I-93 Peng, Ting II-211 Peng, Yanfei V-448 Peng, Zhaoyang V-293 Pheera, Wittaya I-244

Ma, Bitao II-552 Ma, Bole II-137 Ma, Dongjuan I-1 Ma, F.Y. III-468 Ma, Guang III-202 Ma, Hongji III-226 Ma, Jibin I-143 Ma, Liang IV-543, V-314, V-329 Ma, MingLi III-532 Ma, Qiang I-600, II-11 Ma, TaoLin I-149, I-155 Ma, Wenxin III-485 Ma, Xiaoyan III-481 Ma, Xi-qiang I-457 Ma, Yi V-221 Mao, PanPan II-253 Mei, BaiShan IV-93 Meng, Haoyu V-303 Meng, Jian V-133 Meng, Xiankun IV-268, V-94 Meng, Yi III-303 Ming, Xiao IV-111 Mu, Dinghong V-105, V-554

Qi, Bingchen IV-308 Qi, ShuHua V-267 Qi, Wei I-501 Qi, Weiwei II-211, II-284 Qi, XiaoXuan IV-6 Qi, Yun V-22 Qian, Manqiu IV-117 Qiao, Jinxia V-452 Qiao, Shan Ping III-21 Qiao, XinXin III-232 Qiao, Ying-xu II-473 Qin, Ping I-194 Qin, QianQing I-55 Qin, Yanhong IV-566, V-11 Qing, Xin I-501 Qiong, Li I-111

Nai, Changxin I-118 Niu, JiaYing II-440 Niu, Jingchun III-260 Okawa, Yoshikuni IV-308 Ou, Jun V-314, V-329, V-506 Ou, Xiaoxia III-598, III-604 Pan, Hongli II-380 Pan, Kailing III-502 Pan, Weigang I-470, I-476 Pan, Xinyu IV-404 Pan, Yang IV-143 Pang, Yingbo V-484 Park, Hyung Chul II-157 Pei, Yulong II-211, II-284 Pei, Yun V-314, V-329 Peng, Chen-Tzu III-557 Peng, Guobin II-186, II-192 Peng, Kang IV-572

Rao, Congjun III-430 Ren, Chenggao I-423 Ren, GuangHui IV-504 Ren, Honghong III-568 Ren, Liying V-376 Ren, Wen-shan II-452 Ren, Xiaozhong IV-122 Ren, YanLing II-354 Ru, Wang III-63 Rui, Yannian III-226 Sang, Junyong IV-170, V-392 Sangarun, Peerasak I-244 Sarula IV-340 Shan, Rong V-518 Shanjie, Wu IV-602 Shao, Yongni II-341 Shao-lin, Liu III-143 Shen, Bo V-423 Shen, HongYan V-472 Shen, Huailiang II-490 Shen, Limin III-260 Shen, Wei II-513 Shen, Xiangxing IV-154, IV-486 Shen, Xiaolong I-423 Shen, XiuGuo IV-210 Shen, Zhipeng IV-459

Author Index Shi, Jianhong I-606, I-612, I-616, II-7 Shi, Ji cui I-201 Shi, Jinliang V-376 Shi, Ming-wang III-73 Shi, Penghui II-89 Shi, Run-hua I-489 Shi, ShengBo IV-536 Shi, Yaqing IV-303 Shu, Yang IV-602, V-402 Song, Ani V-81 Song, HaiYu IV-388 Song, Huazhu V-477 Song, Jianhui I-396, I-402 Song, Jianwei V-100 Song, Lixia V-402 Song, XiaoWei I-187 Song, Xi-jia I-457 Song, Yunxia IV-11, IV-313, IV-418, IV-433 Soomro, Safeeullah I-161, I-290 Soomro, Sajjad Ahmed I-161 Su, Ruijing I-501, II-89 Su, Te-Jen V-386 Su, YangNa III-68 Su, Yen-Ju V-362 Sui, Li-ping V-467 Suk, Yong Ho II-34 Sun, Chunling V-576 Sun, Dong III-156 Sun, Hongqi IV-439 Sun, Jianhong I-525 Sun, Jie III-516 Sun, Jinguang V-448 Sun, Junding I-359 Sun, Li IV-470 Sun, Peixin I-347 Sun, Qiudong III-485 Sun, Qiuye IV-577 Sun, Shusen V-185 Sun, Shuying V-418 Sun, Wei III-160 Sun, Weiming II-243, II-248 Sun, Xiao IV-274 Sun, XiaoLan I-155 Sun, XiuYing III-592 Sun, Yakun I-118 Sun, Yansong I-149 Sun, Ying II-513 Sun, Yu II-192 Sun, Yuei-Jyun V-386

Sun, Yuqiang I-239, I-251, III-165 Sun, Yuzhou III-36 Sun, Zebin I-534 Sun, Zhongmin III-160 Suo, Zhilin V-442 Tai, David Wen-Shung V-309 Tai, David W.S. IV-376, V-362 Takatera, Masayuki II-28 Tan, Gangping II-458 Tan, Gongquan I-309 Tan, Ran III-378 Tan, Wenan IV-243 Tan, Wentao V-213 Tan, Wenxue IV-215 Tan, Xianghua IV-514 Tan, Xilong V-213 Tan, YaKun IV-233 Tan, Zhen-hua V-221, V-233 Tan, ZhuWen V-43, V-48 Tang, Xian III-288, IV-293 Tang, Zhihao I-22 Tao, Yi II-545 Tao, Zhiyong I-341 Teng, Yusi IV-88 Tian, DaLun I-123 Tian, Dan III-283 Tian, Daqing IV-474 Tian, Hongjuan II-367 Tian, HongXiang I-574 Tian, Hua V-489 Tian, Jian V-53 Tian, JianGuo IV-393, V-559 Tian, Qiming V-303 Tian, Xianzhi III-26 Tian, Yinlei IV-52, IV-59 Tian, Yu II-176, II-380 Tian, Yuan V-43, V-48 Tien, Li-Chu V-320 Tong, XiaoJun V-88 Tsai, Chang-Shu III-333, IV-367 Tsai, Chung-Hung III-333 Tsai, Hsing-Fen IV-371 Tsai, Tzu-Chieh III-557 Tu, Fei IV-399 Wan, Benting IV-583 Wan, Guo-feng III-322 Wan, Lei I-276 Wang, An I-263

641

642 Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang,

Author Index Baojin III-373 Bing IV-42 Botao IV-11, IV-418 Changshun I-470 ChenChen IV-233 Cheng III-424, IV-262 Chenglong IV-47 Cuiping V-342 CunRui V-267 DaoYang III-221 Dongai III-138 Enqiang II-89 FeiYin I-381 Fengwen II-96 Fengzhu II-102 Fu-Tung I-568 Fuzhong IV-175 Gai I-143 Guilan III-84 GuoQiang I-581 Haichen III-328 HaiYan I-381 HanQing III-575 Hao I-187, I-194 Huiling V-213 Huiping III-598 Jian IV-248, IV-404 Jing I-72 Junxiang V-437 Kaijun I-214 Lan III-418 Lei IV-77 LiangBo III-532 Lijie I-176 Linan V-251, V-257 LingFen IV-274 Long IV-22 Meijuan IV-303 Minggang V-548 Mingyou I-365, I-370 Mingzhe V-81 Qibing II-361 Ray IV-376 Renshu II-102 Ruijin II-113 Runsheng V-570 Sangen II-380 Shengchen I-239 Shiheng I-42 Shilong I-276

Wang, Shi-Xu V-240 Wang, Shouhong IV-313 Wang, Shufang III-1 Wang, Shuying IV-449 Wang, Sida V-251 Wang, Te-Shun IV-595 Wang, Tong IV-243, IV-248 Wang, Wei IV-154 Wang, WeiLi V-59 Wang, Weiwei III-373 Wang, WenWei I-55 Wang, Xianliang I-62 Wang, Xiaodong III-57 Wang, XiaoFei II-216 Wang, Xiaofei I-542 Wang, Xiaohong I-482 Wang, XiaoHua V-180 Wang, Xiaoling III-496 Wang, Xiaotian II-500 Wang, Xinyu II-243, II-248 Wang, Xiping IV-215 Wang, XueFeng III-303 Wang, Xueyan I-143 Wang, Ying III-527, V-570 Wang, YingXia IV-17, V-565 Wang, Yong III-6 Wang, YuMei IV-148, IV-203 Wang, YunWu III-516 Wang, Yuqin III-339 Wang, Yuting IV-459 Wang, ZhangQuan III-545 Wang, Zhongsheng III-112 Wei, JianMing II-592 Wei, Li III-468 Wei, Min II-298 Wei, Wanying IV-474 Wei, WenYuan I-187 Wei, Xianmin I-551, I-556 Wei, YuHang V-48 Wei, Zhang I-316, IV-111 Wei, ZhenGang V-180 Weiwei, Wu III-468 Wen, Xinling II-119 Weng, Chunying V-76 Weng, Pu-Dong IV-279 Wu, Chunmei III-15 Wu, Guo-qing V-467 Wu, Hui V-100 Wu, Jianan II-513 Wu, Jinhua I-616

Author Index Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu, Wu,

Lingyi II-259 MeiYu II-348 Peng IV-572, V-202 Qingxiu V-314, V-329, V-506 QinMing II-482 Shianghau III-609 Shufang IV-138 Shui-gen III-299 Shuo I-347 Tao V-240 Tsung-Cheng IV-279 Tzong-Dar I-568 Wei IV-227 WenQuan I-621 XianLiang IV-412 Xiaoli V-452 Xiaosheng I-359 Xinlin III-413 YanYun IV-210 Yong III-11, III-436 Youbo II-545 Youneng II-186 Yu-jun II-373 Zheng-peng I-49 ZhenGuo V-43 ZhiLu IV-504

Xi, Jinju IV-215 Xi, Wei III-1 Xia, Fangyi I-105 Xia, Lu IV-82 Xiang, LiPing III-575 Xiang, Zhang III-63 Xianyan, Liang I-207 Xiao, Beilei I-365, I-370 Xiao, Guang V-123 Xiao, Hairong I-476 Xiao, Jun I-501 Xiao, Li III-315 Xiao, Zhihong V-523 Xiaoting, Luo V-501 Xie, ChunLi IV-274, IV-388 Xie, Jin II-125 Xie, Kefan V-496 Xie, Min IV-572, V-202 Xie, Wu III-124 Xie, Zhibin III-352, III-357, III-363, III-368 Xin, Jiang IV-127 Xin, Lu II-40

Xing, Chong II-513 Xing, YueHong IV-93 Xiong, Jieqiong IV-181 Xiong, Sujuan II-611 Xiuping, Chen I-207 Xu, Dan III-237, IV-238 Xu, DaWei II-1 Xu, Hang II-373 Xu, HongSheng III-418, III-490 Xu, Huidong IV-382 Xu, Jian V-233 Xu, Jie IV-93 Xu, Junfeng III-36 Xu, LiXiang II-125 Xu, Maozeng V-396 Xu, Meng IV-238 Xu, Qin I-525 Xu, Shan I-187 Xu, Wei Hong I-408 Xu, Xiang I-15 Xu, XiaoSu I-449 Xu, Xinhai II-15 Xu, Yun III-424 Xu, Yuru I-276 Xu, Zhao-di III-254 Xu, Zhe II-259 Xu, Zhenbo V-590 Xu, ZiHan I-187, I-194 Xue, Anke II-259 Xue, Yanxin III-378 Xue, Yongyi IV-1 Xue, Yunfeng III-485 Yali, He II-424 Yan, Hua I-562 Yan, JingJing IV-197 Yan, Mao V-277 Yan, QianTai I-297 Yan, Renyuan V-76 Yan, Wang III-242 Yan, Wenying III-485 Yan, Yujie II-552 Yan, ZheQiong V-543 Yang, Bin V-462 Yang, Chung-Ping IV-371 Yang, Guang I-270, V-207 Yang, Guang-ming V-221, V-233 Yang, Guiyong I-470 Yang, Heng II-310 Yang, Hong-guo II-473

643

644

Author Index

Yang, Hua I-628 Yang, Huan-wen IV-549 Yang, Jianguo I-83 Yang, JingPo V-472 Yang, JinXiang I-330, I-336 Yang, Li V-477 Yang, LiFeng IV-499 Yang, Min IV-11, IV-418 Yang, Peng II-272 Yang, Rui III-73 Yang, Shouyi V-489 Yang, Xianwen I-263 Yang, Xiao V-233 Yang, XiaoFeng I-430 Yang, Xihuai V-167 Yang, Xu-hong II-28, II-373 Yang, YaNing II-291 Yang, Ying V-11 Yang, Yuan IV-486 Yang, Yunchuan II-176 Yang, Zhi II-354 Yang, Zhifeng IV-154, IV-486 Yang, ZhongShan V-273 Yao, Benxian III-221 Yao, DuoXi I-330 Yao, Jie V-196 Yao, Qiong IV-165 Yao, ShanHua IV-412 Yaozhong, Wang III-398 Ye, Xin IV-36 Yi, Jiang IV-127 Yi, Zheng IV-71 Yin, Di III-508 Yin, Guofu IV-474 Yin, Yang IV-66 Yin, ZhenDong IV-504 Yong, Wu IV-66 Yu, Dehai V-437 Yu, Hongqin IV-258 Yu, Jie I-496 Yu, Meng III-57 Yu, Yan I-408 Yu, Yang I-341, I-347, I-396, I-402 Yu, Yen-Chih V-413 Yuan, Deling V-123 Yuan, Jiazheng IV-382 Yuan, Pin V-175 Yuan, Yi IV-143 Yuan, Zhanliang III-237 Yufeng, Wu II-411

Yun, Chao I-167 Yunming, Zhou III-180 Zang, JiYuan I-167 Zang, Shengtao I-72 Zeng, Qingliang IV-47 Zeng, Xiaohui I-309 Zhai, Changhong III-197 Zhan, Hongdan I-99 Zhang, Changyou IV-27 Zhang, Chengbao II-58, II-63 Zhang, ChunHui I-574 Zhang, Chunhui II-40 Zhang, Cuixia IV-382 Zhang, Dejia V-303 Zhang, DengYin I-588 Zhang, Deyu V-1 Zhang, DongMin IV-210 Zhang, FaJun IV-99 Zhang, Fan IV-233 Zhang, Feng-Qin II-335 Zhang, Gui I-123 Zhang, Guohua I-341, I-347 Zhang, Guoyan I-284 Zhang, Hongliang II-216 Zhang, Hui I-588 Zhang, Huimin III-124 Zhang, Huiying III-267 Zhang, JianKai V-299 Zhang, Jie II-205, V-154, V-207 Zhang, Jimin III-283 Zhang, Jin III-522, III-527 Zhang, Jing II-520 Zhang, Jingjing II-40 Zhang, JinGuang II-440 Zhang, Jingyu IV-572 Zhang, JinYu III-562 Zhang, Jun IV-191 Zhang, Junhua I-72 Zhang, Laixi I-423 Zhang, Lei III-352, III-357 Zhang, Li III-133 Zhang, Lian-feng V-467 Zhang, Liang II-605 Zhang, LiangPei I-155 Zhang, Lichen II-316, II-323, II-329 Zhang, Lin I-231 Zhang, Linli III-315 Zhang, Linxian IV-335 Zhang, Mei V-70

Author Index Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang,

Min I-251, II-305, III-165 MingXu I-336 Nan IV-308 Qiang I-628 Qianqian I-501 Qimin I-1 Qingshan I-530, II-496, IV-514 Qiuyan II-310 Rui II-598, III-41, V-59, V-65 RuiLing III-490 Shaomei I-72 Shiqing I-437, I-443, I-595 Shui-Ping II-335 Songtao III-52 Suohuai IV-27 Tao I-449 Wanfang III-175 Wangjun II-539 Wei III-170, V-581 Wenbo V-1 Wenfeng II-89 Wenju V-202 Xia V-396 Xiaochen II-81 Xiao-dong I-302 XiaoJing III-273 Xiaojing IV-253 XiaoMei II-605 Xin II-15 XingPing IV-233 XiPing IV-93 XiuLi V-6 Xiushan II-137 Xuetong II-259 Yan V-196 Yang I-562 Yi-Lai II-305 Yingchen I-501 Yonghong IV-382 Yongmei III-339 YuanYuan I-219, I-225 YueHong V-273 Yue-Ling II-335 Yuhua III-160 YuJie I-219, I-225 Zhan IV-148, IV-203 Zhengwei III-385 ZhenLong I-381 ZhenYou V-59, V-65 Zhenzheng III-502

Zhang, Zifei II-137 Zhao, Chen III-150 Zhao, DanDan IV-274, IV-388 Zhao, Guorong I-606, I-612 Zhao, Hong III-129 Zhao, Jian III-532 Zhao, Jiantang I-519 Zhao, JiYin II-291 Zhao, Lang I-507 Zhao, Languang III-328 Zhao, Lei V-462 Zhao, Liang III-373 Zhao, Lin V-22 Zhao, Ling III-21 Zhao, Pengyuan II-466 Zhao, Song II-216, II-310 Zhao, Wen I-131 Zhao, Xiaoming I-437, I-443 Zhao, Xiaoping IV-583 Zhao, Xin III-41 Zhao, Yanna I-239, I-251, III-165 Zhao, YaQin IV-504 Zhao, Yisong IV-1 Zhao, Yun V-38 Zhao, Yunpeng II-532 Zhao, Zheng-gang II-452 Zhe, Zhao III-180 Zhen, Gao V-501 Zheng, Bin V-133 Zheng, Fanglin III-347 Zheng, Mingxia I-214 Zheng, Qun III-260 Zheng, Rongtian I-416 Zheng, WenTing I-628 Zheng, Xi-feng I-457 Zheng, Yanlin III-347 Zheng, Yeming III-1 Zheng, Yongsheng V-118 Zheng, Yuge II-367 Zheng, Yuhuang III-552 Zhi, Lin IV-127 Zhishui, Zhong II-418 Zhong, Guoqing V-26 Zhong, Hong I-489 Zhong, Luo V-477 Zhou, Chang IV-99 Zhou, Defu III-445 Zhou, Fang III-11 Zhou, Guixiang IV-514 Zhou, Hu I-83

645

646

Author Index

Zhou, Hui II-500 Zhou, Jianguo IV-577 Zhou, Jun I-534 Zhou, Kai xi II-192 Zhou, Rui-jin V-467 Zhou, ShuKe I-29 Zhou, Xu II-513 Zhou, Xuexin IV-465 Zhou, Yingbing I-470 Zhou, You II-513 Zhou, Yu-cheng IV-22 Zhou, Yunming III-187, III-193 Zhu, Bo V-477 Zhu, Dengsheng II-341 Zhu, Dongbi III-407 Zhu, FengBo I-621, II-23 Zhu, Haibo III-207 Zhu, Jiajun III-580 Zhu, Mao IV-154

Zhu, Min I-408 Zhu, Mincong I-501, II-89 Zhu, Peifen IV-530 Zhu, QingSheng III-538 Zhu, ShanLin I-621 Zhu, Wen-Xing II-162 Zhu, XiaoFang II-23 Zhu, XuFang II-23 Zhu, Xunzhi III-193 Zhu, YiHao III-232 Zhu, Ying I-390 Zhu, Yu-Ling IV-549 Zhu, Zhiliang V-221 Zhu, Pei-jun V-196 Zhuang, Shuying III-587 Zong, Xueping III-46 Zou, Kun I-15 Zou, XianLin III-538 Zuo, Long II-452