+ All Categories
Home > Documents > Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in...

Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in...

Date post: 02-May-2018
Category:
Upload: doanhanh
View: 222 times
Download: 0 times
Share this document with a friend
24
Lecture Notes in Artif icial Intelligence 4682 Edited by J. G. Carbonell and J. Siekmann Subseries of Lecture Notes in Computer Science
Transcript
Page 1: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Lecture Notes in Artificial Intelligence 4682Edited by J. G. Carbonell and J. Siekmann

Subseries of Lecture Notes in Computer Science

Page 2: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

De-Shuang Huang Laurent HeutteMarco Loog (Eds.)

Advanced IntelligentComputing Theoriesand Applications

With Aspects of Artificial Intelligence

Third International Conference onIntelligent Computing, ICIC 2007Qingdao, China, August 21-24, 2007Proceedings

13

Page 3: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Series Editors

Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USAJörg Siekmann, University of Saarland, Saarbrücken, Germany

Volume Editors

De-Shuang HuangChinese Academy of SciencesInstitute of Intelligent Machines, ChinaE-mail: [email protected]

Laurent HeutteUniversité de RouenLaboratoire LITIS76800 Saint Etienne du Rouvray, FranceE-mail: [email protected]

Marco LoogUniversity of CopenhagenDatalogical Institute2100 Copenhagen Ø, DenmarkE-mail: [email protected]

Library of Congress Control Number: 2007932602

CR Subject Classification (1998): I.2.3, I.2, F.4.1, F.1, I.5, F.2, G.2, I.4

LNCS Sublibrary: SL 7 – Artificial Intelligence

ISSN 0302-9743ISBN-10 3-540-74201-8 Springer Berlin Heidelberg New YorkISBN-13 978-3-540-74201-2 Springer Berlin Heidelberg New York

This work is subject to copyright. All rights are reserved, whether the whole or part of the material isconcerned, 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 publicationor 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 liableto prosecution under the German Copyright Law.

Springer is a part of Springer Science+Business Media

springer.com

© Springer-Verlag Berlin Heidelberg 2007Printed in Germany

Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, IndiaPrinted on acid-free paper SPIN: 12107902 06/3180 5 4 3 2 1 0

Page 4: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Preface

The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring to-gether researchers and practitioners from both academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing.

ICIC 2007, held in Qingdao, China, August 21-24, 2007, constituted the Third In-ternational Conference on Intelligent Computing. It built upon the success of ICIC 2006 and ICIC 2005 held in Kunming and Hefei, China, 2006 and 2005, respectively.

This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.

ICIC 2007 received 2875 submissions from 39 countries and regions. All papers went through a rigorous peer review procedure and each paper received at least three review reports. Based on the review reports, the Program Committee finally selected 496 high-quality papers for presentation at ICIC 2007, of which 430 papers have been included in three volumes of proceedings published by Springer: one volume of Lecture Notes in Computer Science (LNCS), one volume of Lecture Notes in Artificial Intelligence (LNAI), and one volume of Communications in Computer and Information Science (CCIS). The other 66 papers will be included in four international journals.

This volume of Lecture Notes in Artificial Intelligence (LNAI) includes 139 papers. The organizers of ICIC 2007, including the Ocean University of China and the In-

stitute of Intelligent Machines of the Chinese Academy of Science, made an enor-mous effort to ensure the success of ICIC 2007. We hereby would like to thank the members of the ICIC 2007 Advisory Committee for their guidance and advice, the members of the Program Committee and the referees for their collective effort in reviewing and soliciting the papers. We would like to thank Alfred Hofmann, execu-tive editor from Springer, for his frank and helpful advice and guidance throughout and for his support in publishing the proceedings. In particular, we would like to thank all the authors for contributing their papers. Without the high-quality submis-sions from the authors, the success of the conference would not have been possible. Finally, we are especially grateful to the IEEE Computational Intelligence Society, the International Neural Network Society and the National Science Foundation of China for their sponsorship.

June 2007 De-Shuang Huang Laurent Heutte

Marco Loog

Page 5: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

ICIC 2007 Organization

General Co-chairs De-Shuang Huang, China Luonan Chen, Japan

International Advisory Committee

Moonis Ali, USA Shun-Ichi Amari, Japan Zheng Bao, China John L. Casti, USA Guoliang Chen, China Diane J. Cook, USA Ruwei Dai, China John O Gray, UK Aike Guo, China Fuchu He, China Xingui He, China Tom Heskes, Netherlands

Mustafa Khammash, USA Okyay Knynak, Turkey Yanda Li, China Marios M. Polycarpou, USA Songde Ma, China Erke Mao, China Michael R. Lyu, Hong Kong Yunyu Shi, China Harold Szu, USA Stephen Thompson, UK Mathukumalli Vidyasagar, IndiaShoujue Wang, China

Paul Werbos, USA George W. Irwin, UK DeLiang Wang, USA Youshou Wu, China Xin Yao, UK Nanning Zheng, China Yixin Zhong, China Mengchu Zhou, USA Qingshi Zhu, China Xiang-Sun Zhang, China

Steering Committee Co-chairs Sheng Chen, UK

Xiao-Ping Zhang, Canada Kang Li, UK

Program Committee Chair Laurent Heutte, France

Organizing Committee Co-chairs Guo Chen, China Ming Lv, China Guangrong Ji, China Ji-Xiang Du, China

Publication Chair Marco Loog, Denmark

Special Session Chair Wanquan Liu, Australia

International Liaison Chair Prashan Premaratne, Australia

Tutorial Chair Robert Hsieh, Germany

Page 6: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

VIII Organization

Publicity Co-chairs Liyanage C. De Silva , New Zealand Vitoantonio Bevilacqua, Italy Kang-Hyun Jo, Korea Jun Zhang, China

Exhibition Chair Bing Wang, China

International Program Committee

Andrea Francesco Abate, Italy Waleed H. Abdulla,

New Zealand Shafayat Abrar, Pakistan Parag Gopal Kulkarni, UK Vasily Aristarkhov, Russian

Federation Masahiro Takatsuka, Australia Costin Badica, Romania Soumya Banerjee, India Laxmidhar Behera, India Vitoantonio Bevilacqua, Italy Salim Bouzerdoum, Australia David B. Bracewell, Japan Toon Calders, Belgium Vincent C S Lee, Australia Gianluca Cena, Italy Pei-Chann Chang, Taiwan Wen-Sheng Chen, China Hong-Qiang Wang, Hong Kong Rong-Chang Chen, Taiwan Geoffrey Macintyre, Australia Weidong Chen, China Chi-Cheng Cheng, China Ziping Chiang, Taiwan Min-Sen Chiu, Singapore Tommy Chow, Hong Kong Mo-Yuen Chow, USA Rasoul Mohammadi Milasi,

Canada Alexandru Paul Condurache,

Germany Sonya Coleman, UK Pedro Melo-Pinto, Portugal Roman Neruda, Czech Republic Gabriella Dellino, Italy Grigorios Dimitriadis, UK

Mariagrazia Dotoli, Italy Minh Nhut Nguyen,

Singapore Hazem Elbakry, Japan Karim Faez, Iran Jianbo Fan, China Minrui Fei, China Mario Koeppen, Japan Uwe Kruger, UK Fausto Acernese, Italy Qing-Wei Gao, China Takashi Kuremoto, Japan Richard Lathrop, USA Agostino Lecci, Italy Marco Loog, Denmark Choong Ho Lee, Korea Jinde Cao, China Kang Li, UK Peihua Li, China Jin Li, UK Xiaoli Li, UK Chunmei Liu, USA Paolo Lino, Italy Ju Liu, China Van-Tsai Liu, Taiwan Wanquan Liu, Australia Brian C. Lovell, Australia Hongtao Lu, China Mathias Lux, Austria Sheng Chen, UK Jinwen Ma, China Yongjun Ma, China Guido Maione, Italy Vishnu Makkapati, India Filippo Menolascina, Italy Damien Coyle, UK Cheolhong Moon, Korea

Angelo Ciaramella, Italy

Tark Veli Mumcu, Turkey

Michele Nappi, Italy Kevin Curran, UK Giuseppe Nicosia, Italy Kenji Doya, Japan Ahmet Onat, Turkey Ali Ozen, Turkey Sulin Pang, China Antonino Staiano, Italy David G. Stork, USA Fuchun Sun, China Zhan-Li Sun,

Hong Kong Maolin Tang, Australia John Thompson, UK Amir Atiya, Egypt Anna Tramontano, Italy Jose-Luis Verdegay,

Spain Sergio Vitulano, Italy Anhua Wan, China Chengxiang Wang, UK Bing Wang, China Kongqiao Wang, China Zhi Wang, China Hong Wang, China Hong Wei, UK Xiyuan Chen, China Chao-Xue Wang, China Yong Wang, Japan Xue Wang, China Mike Watts,

New Zealand Ling-Yun Wu, China

Page 7: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Organization IX

Jiangtao Xi, Australia Shunren Xia, China Jianhua Xu, China Yu Xue, China Takeshi Yamakawa, Japan Ching-Nung Yang, Taiwan Hsin-Chang Yang, Taiwan Jun-Heng Yeh, Taiwan Xinge You, China Huan Yu, China Wen Yu, Mexico Zhi-Gang Zeng, China Dengsheng Zhang, Australia Huaguang Zhang, China Jun Zhang, China Guang-Zheng Zhang, Korea Shaoning Pang, New Zealand Sim-Heng Ong, Singapore Liang Gao, China Xiao-Zhi Gao, Finland Carlos Alberto Reyes Garcia,

Mexico Joaquin Orlando Peralta,

Argentina José Andrés Moreno Pérez,

Spain Andrés Ferreyra Ramírez,

Mexico Francesco Pappalardo, Italy Fei Han, China Kyungsook Han, Korea Jim Harkin, UK

Pawel Herman, UK Haibo He, USA Yuexian Hou, China Zeng-Guang Hou, China Eduardo R. Hruschka,

Brazil Estevam Rafael Hruschka

Junior, Brazil Dewen Hu, China Jiankun Hu, Australia Muhammad Khurram

Khan, Pakistan Chuleerat Jaruskulchai,

Thailand Nuanwan Soonthornphisaj,

Thailand Naiqin Feng, China Bob Fisher, UK Thierry Paquet, France Jong Hyuk Park, Korea Aili Han, China Young-Su Park, Korea Jian-Xun Peng, UK Yuhua Peng, China Girijesh Prasad, UK Hairong Qi, USA Hong Qiao, China Nini Rao, China Michael Reiter, Austria Angel D. Sappa, Spain Angel Sappa, Spain Aamir Shahzad, Sweden

Li Shang, China Xiaolong Shi, China Brane Sirok, Slovenia Doan Son, Japan Venu Govindaraju, USA Kayhan Gulez, Turkey Ping Guo, China Junping Zhang, China Wu Zhang, China Xi-Wen Zhang, China Hongyong Zhao, China Qianchuan Zhao, China Xiaoguang Zhao, China Xing-Ming Zhao, Japan Chun-Hou Zheng,

China Fengfeng Zhou, USA Weidong Zhou, China Daqi Zhu, China Guangrong Ji, China Zhicheng Ji, China Li Jia, China Kang-Hyun Jo, Korea Jih-Gau Juang, Taiwan Yong-Kab Kim, Korea Yoshiteru Ishida, Japan Peter Chi Fai Hung,

Ireland Turgay Ibrikci, Turkey Myong K. Jeong, USA Jiatao Song, China Tingwen Huang, Qatar

Reviewers

Elham A. Boroujeni, Khalid Aamir, Ajith Abraham, Fabrizio Abrate, Giuseppe M.C. Acciani, Ali Adam, Bilal Al Momani, Ibrahim Aliskan, Roberto Amato, Claudio Amorese, Senjian An, Nestor Arana Arexolaleiba, Sebastien Ardon, Khaled Assaleh, Amir Atiya, Mutlu Avci, Pedro Ayrosa, Eric Bae, Meng Bai, Amar Balla, Zaochao Bao, Péter Baranyi, Nicola Barbarini, Edurne Barrenechea, Marc Bartels, Edimilson Batista dos Santos, Devon Baxter, Yasar Becerikli, Ammar Belatreche, Domenico Bellomo, Christian Benar, Vitoantonio Bevilacqua, Daowei Bi, Ida Bifulco, Abbas Bigdeli, Hendrik Blockeel, Leonardo Bocchi, Gennaro Boggia, David Bracewell, Janez Branj, Nicolas Brodu, Cyril Brom, Dariusz Burak, Adrian Burian, Jose M. Cadenas, Zhiyuan Cai, David Camacho, Heloisa Camargo, Maria Angelica Camargo-Brunetto, Francesco Camastra, Ricardo Campello, Galip Cansever, Bin Cao, Dong

Page 8: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

X Organization

Dong Cao, Alessandra Carbotti, Jesus Ariel Carrasco-Ochoa, Deborah Carvalho, Roberto Catanuto, Xiujuan Chai, Kap Luk Chan, Chien-Lung Chan, Ram Chandra-gupta, Hong Chang, Hsueh-Sheng Chang, Clément Chatelain, Dongsheng Che, Chun Chen, Chung-Cheng Chen, Hsin-Yuan Chen, Tzung-Shi Chen, Xiaohan Chen, Y.M. Chen, Ying Chen, Ben Chen, Yu-Te Chen, Wei-Neng Chen, Chuyao Chen, Jian-Bo Chen, Fang Chen, Peng Chen, Shih-Hsin Chen, Shiaw-Wu Chen, Baisheng Chen, Zhimin Chen, Chun-Hsiung Chen, Mei-Ching Chen, Xiang Chen, Tung-Shou Chen, Xinyu Chen, Yuehui Chen, Xiang Cheng, Mu-Huo Cheng, Long Cheng, Jian Cheng, Qiming Cheng, Ziping Chiang, Han-Min Chien, Min-Sen Chiu, Chi Yuk Chiu, Chungho Cho, Sang-Bock Cho, Soo-Mi Choi, Yoo-Joo Choi, Wen-Shou Chou, T Chow, Xuezheng Chu, Min Gyo Chung, Michele Ciavotta, Ivan Cibrario Bertolotti, Davide Ciucci, Sonya Coleman, Simona Colucci, Patrick Connally, David Corne, Damien Coyle, Cuco Cristi, Carlos Cruz Corona, Lili Cui, Fabrizio Dabbene, Weidi Dai, Thouraya Daouas, Cristina Darolti, Marleen De Bruijne, Leandro De Castro, Chaminda De Silva, Lara De Vinco, Carmine Del Mondo, Gabriella Dellino, Patrick Dempster, Da Deng, Yue Deng, Haibo Deng, Scott Dexter, Nele Dexters, Bi Dexue, Wan Dingsheng, Banu Diri, Angelo Doglioni, Yajie Dong, Liuhuan Dong, Jun Du, Wei-Chang Du, Chen Duo, Peter Eisert, Mehdi El Gueddari, Elia El-Darzi, Mehmet Engin, Zeki Erdem, Nuh Erdogan, Kadir Erkan, Osman Kaan Erol, Ali Esmaili, Alex-andre Evsukoff, Marco Falagario, Shu-Kai Fan, Chin-Yuan Fan, Chun-I Fan, Lixin Fan, Jianbo Fan, Bin Fang, Yikai Fang, Rashid Faruqui, Markus Fauster, Guiyu Feng, Zhiyong Feng, Rui Feng, Chen Feng, Yong Feng, Chieh-Chuan Feng, Fran-cisco Fernandez Periche, James Ferryman, Mauricio Figueiredo, Vítor Filipe, Celine Fiot, Alessandra Flammini, Girolamo Fornarelli, Katrin Franke, Kechang Fu, Tiaop-ing Fu, Hong Fu, Chaojin Fu, Xinwen Fu, Jie Fu, John Fulcher, Wai-keung Fung, Zhang G. Z., Sebastian Galvao, Junying Gan, Zhaohui Gan, Maria Ganzha, Xiao-Zhi Gao, Xin Gao, Liang Gao, Xuejin Gao, Xinwen Gao, Ma Socorro Garcia, Ignacio Garcia-del-Amo, Lalit Garg, Shuzi Sam Ge, Fei Ge, Xin Geng, David Geronimo, Reza Ghorbani, Paulo Gil, Gustavo Giménez-Lugo, Tomasz Gingold, Lara Giordano, Cornelius Glackin, Brendan Glackin, Juan Ramón González González, Jose-Joel Gonzalez-Barbosa, Padhraig Gormley, Alfredo Grieco, Giorgio Grisetti, Hanyu Gu, Xiucui Guan, Jie Gui, Aaron Gulliver, Feng-Biao Guo, Ge Guo, Tian-Tai Guo, Song Guo, Lingzhong Guo, Yue-Fei Guo, P Guo, Shwu-Ping Guo, Shengbo Guo, Shou Guofa, David Gustavsson, Jong-Eun Ha, Risheng Han, Aili Han, Fengling Han, Hi-sashi Handa, Koji Harada, James Harkin, Saadah Hassan, Aboul Ella Hassanien, Jean-Bernard Hayet, Hanlin He, Qingyan He, Wangli He, Haibo He, Guoguang He, Pilian He, Yanxiang He, Pawel Herman, Francisco Herrera, Jan Hidders, Grant Hill, John Ho, Xuemin Hong, Tzung-Pei Hong, Kunjin Hong, Shi-Jinn Horng, Lin Hou, Eduardo Hruschka, Shang-Lin Hseih, Chen-Chiung Hsieh, Sun-Yuan Hsieh, Jih-Chang Hsieh, Chun-Fei Hsu, Honglin Hu, Junhao Hu, Qinglei Hu, Xiaomin Hu, Xiaolin Hu, Chen Huahua, Xia Huang, Jian Huang, Xiaojing Huang, Gan Huang, Weitong Huang, Jing Huang, Weimin Huang, Yufei Huang, Zhao Hui, Sajjad Hus-sain, Thong-Shing Hwang, Giorgio Iacobellis, Francesco Iorio, Mohammad Reza Jamali, Horn-Yong Jan, Dar-Yin Jan, Jong-Hann Jean, Euna Jeong, Mun-Ho Jeong, Youngseon Jeong, Zhen Ji, Qing-Shan Jia, Wei Jia, Fan Jian, Jigui Jian, Peilin Jiang, Dongxiang Jiang, Minghui Jiang, Ping Jiang, Xiubao Jiang, Xiaowei Jiang, Hou Jian-grong, Jing Jie, Zhang Jihong, Fernando Jimenez, Guangxu Jin, Kang-Hyun Jo,

Page 9: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Organization XI

Guillaume Jourjon, Jih-Gau Juang, Carme Julià, Zhou Jun, Dong-Joong Kang, Hee-Jun Kang, Hyun Deok Kang, Hung-Yu Kao, Indrani Kar, Cihan Karakuzu, Bekir Karlik, Wolfgang Kastner, John Keeney, Hrvoje Keko, Dermot Kerr, Gita Khalili Moghaddam, Muhammad Khurram Khan, Kavi Umar Khedo, Christian Kier, GwangHyun Kim, Dae-Nyeon Kim, Dongwon Kim, Taeho Kim, Tai-hoon Kim, Paris Kitsos, Kunikazu Kobayashi, Sarath Kodagoda, Mario Koeppen, Nagahisa Kogawa, Paul Kogeda, Xiangzhen Kong, Hyung Yun Kong, Insoo Koo, Marcin Korze, Ibra-him Kucukdemiral, Petra Kudova, Matjaz Kukar, Parag Kulkarni, Saravana Kumar, Wen-Chung Kuo, Takashi Kuremoto, Janset Kuvulmaz, Jin Kwak, Lam-For Kwok, Taekyoung Kwon, Marcelo Ladeira, K. Robert Lai, Darong Lai, Chi Sung Laih, Senthil Kumar Lakshmanan, Dipak Lal Shrestha, Yuk Hei Lam, M. Teresa Lamata, Oliver Lampl, Peng Lan, Vuokko Lantz, Ana Lilia Laureano-Cruces, Yulia Ledeneva, Vincent C S Lee, Narn-Yih Lee, Malrye Lee, Chien-Cheng Lee, Dong Hoon Lee, Won S Lee, Young Jae Lee, Kyu-Won Lee, San-Nan Lee, Gang Leng, Agustin Leon Barranco, Chi Sing Leung, Cuifeng Li, Fuhai Li, Chengqing Li, Guo-Zheng Li, Hongbin Li, Bin Li, Liberol Li, Bo Li, Chuandong Li, Erguo Li, Fangmin Li, Juntao Li, Jinshan Li, Lei Li, Ming Li, Xin Li, Xiaoou Li, Xue li, Yuan Li, Lisa Li, Yuancheng Li, Kang Li, Jun Li, Jung-Shian Li, Shijian Li, Zhihua Li, Zhijun Li, Zhenping Li, Shutao Li, Xin Li, Anglica Li, Wanqing Li, Jian Li, Shaoming Li, Xiaohua Li, Xiao-Dong Li, Xiaoli Li, Yuhua Li, Yun-Chia Liang, Wei Liang, Wux-ing Liang, Jinling Liang, Wen-Yuan Liao, Wudai Liao, Zaiyi Liao, Shizhong Liao, Vicente Liern, Wen-Yang Lin, Zhong Lin, Chih-Min Lin, Chun-Liang Lin, Xi Lin, Yu Chen Lin, Jun-Lin Lin, Ke Lin, Kui Lin, Ming-Yen Lin, Hsin-Chih Lin, Yu Ling, Erika Lino, Erika Lino, Paolo Lino, Erika Lino, Shiang Chun Liou, Ten-Yuang Liu, Bin Liu, Jianfeng Liu, Jianwei Liu, Juan Liu, Xiangyang Liu, Yadong Liu, Yubao Liu, Honghai Liu, Kun-Hong Liu, Kang-Yuan Liu, Shaohui Liu, Qingshan Liu, Chen-Hao Liu, Zhiping Liu, Yinyin Liu, Yaqiu Liu, Van-Tsai Liu, Emmanuel Lochin, Marco Loog, Andrew Loppingen, Xiwen Lou, Yingli Lu, Yao Lu, Wen-Hsiang Lu, Wei Lu, Hong Lu, Huijuan Lu, Junguo Lu, Shangmin Luan, Jiliang Luo, Xuyao Luo, Tuan Trung Luong, Mathias Lux, Jun Lv, Chengguo Lv, Bo Ma, Jia Ma, Guang-Ying Ma, Dazhong Ma, Mi-Chia Ma, Junjie Ma, Xin Ma, Diego Magro, Liam Maguire, Aneeq Mahmood, Waleed Mahmoud, Bruno Maione, Agostino Marcello Mangini, Weihua Mao, Kezhi Mao, Antonio Maratea, Bogdan Florin Marin, Mario Marinelli, Urszula Markowska-Kaczmar, Isaac Martin, Francesco Martinelli, Jose Fco. Martínez-Trinidad, Antonio David Masegosa Arredondo, Louis Massey, Emilio Mas-triani, Marco Mastrovito, Kerstin Maximini, Radoslaw Mazur, Daniele Mazzocchi, Malachy McElholm, Gerard McKee, Colin McMillen, Jian Mei, Belen Melian, Carlo Meloni, Pedro Melo-Pinto, Corrado Mencar, Luis Mesquita, Jianxun Mi, Pauli Miet-tinen, Claudia Milaré, Rasoul Milasi, Orazio Mirabella, Nazeeruddin Mohammad, Eduard Montseny, Inhyuk Moon, Hyeonjoon Moon, Raul Morais, J. Marcos Moreno, José Andrés Moreno, Philip Morrow, Santo Motta, Mikhal Mozerov, Francesco Na-politano, David Naso, Wang Nengqiang, Mario Neugebauer, Yew Seng Ng, Wee Keong Ng, Tam Nguyen, Quang Nguyen, Thang Nguyen, Rui Nian, James Niblock, Iaobing Nie, Eindert Niemeijer, Julio Cesar Nievola, Haijing Niu, Qun Niu, Chan-gyong Niu, Asanao Obayashi, Kei Ohnishi, Takeshi Okamoto, Jose Angel Olivas, Stanley Oliveira, Kok-Leong Ong, Chen-Sen Ouyang, Pavel Paclik, Tinglong Pan, Sanjib Kumar Panda, Tsang-Long Pao, Emerson Paraiso, Daniel Paraschiv, Giuseppe

Page 10: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XII Organization

Patanè, Kaustubh Patil, Mykola Pechenizkiy, Carlos Pedroso, Zheng Pei, Shun Pei, Chang Pei-Chann, David Pelta, Jian-Xun Peng, Sheng-Lung Peng, Marzio Pennisi, Cathryn Peoples, Eranga Perera, Alessandro Perfetto, Patrick Peursum, Minh-Tri Pham, Phuong-Trinh Pham-Ngoc, Lifton Phua, Son Lam Phung, Alfredo Pironti, Giacomo Piscitellei, Elvira Popescu, Girijesh Prasad, Prashan Premaratne, Alfredo Pulvirenti, Lin Qi, HangHang Qi, Yu Qiao, Xiaoyan Qiao, Lixu Qin, Kai Qin, Jian-long Qiu, Ying-Qiang Qiu, Zhonghua Quan, Thanh-Tho Quan, Chedy Raïssi, Jochen Radmer, Milo Radovanovi, Bogdan Raducanu, Humera Rafique, Thierry Rako-toarivelo, Nini Rao, Ramesh Rayudu, Arif Li Rehman, Dehua Ren, Wei Ren, Xinmin Ren, Fengli Ren, Orion Reyes, Napoleon Reyes, Carlos Alberto Reyes-Garcia, Ales-sandro Rizzo, Giuseppe Romanazzi, Marta Rosatelli, Heung-Gyoon Ryu, Hichem Sahbi, Ying Sai, Paulo Salgado, Luigi Salvatore, Nadia Salvatore, Saeid Sanei, Jose Santos, Angel Sappa, Heather Sayers, Klaus Schöffmann, Bryan Scotney, Carla Seatzu, Hermes Senger, Murat Sensoy, Carlos M.J.A. Serodio, Lin Shang, Li Shang, XiaoJian Shao, Andrew Shaw, Sheng Yuan Shen, Yanxia Shen, Yehu Shen, Linlin Shen, Yi Shen, Jinn-Jong Sheu, Mingguang Shi, Chaojian Shi, Dongfeng Shi, June-Horng Shiesh, Yen Shi-Jim, Zhang Shuhong, Li Shundong, Nanshupo Shupo, Oliver Sinnen, Sukree Sinthupinyo, Silvia Siri, Ernest Sithole, Nicolas Sklavos, Stanislav Slusny, Pilar Sobrevilla, Ignacio Solis, Anthony Solon, Andy Song, Liu Song, Qiankun Song, Zheng Song, Yinglei Song, Nuanwan Soonthornphisaj, Aureli Soria-Frisc, Jon Sporring, Kim Steenstrup Pedersen, Domenico Striccoli, Juhng Perng Su, Shanmugalingam Suganthan, P. N. Suganthan, Youngsoo Suh, Yonghui Sun, Xinghua Sun, Ning Sun, Fuchun Sun, Lily Sun, Jianyong Sun, Jiande Sun, Worasait Suwannik, Roberto T. Alves, Tele Tan, Taizhe Tan, Xuan Tan, Xiaojun Tan, Hong Zhou Tan, Feiselia Tan, Hong Tang, Chunming Tang, David Taniar, Michele Ta-ragna, David M.J. Tax, Ziya Telatar, Zhi Teng, John Thompson, Bin Tian, Ching-Jung Ting, Fok Hing Chi Tivive, Alexander Topchy, Juan Carlos Torres, Ximo Tor-res, Joaquin Torres-Sospedra, Hoang Hon Trinh, Chia-Sheng Tsai, Chieh-Yuan Tsai, Huan-Liang Tsai, Wang-Dauh Tseng, Yuan-Jye Tseng, Yifeng Tu, Biagio Turchiano, Cigdem Turhan, Anna Ukovich, Muhammad Muneeb Ullah, Nurettin Umurkan, Mustafa Unel, Daniela Ushizima, Adriano Valenzano, Pablo A. Valle, Bram Van Ginneken, Christian Veenhuis, Roel Vercammen, Enriqueta Vercher, Silvano Ver-gura, Brijesh Verma, Raul Vicente Garcia, Boris X. Vintimilla Burgos, Gareth Vio, Stefano Vitturi, Aristeidis Vlamenkoff, John Wade, Manolis Wallace, Li Wan, Shijun Wang, Xiaodong Wang, Xue Wang, Zhi Wang, Bing Wang, Chih-Hung Wang, Chao Wang, Da Wang, Jianying Wang, Le Wang, Min Wang, Rui-Sheng Wang, Sheng Wang, Jiahai Wang, Guanjun Wang, Linshan Wang, Yanyan Wang, Xuan Wang, Xiao-Feng Wang, Yong Wang, Zidong Wang, Zhongsheng Wang, Zhengyou Wang, Yen-Wen Wang, Shiuh-Jeng Wang, Shouqi Wang, Ling Wang, Xiang Wang, Lina Wang, Qing-Guo Wang, Yebin Wang, Dingcheng Wang, Dianhui Wang, Meng Wang, Yi Wang, Bao-Yun Wang, Xiaomin Wang, Huazhong Wang, Jeen-Shing Wang, Haili Wang, Haijing Wang, Jian Wang, Yoshikazu Washizawa, Yuji Wata-nabe, Wiwat Watanawood, Michael Watts, Richard Weber, Lisheng Wei, Zhi Wei, Yutao Wei, Hong Wei, Li Weigang, Dawid Weiss, Hou Weiyan, Guo-Zhu Wen, Brendon Woodford, Derek Woods, Lifang Wu, Zikai Wu, Ke Wu, Xinan Wu, Hsien-Chu Wu, QingXiang Wu, Shiqian Wu, Lihchyau Wuu, Jun-Feng Xia, Li Xia, Xiao Lei Xia, Zhiyu Xiang, Kui Xiang, LiGuo Xiang, Tao Xiang, Jing Xiao, Min Xiao, Liu

Page 11: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Organization XIII

Xiaodong, Zhao Xiaoguang, Xiangpeng Xie, Zhijun Xie, Shaohua Xie, Jiang Xie, Hong Xie, Rui Xing, Li Xinyu, Wei Xiong, Huan Xu, Jiangfeng Xu, Jianhua Xu, Yongjun Xu, Jun Xu, Hongji Xu, Bingji Xu, Yu Xue, Yun Xue, Mehmet Yakut, Xing Yan, Jiajun Yan, Hua Yan, Yan Yang, Hsin-Chang Yang, Tao Yang, Chengfu Yang, Banghua Yang, Ruoyu Yang, Zhen Yang, Zhichun Yang, Wu-Chuan Yang, Ming Yang, Cheng-Zen yang, Shouyi Yang, Ming-Jong Yao, Kim-Hui Yap, Hao Ye, Chia-Hsuan Yeh, James Yeh, Jun-Heng Yeh, Shwu-Huey Yen, Sang-Soo Yeo, Yang Yi, Tulay Yildirim, PeiPei Yin, Junsong Yin, Lin Ying, Ling Ying-Biao, Yang Yongqing, Kaori Yoshida, Tomohiro Yoshikawa, Qi Yu, Wen Yu, Wen-Shyong Yu, Kun Yuan, Kang Yuanyuan, Chen Yuepeng, Li Yun, Kun Zan, Chuanzhi Zang, Ramon Zatarain-Cabada, Faiz ul Haque Zeya, Zhihui Zhan, Changshui Zhang, Yongping Zhang, Jie Zhang, Jun Zhang, Yunchu Zhang, Zanchao Zhang, Yifeng Zhang, Shihua Zhang, Ningbo Zhang, Junhua Zhang, Jun Zhang, Shanwen Zhang, Hengdao Zhang, Wen-sheng Zhang, Haoshui Zhang, Ping Zhang, Huaizhong Zhang, Dong Zhang, Hua Zhang, Byoung-Tak Zhang, Guohui Zhang, Li-Bao Zhang, Junping Zhang, Junpeng Zhang, Jiye Zhang, Junying Zhang, JingRu Zhang, Jian Zhang, Duanjin Zhang, Xin Zhang, Huaguang Zhang, Guo Zhanjie, Jizhen Zhao, Zhong-Qiu Zhao, Li Zhao, Ming Zhao, Yinggang Zhao, Ruijie Zhao, Guangzhou Zhao, Liu Zhaolei, Fang Zheng, Ying Zheng, Chunhou Zheng, Cong Zheng, Guibin Zheng, Qinghua Zheng, Wen-Liang Zhong, Jinghui Zhong, Jiayin Zhou, Jie Zhou, Xiaocong Zhou, Fengfeng Zhou, Chi Zhou, Sue Zhou, Mian Zhou, Zongtan Zhou, Lijian Zhou, Zhongjie Zhu, Xinjian Zhuo, Xiaolan Zhuo, Yanyang Zi, Ernesto Zimmermann, Claudio Zunino, Haibo Deng, Wei Liu.

Page 12: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents

Neural Networks

A New Watermarking Approach Based on Neural Network in WaveletDomain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Xue-Quan Xu, Xian-Bin Wen, Yue-Qing Li, and Jin-Juan Quan

Analysis of Global Convergence and Learning Parameters of theBack-Propagation Algorithm for Quadratic Functions . . . . . . . . . . . . . . . . . 7

Zhigang Zeng

Application Server Aging Prediction Model Based on Wavelet Networkwith Adaptive Particle Swarm Optimization Algorithm . . . . . . . . . . . . . . . 14

Meng Hai Ning, Qi Yong, Hou Di, Pei Lu Xia, and Chen Ying

Edge Detection Based on Spiking Neural Network Model . . . . . . . . . . . . . . 26QingXiang Wu, Martin McGinnity, Liam Maguire,Ammar Belatreche, and Brendan Glackin

Gait Parameters Optimization and Real-Time Trajectory Planning forHumanoid Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Shouwen Fan and Min Sun

Global Asymptotic Stability of Cohen-Grossberg Neural Networks withMultiple Discrete Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Anhua Wan, Weihua Mao, Hong Qiao, and Bo Zhang

Global Exponential Stability of Cohen-Grossberg Neural Networks withReaction-Diffusion and Dirichlet Boundary Conditions . . . . . . . . . . . . . . . . 59

Chaojin Fu and Chongjun Zhu

Global Exponential Stability of Fuzzy Cohen-Grossberg NeuralNetworks with Variable Delays and Distributed Delays . . . . . . . . . . . . . . . . 66

Jiye Zhang, Dianbo Ren, and Weihua Zhang

Global Exponential Synchronization of a Class of Chaotic NeuralNetworks with Time-Varying Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Jing Lin and Jiye Zhang

Grinding Wheel Topography Modeling with Application of an ElasticNeural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

B�lazej Ba�lasz, Tomasz Szatkiewicz, and Tomasz Krolikowski

Hybrid Control of Hopf Bifurcation for an Internet CongestionModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

Zunshui Cheng, Jianlong Qiu, Guangbin Wang, and Bin Yu

Page 13: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XVI Table of Contents

MATLAB Simulation of Gradient-Based Neural Network for OnlineMatrix Inversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Yunong Zhang, Ke Chen, Weimu Ma, and Xiao-Dong Li

Mean Square Exponential Stability of Uncertain Stochastic HopfieldNeural Networks with Interval Time-Varying Delays . . . . . . . . . . . . . . . . . . 110

Jiqing Qiu, Hongjiu Yang, Yuanqing Xia, and Jinhui Zhang

New Stochastic Stability Criteria for Uncertain Neural Networks withDiscrete and Distributed Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

Jiqing Qiu, Zhifeng Gao, and Jinhui Zhang

Novel Forecasting Method Based on Grey Theory and NeuralNetwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130

Cheng Wang and Xiaoyong Liao

One-Dimensional Analysis of Exponential Convergence Condition forDual Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Yunong Zhang and Haifeng Peng

Stability of Stochastic Neutral Cellular Neural Networks . . . . . . . . . . . . . . 148Ling Chen and Hongyong Zhao

Synchronization of Neural Networks by Decentralized Linear-FeedbackControl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

Jinhuan Chen, Zhongsheng Wang, Yanjun Liang, Wudai Liao, andXiaoxin Liao

Synchronous Pipeline Circuit Design for an Adaptive Neuro-FuzzyNetwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

Che-Wei Lin, Jeen-Shing Wang, Chun-Chang Yu, and Ting-Yu Chen

The Projection Neural Network for Solving Convex NonlinearProgramming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174

Yongqing Yang and Xianyun Xu

Usage of Hybrid Neural Network Model MLP-ART for Navigation ofMobile Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

Andrey Gavrilov and Sungyoung Lee

Using a Wiener-Type Recurrent Neural Network with the MinimumDescription Length Principle for Dynamic System Identification . . . . . . . . 192

Jeen-Shing Wang, Hung-Yi Lin, Yu-Liang Hsu, and Ya-Ting Yang

Independent Component Analysis and Blind SourceSeparation

A Parallel Independent Component Implement Based on LearningUpdating with Forms of Matrix Transformations . . . . . . . . . . . . . . . . . . . . . 202

Jing-Hui Wang, Guang-Qian Kong, and Cai-Hong Liu

Page 14: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XVII

Application Study on Monitoring a Large Power Plant Operation . . . . . . 212Pingkang Li, Xun Wang, and Xiuxia Du

Default-Mode Network Activity Identified by Group IndependentComponent Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

Conghui Liu, Jie Zhuang, Danling Peng, Guoliang Yu, andYanhui Yang

Mutual Information Based Approach for Nonnegative IndependentComponent Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

Hua-Jian Wang, Chun-Hou Zheng, and Li-Hua Zhang

Combinatorial and Numerical Optimization

Modeling of Microhardness Profile in Nitriding Processes UsingArtificial Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245

Dariusz Lipinski and Jerzy Ratajski

A Similarity-Based Approach to Ranking Multicriteria Alternatives . . . . 253Hepu Deng

Algorithms for the Well-Drilling Layout Problem . . . . . . . . . . . . . . . . . . . . . 263Aili Han, Daming Zhu, Shouqiang Wang, and Meixia Qu

Application of Dynamic Programming to Solving K Postmen ChinesePostmen Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272

Rong Fei, Duwu Cui, Yikun Zhang, and Chaoxue Wang

Choices of Interacting Positions on Multiple Team Assembly . . . . . . . . . . 282Chartchai Leenawong and Nisakorn Wattanasiripong

Genetic Local Search for Optimum Multiuser Detection Problem inDS-CDMA Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292

Shaowei Wang and Xiaoyong Ji

Motion Retrieval with Temporal-Spatial Features Based on EnsembleLearning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300

Jian Xiang

The Study of Pavement Performance Index Forecasting Via ImprovingGrey Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309

Ziping Chiang, Dar-Ying Jan, and Hsueh-Sheng Chang

Neural Computing and Optimization

An Adaptive Recursive Least Square Algorithm for Feed ForwardNeural Network and Its Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315

Xi-hong Qing, Jun-yi Xu, Fen-hong Guo, Ai-mu Feng,Wei Nin, and Hua-xue Tao

Page 15: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XVIII Table of Contents

BOLD Dynamic Model of Functional MRI . . . . . . . . . . . . . . . . . . . . . . . . . . 324Ling Zeng, Yuqi Wang, and Huafu Chen

Partial Eigenanalysis for Power System Stability Study by ConnectionNetwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330

Pei-Hwa Huang and Chao-Chun Li

Knowledge Discovery and Data Mining

A Knowledge Navigation Method for the Domain of Customers’Services of Mobile Communication Corporations in China . . . . . . . . . . . . . 340

Jiangning Wu and Xiaohuan Wang

A Method for Building Concept Lattice Based on Matrix Operation . . . 350Kai Li, Yajun Du, Dan Xiang, Honghua Chen, and Zhenwen Liao

A New Method of Causal Association Rule Mining Based on LanguageField . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360

Kaijian Liang, Quan Liang, and Bingru Yang

A Particle Swarm Optimization Method for Spatial Clustering withObstacles Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367

Xueping Zhang, Jiayao Wang, Zhongshan Fan, and Xiaoqing Li

A PSO-Based Classification Rule Mining Algorithm . . . . . . . . . . . . . . . . . . 377Ziqiang Wang, Xia Sun, and Dexian Zhang

A Similarity Measure for Collaborative Filtering with ImplicitFeedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385

Tong Queue Lee, Young Park, and Yong-Tae Park

An Adaptive k -Nearest Neighbors Clustering Algorithm for ComplexDistribution Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398

Yan Zhang, Yan Jia, Xiaobin Huang, Bin Zhou, and Jian Gu

Defining a Set of Features Using Histogram Analysis for Content BasedImage Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408

Jongan Park, Nishat Ahmad, Gwangwon Kang, Jun H. Jo,Pankoo Kim, and Seungjin Park

Determine the Kernel Parameter of KFDA Using a Minimum SearchAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 418

Yong Xu, Chuancai Liu, and Chongyang Zhang

Hidden Markov Models with Multiple Observers . . . . . . . . . . . . . . . . . . . . . 427Hua Chen, Zhi Geng, and Jinzhu Jia

K-Distributions: A New Algorithm for Clustering Categorical Data . . . . . 436Zhihua Cai, Dianhong Wang, and Liangxiao Jiang

Page 16: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XIX

Key Point Based Data Analysis Technique . . . . . . . . . . . . . . . . . . . . . . . . . . 444Su Yang and Yong Zhang

Mining Customer Change Model Based on Swarm Intelligence . . . . . . . . . 456Peng Jin and Yunlong Zhu

New Classification Method Based on Support-Significant AssociationRules Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465

Guoxin Li and Wen Shi

Scaling Up the Accuracy of Bayesian Network Classifiers byM-Estimate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475

Liangxiao Jiang, Dianhong Wang, and Zhihua Cai

Similarity Computation of Fuzzy Membership Function Pairs withSimilarity Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485

Dong-hyuck Park, Sang H. Lee, Eui-Ho Song, and Daekeon Ahn

Spatial Selectivity Estimation Using Cumulative Density WaveletHistogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493

Byung Kyu Cho

Artificial Life and Artificial Immune Systems

Image Segmentation Based on Chaos Immune Clone SelectionAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505

Junna Cheng, Guangrong Ji, and Chen Feng

Ensemble Methods

Research a Novel Integrated and Dynamic Multi-object Trade-OffMechanism in Software Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513

Weijin Jiang and Yuhui Xu

Manifold Learning Theory

A Swarm-Based Learning Method Inspired by Social Insects . . . . . . . . . . . 525Xiaoxian He, Yunlong Zhu, Kunyuan Hu, and Ben Niu

Evolutionary Computing and Genetic Algorithms

A Genetic Algorithm for Shortest Path Motion Problem in ThreeDimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 534

Marzio Pennisi, Francesco Pappalardo, Alfredo Motta, andAlessandro Cincotti

Page 17: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XX Table of Contents

A Hybrid Electromagnetism-Like Algorithm for Single MachineScheduling Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543

Shih-Hsin Chen, Pei-Chann Chang, Chien-Lung Chan, and V. Mani

A Self-adaptive Evolutionary Algorithm for Multi-objectiveOptimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553

Ruifen Cao, Guoli Li, and Yican Wu

An Adaptive Immune Genetic Algorithm for Edge Detection . . . . . . . . . . 565Ying Li, Bendu Bai, and Yanning Zhang

An Improved Nested Partitions Algorithm Based on SimulatedAnnealing in Complex Decision Problem Optimization . . . . . . . . . . . . . . . . 572

Yan Luo and Changrui Yu

DE and NLP Based QPLS Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 584Xiaodong Yu, Dexian Huang, Xiong Wang, and Bo Liu

Fuzzy Genetic Algorithm Based on Principal Operation and InequityDegree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593

Fachao Li and Chenxia Jin

Immunity-Based Adaptive Genetic Algorithm for Multi-robotCooperative Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605

Xin Ma, Qin Zhang, Weidong Chen, and Yibin Li

Improved Genetic Algorithms to Fuzzy Bimatrix Game . . . . . . . . . . . . . . . 617RuiJiang Wang, Jia Jiang, and XiaoXia Zhu

K⊕

1 Composite Genetic Algorithm and Its Properties . . . . . . . . . . . . . . . 629Fachao Li and Limin Liu

Parameter Tuning for Buck Converters Using Genetic Algorithms . . . . . . 641Young-Kiu Choi and Byung-Wook Jung

Research a New Dynamic Clustering Algorithm Based on GeneticImmunity Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 648

Yuhui Xu and Weijin Jiang

Fuzzy Systems and Soft Computing

Applying Hybrid Neural Fuzzy System to Embedded SystemHardware/Software Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 660

Yue Huang and YongSoo Kim

Design of Manufacturing Cells for Uncertain Production Requirementswith Presence of Routing Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 670

Ozgur Eski and Irem Ozkarahan

Page 18: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XXI

Developing a Negotiation Mechanism for Agent-Based Scheduling ViaFuzzy Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 682

K. Robert Lai, Menq-Wen Lin, and Bo-Ruei Kao

Lyapunov Stability of Fuzzy Discrete Event Systems . . . . . . . . . . . . . . . . . . 693Fuchun Liu and Daowen Qiu

Managing Target Cash Balance in Construction Firms Using NovelFuzzy Regression Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 702

Chung-Fah Huang, Morris H.L. Wang, and Cheng-Wu Chen

Medical Diagnosis System of Breast Cancer Using FCM Based ParallelNeural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 712

Sang-Hyun Hwang, Dongwon Kim, Tae-Koo Kang, andGwi-Tae Park

Optimal Sizing of Energy Storage System in Solar Energy ElectricVehicle Using Genetic Algorithm and Neural Network . . . . . . . . . . . . . . . . 720

Shiqiong Zhou, Longyun Kang, MiaoMiao Cheng, and Binggang Cao

Research on Error Compensation for Oil Drilling Angle Based onANFIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 730

Fan Li, Liyan Wang, and Jianhui Zhao

Rough Set Theory of Shape Perception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 738Andrzej W. Przybyszewski

Stability Analysis for Floating Structures Using T-S Fuzzy Control . . . . . 750Chen-Yuan Chen, Cheng-Wu Chen, Ken Yeh, and Chun-Pin Tseng

Uncertainty Measures of Roughness of Knowledge and Rough Sets inOrdered Information Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 759

Wei-Hua Xu, Hong-zhi Yang, and Wen-Xiu Zhang

Particle Swarm Optimization and Niche Technology

Particle Swarm Optimization with Dynamic Step Length . . . . . . . . . . . . . . 770Zhihua Cui, Xingjuan Cai, Jianchao Zeng, and Guoji Sun

Stability Analysis of Particle Swarm Optimization . . . . . . . . . . . . . . . . . . . 781Jinxing Liu, Huanbin Liu, and Wenhao Shen

Swarm Intelligence and Optimization

A Novel Discrete Particle Swarm Optimization Based on Estimation ofDistribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 791

Jiahai Wang

Page 19: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XXII Table of Contents

An Improved Particle Swarm Optimization for Traveling SalesmanProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 803

Xinmei Liu, Jinrong Su, and Yan Han

An Improved Swarm Intelligence Algorithm for Solving TSPProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 813

Yong-Qin Tao, Du-Wu Cui, Xiang-Lin Miao, and Hao Chen

MAS Equipped with Ant Colony Applied into Dynamic Job ShopScheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 823

Kai Kang, Ren feng Zhang, and Yan qing Yang

Optimizing the Selection of Partners in Collaborative OperationNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 836

Kai Kang, Jing Zhang, and Baoshan Xu

Quantum-Behaved Particle Swarm Optimization with GeneralizedLocal Search Operator for Global Optimization . . . . . . . . . . . . . . . . . . . . . . 851

Jiahai Wang and Yalan Zhou

Kernel Methods and Support Vector Machines

Kernel Difference-Weighted k-Nearest Neighbors Classification . . . . . . . . . 861Wangmeng Zuo, Kuanquan Wang, Hongzhi Zhang, and David Zhang

Novel Design of Decision-Tree-Based Support Vector MachinesMulti-class Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871

Liaoying Zhao, Xiaorun Li, and Guangzhou Zhao

Tuning Kernel Parameters with Different Gabor Features for FaceRecognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 881

Linlin Shen, Zhen Ji, and Li Bai

Two Multi-class Lagrangian Support Vector Machine Algorithms . . . . . . . 891Hua Duan, Quanchang Liu, Guoping He, and Qingtian Zeng

Fine Feature Extraction Methods

Research on On-Line Modeling of Fed-Batch Fermentation ProcessBased on v-SVR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 900

Yongjun Ma

Kernel Generalized Foley-Sammon Transform with Cluster-Weighted . . . 909Zhenzhou Chen

Supervised Information Feature Compression Algorithm Based onDivergence Criterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 919

Shiei Ding, Wei Ning, Fengxiang Jin, Shixiong Xia, and Zhongzhi Shi

Page 20: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XXIII

The New Graphical Features of Star Plot for K Nearest NeighborClassifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 926

Jinjia Wang, Wenxue Hong, and Xin Li

Intelligent Fault Diagnosis

A Mixed Algorithm of PCA and LDA for Fault Diagnosis of InductionMotor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 934

Wook Je Park, Sang H. Lee, Won Kyung Joo, and Jung Il Song

A Test Theory of the Model-Based Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . 943XueNong Zhang, YunFei Jiang, and AiXiang Chen

Bearing Diagnosis Using Time-Domain Features and Decision Tree . . . . . 952Hong-Hee Lee, Ngoc-Tu Nguyen, and Jeong-Min Kwon

CMAC Neural Network Application on Lead-Acid Batteries ResidualCapacity Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 961

Chin-Pao Hung and Kuei-Hsiang Chao

Diagnosing a System with Value-Based Reasoning . . . . . . . . . . . . . . . . . . . . 971XueNong Zhang, YunFei Jiang, and AiXiang Chen

Modeling Dependability of Dynamic Computing Systems . . . . . . . . . . . . . . 982Salvatore Distefano and Antonio Puliafito

Particle Swarm Trained Neural Network for Fault Diagnosis ofTransformers by Acoustic Emission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 992

Cheng-Chien Kuo

Prediction of Chatter in Machining Process Based on HybridSOM-DHMM Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1004

Jing Kang, Chang-jian Feng, Qiang Shao, and Hong-ying Hu

Research of the Fault Diagnosis Method for the Thruster of AUVBased on Information Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1014

Yu-Jia Wang, Ming-Jun Zhang, and Juan Wu

Synthesized Fault Diagnosis Method Based on Fuzzy Logic and D-SEvidence Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1024

Guang Yang and Xiaoping Wu

Test Scheduling for Core-Based SOCs Using Genetic Algorithm BasedHeuristic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1032

Chandan Giri, Soumojit Sarkar, and Santanu Chattopadhyay

The Design of Finite State Machine for Asynchronous ReplicationProtocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1042

Yanlong Wang, Zhanhuai Li, Wei Lin, Minglei Hei, and Jianhua Hao

Page 21: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XXIV Table of Contents

Unbalanced Underground Distribution Systems Fault Detection andSection Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1054

Karen Rezende Caino de Oliveira, Rodrigo Hartstein Salim,Andre Daros Filomena, Mariana Resener, and Arturo Suman Bretas

Fuzzy Control

Stability Analysis and Synthesis of Robust Fuzzy Systems with Stateand Input Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1066

Xiaoguang Yang, Li Li, Qingling Zhang, Xiaodong Liu, andQuanying Zhu

Intelligent Human-Computer Interactions forMulti-modal and Autonomous Environment

Biometric User Authentication Based on 3D Face Recognition UnderUbiquitous Computing Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1076

Hyeonjoon Moon and Taehwa Hong

Score Normalization Technique for Text-Prompted Speaker Verificationwith Chinese Digits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1082

Jing Li, Yuan Dong, Chengyu Dong, and Haila Wang

Computational Systems Biology

Identifying Modules in Complex Networks by a Graph-TheoreticalMethod and Its Application in Protein Interaction Networks . . . . . . . . . . . 1090

Rui-Sheng Wang, Shihua Zhang, Xiang-Sun Zhang, andLuonan Chen

Intelligent Robot Systems Based on VisionTechnology

Autonomous Kinematic Calibration of the Robot Manipulator with aLinear Laser-Vision Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1102

Hee-Jun Kang, Jeong-Woo Jeong, Sung-Weon Shin,Young-Soo Suh, and Young-Schick Ro

Intelligent Computing for Motion Picture Processing

Robust Human Face Detection for Moving Pictures Based onCascade-Typed Hybrid Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1110

Phuong-Trinh Pham-Ngoc, Tae-Ho Kim, and Kang-Hyun Jo

Page 22: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XXV

Particle Swarm Optimization: Theories andApplications

Multimodality Image Registration by Particle Swarm Optimization ofMutual Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1120

Qi Li and Isao Sato

Multiobjective Constriction Particle Swarm Optimization and ItsPerformance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1131

Yifeng Niu and Lincheng Shen

Recent Advances of Intelligent Computing withApplications in the Multimedia Systems

An Intelligent Fingerprint-Biometric Image Scrambling Scheme . . . . . . . . 1141Muhammad Khurram Khan and Jiashu Zhang

Reversible Data Hiding Based on Histogram . . . . . . . . . . . . . . . . . . . . . . . . . 1152Wen-Chung Kuo, Dong-Jin Jiang, and Yu-Chih Huang

Computational Intelligence in Chemoinformatics

Evolutionary Ensemble for In Silico Prediction of Ames TestMutagenicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1162

Huanhuan Chen and Xin Yao

Parallel Filter: A Visual Classifier Based on Parallel Coordinates andMultivariate Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1172

Yonghong Xu, Wenxue Hong, Na Chen, Xin Li, WenYuan Liu, andTao Zhang

Strategy Design and Optimization of ComplexEngineering Problems

Constrained Nonlinear State Estimation – A Differential EvolutionBased Moving Horizon Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1184

Yudong Wang, Jingchun Wang, and Bo Liu

Multi-agent Optimization Design for Multi-resource Job ShopScheduling Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193

Fan Xue and Wei Fan

Multi-units Unified Process Optimization Under Uncertainty Based onDifferential Evolution with Hypothesis Test . . . . . . . . . . . . . . . . . . . . . . . . . 1205

Wenxiang Lv, Bin Qian, Dexian Huang, and Yihui Jin

Page 23: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

XXVI Table of Contents

Traffic Optimization

An Angle-Based Crossover Tabu Search for Vehicle Routing Problem . . . 1215Ning Yang, Ping Li, and Mingsen Li

Intelligent Mobile and Wireless Sensor Networks

Saturation Throughput Analysis of IEEE 802.11e EDCA . . . . . . . . . . . . . . 1223Yutae Lee, Kye-Sang Lee, and Jong Min Jang

Intelligent Prediction and Time Series Analysis

A Wavelet Neural Network Optimal Control Model for Traffic-FlowPrediction in Intelligent Transport Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 1233

Darong Huang and Xing-rong Bai

Conditional Density Estimation with HMM Based Support VectorMachines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1245

Fasheng Hu, Zhenqiu Liu, Chunxin Jia, and Dechang Chen

Estimating Selectivity for Current Query of Moving Objects UsingIndex-Based Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1255

Jeong Hee Chi and Sang Ho Kim

Forecasting Approach Using Hybrid Model ASVR/NGARCH withQuantum Minimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1265

Bao Rong Chang and Hsiu Fen Tsai

Forecasting of Market Clearing Price by Using GA Based NeuralNetwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1278

Bo Yang, Yun-ping Chen, Zun-lian Zhao, and Qi-ye Han

A Difference Scheme for the Camassa-Holm Equation . . . . . . . . . . . . . . . . . 1287Ahamed Adam Abdelgadir, Yang-xin Yao, Yi-ping Fu, andPing Huang

Research on Design of a Planar Hybrid Actuator Based on a HybridAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1296

Ke Zhang

Network Traffic Prediction and Applications Based on Time SeriesModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1306

Jun Lv, Xing Li, and Tong Li

On Approach of Intelligent Soft Computing for Variables Estimate ofProcess Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1316

Zaiwen Liu, Xiaoyi Wang, and Lifeng Cui

Page 24: Lecture Notes in Artificial Intelligence 4682 - Springer978-3-540-74205-0/1.pdf · Lecture Notes in Artificial Intelligence 4682 Edited by J.G. Carbonell and J. Siekmann Subseries

Table of Contents XXVII

ICA Based on KPCA and Hierarchical RBF Network for FaceRecognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1327

Jin Zhou, Haokui Tang, and Weidong Zhou

Intelligent Computing in Neuroinformatics

Long-Range Temporal Correlations in the Spontaneous in vivo Activityof Interneuron in the Mouse Hippocampus . . . . . . . . . . . . . . . . . . . . . . . . . . 1339

Sheng-Bo Guo, Ying Wang, Xing Yan, Longnian Lin,Joe Tsien, and De-Shuang Huang

Implementation and Performance Analysis of Noncoherent UWBTransceiver Under LOS Residential Channel Environment . . . . . . . . . . . . . 1345

Sungsoo Choi, Insoo Koo, and Youngsun Kim

MemoPA: Intelligent Personal Assistant Agents with a Case MemoryMechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1357

Ke-Jia Chen and Jean-Paul Barthes

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1369

Erratum

E1Choices of Interacting Positions on Multiple Team Assembly . . . . . . . . . .Chartchai Leenawong and Nisakorn Wattanasiripong


Recommended