Lecture Notes in Artificial Intelligence 2774 Edited by J. G. Carbonell and J. Siekmann

Subseries of Lecture Notes in Computer Science

Vasile Palade Robert J. Howlett Lakhrni Jain (Eds.)

dge-Based ent Information

and Engineering Systems

7th International Conference, KES 2003 Oxford, UK, September 3-5,2003 Proceedings, Part I1

Springer

Series Editors

Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jorg Siekmann, University of Saarland, Saarbriicken, Germany

Volume Editors

Vasile Palade Oxford University, Computing Laboratory Parks Road, Oxford OX1 3QD, United Kingdom E-mail: vasile.palade@comlab.ox.ac.uk Robert 3. Howlett University of Brighton, Intelligent Systems and Signal Processing Labs Moulsecoomb, Brighton BN2 4GJ, United Kingdom E-mail: r.j.howlett@brighton.ac.uk

Lakhmi Jain University of South Auswalia Knowledge-Based Intelligent Engineering Systems Centre Mawson Lakes, Adelaide, SA 5095, Australia E-mail: lakhmi.jain@unisa.edu.au

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Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliographie; detailed bibliographic data is available in the Internet at <http://dnd.ddb.de>.

CR Subject Classification (1998): 1.2, H.4, H.3, E l , J.l, (2.2, H.5, K.6, K.4

ISSN 0302-9743 ISBN 3-540-40804-5 Springer-Verlag Berlin Heidelberg New York

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Preface

Delegates and friends, I am very pleased to extend to you the warmest of wel- comes to this, the seventh International Conference on I(now1edge-Based Intel- ligent Information and Engineering Systems at the University of Oxford in the UK. It was a great pleasure to be involved in the organization of this popular conference, and it gives us a great deal of satisfaction to be so involved.

The KES conference series is now well established, and it continues each year to attract participants from all geographical areas of the world, including Europe, the Americas, Australasia, and the Pacific Rim. The conference continues to attract large numbers of papers. We are impressed this year by the quality of the papers we have received and the wide range of topics. I am sure that the presentations will be of great interest to you as delegates, and will act as useful catalysts for discussion.

The papers for KES 2003 were either submitted to Invited Sessions, chaired and organized by respected experts in their fields, or to General Sessions, man- aged by an extensive International Program Committee. Whichever route they came through, all papers for KES 2003 were thoroughly reviewed. This has re- sulted in a satisfying level of quality in the accepted papers appearing in the proceedings.

Thanks are due to very many people who have given their time and goodwill freely to male the conference a success. Thanking individuals is always fraught with difficulty, as someone is always unintentionally omitted. The conference Administrator, Maria Booth, the ICES Secretariat at the University of Brighton, together with the local Oxford Committee have all worked hard to bring the conference to a high level of organization, and we thank them. The Interna- tional Program Committee gave their expertise in the review of the papers and we are grateful for that. We particularly thank the Invited Session Chairs Com- mittee for bringing many interesting sessions to the conference. We thank the keynote speakers for their high-profile keynote talks. Finally, we thank the au- thors, presenters, and delegates without whom the conference would not take place.

Knowledge-based intelligent engineering systems continue to be a subject that attracts the interest of researchers, and makes a significant contribution to the world economy. We are fortunate to be involved in such a fascinating research area. Enjoy your conference, and we loolc forward to meeting you and talking with you.

July 2003 Vasile Palade, Bob Howlett, and Lakhmi Jain

KES 2003 Conference Organization

General Chair

Vasile Palade Computing Laboratory, Oxford University, UI<

Honorary Founder Chair

Lalchmi Jain Knowledge-Based Intelligent Information Engineering Systems Centre, University of South Australia, Australia

Executive Chair

Bob Howlett Intelligent Systems and Signal Processing Laboratories / KTP Centre, University of Brighton, UK

Administration

Conference Administrator

M. Booth, University of Brighton, UK

KES Journal General Editor

B. Gabrys, University of Bournemouth, UK

Conference Liaison

S.D.Walters, University of Brighton, UK

Local Organizing Committee

K. Chinnasarn, S. Moyle, S. Rodtook, A. Srinivasan, J.Z. Suklcarieh Oxford University, UK

Organization VII

International Program Committee

Ajith Abraham, Oklahoma State University, USA Uwe Aicltelin, University of Bradford, UK Norio Baba, Osalta-Kyoiltu University, Japan Robert Babuska, Delft University of Technology, The Netherlands Andrzej Bargiela, Nottingham Trent University, UK Severin Bumbaru, University of Galati, Romania Jonathon Chambers, Icing's College London, UK Susan Craw, Robert Gordon University, Aberdeen, UK Ernesto Damiani, University of Milan, Italy Manuel Fernandez Delgado, University of Santiago de Compostela, Spain Vladan Devedzic, University of Belgrade, Serbia and Montenegro Didier Dubois, Universite Paul Sabatier, Toulouse, France Anna Maria Fanelli, University of Bari, Italy Colette Faucher, University of Aix-Marseille 111, France Toshio Fukuda, Nagoya University, Japan Kunihiko Fukushima, Tolcyo University of Technology, Japan Colin Fyfe, University of Paisley, UK Bogdan Gabrys, University of Bournemouth, UK Joydeep Ghosh, University of Texas, Austin, USA Marlt Girolami, University of Paisley, UK Adolf Grauel, University of Applied Sciences, Germany Altay Giivenir, Bilkent University of Ankara, Turkey Susan Haller, University of Wisconsin - Parkside, USA Robert F. Harrison, University of Sheffield, UK Ioannis Hatzilygeroudis, University of Patras, Greece Altira Hirose, University of Tokyo, Japan Nikhil Ichalkaranje, University of South Australia, Adelaide, Australia Taltumi Ichimura, Hiroshima City University, Japan Hisao Ishibuchi, Osaka Prefecture University, Japan Yoshiteru Ishida, Toyohashi University of Technology, Japan Naohiro Ishii, Nagoya Institute of Technology, Japan Janusz Kacprzylc, Polish Academy of Sciences, Poland Falthri Karray, University of Waterloo, Canada Ron Kates, REK Consulting, Germany Piet Kommers, University of Twente, The Netherlands Andreas Konig, University of Dresden, Germany Ludmilla I. Kuncheva, University of Wales Bangor, UK Beatrice Lazzerini, University of Pisa, Italy C.P. Lim, University of Science, Malaysia Vincenzo Loia, University of Salerno, Italy Donald MacDonald, University of Paisley, UK Nadia Magnenat-Thalmann, University of Geneva, Switzerland Manuel Mora, Universidad Autonoma de Aguascalientes, Mexico Steve Moyle, Oxford University, UK

VIII Organization

Jun Munemori, Walayama University, Japan Hirofumi Nagashino, University of Tokushima, Japan Zensho Nakao, University of the Ryukyus, Japan Daniel Neagu, University of Bradford, UK Mircea Gh. Negoita, Wellington Institute of Technology, New Zealand Toyoalti Nishida, University of Tokyo, Japan Vesa A. Nislanen, University of Helsinki, Finland Nilrhil R. Pal, Indian Statistical Institute, Calcutta, India Ron J. Patton, University of Hull, UK Witold Pedrycz, University of Alberta, Canada Vincenzo Piuri, Politecnico di Milano, Italy Bhanu Prassad, Georgia South-Western State University, USA Bernd Reusch, University of Dortmund, Germany Raj kumar Roy, Cranfield University, UK Marco Russo, University of Messina, Italy David Sanchez, Neurocomputing, Elsevier, USA Manfred Schmitt, Technical University of Munich, Germany Jonathan Shapiro, University of Manchester, UK Clarence W. de Silva, University of British Columbia, Canada Ashwin Srinivasan, Oxford University, UK Maria Taboada, University of Santiago de Compostela, Spain Katsumi Tanaka, Kyoto University, Japan Lionel Tarassenko, Oxford University, UK Eiichiro Tazalti, Toin University of Yolohama, Japan George Tecuci, George Mason University, USA Horia-Nicolai Teodorescu, Technical University of Iasi, Romania Shusalru Tsumoto, Shimane Medical University, Japan Dan Tufis, Artificial Intelligence Institute, Romanian Academy,

Bucharest, Romania Spyros Tzafestas, Technical University of Athens, Greece Rao Vemuri, University of California at Davis, USA Jose Verdegay, University of Granada, Spain Rob Vingerhoeds, ENIT, France Simon D. Walters, University of Brighton, UK Graham Winstanley, University of Brighton, UK Xindong Wu, University of Vermont, USA

Organization IX

Invited Session Chairs Committee

Norio Baba, Osalta-Kyoiltu University, Japan Marina Resta, University of Genova, Italy Hirotaka Nakayama, Konan University, Japan Seiichi Ozawa, Kobe University, Japan Yasue Mitsultura, Okayama University, Japan Minoru Fukumi, University of Toltushima, Japan Fumialti Takeda, Kochi University of Technology, Japan Javier Carbo, University Carlos 111 of Madrid, Spain Julio C. Hernandez, University Carlos I11 of Madrid, Spain Giovanna Castellano, University of Bari, Italy Ciro Castiello, University of Bari, Italy Corrado Mencar, University of Bari, Italy Chuei-Tin Chang, National Cheng Kung University Tainan, Taiwan Jonathon Chambers, King's College London, UK Andreas Jaltobsson, King's College London, UK Massimo Cossentino, National Research Council, Italy Antonio Chella, University of Palermo, Italy Yen-Wei Chen, Ryultyus University, Japan t

Antonio Fernandez-Caballero, University of Castilla-La Mancha, Spain Manuel Fernandez Delgado, University of Santiago de Compostela, Spain Guissepi Forgionne, University of Maryland Baltimore County, USA Manuel Mora, Universidad Autonoma de Aguascalientes, Mexico Jatinger N.D. Gupta, University of Alabama at Huntsville, USA Kunihilto Fukushima, Tokyo University of Technology, Japan Claude Ghaoui, Liverpool John Moores University, UK Ugur Halici, Middle East Technical University, Turkey Ioannis Hatzilygeroudis, University of Patras, Greece Altira Hirose, University of Tolyo, Japan Talcumi Ichimura, Hiroshima City University, Japan Katsumi Yoshida, St. Marianna University, Japan Masahito Aoyama, Hiroshima City University, Japan Toshiyulti Yamashita, Tolyo Metropolitan Institute of Technology, Japan Yoshiteru Ishida, Toyohashi University of Technology, Japan Naohiro Ishii, Nagoya Institute of Technology, Japan Yoshinori Adachi, Chubu University, Japan Takamasa Koshizen, Honda R&D Co. Ltd., Wako Research Center, Japan Beatrice Lazzerini, University of Pisa, Italy Francesco Mascelloni, University of Pisa, Italy Kim Le, University of Canberra, Australia Laurent Lecornu, ENST Bretagne, Fsance Renaud Debon, ENST Bretagne, France Igiiac Lovrelt, University of Zagreb, Croatia Frank Lui, Defence Science and Technology Organization, Australia Nilthil Ichallcaranje, University of South Australia, Adelaide, Australia

X Organization

Jun Munemori, Walayama University, Japan Takashi Yoshino, Walayama University, Japan Talaya Yuizono, Shimane University, Japan Hirofumi Nagashino, University of Tokushima, Japan Abhijit S. Pandhya, Florida Atlantic University, USA Norilco Nagata, Kwansei Gakuin University, Japan Hiroyasu Koshimizu, Chulcyo University, Japan Seiji Inokuchi, Osaka University, Japan Ryohei Nakatsu, Kwansei Galcuin University, Japan Daniel Neagu, University of Bradford, UK Vasile Palade, Oxford University, UK Mircea Gh. Negoita, Wellington Institute of Technology, New Zealand Nengsheng Zhang, Institute of Manufacturing Technology, Singapore Kamal Youcef-Toumi, Massachusetts Institute of Technology, USA Weng-Feng Lu, Institute of Manufacturing Technology, Singapore Toyoalti Nishida, University of Tokyo, Japan Alain Cardon, University of Le Havre, France Rancisco Javier Ropero-Pelaez, University of Sao Paolo, Brazil Roberto Pirrone, University of Palermo, Italy Rancesco Alonge, University of Palermo, Italy Vincenzo Piuri, University of Milan, Italy Alberto Borghese, University of Milan, Italy Stefano Ferrari, University of Milan, Italy Cristina Segal, University of Galati, Romania Luminita Dumitriu, University of Galati, Romania Udo Seiffert, Leibniz Institute of Plant Genetics, Gatersleben, Germany Lalchmi Jain, University of South Australia, Adelaide, Australia Konstantinos Sirlantzis, University of Kent, UK Michael Fairhurst, University of Kent, UK Maria Taboada, University of Santiago de Compostela, Spain Ian Duncan, Lotter Actuarial Partners, New York, USA Yoshiyasu Talcefuji, Keio University, Japan Eiichiro Tazaki, University of Yokohama, Japan Kenneth J. Mackin, Tokyo University of Information Sciences, Japan Georgia Tourassi, Duke University, USA Kazuhiko Tsuda, University of Tsukuba, Tokyo, Japan Claudio Turchetti, University of Ancona, Italy

Organization XI

KES 2003 Reviewers

A. Abraham, Oklahoma State University, USA Y . Adachi, Chubu University, Japan U. Aickelin, University of Bradford, UK H. Ahriz, The Robert Gordon University, Aberdeen, UK M. Aoyama, Hiroshima City University, Japan E. Ardizzone, University of Palermo, Italy D. Arita, Kyushu University, Japan V. Ariton, Danubius University, Romania M.R. Asharif, Ryukyus University, Japan U. Averweg, Government Staff, South Africa N. Baba, Osaka-Kyoiku University, Japan N. Babaguchi, Osaka University, Japan R. Babusla, Delft University of Technology, The Netherlands L.A. Baccala, University of Sao Paolo, Brazil A. Badri, University of Liverpool, UK M. Barbulescu, George Mason University, USA A. Bargiela, Nottingham Trent University, UK B.L. Barranco, National Microelectronics Center, Seville, Spain C. Boicu, George Mason University, USA K. Bontcheva, University of Sheffield, UK P. Bresciani, ITC-irst, Italy S. Bumbaru, University of Galati, Romania K. Brian, Massachusetts Institute of Technology, USA M. Callisti, Whitestein Tecnologies AG, Germany J. Carbo, University Carlos I11 of Madrid, Spain G. Castellano, University of Bari, Italy C. Castiello, University of Bari, Italy J. Chambers, King's College London, UK C.-T. Chang, National Cheng Kung University, Taiwan A. Chella, University of Palermo, Italy C.-L. Chen, National Taiwan University, Taiwan Y.-W. Chen, Ryukyus University, Japan A. Christea, Eindhoven University of Technology, The Netherlands M. Cossentino, Italian National Research Council, Italy S. Craw, Robert Gordon University, Aberdeen, UK M. Cronin, Liverpool John Moores University, UK E. Damiani, University of Milan, Italy T. Deguchi, Gifu National College of Technology, Japan M.F. Delgado, University of Santiago de Compostela, Spain J. Dempster, University of Warwiclc, UK F. Deravi, University of Kent, UK V. Devedzic, University of Belgrade, Serbia and Montenegro F. J. Diez, UNED, Spain V. Dimitrova, University of Leeds, UK

XI1 Organization

P. Donzelli, Dept. for Innovation and Technologies of the Italian Gov., Italy D. Dubois, Universite Paul Sabatier, Toulouse, France P. Duggan, Liverpool John Moores University, UK L. Dumitriu, University of Galati, Romania A. Eales, Wellington Institute of Technology, New Zealand J . Eggert, Honda Research Institute Europe Inc., Germany M.C. Fairhurst, University of Kent, UK A.M. Fanelli, University of Bari, Italy C. Faucher, University of Aix-Marseille 111, France P. Felix, University of Santiago de Compostela, Spain G. Forgionne, University of Maryland Baltimore County, USA M. Frean, Victoria University of Wellington, New Zealand T. Fukuda, Nagoya University, Japan M. Fukumi, University of Tolrushima, Japan K. Fukushima, Tokyo University of Technology, Japan C. Fyfe, University of Paisley, UK B. Gabrys, University of Bournemouth, UK B. Garrett, Oxford Broolres University, UK L. Garrido, ITESM, Mexico A. Gelman, University of Arizona, USA C. Ghaoui, Liverpool John Moores University, UK D. Ghica, Oxford University, UK G. Gini, Politecnico di Milano, Italy P. Giorgini, University of Trento, Italy M. Girolami, University of Paisley, UK J. Goguen, University of California at San Diego, USA T.S. Gotarredona, National Microelectronics Center, Seville, Spain F. Grasso, University of Liverpool, UK A. Grauel, University of Applied Sciences, Germany J.N.D. Gupta, University of Alabama at Huntsville, USA A. Giivenir, Bilkent University of Ankara, Turkey S. Haller, University of Wisconsin - Parkside, USA A. Hara, Hiroshima City University, Japan R.F. Harrison, University of Sheffield, UK P. Hartono, Waseda University, Japan Y. Hasegawa, Honda Research Institute Japan Inc., Japan I, Hatzilygeroudis, University of Patras, Greece I. Hayashi, Hannan University, Japan N. Henze, University of Hanover, Germany 0. Herden, Horb University, Germany J.C. Hernandez, University Carlos I11 of Madrid, Spain A. Hirose, University of Tokyo, Japan S. Hoque, University of Kent, UK G. Howells, University of Kent, UK N. Ichalkaranje, University of South Australia, Adelaide, Australia

Organization XI11

T. Ichimura, Hiroshima City University, Japan S. Inokuchi, Osaka University, Japan N. Inuzuka, Nagoya Institute of Technology, Japan H. Ishibuchi, Osaka Prefecture University, Japan Y. Ishida, Toyohashi University of Technology, Japan N. Ishii, Nagoya Institute of Technology, Japan S. Ito, Japan Advanced Institute of Science and Technology, Japan Y. Ivanov, Honda Research Institute America Inc., USA M. Iwata, University of Electro-Communications, Japan L.C. Jain, University of South Australia, Adelaide, Australia A. Jakobsson, King's College London, UK S.-S. Jang, National Tsing Hua University, Taiwan W. Janvier, Liverpool John Moores University, UK B. Jayatilaka, Binghamton University, USA J. Kacprzyk, Polish Academy of Sciences, Poland K. Kakusho, Kyoto University, Japan R. Kates, REK Consulting, Germany H. Kawada, Nagoya Women's University, Japan M. Kilcuchi, Tokyo University of Technology, Japan Y. Kinouchi, University of Tolcushima, Japan F. Kirchner, Bremen University, Germany E. Koernar, Honda Research Institute Europe Inc. A. Konar, Jadavpur University Calcutta, India T. Kondo, University of Tolcushima, Japan A. Konig, University of Dresden, Germany H. Koshimizu, Chulyo University, Japan T. Koshizen, Honda R&D Co. Ltd., Walco Research Center, Japan L.I. Kuncheva, University of Wales Bangor, UK C. Kuroda, Tokyo Institute of Technology, Japan S. Kurohashi, University of Tokyo, Japan Y. Kurosawa, Hiroshima City University, Japan M. La Cascia, University of Palermo, Italy S. Lambotharan, King's College London, UK B. Lazzerini, University of Pisa, Italy P. Leng, University of Liverpool, UK C.P. Lim, University of Science, Malaysia J.A. Lopez-Alcantud, University of Murcia, Spain I. Lovrek, University of Zagreb, Croatia F. Lui, Defence Science and Technology Organization, Australia B. MacCallum, Stoclcholm University, Sweden D. MacDonald, University of Paisley, UK K.J. Maclcin, Tokyo University of Information Sciences, Japan N. Magnenat-Thalmann, University of Geneva, Switzerland F. Marcelloni, University of Pisa, Italy M. Marcos, University Jaume I, Spain

XIV Organization

D. Marcu, George Mason University, USA D. Martinez, University of Santiago de Compostela, Spain S. McKinlay, Wellington Institute of Technology, New Zealand C. Mencar, University of Bari, Italy K. Mera, Hiroshima City University, Japan E. Millan, University of Malaga, Spain M. Minoh, Kyoto University, Japan Y. Mitsukura, Okayama University, Japan T. Mizuno, Shizuola University, Japan M. Mora, Universidad Autonoma de Aguascalientes, Mexico Y. Moriya, Aichi Galcusen University, Japan S. Moyle, Oxford University, UK J . Munemori, Walayama University, Japan N. Nagata, Kwansei Galtuin University, Japan H. Nagashino, University of Tokushima, Japan Y. Nakamura, University of Tsulcuba, Japan Z. Nakao, Ryulcyus University, Japan H. Naltayama, Konan University, Japan U. Naomi, Nagoya University of Technology, Japan D. Neagu, University of Bradford, UK M. Gh. Negoita, Wellington Institute of Technology, New Zealand I. Nemoto, Tokyo Denlci University, Japan C. Ng, Yuan Ze University, Taiwan A. Niimi, Future University-Haltodate, Japan T. Nishida, University of Tokyo, Japan E. Nunohiro, Tokyo University of Information Sciences, Japan P. Nykanen, STAKES, Finland T. Ohnuki, Nagoya Institute of Technology, Japan S. Oeda, Tokyo Metropolitan Institute of Technology T. Olamoto, Kanagawa Institute of Technology, Japan S. Omatu, Osaka Prefecture University, Japan M. Ozaki, Chubu University, Japan S. Ozawa, Kobe University, Japan N.R. Pal, Indian Statistical Institute, Calcutta, India J.T. Palma, University of Murcia, Spain AS . Pandhya, Florida Atlantic University, USA E. Pecheanu, University of Galati, Romania W. Pedrycz, University of Alberta, Canada V. Piuri, Politecnico di Milano, Italy '

J . Pomylalslci, Susquehanna University, USA B. Prassad, Georgia South-Western State University, USA J. Prentzas, University of Patras, Greece G. Puscasu, University of Galati, Romania R.T. Ramos, University of Sao Paolo, Brazil E.M. Raybourn, Sandia National Labs, USA

Organization XV

H. Reichgelt, Georgia Southern University, USA M. Resta, University of Genova, Italy B. Reusch, University of Dortmund, Germany R.1. Rodriguez, University of Santiago de Compostela, Spain F.J. Ropero-Pelaez, University of Sao Paolo, Brazil I. Russell, University of Hartford, USA M. Russo, University of Messina, Italy L. Sabatucci, Italian National Research Council, Italy R. Saltamoto, Japan Advanced Institute of Science and Technology, Japan A. Sato, University of Tsukuba, Japan F. Sato, Shizuoka University, Japan S. Satoh, Toholtu University, Japan C. Segal, University of Galati, Romania J . Shapiro, University of Manchester, UK G. Siegle, University of Pittsburgh, USA J.M. Sierra, University Carlos 111 of Madrid, Spain K. Sirlantzis, University of Kent, UK S. Smith, Middlesex University, UK D. Spenneberg, Bremen University, Germany A. Srinivasan, Oxford University, UK A. Stam, University of Missouri, USA B. Stanescu, George Mason University, USA D. Stefanescu, University of Galati, Romania D. Stefanoiu, University of Applied Sciences, Konstanz, Germany M. Sulta, St. Marianna University, Japan M. Taboada, University of Santiago de Compostela, Spain T. Taguchi, Nagoya Women's University, Japan F. Talteda, Kochi University of Technology, Japan T. Tanala, Fultuolta Institute of Technology, Japan R. Taniguchi, Kyushu University, Japan S.F. Taniguchi, Albert Einstein Hospital School of Health, Sao Paolo, Brazil Y. Talama, Tokyo Metropolitan Institute of Technology, Japan A. Tay, Nanyang Technological University, Singapore E. Tazaki, University of Yokohama, Japan G. Tecuci, George Mason University, USA S. Thompson, BTexact Research, UK R.M. Tomas, National University of Distance Education, Spain H. Tsujino, Honda Research Institute Japan Inc., Japan N. Tsuruta, Fukuolta University, Japan D. Tufis, Artificial Intelligence Institute, Romanian Academy,

Bucharest, Romania J. Tweedale, Defence Science and Technology Organization, Australia K. Ueda, University of Tokyo, Japan H. Ukida, University of Toltushima, Japan P. Urlings, Defence Science and Technology Organization, Australia

XVI Organization

M. Usuki, Japan Advanced Institute of Science and Technology, Japan J . Verdegay, University of Granada, Spain R. Vemuri, University of California at Davis, USA R. Vingerhoeds, ENIT, France M. Virvou, University of Piraeus, Greece S. Vitabile, Italian National Research Council, Italy D. Vogel, Ross University, Dominica S.D. Walters, University of Brighton, UK J. Wang, Institute of Manufacturing Technology, Singapore Y. Watanabe, Toyohashi University of Technology, Japan G. Winstanley, University of Brighton, UK N. Wiratunga, The Robert Gordon University, Aberdeen, UK F. Wittig, University of Saarbrucken, Germany C.R. Wren, Mitsubishi Electric Research Laboratories, Japan G. Wren, University of Maryland Baltimore County, USA X. Wu, University of Vermont, USA K. Yamasaki, Tolryo University of Information Sciences, Japan K. Yamashita, Osaka Prefecture University, Japan T. Yamashita, Tolryo Metropolitan Institute of Technology, Japan Y. Yamashita, Tohoku University, Japan M. Yamura-Talrei, Hiroshima City University, Japan I<. Yoshida, St. Marianna University, Japan T. Yoshino, Walayama University, Japan T. Yuizono, Shimane University, Japan N. Zhang, Institute of Manufacturing Technology, Singapore

Table of Contents, Part I1

Advances on Adaptive Resonance Theory and Applications

Putting the Utility of Match Tracking in Fuzzy ARTMAP Training to the Test Georgios C. Anagnostopoulos and Michael Georgiopoulos . . . . . . . . . . . . . . . . . . . . 1

An ART-Based Hybrid Networlc for Medical Pattern Classification Taslts with Missing Data Chee Peng Lim, Mei Ming Kuan, and Robert F. Harrison.. . . . . . . . . . . . . . . . . . 7

Combining Support Vector Machines and ARTMAP Architectures for Natural Classification

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alberto Mufioz and Javier M , Moguerza.. 16

ART-Based Neuro-fuzzy Modelling Applied to Reinforcement Learning Konstantinos C. Zikidis and Spyros G. Tzafestas . . . . . . . . . . . . . . . . . . . . . . . . . . 22

AFC: ART-Based Fuzzy Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena P. Sapozhnikova and Wolfgang Rosenstiel 30

Intelligent Decision Support Malcing Systems

Intelligent Assistance, Retrieval, Reminder and Advice for Fuzzy Multicriteria Decision-Malting

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jocelyn Sun Pedro and Frada Burstein 37

Facilitating Electronic Business Planning with Decision Malcing Support Systems Lidan Ha, Guisseppi Forgionne, and Fen Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Critical Context for Decision Malcing: A Modeling Approach Based on a Re-planning Tool

. . . . . . . . . . . . . . . . . . . . . . Guy Camilleri, Jean-Luc Soubie, and Pascale Zaratk. 52

A Framework to Assess Intelligent Decision-Making Support Systems M. Mora, G. Forgionne, J. Gupta, F. Cervantes, and 0. Gelman . . . . . . . . . . 59

An Information Market for Multi-agent Decision Making: Observations from a Human Experiment Bartel Van de Walle and Mihai Moldovan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

XVIII Table of Contents, Part I1

Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis Serafeim Fragos, Lampros K . Stergioulas, and Costas S . Xydeas.. . . . . . . . . . . 73

Design, Integration and Evaluation of an Artificial Intelligence-Based Control System for the Improvement of the Monitoring and Quality Control Process in the Manufacturing of Metal Casting Components Emma L. Mares and Jerry H. Sokolowski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Developing Intelligent Decision Support Systems: A Bipartite Approach Alexandre Gachet and Pius Haettenschwiler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Fuzzy Support Systems for Discretionary Judicial Decision Malting Felipe Lara-Rosano and Maria del Socorro Tkllez-Silva . . . . . . . . . . . . . . . . . . . . . 94

Intelligent Decision Malting Support through Just-in-Time Knowledge Management Nabie Y. Conteh and Guisseppi Forgionne.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Integrating Simulation and Argumentation in Organizational Decision Malting Nikos Karacapilidis and Emmanuel Adamides, . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Neura l Networks for Vision - Biological a n d Artificial

Perceptual Grouping to Motion Direction and Speed in Apertures Isao Hayashi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

Assignment of Figural Side to Contours Based on Symmetry, Parallelism, and Convexity Masayuki Kikuchi and Kunihiko Fukushima.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

Neural Network Model Restoring Partly Occluded Patterns Kunihiko Fukushima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

Face Localization in the Neural Abstraction Pyramid Sven Behnke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

A Model for Selective Visual Attention Based on Discrete Scale-Spaces Shunji Satoh and Shogo Miyalce.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

A Trainable Object-Detection Method Using Equivalent Retinotopical Sampling and Fisher Kernel Hirotaka Niitsuma.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

Self-organizing Feature Maps for HMM Based Lip-Reading Naoyuki Tsuruta, Hirotaka Iuchi, Alaa El. Sagheer, and Tarek El. Tobely . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

Table of Contents, Part I1 XIX

A Convolutional Neural Network VLSI for Image Recognition Using MergedIMixed Analog-Digital Architecture I{eisuke Korekado, Takashi Morie, Osamu Nomura, Hiroshi Ando,

. . . . . . . . . . . . . . . . . . . Teppei Nakano, Masakazu Matsugu, and Atsushi Iwata 169

Promot ing S m a r t User-Centred Approaches in Innovative Teaching a n d Learning

Making Intelligent Learning Technologies Meaningful: Practical Lessons Learnt from Public Administration Training Programs in South Africa and Canada

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Albert A. Einsiedel, Jr.. 177

Using Communication Preference and Mapping Learning Styles to Teaching Styles in the Distance Learning Intelligent Tutoring System - WISDeM

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . William A. Janvier and Claude Ghaoui.. 185

Evaluation of Discussions in Online Classrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . Aiman Badri, Floriana Grasso, and Paul Leng 193

Web-Based Synchronized Multimedia System Design for TeachingILearning Chinese as a Foreign Language

. . . . . . . . . . . . . . . . . . . . . . . Natalius Huang, Herng- Yow Chen, and R. C. T. Lee 201

An Integrated Courseware Usability Evaluation Method Maria Alexandra Rentroia-Bonito and Joaquim Armando Pires Jorge . . . . . 208

opment of a Level-Based Instruction Model b-Based Education

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . njung Park and Maenghee Kim 215

chniques i n Web-Based Educational Systems

Fuzzy Techniques to Model Students b-Based Learning Environments

. . . . . . . . . . . . . . . . . . . . . . . . . Kosba, Vania Dimitrova, and Roger Boyle 222

of Conceptual Graphs for Interactive Student Modelling aptive Web Explanations

Dimitrova and Kalina Bontcheva.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230

ting Collaborative Knowledge Building with Intelligent Agents Chen, Jan Dolonen, and Barbara Wasson.. . . . . . . . . . . . . . . . . . . . . . . . 238

ersonalised Recommendations ed Education System

O'Riordan and Josephine Grifith.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245

XX Table of Contents, Part I1

A Rule-Based Formalism for Describing Collaborative Adaptive Courses Rosa M. Carro, Alvaro Ortigosa, and Johann Schlichter . . . . . . . . . . . . . . . . . . 252

User Modeling on Adaptive Web-Based Learning Communities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Gaudioso and Jesus G. Boticario.. 260

Preventing Student Dropout in Distance Learning Using Machine Learning Techniques S.B. Kotsiantis, C.J. Pierrakeas, and P.E. Pintelas.. . . . . . . . . . . . . . . . . . . . . . 267

Evaluation of an Intelligent Web-Based Language Tutor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Victoria Tsiriga and Maria Virvou 275

Domain Knowledge Acquisition and Plan Recognition by Probabilistic Reasoning Manolis Maragoudakis, Aristomenis Thanopoulos, Kyriakos Sgarbas,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Nikos Fakotakis 282

Web Based Education as a Result of A1 Supported Classroom Teaching Gerald Friedland, Lars Knipping, Radl Rojas, and Ernesto Tapia . . . . . . . . . 290

From Web-Based Educational Systems to Education on the Web: On the Road to the Adaptive Web

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nicola Henze 297

Complex-Valued Neural Networks

Qubit Neural Networlc and Its Efficiency Noriaki Kouda, Nobuyuki Matsui, Haruhiko Nishimura,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Ferdinand Peper 304

Performance of Adaptive Beamforming by Using Complex-Valued Neural Network

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andriyan Bayu Suksmono and Akira Hirose 311

Quaternion Neural Network and Its Application Teijiro Isokawa, Tomoaki Kusakabe, Nobuyuki Matsui,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Ferdinand Peper 318

Building Up of a Pen Oriented Human-Software Interface with Complex-Valued Spiking Machines A. Ardouin, N. Brouard, C. Moreau, R. Plouvier, S. Rouchy, and G. Vaucher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325

Pitch-Asynchronous Overlap-Add Waveform-Concatenation Speech Synthesis by Using a Phase-Optimizing Neural Network Keiichi Tsuda and Akira Hirose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332

Table of Contents, Part I1 XXI

A Data-Reusing Gradient Descent Algorithm for Complex-Valued Recurrent Neural Networks

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Su Lee Goh and Danilo P. Mandic. . 340

Some Properties of the Network Consisting of Two Complex-Valued Nagumo-Sato Neurons

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Iku Nemoto 351

Knowledge Based Computer Assisted Systems for Health Care

Ontology-Based Medical Information Service System Hirokazu Taki, Noriyuki Matsuda, Michiyasu Hiramatsu, Yuki Naito, Jiro Nakajima, Tadashi Nakamura, Akihisa Imagawa, Yuji Matsuzawa, Norihiro Abe, and Satoshi Hori . . . . . . . . . . . . . . . . . . . . . . . . . 358

Abstraction of Long-Term Changed Tests in Mining Hepatitis Data Saori Kawasaki, Tu Bao Ho, and Dung Dong Nguyen. . . . . . . . . . . . . . . . . . . . 366

A Classification Capability of Reflective Neural Networlts in Medical Databases Takumi Ichimura, Shinichi Oeda, Machi Suka, and Katsumi Yoshida. . . . . . 373

A Classification Method of Medical Database by Immune Multi-agent Neural Networlts with Planar Lattice Architecture Takumi Ichimura, Shinichi Oeda, Toshiyuki Yamashita, and Katsumi Yoshida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380

Physiological Simulation by Integrating a Circulatory System Model with Beat-by-Beat Hemodynamics I'en'ichi Asami and Tadashi Kitamura.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388

Collimation Detection in Digital Radiographs Using Plane Detection Hough nansform Ikuo Kawashita, Masahito Aoyama, Tomoaki Kajiyama, and Naoki Asada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394

Automated Cerebral Arteries Segmentation and Diameter Measurement of Aneurysm from MR Angiograms Masahito Aoyama, Ikuo Kawashita, Yoko Naruse, Naoki Asada, and Kazuo Awai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402

Data Mining for Seelting Relationships between Sicltness Absence and Japanese Worker's Profile Hiroki Sugimori, Yukiyasu Iida, Machi Suka, Takumi Ichimura, and Katsumi Yoshida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410

Clinical Decision Support System Applied the Analytic Hierarchy Process Machi Suka, Takumi Ichimura, and Katsumi Yoshida.. . . . . . . . . . . . . . . . . . . . 417

XXII Table of Contents, Part I1

Intelligent Human Computer Interaction Systems

Emotion Generating Calculations Based on Hidden Marlcov Model Kazuya Mera and Takumi Ichimura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424

Support System for Analysis of Student's Motivation in Group Learning Manabu Nakamura, Takumi Ichimura, Kazuya Mera, and Setsuko Otsuki.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432

Personalization of Help System Output in the F'rameworlc of Everyday Language Computing Shino Iwashita, Ichiro Kobayashi, Noriko Ito, Toru Sugimoto, and Michio Sugeno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439

A Description Method of Syntactic Rules on Japanese Filmscript Yoshiaki Kurosawa, Takumi Ichimura, and Teruaki Aizawa . . . . . . . . . . . . . . . 446

I(now1edge Structure for Acquiring Personal Taste Information Kazuya Mera and Takumi Ichimura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454

A Proposal of Kansei Description for Multimedia Contents Kaori Yoshida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461

Interactive Navigation for Problem-Solving Oriented Learning Processes Kazuhisa Seta, Kei Tachibana, and Motohide Umano . . . . . . . . . . . . . . . . . . . . . 466

Multi-objective Decision Malting by AHP and Its Application to Personal Preference Retrieval System Takumi Ichimura, Akira Hara, Tetsuyuki Takahama, Yoshinori Isomichi, and Rie Utsunomiya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474

Interactive Design Support System by Customer Evaluation and Genetic Evolution: Application to Eye Glass n a m e Hideyoshi Yanagisawa and Shuichi Fukuda.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481

Immunity-Based Systems

Towards an Immunity-Based System for Detecting Masqueraders Takeshi Okamoto, Takayuki Watanabe, and Yoshiteru Ishida.. . . . . . . . . . . . . 488

Noisy Channel and Reaction-Diffusion Systems: Models for Artificial Immune Systems Vincenzo Cutello and Giuseppe Nicosia.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 496

Immunity-Based Approaches for Self-Monitoring in Distributed Intrusion Detection System Yuji Watanabe and Yoshiteru Ishida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503

Table of Contents, Part I1 XXIII

Idiotypic Network Model for Feature Extraction in Pattern Recognition - Effect of Diffusion of Antibody Toshiyuki Shimooka and Koichi Shimizu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511

Mechanism of a Transient but Long-Lasting Immune Memory Function on a Self/Non-Self Boundary Kouji Harada and Norio Shiratori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519

A Proposal of Immune Multi-agent Neural Networks and Its Application to Medical Diagnostic System for Hepatobiliary Disorders Shinichi Oeda, Takumi Ichimura, Toshiyuki Yamashita, and Katsumi Yoshida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526

Intelligent Knowledge-Based Interface Systems (I)

Development of an ESP E-learning Tool Using In-House Corpora Yukie Koyama,, Tomofumi Nakano, and Chikako Matsuura.. . . . . . . . . . . . . . 533

Evaluation of Learning Support System for Agent-Based C Programming Kazuhiko Nagao and Naohiro Ishii.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 540

EM Algorithm for Cleaning of Answers Generated by an E-learning System Tomofumi Nakano, Yukie Koyama, Nobuhiro Inuzuka, and Chikako Matsuura.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547

Reinforcement Learning Methods to Handle Actions with Differing Costs in MDPs Takahisa Ishiguro, Tohgoroh Matsui, Nobuhiro Inuzuka, and Koichi Wada.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553

Intelligent Knowledge-Based Interface Systems (11)

Extraction of Face Parts by Using Flesh Color and Boundary Images . . . . . . . . . . . . . . . . . . Yoshinori Adachi, Saori Takeoka, and Masahiro Ozaki.. 561

Web Type CAI System with Dynamic Text Change from Database by Understanding Masahiro Ozaki, Koji Koyama, Yoshinori Adachi, and Naohiro Ishii . . . . . . 567

A Study on Saccadic Eye Movements at the Mutual Gazing Hiroshi Sasaki, Kazuhiro Murai, and Naohiro Ishii. . . . . . . . . . . . . . . . . . . . . . . . 573

Direction Selective Artificial Vision Model and the Layout for Analog VLSI Masashi Kawaguchi, Takashi Jimbo, Masayoshi Umeno, and Naohiro Ishii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 578

XXIV Table of Contents, Part I1

Knowledge-Based and Cognitive Neuroscience Systems for Future Humanoid Robot Development

Cognitive Humanoid Robots Based on Complex Kinematic Features Frank Kirchner, Takamasa Koshizen, and Dirk Spenneberg . . . . . . . . . . . . . . . . 584

A Multi-layered Hierarchical Architecture for a Humanoid Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kenji Suzuki and Shuji Hashimoto.. 592

Active Detection of Anomalous Region as Primitive Processing for Visual Object Segregation Shinichi Nagai, Koji Akatsuka, Tetsuya Ido, Hiroshi Kondo,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atsushi Miura, and Hiroshi Tsujino 600

ANNA: An Artificial Neural Network for Attention to Emotional Recognition

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J.G. Taylor and N. Fragopanagos.. 607

Attention-Based Robot Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S . ICasderidis and J.G. Taylor. . 615

Industrial Applications of Soft Computing

Two Industrial Problems Solved through a Novel Optimization Algorithm M. Vannucci, V . Colla, G. Bioli, and R . Valentini.. . . . . . . . . . . . . . . . . . . . . . . 622

Do Neurofuzzy Systems Have Chances in Industrial Applications? Leonardo M. Reyneri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629

Clusterability and Centroid Approximation Alina Romero and Mukkai S. Krishnamoorthy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637

An Artificial Olfactory System for Quality and Geographical Discrimination of Olive Oils

. . . . . . . . . . Marco Cococcioni, Beatrice Lazzerini, and Francesco Marcelloni 647

A Fuzzy Logic Approach to Improve Manufacturing Effectiveness Riccardo Dulmin and Valeria Mininno.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 654

Intelligent Mobile Agents in Mobile Networks: All-Mobile Networks

Knowledge-Based Mobility Management in All-Mobile Network Ignac Lovrek and I/jekoslav Sinkovic.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661

The Intelligent Agent-Based Control of Service Processing Capacity Dragan Jevtic, Marijan Kunstic, and Nenad Jerkovic.. . . . . . . . . . . . . . . . . . . . 668

Table of Contents, Part I1 xxv

Multi-agent System for Remote Software Operations Gordan Jezic, Mario Kusek, Sasa Desic, Ozren Labor, Antun Caric,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Darko Huljenic.. 675

Command and Control (C2) and Situation Awareness - Reasoning in Intelligent Agents

A F'rigate Movement Survival Agent-Based Approach Pierrick Plamondon, Brahim Chaib-draa, Patrick Beaumont,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Dale Blodgett 683

Weasel: A User Guided Enemy Course of Action Generator Caroline C. Hayes and Ujwala Ravinder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 692

A Multi-agent System for Executing Group Tasks Jeremy W . Baxter and Graham S. Horn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697

Knowledge Elicitation and Decision-Modelling for Command Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marcus Watson and Frank Lui 704

The Wargame Infrastructure and Simulation Environment (Wise) Paul Pearce, Alan Robinson, and Susan Wright . . . . . . . . . . . . . . . . . . . . . . . . . . . 714

Intelligent Agents and Situation Awareness Pierre Urlings, Jeffrey Tweedale, Christos Sioutis,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Nikhil Ichalkaranje

Intelligent Groupware

A New MPEG-2 Solution Using a 2nd ALU in the RISC Kunihiro Yamada, Yukihisa Naoe, Masanori Kojima,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Tadanori Mizuno 734

Idea Generation Support System GUNGEN DX I1 beyond Papers Tomohiro Shigenobu, Takashi Yoshino, and Jun Munemori . . . . . . . . . . . . . . . 741

Data Processing Method of Small-Scale Five Senses Communication System Takashi Yoshino, Yoshinori Fujihara, and Jun Munemori . . . . . . . . . . . . . . . . . 748

A Bia l of a Bidirectional Learning Management Tool for Promoting Learning by Mobile Phone Kouji Yoshida, Kouiti Matsumoto, Kazuhiro Nakada, Tomonori Akutsu, Satoru Fujii, and Hiroshi Ichimura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756

Development of a Remote Communication System for Computer Novices and Their Instructors

. . . . . . . . . . Satoru Fujii, Jun Iwata, Kouji Yoshida, and Tadanori Mixuno.. 764

XXVI Table of Contents, Part I1

Personalized Environment for Skimming Documents Tessai Hayama, Takashi ICanai, and Susumu Kunifuji . . . . . . . . . . . . . . . . . . . . 771

GUNGEN-GO: Real-Time Groupware Development Environment for a Hypermedia System Takaya Yuizono, Takashi Yoshino, and Jun Munemori . . . . . . . . . . . . . . . . . . . . 779

Visualization Methods for Sharing Knowledge Pieces and Relationships Based on Biological Models Masao Usuki and ICozo Sugiyama.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 786

Intelligent Paradigms i n Biocybernetics a n d Biomedical Engineering

Functional Imaging of Tinnitus: Seeing of the Unseeable! Ali A . Danesh, Yohsuke Kinouchi, Deena L. Wener, and Abhijit Pandya.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 794

Brain Signal Source Localization Using a Method Combining BP Neural Networks with Nonlinear Least Squares Method Qinyu Zhang, Masatake Akutagawa, Xiaoxiao Bai, Hirofumi Nagashino, and Yohsuke Kinouchi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 800

System Identification of the Brain Dynamics by EEG Analysis Using Neural Networlts Toshio Kawano, Masatake Akutagawa, Qinyu Zhang, Hirofumi Nagashino, Yohsuke Kinouchi, Fumio Shichijo, and Shinji Nagahiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 807

A Neural Network Model for Pattern Recognition Hirohito Shintani, Hirofumi Nagashino, Masatake Akutagawa, and Yohsuke Kinouchi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 814

A Predictive Feedback Control Model Using NN and NLMS Malrey Lee, Dongju Im, Sung Su Park, Jung sik Lee, and Jae wanLee.. . . . 822

Intelligent Systems Design

Representing of Dependence Model and Class Testing Using Program Dependence Model Malrey Lee, Dong- Ju Im, SungSu Park, Jungsik Lee, Jaewan Lee, and Bumjun Cho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 828

Secure Transaction Processing in Multi-expert Systems with Replicated Data Jeong Hyun-Cheol, Malrey Lee, and Bumjun Cho . . . . . . . . . . . . . . . . . . . . . . . . . 834

Table of Contents, Part I1 XXVII

Goal-Directed Design for Proactive and Intelligent Device Collaboration Michael VanHilst and Martin Griss. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841

Recognition of X-ray Images by Using Revised GMDH-type Neural Networks Tadashi Kondo and Abhijit S. Pandya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 849

Low Power Design of the Neuroprocessor A.S. Pandya, Ankur Agarwal, and P.K. K i m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 856

Visual Sensing ahd Human Interface for Affective Computing

Age and Gender Estimation Based on Facial Image Analysis Jun-ichiro Hayashi, Hiroyasu Koshimizu, and Seiji Hata. . . . . . . . . . . . . . . . . . 863

Age and Gender Estimations by Modeling Statistical Relationship among Faces Takayuki Fujiwara and Hiroyasu Koshimizu. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 870

Subjective Age Obtained from Facial Images - How Old We Feel Compared to Others Noriko Nagata and Seiji Inokuchi.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 877

Robust Facial Parts Detection by Using Four Directional Features and Relaxation Matching Ken@ Iwata, Hitoshi Hongo, ICazuhiko Yamamoto, and Yoshinori Niwa . . . 882

Event Detection for a Visual Surveillance System Using Stereo Omni-directional System Hiroki Watanabe, Hidelci Tanahashi, Yutaka Satoh, Yoshinori Niwa, and Kazuhiko Yamamoto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 890

Mental Workload of Ship's Navigator - A Few Comments on Heart Rate Variability during Navigational Watch Keeping Koji Murai, Yuji Hayashi, Noriko Nagata, and Seiji Inokuchi . . . . . . . . . . . . . 897

Face Dacliing System with Fixed CCD and PTZ Camera Takuma Funahashi, Tsuyoshi Yamaguchi, Masafumi Tominaga, George Lashkia, and Hiroyasu Koshimizu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 904

Intelligent Techniques for Biology and Chemistry

A Study of Aquatic Toxicity Using Artificial Neural Networks Marian Viorel CrZciun, Daniel C. Neagu, Christoph Konig, and Severin Bumbaru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 911

XXVIII Table of Contents, Part I1

Discovery of Toxicological Patterns with Lazy Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eva Armengol and Enric Plaza. . 919

Discovering Active Regions in Non-redundant Genome Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ramesh and Shivashankar B . Nair 927

Neural Network Application to Eggplant Classification Yasuo Saito, Toshiharu Hatanaka, Katsuji Uosaki,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Hidekazu Shigeto.. 933

Intelligent Optimal Control of a Biosynthesis Process Using a Neural Network Based Estimator Grigore Fetecc'iu, Viorel Nicolau, Vasile Palade, and Maria Fetecc'iu . . . . . . . 941

Methods and Applications of Intelligent Hybrid Systems

On the Analysis of Neural Networks for Image Processing Berend Jan van der Zwaag, Kees Slump, and Lambert Spaanenburg . . . . . . . 950

Development of Methods How to Avoid the Overfitting-Effect within the GeLog-System

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gabriella Kdkai 958

An Optimal Algorithm for Combining Multivariate Forecasts in Hybrid Systems

. . . . . . . . . . . . . . . . . . . . . . . . . Ye, Bodyanskiy, P. Otto, I. Pliss, and S. Popov.. 967

Probabilistic Neuro-fuzzy Network with Non-conventional Activation Functions

. . . . . . . Ye. Bodyanskiy, Ye. Gorshkov, V . Kolodyazhniy, and J. Wernstedt 973

An Optimization of Data Mining Algorithms Used in Fuzzy Association Rules

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dragos Arotaritei and Mircea Gh. Negoita 980

Some Test Problems Regarding Intelligent Tutoring Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mircea Gh. Negoita and David Pritchard.. 986

Knowledge Based Methods and Applications for Product Development

A Web-Based Intelligent Forecasting System Xiang Li, King-Jim Hee, and Yushi Cheng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 993

A Tabu Search-Based Optimization Approach for Process Planning WD Li, S K Ong, YQ Lu, and A Y C Nee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000

Table of Contents, Part I1 XXIX

Automated Text Classification for Fast Feedback - Investigating the Effects of Document Representation Rakesh Menon, Loh Hun Tong, S. Sathiyakeerthi, and Aarnout Brombacher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1008

A Solution to Billiard Balls Puzzle Using AO* Algorithm and Its Application to Product Development Zhu Fuxi, Tian Ming, and He Yanxiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1015

A Product Model for Mass - Customisation Products Dennis Janitza, Martin Lacher, Maik Maurer, Udo Pulm, and Henning Rudo l f . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1023

Intelligent Media Technology for Communicative Intelligence

Partl: Embodied Conversational Agents and Intelligent Support for Content Creation

Embodied Conversational Agents for Presenting Intellectual Multimedia Contents Yukiko I. Nakano, Toshihiro Murayama, Daisuke Kawahara, Sadao Kurohashi, and Toyoaki Nishida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1030

Channel Design for Strategic Knowledge Interaction Hidekazu Kubota and Toyoaki Nishida.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1037

Object Tracking and Task Recognition for Producing Interactive Video Content - Semi-automatic Indexing for QUEVICO Motoyuki Ozeki, Masatsugu Itoh, Hidekatsu Izuno, Yuichi Nakamura, and Yuichi Ohta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1044

Structural Analysis of Instruction Utterances Tornohide Shibata, Daisuke Kawahara, Masashi Okamoto, Sadao Kurohashi, and Toyoaki Nishida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1054

On Personalizing Video Portal System with Metadata Kouzou Ohara, Takehiro Ogura, and Noboru Babaguchi.. . . . . . . . . . . . . . . . . 1062

Part2: Environmental Media and Intelligent Interaction Support

Environmental Media - In the Case of Lecture Archiving System - Michihiko Minoh and Satoshi Nishiguchi . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . 1070

Non-verbal Human Communication Using Avatars in a Virtual Space Daisaku Arita and Rin-ichiro Taniguchi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1077

XXX Table of Contents, Part I1

Adjustment of Nonverbal Conversational Signals from Embodied Agents in Dialogues Junko Itou, I<oh Kakusho, and Michihiko Minoh, . . . . . . . . . . . . . . . . . . . . . . . . 1085

Toward the Human Communication Efficiency Monitoring from Captured Audio and Video Media in Real Environments Tomasz M. Rutkowski, Susumu Seki, Yoko Yamakata, Icoh Kakusho, and Michihiko Minoh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1093

Toward a Mutual Adaptive Interface: An Interface and a User Induce and Utilize the Partner's Adaptation Takanori Komatsu, Atsushi Utsunomiya, Kentaro Suzuki, Kazuhiro Ueda, Kazuo Hiraki, and Natsuki Oka . . . . . . . . . . . . . . . . . . . . . . . . . 1101

Neural Network Models of Brain Disease, Plasticity and Rehabilitation

Neural Network Theory and Recent Neuroanatoniical Findings Indicate that Inadequate Nitric Oxide Synthase Will Cause Autism Lennart Gustafsson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1109

From Dopamine to Psychosis: A Computational Approach Andrew Smith, Suzanna Becker, and Shitij Kapur . . . . . . . . . . . . . . . . . . . . . . . 1115

Preoccupation with a Restricted Pattern of Interest in Modelling Autistic Learning Lennart Gustafsson and Andrew P. Papliriski. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1122

The CODAM Model and Deficits of Consciousness I: CODAM J.G. Taylor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1130

CODAM and Deficits of Consciousness 11: Schizophrenia and Neglect/Extinction J.G. Taylor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A Neurocomputational Model of Early Psychosis Eric Y.H. Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1149

Schizophrenia Positive Symptonls Interpreted as Cognitive Hallucinations Javier Ropero Pelaez . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156

Selfreparing Neural Networks: A Model for Recovery from Brain Damage

. . . . . . . . . . . . . . . . . . Jaap M. J. Murre, Robert Grifioen, and I. H. Robertson 1164

Dopaminergic Noise Control of Memory in Psychic Aparatus F'unctioning Luis Alfredo V. de Carvalho, Roseli S . Wedemann, Raul Donangelo, and Daniele Q. Mendes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1172

Table of Contents, Part I1 XXXI

Soft Computing Techniques for 3D Computer Vision

Contour Based Super quadric Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jaka Krivic and Franc Solina.. 1180

2D Qualitative Recognition of SymGeon Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fiora Pirri and Massimo Romano.. 1187

Accelerated Bundle Adjustment in Multiple-View Reconstruction Bing Liu, Maoyuan Yu, Dennis Maier, and Reinhard Manner . . . . . . . . . . . 1195

Knowledge Based E-learning

Learning Method Objects for Knowledge-Driven Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ignatz Heinz and Ursula Suter-Seuling 1202

Open Web-Based Learning Environments and Knowledge Forums to Support Disabled People Ileana Hamburg, Miona Lazea, and Mihnea Marin.. . . . . . . . . . . . . . . . . . . . . . 1208

A Model Conception for Learner Profile Construction and Determination of Optimal Scenario in Intelligent Learning Systems E. Kukla, N. T. Nguyen, J. Sobecki, C. Danilowicz, and M. Lenar . . . . . . . . 1216

Adaptive Learning Scenarios in Intelligent Instructional Environment Emilia Pecheanu, Luminita Dumitriu, and Cristina Segal . . . . . . . . . . . . . . . . 1223

Content Modeling in Intelligent Instructional Environments Emilia Pecheanu, Cristina Segal, and Diana Stefanescu. . . . . . . . . . . . . . . . . . 1229

edge Engineering at the User Interface elligent Biometric Processing

Factors that Affected the Benchmarking of NAFIS: Study

a Suman.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1235

Performance Evaluation ess Detection for Various Fingerprint Sensor Modules

ang, Bongku Lee, Hakil Kim, Daecheol Shin, sung Kim. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1245

of Multimodal Biometric Transactions . . . . irhurst, F. Deravi, N. Mavity, J. George, and K. Sirlantzis.. 1254

on Measuring Image Quality

. . . . . . . . . . OOIC Joun, Hakil Kim, Yongwha Chung, and Dosung Ahn 1261

XXXII Table of Contents, Part I1

A Study of the User Interface in Biometric Verification Based on the Characteristics of Human Signature Checking

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M.C. Fairhurst and E. Kaplani. . 1270

Advances on Knowledge Engineering

I<nowledge Model of a Therapy Administration Task Applied to an Agricultural Domain Isabel Maria del Aguila, Josk Joaquin Cafiadas, Alfonso Bosch, Samuel Tdnez, and Roque Marin . . . . . . . . . . . . . . . . . . . . . . . . 1277

Acquisition and Representation of Causal and Temporal Knowledge in Medical Domains J. Palma, B. Llamas, A. Gonzdlez, and M. Mendrguez . . . . . . . . . . . . . . . . . . 1284

Extended Models of Dynamic Selection Using Ontological Elements Application to Design and Image Analysis Problems J. Fernando Bienvenido and Isabel M. Flores-Parra . . . . . . . . . . . . . . . . . . . . . 1291

Experiences in Reusing Problem Solving Methods An Application in Constraint Programming Abraham Rodriguez, Josk Palma, and Francisca Quintana . . . . . . . . . . . . . . . 1299

Problem-Solving Analysis for the Budgeting Task in Furniture Industry J.C. Vidal, M. Lama, A . Bugarin, and S. Barro. . . . . . . . . . . . . . . . . . . . . . . . . 1307

Collecting, Analyzing and Interpreting Data for User Model Acquisition in Open Web-Based Adaptive Collaborative Environment

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Gaudioso and Jesus G. Boticario.. 1314

Some Issues about the Representation and Exploitation of Imprecise Temporal Knowledge for an A1 Planner

. . . . . . . . . . Luis Castillo, Juan Ferndndez-Olivares, and Antonio Gonzdlez 1321

On Selecting and Scheduling Assembly Plans Using Constraint Programming Carmelo Del Valle, Antonio A . Mdrquez, Rafael M. Gasca,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Miguel Toro 1329

Dynamic versus Static Student Models Based on Bayesian Networlts: An Empirical Study Eva Milldn, Jose' Luis Pkrez-de-la-Cruz, and Felipe Garcia. . . . . . . . . . . . . . . 1337

Knowledge Acquisition in PROSTANET - A Bayesian Network for Diagnosing Prostate Cancer Carmen Lacave and Francisco J. Diez . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1345

Table of Contents, Part I1 XXXIII

Construction of a Development Environment for GPMs Based on 00 Analysis Patterns Manuel Arias, Angeles Manjarrks, Francisco J. Diez, and Simon Pickin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1351

Using Electronic Documents for Knowledge Acquisition and Model Maintenance Martin Molina and Gemma Blasco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1357

Design of a Validation Tool Based on Design Patterns for Intelligent Systems Eduardo Mosqueira-Rey, Juan Gabriel Ferncindez Garcia de la Rocha, and Vicente Moret-Bonillo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1365

Knowledge Base Development D. Martinez, M. Taboada, and J. Mira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1373

KB-Grid: Towards Building Large-Scale Knowledge System in Semantic Web Huajun Chen, Zhaohui Wu, and Jiefeng X u . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1381

First Steps towards an Ontology for Astrophysics Luis M. Sarro and Rafael Martinez. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1389

Emergence and Self-organization in Agent Systems

Cellular Automata Model Based on Multiagent Techniques Y. Hassan, E. Tazaki, and D. Yamaguchi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1396

traction of Rules by Heterogeneous;Agents omatically Defined Groups ~s :

a, Takumi Ichimura, Tetsuyuki Takahama, inori Isomichi.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1405

Data Mining for Distributed Databases with Multiagents Ayuhiko Niimi and Osamu Konishi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1412

Applying Self-organizing Agents to University Class Scheduling Eiji Nunohiro and Kenneth J. Muckin!;. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1419

gence i n Agents with Different .Internal Time Frames eth J. Mackin' and Kazuko Yamasaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1426

hor Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1433

Table of Contents, Part I

Keynote Lectures

Distributed Prediction and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gail A. Carpenter. . 1

The Brain's Cognitive Dynamics: The Link between Learning, Attention, Recognition, and Consciousness

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stephen Grossberg.. 5

Adaptive Data Based Modelling and Estimation with Application to Real Time Vehicular Collision Avoidance

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chris J. Harris. . 13

Creating a Smart Virtual Personality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nadia Magnenat- Thalmann 15

elligent Navigation on the Mobile Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rry Smyth 17

e Evolution of Evolutionary Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y a o . . . . . . . . . . . . . . . . ... ..... .... 19

eneral Session Papers

owledge-Based Systems

nified Model Maintains Knowledge Base Integrity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . n Debenham 21

Argumentation Fkameworlts Extended Generalized Annotated Logic Programs

isa Takahashi,, Yuichi Umeda, and Hajime Sawamura . . . . . . . . . . . . . . . . 28

g and Validating Reactive Systems mmonKADS Methodology

mar El-Amine Hamri, Claudia Frydman, and Lucile Torres . . . . . . . . . . . 39

: Tool Supporting Knowledge Modelling milleri, Jean-Luc Soubie, and Joseph Zalaket . . . . . . . . . . . . . . . . . . . . . . . 45

Based Planning with Numerical Knowledge h Zalaket and Guy Camilleri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

XXXVI Table of Contents, Part I

KAMET 11: An Extended Knowledge-Acquisition Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Osvaldo Cairo' and Julio Char Alvarez 61

Automated Knowledge Acquisition by Relevant Reasoning Based on Strong Relevant Logic

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jingde Cheng.. 68

CONCEPTOOL: Intelligent Support to the Management of Domain Knowledge

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ernesto Compatangelo and Helmut Meisel 81

Combining Revision Production Rules and Description Logics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chan Le Duc and Nhan Le Thanh 89

Knowledge Support for Modeling and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michal Sev~enko. . 99

Expert System for Simulating and Predicting Sleep and Alertness Patterns Udo fiutschel, Rainer Guttkuhn, Anneke Heitmann,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acacia Aguirre, and Martin Moore-Ede 104

Two Expert Diagnosis Systems for SMEs: From Database-Only Technologies to the Unavoidable Addition of A1 Techniques

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sylvain Delisle and Jose'e St-Pierre 111

Using Conceptual Decision Model in a Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Miki Sirola.. 126

Neural Networks and Applications

Automated Knowledge Acquisition Based on Unsupervised Neural Network and Expert System Paradigms

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nazar Elfadil and Dino Isa 134

Selective-Learning-Rate Approgch for Stoclc Market Prediction by Simple Recurrent Neural Networks

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kazuhiro Kohara 141

A Neural-Network Technique foe! Recognition of Filaments in Solar Images

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. V . Zharkova and V . Schetinin.. 148

Learning Multi-class Neural-Netwbrk Models from Electroencephalograms Vitaly Schetinin, Joachim Schult, Burkhart Scheidt, and Valery Kuviakin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

Table of Contents, Part I XXXVII

Establishing Safety Criteria for Artificial Neural Networlts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zeshan Kurd and Tim Kelly.. 163

Neural Chaos Scheme of Perceptual Conflicts Haruhiko Nishimura, Natsulci Nagao, and Nobuyuki Matsui . . . . . . . . . . . . . . . 170

Learning of SAINNs from Covariance Function: Historical Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paolo Crippa and Claudio Turchetti 177

Use of the Kolmogorov's Superposition Theorem and Cubic Splines for Efficient Neural-Network Modeling

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Boris Igelnik 184

The Influence of Prior Knowledge and Related Experience on Generalisation Performance in Connectionist Networks F.M. Richardson, N. Davey, L. Peters, D.J. Done, and S.H. Anthony . . . . 191

Urinary Bladder Tumor Grade Diagnosis Using On-line Trained Neural Networks D.K. Tasoulis, P. Spyridonos, N.G. Pavlidis, D. Cavouras, P. Ravazoula, G. Nikiforidis, and M.N. Vrahatis.. . . . . . . . . . . . . . . . . . . . . . . . . 199

Invariants and Fuzzy Logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gemano Resconi and Chiara Ratti.. 207

Newsvendor Problems Based on Possibility Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Peijun Guo 213

ncertainty Management in Rule Based Systems Application Maneuvers Recognition

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benouhiba and J.M. Nigro. 220

Coefficients and Fuzzy Preference Relations 1s of Decision Malting el, EJim Galperin, Reinaldo Palhares, Claudio Campos,

Marina Silva.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

ing Fuzzy Rules for a Traffic Information System exandre G. Evsukoff and Nelson F.F. Ebecken . . . . . . . . . . . . . . . . . . . . . . . . . . 237

ibilistic Hierarchical Fuzzy Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o Salgado 244

zzy Knowledge Based Guidance in the Homing Missiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . stafa Resa Becan and Ahmet Kuzucu 251

XXXVIII Table of Contents, Part I

Evolutionary Computation and Applications

Evolutionary Design of Rule Changing Cellular Automata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hitoshi Kanoh and Yun W u 258

Dynamic Control of the Browsing-Exploitation Ratio for Iterative Optimisations L. Baumes, P. Jouve, D. Farrusseng, M. Lengliz, N . Nicoloyannis,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and C. Mirodatos.. 265

Intelligent Motion Generator for Mobile Robot by Automatic Constructed Action Knowledge-Base Using GA Hirokazu Watabe, Chikara Hirooka, and Tsukasa Kawaoka.. . . . . . . . . . . . . . . 271

Population-Based Approach to Multiprocessor Task Scheduling in Multistage Hybrid Flowshops Joanna Jqdrzejowicz and Piotr J~drzejowicz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279

A New Paradigm of Optimisation by Using Artificial Immune Reactions M. Koster, A . Grauel, G. Klene, and H. Convey. . . . . . . . . . . . . . . . . . . . . . . . . . 287

Multi-objective Genetic Programming Optimization of Decision Trees for Classifying Medical Data Ernest Muthomi Mugambi and Andrew Hunter . . . . . . . . . . . . . . . . . . . . . . . . . . . 293

Machine Learning and Applications

A Study of the Compression Method for a Reference Character Dictionary Used for On-line Character Recognition Jungpil Shin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300

Mercer Kernels and 1-Cohomology of Certain Semi-simple Lie Groups Bernd- Jurgen Fallcowski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310

On-line Profit Sharing Works Efficiently Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki . . . . . . . . . . . . . . . . . . . 317

Fast Feature Ranking Algorithm Roberto Ruiz, Jose' C, Riquelme, and Jeslis S . Aguilar-Ruiz . . . . . . . . . . . . . . . 325

Visual Clustering with Artificial Ants Colonies Nicolas Labroche, Nicolas Monmarche', and Gilles Venturini . . . . . . . . . . . . . . 332

Maximizing Benefit of Classifications Using Feature Intervals Nazlz jkizler and H. Altay Giivenir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339

Parameter Estimation for Bayesian Classification of M~l t i s~ec t r a l Data Refaat M Mohamed and Aly A Farag.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

Table of Contents, Part I XXXIX

Goal Programming Approaches to Support Vector Machines Hirotalca Nakayama, Yeboon Yun, Talceshi Asada, and Min Yoon . . . . . . . . . 356

Asymmetric Triangular Fuzzy Sets for Classification Models J.F. Baldwin and Sachin B. Karale. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364

Machine Learning to Detect Intrusion Strategies Stewe Moyle and John Heasman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371

On the Benchmarking of Multiobjective Optimization Algorithm Mario Koppen.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379

Multicategory Incremental Proximal Support Vector Classifiers Amund Tweit and Magnus Lie Hetland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386

c Consistency for Dynamic CSPs lek Mouhoub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

ermination of Decision Boundaries for Online Signature Verification ahiro Tanaka, Yumi Ishino, Hironori Shimada, Takashi Inoue, Andrzej Bargiela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401

he Accuracy of Rotation Invariant Wavelet-Based Moments Applied ecognize Traditional Thai Musical Instruments

tisalc Rodtook and Stanislaw Makhanow.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408

ti-agent Systems

lti-agent System for Knowledge Management ftware Maintenance ra Vizcaino, Jesds Favela, and Mario Piattini . . . . . . . . . . . . . . . . . . . . . . . 415

A: A Distributed Double Guided Genetic Algorithm x-CSPs Bouamama, Boutheina Jliji, and Khaled Ghddira.. . . . . . . . . . . . . . . . . . 422

ing Intelligent Agents for Organisational Memories . . . . . . . . . . . . . . . . . . . . . . . . . E. Arenas and Gareth Bar r ia . . 430

dy on the Multi-agent Appr rge Complex Systems glory Tianfield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438

-layered Distributed Agent Ontology for Soft Computing Systems Khosla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445

ode1 for Personality and Emotion Simulation . . . . . . . Egges, Sumedha Kshirsagar, and Nadia Magnenat-Thalmann 453

XL Table of Contents, Part I

Data Mining & Knowledge Discovery

Using Loose and Tight Bounds to Mine Frequent Itemsets Lei Jia, Jun Yao, and Renqing Pei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 462

Mining Association Rules with Frequent Closed Itemsets Lattice Lei Jia, Jun Yao, and Renqing Pei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469

Mining Generalized Closed Frequent Itemsets of Generalized Association Rules Kritsada Sriphaew and Thanaruk Theeramunkong . . . . . . . . . . . . . . . . . . . . . . . . 476

Qualitative Point Sequential Patterns , Aomar Osmani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485

Visualization and Evaluation Support of Knowledge Discovery through the Predictive Model Markup Language

. . . . . . . . . . . . . . . . . . . . . Dietrich Wettschereck, Alipio Jorge, and Steve Moyle 493

Detecting Patterns of Fraudulent Behavior in Forensic Accounting Boris Kovalerchuk and Evgenii Vityaev. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502

SPIN!-An Enterprise Architecture for Spatial Data Mining Michael May and Alexandr Savinov.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 510

The Role of Discretization Parameters in Sequence Rule Evolution Magnus Lie Hetland and Pi1 Setrom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 518

Feature Extraction for Classification in Knowledge Discovery Systems Mykola Pechenizkiy, Seppo Puuronen, and Alexey Tsymbal . . . . . . . . . . . . . . . . 526

Adaptive Per-application Load Balancing with Neuron-Fuzzy to Support Quality of Service for Voice over IP in the Internet Sanon Chimmanee, Komwut Wipusitwarakun, and Suwan Runggeratigul . . 533

Hybrid Intelligent Systems

Hybrid Intelligent Production Simulator by GA and Its Individual Expression Hidehiko Yamamoto and Etsuo Marui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542

On the Design of an Artificial Life Simulator Dara Curran and Colm O'Riordan.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549

3-Dimensional Object Recognition by Evolutional RBF Networlr Hideki Matsuda, Yasue Mitsukura, Minoru Fukumi, and Norio Akamatsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556

Soft Computing-Based Design and Control for Vehicle Health Monitoring Preeti Bajaj and Avinash Keskar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 563

Table of Contents, Part I XLI

Signal and Image Processing

An Adaptive Novelty Detection Approach to Low Level Analysis of Images Corrupted by Mixed Noise Alexander N. Dolia, Martin Lages, and Ata Kaban.. . . . . . . . . . . . . . . . . . . . . . . 570

The Image Recognition System by Using the FA and SNN Seiji Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Sigeru Omatu.. 578

nse Plate Detection Using Hereditary Threshold Determine Method i Yoshimori, Yasue Mitsukura, Minoru Fukumi,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Norio Akamatsu 585

ognition from EMG Signals by an Evolutional Method Non-negative Matrix Factorization ki Yazama, Yasue Mitsukura, Minom Fukumi, and Norio Akamatsu . . 594

ture Extraction Method for Personal Identification System ri Takimoto, Yasue Mitsukura, Minoru Fukumi,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rio Akamatsu 601

ature Extraction of the EEG Using the Factor Analysis eural Networlcs

-%chi Ito, Yasue Mitsukura, Minom Fukumi, and Norio Akamatsu . . . . 609

eural Network Approach to Color Image Classification ayuki Shinmoto, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617

nition of EMG Signal Patterns by Neural Networks tsumura, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu,

miaki Takeda.. . . . . . . . . . . . . . . .... ... .... .. . . . . . . . . . . . . . . . . . . . . . 623

ile Recognition Using Neural Networks and Simple PCA Nakano, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu,

miko Yasukata.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631

ion of Sea Ice Movement Using Locally Parallel Matching Model Xiangwei, Chen Feishi, Liu Zhiyuan, and Zong Shaoxiang . . . . . . . . . . 638

ation of a Combined Wavelet and ined Principal Component Analysis Classification System

Diagnostic Problem . . . . . . . . . . . . . . . . . . . g Yu, Dejun Gong, Siren Li, and Yongping Xu 646

m the Expert: Improving Boundary Definitions

wford-Hines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653

XLII Table of Contents, Part I

Low Complexity Functions for Stationary Independent Component Mixtures

. . . . . . . . . . . . . . . . . . . . . . . . . . . K. Chinnasarn, C. Lursinsap, and V , Palade.. 660

Intelligent Industr ial Applications

Knowledge-Based Automatic Components Placement for Single-Layer PCB Layout

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Distan Pannkrec.. 669

Knowledge-Based Hydraulic Model Calibration '

Jean-Philippe Vidal, Sabine Moisan, and Jean-Baptiste Faure . . . . . . . . . . . . . 676

Using Artificial Neural Networlcs for Combustion Interferometry . . . . . . . . . . . . . . . . . . . . Victor Abrulcov, Vitaly Schetinin, and Pave1 Deltsov.. 684

An Operating and Diagnostic Knowledge-Based System for Wire EDM . . . . . . . . . . . . . . . . . . . . . . . . . . . Samy Ebeid, Raouf Fahmy, and Sameh Habib.. 691

The Application of Fuzzy Reasoning System in Monitoring EDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiao Zhiyun and Ling Shih-Fu 699

Knowledge Representation for Structure and Function of Electronic Circuits

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TaLushi Tanaka 707

A Web-Based System for Transformer Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J.G. Breslin and W.G. Hurley 715

A Fuzzy Control System for a Small Gasoline Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S.H. Lee, R.J. Howlett, and S.D. Walters.. 722

Computat ional Intelligence for Fault Diagnosis

Faults Diagnosis through Genetic Matching Pursuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dan Stefanoiu and Florin Ionescu 733

A Fuzzy Classification Solution for Fault Diagnosis of Valve Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . C.D. BocGnialG, J. Sa da Costa, and R. Louro.. 741

Deep and Shallow Knowledge in Fault Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Viorel Ariton.. 748

Table of Contents, Part I XLIII

atural Language Processing

arning Translation Templates for Closely Related Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . emal Altintas and Halil Altay Guvenir 756

lementation of an Arabic Morphological Analyzer in Constraint Logic Programming Framework

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . mza Zidoum 763

'ent Automatic Correction of Misspelled Arabic Words Based ontextual Information

. . . . . . . . . . . . . . . . . raz Ben Othmane Zribi and Mohammed Ben Ahmed.. 770

Knowledge-Belief System and Its Application

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o Matsumoto and Akifumi Tokosumi.. 778

ledge-Based Question Answering Rinaldi, James Dowdall, Michael Hess, Diego Molld,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Schwitter, and Kaarel Kaljurand.. 785

ledge-Based System Method for the Unitarization aningful Augmentation in Horizontal Transliteration of Hanman

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . lory Tianfield 793

pressive Efficient Representation: mg a Gap between NLP and KR

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Sukkarieh.. 800

Mining & Information Retrieval

cting Word Clusters to Represent Concepts pplication to Web Searching

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Khare 816

work for Integrating Deep low Semantic Structures in Text Mining

1 Collier, Koichi Takeuchi, Ai Kawazoe, Tony Mullen, Tuangthong Wattarujeekrit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 824

ethods for Knowledge Discovery from Multilingual Text a Chau and Chung-Hsing Yeh.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 835

Automatic Extraction of Keywords from Abstracts Yaaleov HaCohen-Kerner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 843

length Normalization for Centroid-based Text Categorization h Lertnattee and Thanaruk Theeramunkong . . . . . . . . . . . . . . . . . . . . . . . 850

XLIV Table of Contents, Part I

Recommendation System Based on the Discovery of Meaningful Categorical Clusters

. . . . . . . . . . . . . . . . . . . Nicolas Durand, Luigi Lancieri, and Bruno Crdmilleux 857

A Formal Framework for Combining Evidence in an Information Retrieval Domain

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Josephine Grif i th and Colm O'Riordan.. 864

Managing Articles Sent to the Conference Organizer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yousef Abuzir 871

Information Retrieval Using Deep Natural Language Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rossitza Setchi, Qiao Tang, and Lixin Cheng 879

Intelligent Tutoring Systems

Ontology of Domain Modeling in Web Based Adaptive Learning System

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pinde Chen and Kedong L i . . 886

Individualizing a Cognitive Model of Students' Memory in Intelligent Tutoring Systems

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maria Virvou and Konstantinos Manos. . 893

An Ontology-Based Approach to Intelligent Instructional Design Support

. . . . . . . . . . . . Helmut Meisel, Ernesto Compatangelo, and Andreas Horhrter 898

Javy: Virtual Environment for Case-Based Teaching of Java Virtual Machine Pedro Pablo Gdmez-Martin, Marco Antonio Gdmez-Martin,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Pedro A . Gonzdlez- Calero 906

Artificial Intelligence and the Internet

Self-organization Leads to Hierarchical Modularity in an Internet Community

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jennifer Hallinan. 914

Rule-Driven Mobile Intelligent Agents for Real-Time Configuration of IP Networlrs

........................ K u n Yang, Alex Galis, X in Guo, and Dayou L i u . . 921

Neighborhood Matchmaker Method: A Decentralized Optimization Algorithm for Personal Human Network Masahiro Hamasaki and Hideaki Takeda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 929

Table of Contents, Part I XLV

Design and Implementation of an Automatic Installation System for Application Program in PDA Seungwon Na and Seman O h . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 936

Combination of a Cognitive Theory with the Multi-attribute Utility Theory

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Katerina Kabassi and Maria Virvou. . 944

Intelligent Web Applications

Using Self Organizing Feature Maps to Acquire Knowledge about Visitor Behavior in a Web Site Juan D. Vela'squez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Eduardo Vera. . 951

amework for the Development of Personalized Agents o Abbattista, Graziano Catucci, Marco Degemmis, Pasquale Lops,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vanni Semeraro, and Fabio Zambetta.. 959

Topic Cascades: An Interactive Interface for Exploration of Clustered Web Search Results Based on the SVG Standard M. Lux, M. Granitzer, V. Sabol, W . Kienreich, and J. Beclcer . . . . . . . . . . . . 967

ctive Knowledge Mining for Intelligent Web Page Management shi Ishikawa, Manabu Ohta, Shohei Yokoyama, Takuya Watanabe,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Iiaoru Iiatayama 975

se-Based Reasoning

-Based Reasoning for Time Courses Prognosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . er Schmidt and Lothar Gierl 984

Adaptation Problems in Therapeutic Case-Based Reasoning Systems Rainer Schmidt, Olga Vorobieva, and Lothar Gierl.. . . . . . . . . . . . . . . . . . . . . . . 992

nowledge Management and Quality Model for R&D Organizations llermo Rodriguex- Ortiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000

wledge Management & Information Systems

wledge Management Systems Development: A Roadmap r Andrade, Juan Ares, Rafael Garcia, Santiago Rodn'guez,

rks Silva, and Sonia Sua'rez . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1008

xtensible Environment for Expert System Development el Pop and Viorel Negrm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1016

XLVI Table of Contents, Part I

An Innovative Approach for Managing Competence: An Operational Knowledge Management Framework Giulio Valente and Alessandro Riga110 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1023

A Synergy of Modelling for Constraint Problems Gerrit Renker, Hatem Ahriz, and Inks Arana. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1030

Object-Oriented Design of EGovernment System: A Case Study Jiang Tian and Huaglory Tianfield.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1039

Posters

A Practical Study of Some Virtual Sensor Methods as Part of Data Fusion Jouni Muranen, Riitta Penttinen, Ari J Joki, and Jouko Saikkonen . . . . . . 1046

A Mamdaili Model to Predict the Weighted Joint Density Hakan A . Nefeslioglu, Candan Gokceoglu, and Harun Sonmez . . . . . . . . . . . . 1052

Mining Spatial Rules by Finding Empty Intervals in Data Alexandr Savinov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1058

The Application of Virtual Reality to the Understanding and Treatment of Schizophrenia Jennifer Tichon and Jasmine Banks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1064

Representation of Algorithmic Knowledge in Medical Information Systems Yuriy Prokopchuk and Vladimir Kostra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1069

A Case-Based Reasoning Approach to Business Failure Prediction Angela Y. N. Y ip and Hepu Deng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1075

A Metaheuristic Approach to Fuzzy Project Scheduling Hongqi Pan and Chung-Hsing Y e h . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1081

Invited Sessions Papers

Soft Computing Techniques for Financial Market

A Note on the Sensitivity to Parameters in the Convergence of Self-organizing Maps Marcello Cattaneo Adorno and Marina Resta . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1088

Table of Contents, Part I XLVII

Utilization of A1 & GAS to Improve the Traditional Technical Analysis in the Financial Markets Norio Baba, Yaai Wang, Tomoko Kawachi, Lina Xu, and Zhenglong Deng.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1095

the Predictability of High-Frequency Financial Time Series ko Tanaka- Yamawaki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1100

remental Learning and Forgetting in RBF Networlts and SVMs h Applications to Financial Problems

taka Nakayama and Atsushi Hattori.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1109

ural Networks and Genetic Algorithms sed Intelligent Systems (I)

nded Neural Networks in System Identification nobu Yamawaki and Lakhmi Jain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1116

Learning Algorithm e Hierarchical Structure Learning Automata Operating General Nonstationary Multiteacher Environment Baba and Yoshio Mogami . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1122

Estimation System Using the Neural Network e Mitsukura, Yasue Mitsukura, Minoru Fukumi,

Sigeru Omatu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1129

ruction of Facial Sltin Color in Color Images en Karungaru, Minoru Fukumi, and Norio Akamatsu . . . . . . . . . . . . . . 1135

haped Control System by Using the SPCA . . . . . shimori, Yasue Mitsukura, Shigeru Omatsu, and Kohji Kita 1142

Networks and Genetic Algorithms ntelligent Systems (11)

ent Learning Using RBF Networks ry Mechanism

zawa and Naoto Shiraga.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1149

tification Method Using the Face Shape Takimoto, Yasue Mitsukura, Norio Akamatsu, Khosla. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1157

f Moving Object Using Deformable Template kashi, Minoru Fukurni, and Norio Akamatsu . . . . . . . . . . . . . . . . . . . 1162

XLVIII Table of Contents, Part I

Thai Banltnote Recognition Using Neural Network and Continues Learning by DSP Unit Fumiaki Takeda, Lalita Sakoobunthu, and Hironobu Satou . . . . . . . . . . . . . . . 1169

Color-Identification System Using the Sandglass-Type Neural Networks Shin-ichi Ito, Kensuke Yano, Yasue Mitsukura, Norio Alcamatsu, and Rajiv Khosla.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1178

Artificial Intelligence Applications to Information Security

Secure Matchmalting of Fuzzy Criteria between Agents Javier Carbd, Jose M. Molina, and Jorge Ddvila.. . . . . . . . . . . . . . . . . . . . . . . . 1185

Finding Efficient Nonlinear Functions by Means of Genetic Programming Julio Cdsar Herndndez Castro, Pedro Isasi Vifiuela, and Cristdbal Luque del Arco-Calderdn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1192

Keystream Generator Analysis in Terms of Cellular Automata Amparo Fhter-Sabater and Dolores de la Guia-Martinez . . . . . . . . . . . . . . . . 1199

Graphic Cryptography with Pseudorandom Bit Generators and Cellular Automata Gonzalo Alvarez Marafidn, Luis Herndndez Encinas, Ascensidn Herndndez Encinas, Angel Martin del Rey, and Gerardo Rodm'guez Sdnchez . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1207

Agent-Oriented Public Key Infrastructure for Multi-agent E-service Yuh- Jong Hu and Chao- Wei Tang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1215

SOID: An Ontology for Agent-Aided Intrusion Detection Prancisco J. Martin and Enric Plaza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1222

Pseudorandom Number Generator - The Self Programmable Cellular Automata Sheng- Uei Guan and Syn Kiat Tan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1230

Soft Computing for Knowledge Extraction

Exclusion/Inclusion Fuzzy Classification Network Andrzej Bargiela, Witold Pedrycz, and Masahiro Tanaka . . . . . . . . . . . . . . . . 1236

Discovering Prediction Rules by a Neuro-fuzzy Modeling Frameworlt Giovanna Castellano, Ciro Castiello, Anna Maria Fanelli, and Corrado Mencar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1242

SAMIR: Your 3D Virtual Bookseller Fabio Zambetta, Graziano Catucci, Fabio Abbattista, and Giovanni Semeraro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1249

Table of Contents, Part I XLIX

Intelligent Data Processing in Chemical Process Systems and Plants

tion and Diagnosis of Oscillations in Process Plants . . . . . . . . . . . . . . . . . Matsuo, Hideki Sasaoka, and Yoshiyuki Yamashita 1258

-Net Based Reasoning Procedure for Fault Identification ential Operations

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ng Wang and Chuei- Tin Chang 1265

ing Procedures for Material and Energy Conversions

hiyuki Yamashita, and Kenji Hoshi . . . . . . . . . . . . . . . . . . 1273

el Based Design Rationale Supporting Environment

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o Fuchino and Yukiyasu Shimada 1281

Optimal Profit Distribution Problem Multi-Echelon Supply Chain Network: zzy Optimization Approach g-Liang Chen, Bin- Wei Wang, and Wen-Cheng Lee . . . . . . . . . . . . . . . . 1289

Experimental Study of Model Predictive Control on Artificial Neural Networks ng Chu, Po-Feng Tsai, Wen- Yen Tsai, Shi-Shang Jang, Shun-Hill Wong, Shyan-Shu Shieh, Pin-Ho Lin,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i-Jer Jiang 1296

Recognition System of Electrical Components in Scrubber Infrared Images

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o-Chao Lin and Chia-Shun Lai 1303

ear Process Modeling Based on Just-in-Time Learning

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cheng and Min-Sen Chiu.. 1311

igent Signal Processing

Vector Machines for Improved Voiceband Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Alty 1319

tive Prediction of Mobile Radio Channels Utilizing ered Random Walk Model for the Coefficients rn Ekman.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1326

tude Modulated Sinusoidal Models dio Modeling and Coding Gr~sb@ll Christensen, S@ren Vang Andersen, ren Holdt Jensen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1334

L Table of Contents, Part I

A Fast Converging Sequential Blind Source Separation Algorithm for Cyclostationary Sources M. G. Jafari, D.P. Mandic, and J.A. Chambers . . . . . . . . . . . . . . . . . . . . . . . . . . 1343

Computationally Efficient Doubletallc Detection Using Estimated Loudspeaker Impulse Responses Per Ahgren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1350

Texture Segmentation Using Semi-supervised Support Vector Machine S. Sanei.. . . . . . . . . . . . . .. .. ... ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1357

A Non-parametric Test for Detecting the Complex-Valued Nature of Time Series Temujjin Gautama, Danilo P. Mandic, and Marc M. Van Hulle . . . . . . . . . . 1364

Ontology and Multi-agent Systems Design

Domain Ontology Analysis in Agent-Oriented Requirements Engineering Paolo Donzelli and Paolo Bresciani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1372

A Framework for ACL Message nanslation for Information Agents Zhan Cui, Yang Li, and John Shepherdson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1380

An Ontology for Modelling Security: The Tropos Approach Haralambos Mouratidis, Paolo Giorgini, and Gordon Manson.. . . . . . . . . . . 1387

Towards a Pragmatic Use of Ontologies in Multi-agent Platforms Philippe Mathieu, Jean-Christophe Routier, and Yann Secq . . . . . . . . . . . . . . 1395

Ontological Foundations of Natural Language Communication in Multiagent Systems Luc Schneider and Jim Cunningham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1403

Ontology Management for Agent Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kwun-talc Ng, Qin Lu, and Yu Le 1411

A Multiagent, Distributed Approach to Service Robotics Maurizio Miozzo, Antonio Sgorbissa, and Renato Zaccaria. . . . . . . . . . . . . . . 1419

PCA and ICA Based Signal and Image Processing

PCA Based Digital Watermarking Thai D Hien, Yen- Wei Chen, and Zensho Nalcao . . . . . . . . . . . . . . . . . . . . . . . . 1427

Image Retrieval Based on Independent Components of Color Histograms Xiang- Yan Zeng, Yen- Wei Chen, Zensho Nalcao, Jian Cheng, and Hanqing Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1435

Table of Contents, Part I

Face Recognition Using Overcomplete Independent Component Analysis Jian Cheng, Hanqing Lu, Yen- Wei Chen, and Xiang- Yan Zeng . . . . . . . . . . 1443

An ICA-Based Method for Poisson Noise Reduction Xian-Hua Han, Yen- Wei Chen, and Zensho Nakao . . . . . . . . . . . . . . . . . . . . . . 1449

Recursive Approach for Real-Time Blind Source Separation of Acoustic Signals

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shuxue Ding and Jie Huang 1455

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1463