An information management system with the facility to support long-term creative thinking

Most previous creativity support systems sustain short-term temporal thinking that is separate from users’ daily activities. In this paper, we propose a system to support long-term idea-generation in daily life. The system consists of two subsystems: a management system for problems and ideas calledIdeaManager, and a personal information storage system callediBox. When information is registered in iBox, it searches related problems and ideas in IdeaManager and presents the results. Users then try to generate or enhance ideas for automatically retrieved problems or ideas using registered information as the hint. To evaluate and enhance our system, we carried out a six-week experiment. Based on the results, we give some proposals for future systems. Hirohito Shibata: He received his B.Sci. degree from Kanazawa University in 1992 and his M.Sci. degree from Osaka University in 1994. He was a software engineer at Fuji Xerox Co., Ld from 1994 to 2000. He is currently a doctoral student with Department of Advanced Interdisciplinary Studies, University of Tokyo. His research interests include human-computer interaction and computer support for creative activities. He is a member of Japanese Society for Artificial Intelligence (JSAI) and Japanese Cognitive Science Society (JCSS). Koichi Hori, D.Eng.: He received his B.Eng, M.Eng, and Dr.Eng. degrees in electronic engineering from the University of Tokyo in 1979, 1981, and 1984, respectively. In 1984, he joined National Institute of Japanese Literature, where he developed AI systems for literature studies. Since 1988, he has been with the University of Tokyo. He is currently a professor with Department of Advanced Interdisciplinary Studies, the University of Tokyo. From September 1989 to January 1990, he also held a visiting position at University of Compiegne, France. His current research interests include AI technology for supporting human creative activities, cognitive engineering and Intelligent CAD systems. He is a member of IEEE, ACM, IEICE, IPS J, JSAI, JSSST, and JCSS.     

An approach to discovering risks in development process of large and complex systems

When building a large and complex system, such as satellites, all sorts of risks have to be managed if it were to be successful. For risks in the design of an artifact, various reliability analysis techniques such as FTA or FMEA have been employed in the engineering domain. However, risks exist as well in the development process, and they could result in a failure of the system. In this paper, we present an approach to discovering risks in development process by collecting and organizing information produced during development process at low cost. We describe a prototype system called IDIMS, and show how it can be used to discover risks from e-mail communications between developers. The motivation of our work is to overcome thecapture bottleneck problem, and utilize now wasted information to improve development process. Yoshikiyo Kato: He received his B. Eng. (1998) and M.Eng. (2000) degrees in aeronautics and astronautics from The University of Tokyo. From September 1998 to July 1999, he was an exchange student at Department of Computer Science and Engineering of University of California, San Diego, and worked on software engineering tools. From May 2001 to July 2002, he was a research assistant at National Institute of Informatics (Japan). He is currently a Ph.D. student at Department of Advanced Interdisciplinary Studies of the University of Tokyo. His research interests include knowledge management, CSCW, HCI and software engineering He is a member of AAAI and JSAI. Takahiro Shirakawa: He received his B.Eng. (2000) and M.Eng. (2002) degrees in aeronautics and astronautics from the University of Tokyo. He is currently an assistant examiner at Japan Patent Office. Kohei Taketa: He received his B.Eng. (2000) and M.Eng. (2002) degrees in aeronautics and astronautics from the University of Tokyo. He is currently a software engineer at NTT Data Corp. Koichi Hori, Dr.Eng.: He received B.Eng, M.Eng, and Dr.Eng. degrees in electronic engineering from the University of Tokyo, Japan, in 1979, 1981, and 1984, respectively. In 1984, he joined National Institute of Japanese Literature where he developed AI systems for literature studies. Since 1988, he has been with the U University of Tokyo. He is currently a professor with Department of Advanced Interdisciplinary Studies, The University of Tokyo. From September 1989 to January 1990, he also held a visiting position at University of Compiegne, France. His current research interests include AI technology for supporting human creative activities, cognitive engineering, and Intelligent CAD systems. He is a member of IEEE, ACM, IEICE, IPSJ, JSAI, JSSST and JCSS.     

Web information visualization method employing immune network model for finding topic stream from document-set sequence

A Web information visualization method based on the document set-wise processing is proposed to find the topic stream from a sequence of document sets. Although the hugeness as well as its dynamic nature of the Web is burden for the users, it will also bring them a chance for business and research if they can notice the trends or movement of the real world from the Web. A sequence of document sets found on the Web, such as online news article sets is focused on in this paper. The proposed method employs the immune network model, in which the property of memory cell is used to find the topical relation among document sets. After several types of memory cell models are proposed and evaluated, the experimental results show that the proposed method with memory cell can find more topic streams than that without memory cell. Yasufumi Takama, D.Eng.: He received his B.S., M.S. and Dr.Eng. degrees from the University of Tokyo in 1994, 1996, and 1999, respectively. From 1999 to 2002 he was with Tokyo Institute of Technology, Japan. Since 2002, he has been Associate Professor of Department of Electronic Systems and Engineering, Tokyo Metropolitan Institute of Technology, Tokyo, Japan. He has also been participating in JST (Japan Science and Technology Corporation) since October 2000. His current research interests include artificial intelligence, Web information retrieval and visualization systems, and artificial immune systems. He is a member of JSAI (Japanese Society of Artificial Intelligence), IPS J (Information Processing Society of Japan), and SOFT (Japan Society for Fuzzy Theory and Systems). Kaoru Hirota, D.Eng.: He received his B.E., M.E. and Dr.Eng. degrees in electronics from Tokyo Institute of Technology, Tokyo, Japan, in 1974, 1976, and 1979, respectively. From 1979 to 1982 and from 1982 to 1995 he was with the Sagami Institute of Technology and Hosei University, respectively. Since 1995, he has been with the Interdisciplinary Graduate School of Science and Technology, Tokyo Institute of Technology, Yokohama, Japan. He is now a department head professor of Department of Computational Intelligence and Systems Science. Dr.Hirota is a member of IFSA (International Fuzzy Systems Association (Vice President 1991–1993), Treasurer 1997–2001), IEEE (Associate Editors of IEEE Transactions on Fuzzy Systems (1993–1995) and IEEE Transactions on Industrial Electronics (1996–2000)) and SOFT (Japan Society for Fuzzy Theory and Systems (Vice President 1995–1997, President 2001–2003)), and he is an editor in chief of Int. J. of Advanced Computational Intelligence.     

Public opinion channel for communities in the information age

In this paper, we propose as a new challenge a public opinion channel which can provide a novel communication medium for sharing and exchanging opinions in a community. Rather than simply developing a means of investigating public opinion, we aim at an active medium that can facilitate mutual understanding, discussion, and public opinion formation. First, we elaborate the idea of public opinion channels and identify key issues. Second, we describe our first step towards the goal using the talking virtualized egos metaphor. Finally, we discuss a research agenda towards the goal. Toyoaki Nishida, Dr.Eng.: He is a professor of Department of Information and Communication Engineering, School of Engineering, The University of Tokyo. He received the B.E., the M.E., and the Doctor of Engineering degrees from Kyoto University in 1977, 1979, and 1984 respectively. His research centers on artificial intelligence in general. His current research focuses on community computing and support systems, including knowledge sharing, knowledge media, and agent technology. He has been leading the Breakthrough 21 Nishida Project, sponsored by Ministry of Posts and Telecommunications, Japan, aiming at understanding and assisting networked communities. Since 1997, he is a trustee for JSAI (Japanese Society for Artificial Intelligence), and serves as the program chair of 1999 JSAI Annual Convention. He is an area editor (intelligent systems) of New Generation Computing and an editor of Autonomous Agents and Multiagent Systems. Nobuhiko Fujihara, Ph.D.: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E., the M.E., and the Ph.D. in Human Sciences degrees from Osaka University in 1992, 1994, and 1998 respectively. He has a cognitive psychological background. His current research focuses on: (1) cognitive psychological analysis of human behavior in a networked community, (2) investigation of information comprehension process, (3) assessment and proposition of communication tools in networking society. Shintaro Azechi: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E. and the M.E. of Human Sciences degrees from Osaka University in 1994 and 1996 respectively. He is a Doctoral Candidate of Graduate School of Human Sciences, Osaka University. His current researches focus on (1) human behavior in networking community (2) social infomation process in human mind (3) development of acessment technique for communication tools in networkingsociety. His approach is from social psychological view. Kaoru Sumi, Dr.Eng.: She is a Researcher of Breakthrough 21 Nishida Project. She received her Bachelor of Science at School of Physics, Science University of Tokyo. She received her Master of Systems Management at Graduate School of Systems Management, The university of Tsukuba. She received her Doctor of engineering at Graduate School of Engineering, The University of Tokyo. Her research interests include knowledge-based systems, creativity supporting systems, and their applications for facilitating human collaboration. She is a member of the Information Processing Society of Japan (IPSJ), the Japanese Society for Artificial Intelligence (JSAI). Hiroyuki Yano, Dr.Eng.: He is a senior research official of Kansai Advanced Research Center, Communications Research Laboratory, Ministry of Posts and Telecommunications. He received the B.E., the M.E., and the Doctor of Engineering degrees from Tohoku University in 1986, 1988, and 1993 respectively. His interests of research include cognitive mechanism of human communications. His current research focuses on discourse structure, human interface, and dialogue systems for human natural dialogues. He is a member of the Japanese Society for Artificial Intelligence, the Association for Natural Language Processing, and the Japanese Cognitive Science Society. Takashi Hirata: He is a doctor course student in Graduate School of Information Scienc at Nara Institute of Science and Technology (NAIST). He received a master of engineering from NAIST in 1998. His research interest is knowledge media and knowledge sharing. He is a member of Information Processing Society of Japan (IPSJ), Japan Association for Artificial Intelligence (JSAI) and The Institute of Systems, Control and Information Engineers (ISCIE).     

A New Approach to Humanitarian Demining

Landmines can deprive whole areas of valuable resources, and continue to kill and cause injuries years after the end of armed conflicts. Armored vehicles are used for mine clearance, but with limited reliability. The final inspection of minefields is still performed by human deminers exposed to potentially fatal accidents. The aim of this research is to introduce automation as a way to improve the final level of humanitarian demining. This paper addresses mobility and manipulation, while sensing, communication and visualization shall be discussed in detail in a subsequent paper. After analyzing the merits and limitations of previous works, a new approach to tele-operated demining is considered, using off-road buggies equipped with combustion engines, and taking into account actual field requirements. Control of the automated buggies on rough terrain is also discussed, as well as the development of a new weight-balanced manipulator for landmine clearance operations.Paulo Debenest received the B. Eng. degree in mechanical engineering (major in automation and systems) from Polytechnic School of the University of São Paulo (EPUSP), Brazil, in 1998, and the M. Eng. degree in mechanical and aerospace engineering from Tokyo Institute of Technology (Tokyo Tech), Japan, in 2002. He is currently working toward the Ph.D. degree in mechanical science engineering at Tokyo Tech and member of IEEE. His current research activities include development of demining robots and mechanical design of machines for field applications.Edwardo F. Fukushima is an assistant professor in the Department of Mechanical and Aerospace Engineering at Tokyo Institute of Technology (Tokyo Tech). He received the B. Eng. degree in electric engineering (major in electronics and telecommunications) from Federal Center of Technological Education of Paraná (CEFET-PR), Brazil, in 1989, and M. Eng. degree in mechanical science engineering from Tokyo Tech in 1993. In 1994 he became a research associate in the same institute. During Sept.–Dec. 2001 he has been a Visiting Researcher at Stanford University, and during Aug.–Sept. 2004 Visiting Scientist at University of Zurich. He is also member of RSJ. His current research activities include development of demining robots, design of controllers for intelligent robots, and development of new brushless motors and drives.Yuki Tojo is a masters course student in the Department of Mechanical and Aerospace Engineering at Tokyo Institute of Technology (Tokyo Tech). He received the B. Eng. degree in mechanical and aerospace engineering from Tokyo Tech in 2003. His research interests include design and control of weight-compensated manipulator on mobile platform. He is also member of RSJ.Shigeo Hirose was born in Tokyo in 1947. He received his B.Eng. Degree with First Class Honors in Mechanical Engineering from Yokohama National University in 1971, and his M. Eng. and Ph.D. Eng. Degrees in Control Engineering from Tokyo Institute of Technology in 1973 and 1976, respectively. From 1976 to 1979 he was a Research Associate, and from 1979 to 1992 an Associate Professor. Since 1992 he has been a Professor in the Department of Mechanical and Aerospace Engineering at the Tokyo Institute of Technology. Since 2002, he has been Honorary Professor in Shengyang Institute of Technology, the Chinese Academy of Sciences. Fellow of JSME and IEEE. He is engaged in creative design of robotic systems. Prof. Hirose has been awarded more than twenty prizes.     

Information gathering and searching approaches on the Web

The information accessible through the Internet is increasing explosively as the Web is getting more and more widespread. In this situation, the Web is indispensable information resource for both of information gathering and information searching. Though traditional information retrieval techniques have been applied to information gathering and searching in the Web, they are insufficient for this new form of information source. Fortunately some Al techniques can be straightforwardly applicable to such tasks in the Web, and many researchers are trying this approach. In this paper, we attempt to describe the current state of information gathering and searching technologies in the Web, and the application of AI techniques in the fields. Then we point out limitations of these traditional and AI approaches and introduce two aapproaches: navigation planning and a Mondou search engine for overcoming them. The navigation planning system tries to collect systematic knowledge, rather than Web pages, which are only pieces of knowledge. The Mondou search engine copes with the problems of the query expansion/modification based on the techniques of text/web mining and information visualization. Seiji Yamada, Dr. Eng.: He received the B.S., M.S. and Ph.S. degrees in control engineering and artificial intelligence from Osaka University, Osaka, Japan, in 1984, 1986 and 1989, respectively. From 1989 to 1991, he served as a Research Associate in the Department of Control Engineering at Osaka University. From 1991 to 1996, he served as a Lecturer in the Institute of Scientific and Industrial Research at Osaka University. In 1996, he joined the Department of Computational Intelligence and Systems Science at Tokyo Institute of Technology, Yokohama, Japan, as an Associate Professor. His research interests include artificial intelligence, planning, machine learning for a robotics, intelligent information retrieval in the WWW, human computer interaction, He is a member of AAAI, IEEE, JSAI, RSJ and IEICE. Hiroyuki Kawano, Dr.Eng.: He is an Associate Professor at the Department of Systems Science, Graduate School of Informatics, Kyoto University, Japan. He obtained his B.Eng. and M.Eng. degrees in Applied Mathematics and Physics, and his Dr.Eng. degree in Applied Systems Science from Kyoto University. His research interests are in advanced database technologies, such as data mining, data warehousing, knowledge discovery and web search engine (Mondou). He has served on the program committees of several conferences in the areas of Data Base Systems, and technical committes of advanced information systems.     

A-SATCHMORE: SATCHMORE with availability checking

We present an improvement of SATCHMORE, calledA-SATCHMORE, by incorporating availability checking into relevancy. Because some atoms unavailable to the further computation are also marked relevant, SATCHMORE suffers from a potential explosion of the search space. Addressing this weakness of SATCHMORE, we show that an atom does not need to be marked relevant unless it is available to the further computation and no non-Horn clause needs to be selected unless all its consequent atoms are marked availably relevant, i.e., unless it is totally availably relevant. In this way,A-SATCHMORE is able to further restrict the ues of non-Horn clauses (therefore to reduce the search space) and makes the proof more goal-oriented. Our theorem prover,A-SATCHMORE, can be simply implemented in PROLOG based on SATCHMORE. We discuss how to incorporate availability cheeking into relevancy, describe our improvement and present the implementation. We also prove that our theorem prover is sound and complete, and provide examples to show the power of our availability approach. This research is supported in part by the Japanese Ministry of Education and the Artificial Intelligence Research Promotion Foundation. Lifeng He, Ph.D: He received the B. E. degree from Northwest Institute of Light Industry, China, in 1982, the M. S. and Ph.D. degrees in AI and computer science from Nagoya Institute of Technology, Japan, in 1994 and 1997, respectively. He currently works at the Institute of Open System in Nagoya, Japan. His research interests include automated reasoning, theorem proving, logic programming, knowledge bases, multi-agent cooperation and modal logic. Yuyan Chao, M. S.: She received the B. E. degree from Northwest Institute of Light Industry, China, in 1984, and the M. S. degree from Nagoya University, Japan, in 1997. She is currently a doctoral candidate in the Department of Human Information, Nagoya University. Her research interests include image processing, graphic understanding, CAD and theorem proving. Yuka Shimajiri, M. S.: She currently works as a Assistant Professor in Department of Artificial Intelligence and Computer Science at the Nagoya Institute of Technology. She received her B.Eng. and M.Eng. from the Nagoya Institute of Technology in 1994 and 1996, respectively. Her current research interests include logic programming and automated deduction. She is a member of IPSJ and JSAI. Hirohisa Seki, Ph.D.: He received the B. E., M. E. and Ph.D degrees from the University of Tokyo in 1979, 1981 and 1991 respectively. He joined the Central Research Laboratory of Mitsubishi Electric Corporation in 1981. From 1985 to 1989, he was with the Institute for New Generation Computer Technology (ICOT). Since 1992, he has been an Associate Professor in the Department of AI and Computer Science at Nagoya Institute of Technology. His current research interests include logic programming, deductive databases and automated deduction. He is a member of ACM, IEEE, IPSJ and JSAI. Hidenori Itoh, Ph.D.: He received the B. S. degree from Fukui University, in 1969, the M. S. degree and Ph.D degree from Nagoya University, Japan, in 1971 and 1974, respectively. From 1974 to 1985, he worked at Nippon Telephone and Telegraph Laboratories, developing operating systems. From 1985 to 1989, he was with the Institute for New Generation Computer Technology, developing knowledge base systems. Since 1989, he has become a professor at the Nagoya Institute of Technology. His current research interests include image processing, parallel computing, fuzzy logic and knowledge processing.     

A study on effects of market systems in an artificial market

In an artificial market approach with multi-agent systems, the static equilibrium concept is often used in market systems to approximate continuous market auctions. However, differences between the static equilibrium concept and continuous auctions have not been discussed in the context of an artificial market study. In this paper, we construct an artificial market model with both of them, namely, the Itayose and Zaraba method, and show simple characteristic differences between these methods based on computer simulations. The result indicates the further need to model the market system by studying artificial markets. Hidenori Kawamura, Ph.D.: He received Ph.D. degree from Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University, Japan in 2000. He is currently an instructor in Graduate School of Information Science and Technology, Hokkaido University, Japan. His research interests include multiagent systems, mass user support, artificial intelligence, complex systems, and tourism informatics. He is a member of IPSJ, JSAI, IEICE, ORSJ, JSTI and AAAI. Yasushi Okada, Ph.D.: He is a master course student in Graduate School of Engineering, Hokkaido University, Japan. He studies multiagent systems. Azuma Ohuchi, Ph.D.: He received his Ph.D. degree in 1974 from Hokkaido University. He is currently the professor in Graduate School of Information Science and Technology, Hokkaido University Japan. His research interstes include systems information engineering, artificial intelligence, complex systems, tourism informatics and medical systems. He is a member of the IPSJ, JSAI, IEEJ, ORSJ, Soc. Contr. Eng., Jap. OR Soc., Soc. Med. Informatics, Hosp. Manag., JSTI and IEEE-SMC. Koichi Kurumatani, Ph.D.: He received his Ph.D. Degree in 1989 from The University of Tokyo. He is currently a leader of Multiagent Research Team in Cyber Assist Research Center (CARC), National Institute of Advanced Industrial Science and Technology (AIST), Japan. His research interests include multiagent systems and mass user support. He is a member of JSAI, IPSJ, JSTI and AAAI.     

An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems

In this paper we propose a new fast learning algorithm for the support vector machine (SVM). The proposed method is based on the technique of second-order cone programming. We reformulate the SVM's quadratic programming problem into the second-order cone programming problem. The proposed method needs to decompose the kernel matrix of SVM's optimization problem, and the decomposed matrix is used in the new optimization problem. Since the kernel matrix is positive semidefinite, the dimension of the decomposed matrix can be reduced by decomposition (factorization) methods. The performance of the proposed method depends on the dimension of the decomposed matrix. Experimental results show that the proposed method is much faster than the quadratic programming solver LOQO if the dimension of the decomposed matrix is small enough compared to that of the kernel matrix. The proposed method is also faster than the method proposed in (S. Fine and K. Scheinberg, 2001) for both low-rank and full-rank kernel matrices. The working set selection is an important issue in the SVM decomposition (chunking) method. We also modify Hsu and Lin's working set selection approach to deal with large working set. The proposed approach leads to faster convergence. Rameswar Debnath is a Ph.D candidate at the University of Electro-Communications, Tokyo, Japan and also a lecturer of the Computer Science & Engineering Discipline at Khulna University, Bangladesh. He received the bachelor's degree in computer science and engineering from Khulna University in 1997 and masters of engineering degree in communication and systems from the University of Electro-Communications in 2002. His research interests include support vector machines, artificial neural networks, pattern recognition, and image processing. Masakazu Muramatsu is an associate professor of the Department of Computer Science at the University of Electro-Communications, Japan. He received a bachelor's degree from the University of Tokyo in 1989, master's degree in engineering from University of Tokyo in 1991, and Ph.D from the Graduate University for Advanced Studies in 1994. He was an assistant professor of the Department of Mechanical Engineering at Sophia University from 1994 to 2000, when he moved to the current university. His research interests include mathematical programming, second-order cone programming and its application to machine learning. Haruhisa Takahashi was born in Shizuoka Prefecture Japan, on March 31, 1952. He graduated from the University of Electro-Communications. He received the Dr Eng. degree from Osaka University. He was a faculty member of the Department of Computer Science and Engineering at Toyohashi University of Technology from 1980 to 1986. Since 1986, he has been with the University of Electro-Communications where he is currently professor of the Department of Information and Communication Engineering. He was previously engaged in the fields of nonlinear network theory, queueing theory and performance evaluation of communication systems. His current research includes learning machines, artificial neural networks, and cognitive science.     

An agent architecture for strategy-centric adaptive QoS control in flexible videoconference system

In this paper, we propose an agent architecture to improve flexibility of a videoconference system with strategy-centric adaptive QoS (Quality of Service) control mechanism. The proposed architecture realizes more flexibility by changing their QoS control strategies dynamically. To switch the strategies, system considers the properties of problems occurred on QoS and status of problem solving process. This architecture is introduced as a part of knowledge base of agent that deals with cooperation between software module of videoconference systems. We have implemented the mechanism, and our prototype system shows its capability of flexible problem solving against the QoS degradation, along with other possible problems within the given time limitation. Thus we confirmed that the proposed architecture can improve its flexibility of a videoconference system compared to traditional systems. Takuo Suganuma, Dr.Eng.: He is a research associate of Research Institute of Electrical Communication of Tohoku University. He received a Dr.Eng. degree from Chiba Institute of Technology in 1997. His research interests include agent-based computing and design methodology for distributed systems. He is a member of IPSJ, IEICE and IEEE. SungDoke Lee: He is a Ph.D. Student in the Graduate School of Information Sciences in Tohoku University. He received his MEng degree at Chonbuk National University, Korea in 1991. His research interests include Flexible Network and Knowledge of Agent. Tetsuo Kinoshita, Dr.Eng.: He is an associate professor of Research Institute of Electrical Communication of Tohoku University. He received a Dr.Eng. degree in information engineering from Tohoku University, Japan. His research interests include knowledge engineering, cooperative distributed processing and agent-based computing. He received the the IPSJ Best Paper Award in 1997, etc. He is a member of IPSJ, IEICE, JSAI, AAAI, ACM and IEEE. Norio Shiratori, Dr.Eng.: After receiving his Dr.Eng degree at Tohoku University, he joined the Research Institute of Electrical Communication of Tohoku University in 1977, and is now a professor at the same University. He has been engaged in research on distributed processing system, and flexible intelligent network. He received the 25th Anniversary of IPSJ Memorial Prize-Winning Paper Award in 1985, the 6th Telecommunications Advancement Foundation Incorporation Award in 1991, the Best Paper Award of ICOIN-9 in 1994, the IPSJ Best Paper Award in 1997, etc. He has been named a Fellow of the IEEE for his contributions to the field of computer communication networks.     

Toward a real-world knowledge medium: Building a guidance system for exhibition tours

We propose a notion of a real-world knowledge medium by presenting our ongoing project to build a guidance system for exhibition tours. In order to realize a knowledge medium usable in the real world, we focus on the context-awareness of users and their environments. Our system is a personal mobile assistant that provides visitors touring exhibitions with information based on their spatial/temporal locations and individual interests. We also describe an application of knowledge sharing used in the actual exhibition spaces. Yasuyuki Sumi, Ph.D.: He has been a researcher at ATR Media Integration & Communications Research Laboratories since 1995. His research interests include knowledge-based systems, creativity supporting systems, and their applications for facilitating human collaboration. He received his B. Eng. degree from Waseda University in 1990, and M. Eng. and D. Eng. degrees in information engineering from the University of Tokyo in 1992 and 1995, respectively. He is a member of Institutes of Electronics, Information and Communication Engineers (IEICE) of Japan, the Information Processing Society of Japan (IPSJ), the Japanese Society for Artificial Intelligence (JSAI), and American Association for Artificial Intelligence (AAAI). Kenji Mase, Ph.D.: He received the B.S. degree in Electrical Engineering and the M.S. and Ph.D. degrees in Information Engineering from Nagoya University in 1979, 1981 and 1992 respectively. He has been with ATR (Advanced Telecommunications Research Institute) Media Integration & Communications Research Laboratories since 1995 and is currently the head of Department 2. He joined the Nippon Telegraph and Telephone Corporation (NTT) in 1981 and had been with the NTT Human Interface Laboratories. He was a visiting researcher at the Media Laboratory, MIT in 1988–1989. His research interests include image sequence processing of human actions, computer graphics, computer vision, artificial intelligence and their applications for computer-aided communications and human-machine interfaces. He is a member of the Information Processing Society of Japan (IPSJ), Institutes of Electronics, Information and Communication Engineers (IEICE) of Japan and IEEE Computer Society.     

Enhanced motion parameters estimation for an active vision system

In this paper, we present an enhanced approach for estimating 3D motion parameters from 2D motion vector fields. The proposed method achieves valuable reduction in computational time and shows high robustness against noise in the input data. The output of the algorithm is part in a multiobject segmentation approach implemented in an active vision system. Hence, the improvement in the motion parameters estimation process leads to speed-up in the overall segmentation process. The text was submitted by the authors in English. Mohamed Shafik obtained his B.Sc. in mechanical engineering at the University of Banha. In 2004 he earned an Information Technology Diploma in Mechatronics from the Information Technology Institute (ITI). In 2006 he obtained his M.Eng. in applied mechatronics at the University of Paderborn. Since 2006, he is a PhD student and a scientific assistant in the GET Lab. His research interests focus on robotic vision, neural networks, and mechatronic systems. Baerbel Mertsching studied electrical engineering and obtained her PhD at the University of Paderborn. Between 1994 and 2003, she was professor of computer science at the University of Hamburg. In 2003 she returned to the University of Paderborn where she is now professor of electrical engineering and director of the GET Lab. Her research interests focus on cognitive systems engineering, especially active vision systems, and microelectronics for image and speech processing. She has been a member of a variety of scientific councils and editorial boards and is author of more than 120 scientific publications.     

Pitch-Dependent Identification of Musical Instrument Sounds

This paper describes a musical instrument identification method that takes into consideration the pitch dependency of timbres of musical instruments. The difficulty in musical instrument identification resides in the pitch dependency of musical instrument sounds, that is, acoustic features of most musical instruments vary according to the pitch (fundamental frequency, F0). To cope with this difficulty, we propose an F0-dependent multivariate normal distribution, where each element of the mean vector is represented by a function of F0. Our method first extracts 129 features (e.g., the spectral centroid, the gradient of the straight line approximating the power envelope) from a musical instrument sound and then reduces the dimensionality of the feature space into 18 dimension. In the 18-dimensional feature space, it calculates an F0-dependent mean function and an F0-normalized covariance, and finally applies the Bayes decision rule. Experimental results of identifying 6,247 solo tones of 19 musical instruments shows that the proposed method improved the recognition rate from 75.73% to 79.73%. This research was partially supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Grant-in-Aid for Scientific Research (A), No.15200015, and Informatics Research Center for Development of Knowledge Society Infrastructure (COE program of MEXT, Japan). Tetsuro Kitahara received the B.S. from Tokyo University of Science in 2002 and the M.S. from Kyoto University in 2004. He is currently a Ph.D. course student at Graduate School of Informatics, Kyoto University. Since 2005, he has been a Research Fellow of the Japan Society for the Promotion of Science. His research interests include music informatics. He recieved IPSJ 65th National Convention Student Award in 2003, IPSJ 66th National Convention Student Award and TELECOM System Technology Award for Student in 2004, and IPSJ 67th National Convention Best Paper Award for Young Researcher in 2005. He is a student member of IPSJ, IEICE, JSAI, ASJ, and JSMPC. Masataka Goto received his Doctor of Engineering degree in Electronics, Information and Communication Engineering from Waseda University, Japan, in 1998. He then joined the Electrotechnical Laboratory (ETL; reorganized as the National Institute of Advanced Industrial Science and Technology (AIST) in 2001), where he has been engaged as a researcher ever since. He served concurrently as a researcher in Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Corporation (JST) from 2000 to 2003, and an associate professor of the Department of Intelligent Interaction Technologies, Graduate School of Systems and Information Engineering, University of Tsukuba since 2005. His research interests include music information processing and spoken language processing. Dr. Goto received seventeen awards including the IPSJ Best Paper Award and IPSJ Yamashita SIG Research Awards (MUS and SLP) from the Information Processing Society of Japan (IPSJ), Awaya Prize for Outstanding Presentation and Award for Outstanding Poster Presentation from the Acoustical Society of Japan (ASJ), Award for Best Presentation from the Japanese Society for Music Perception and Cognition (JSMPC), WISS 2000 Best Paper Award and Best Presentation Award, and Interaction 2003 Best Paper Award. He is a member of the IPSJ, ASJ, JSMPC, Institute of Electronics, Information and Communication Engineers (IEICE), and International Speech Communication Association (ISCA). Hiroshi G. Okuno received the B.A. and Ph.D from the University of Tokyo in 1972 and 1996, respectively. He worked for Nippon Telegraph and Telephone, Kitano Symbiotic Systems Project, and Tokyo University of Science. He is currently a professor at the Department of Intelligence Technology and Science, Graduate School of Informatics, Kyoto University. He was a visiting scholar at Stanford University, and a visiting associate professor at the University of Tokyo. He has done research in programming languages, parallel processing, and reasoning mechanism in AI, and he is currently engaged in computational auditory scene analysis, music scene analysis and robot audition. He received the best paper awards from the Japanese Society for Artificial Intelligence and the International Society for Applied Intelligence, in 1991 and 2001, respectively. He edited with David Rosenthal “Computational Auditory Scene Analysis” from Lawrence Erlbaum Associates in 1998 and with Taiichi Yuasa “Advanced Lisp Technology” from Taylor and Francis Inc. in 2002. He is a member of IPSJ, JSAI, JSSST, JSCS, ACM, AAAI, ASA, and IEEE.     

Algebraic retrieval of fragmentarily indexed video

When dealing with long video data, the task of identifying and indexing all meaningful subintervals that become answers to some queries is infeasible. It is infeasible not only when done by hand but even when done by using latest automatic video indexing techniques. Whether manually or automatically, it is only fragmentary video intervals that we can identify in advance of any database usage. Our goal is to develop a framework for retrieving meaningful intervals from such fragmentarily indexed video data. We propose a set of algebraic operations that includes ourglue join operations, with which we can dynamically synthesize all the intervals that are conceivably relevant to a given query. In most cases, since these operations also produce irrelevant intervals, we also define variousselection operations that are useful in excluding them from the answer set. We also show the algebraic properties possessed by those operations, which establish the basis of an algebraic query optimization. Katsumi Tanaka, D. Eng.: He received his B.E., M.E., and D.Eng. degrees in information science from Kyoto University, in 1974, 1976, and 1981, respectively. Since 1994, he is a professor of the Department of Computer and Systems Engineering and since 1997, he is a professor of the Division of Information and Media Sciences, Graduate School of Science and Technology, Kobe University. His research interests include object-oriented, multimedia and historical databases abd multimedia information systems. He is a member of the ACM, IEEE Computer Society and the Information Processing Society of Japan. Keishi Tajima, D.Sci.: He received his B.S, M.S., and D.S. from the department of information science of University of Tokyo in 1991, 1993, and 1996 respectively. Since 1996, he is a Research Associate in the Department of Computer and Systems Engineering at Kobe University. His research interests include data models for non-traditional database systems and their query languages. He is a member of ACM, ACM SIGMOD, Information Processing Society of Japan (IPSJ), and Japan Society for Software Science and Technology (JSSST). Takashi Sogo, M.Eng.: He received B.E. and M.E. from the Department of Computer and Systems Engineering, Kobe University in 1998 and 2000, respectively. Currently, he is with USAC Systems Co. His research interests include video database systems. Sujeet Pradhan, D.Eng.: He received his BE in Mechanical Engineering from the University of Rajasthan, India in 1988, MS in Instrumentation Engineering in 1995 and Ph.D. in Intelligence Science in 1999 from Kobe University, Japan. Since 1999 May, he is a lecturer of the Department of Computer Science and Mathematics at Kurashiki University of Science and the Arts, Japan. A JSPS (Japan Society for the Promotion of Science) Research Fellow during the period between 1997 and 1999, his research interests include video databases, multimedia authoring, prototypebased languages and semi-structured databases. Dr. Pradhan is a member of Information Processing Society of Japan.     

Trends of internet auctions and agent-mediated Web commerce

Electronic Commerce (EC) is a promising field for applying agent and Artificial Intelligence technologies. In this article, we give an overview of the trends of Internet auctions and agent-mediated Web commerce. We describe the theoretical backgrounds of auction protocols and introduce several Internet auction sites. Furthermore, we describe various activities aimed toward utilizing agent technologies in EC and the trends in standardization efforts on agent technologies. Makoto Yokoo, Ph.D.: He received the B.E. and M.E. degrees in electrical engineering, in 1984 and 1986, respectively, from the University of Tokyo, Japan, and the Ph.D. degree in information and communication engineering in 1995 from the University of Tokyo, Japan. He is currently a distinguished technical member in NTT Communication Science Laboratories, Kyoto, Japan. He was a visiting research scientist at the Department of Electrical Engineering and Computer Science, the University of Michigan, Ann Arbor, from 1990 to 1991. His current research interests include multi-agent systems, search, and constraint satisfaction. Satoru Fujita, D.Eng.: He received his B.E. and M.E. degrees in electronic engineering from the University of Tokyo in 1984 and 1986, respectively. He also received his D.Eng. from the University of Tokyo in 1989 for his research on context comprehension in natural language understanding. He joined NEC Corporation in 1989, and is now a principal researcher of Internet Systems Research Laboratories of NEC. He is engaged in research on mobile agents, distributed systems and Web services.     

The superstructure toward open bioinformatics grid

The grid design strongly depends on not only a network infrastructure but also a superstructure, that is, a social structure of virtual organizations where people trust each other, share resources and work together. Open Bioinformatics Grid (OBIGrid) is a grid aimed at building a cooperative bioinformatics environment for computer sicentists and biologists. In October 2003, OBIGrid consisted of 293 nodes with 492 CPUs provided by 27 sites at universities, laboratories and other enterprises, connected by a virtual private network over the Internet. So many organizations have participated because OBIGrid has been conscious of constructing a superstructure on a grid as well as a grid infrastructure. For the benefit of OBIGrid participants, we have developed a series of life science application services: an open bioinformatics environment (OBIEnv), a scalable genome database (OBISgd), a genome annotation system (OBITco), a biochemical network simulator (OBIYagns), and to name a few. Akihiko Konagaya, Dr.Eng.: He is Project Director of Bioinformatics Group, RIKEN Genomic Sciences Center. He received his B.S. and M.S. from Tokyo Institute of Technology in 1978 and 1980 in Informatics Science, and joined NEC Corporation in 1980, Japan Advanced Institute of Science and Technology in 1997, RIKEN GSC in 2003. His research covers wide area from computer architectures to bioinformatics. He has been much involved into the Open Bioinformatics Grid project since 2002. Fumikazu Konishi, Dr.Eng.: He is researcher at Bioinformatics Group, RIKEN Genomic Sciences Center since 2000. He received his M.S. (1996) and Ph.D. (2001) from Tokyo Metropolitan Institute of Technology. He served as an assistant in Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology since 2000. He also works in Structurome Research Group, RIKEN Harima Institute from 2001. His research interests include concurrent engineering, bioinformatics and the Grid. He has deeply affected to the design of OBIGrid. Mariko Hatakeyama, Ph.D.: She recieved her Ph.D. degree from Tokyo University of Agriculture and Technology. She is Research Scientist at Bioinformactis Group, RIKEN Genomic Sciences Center. Her research topics are: microbiology, enzymology and signal transduction of mammalian cells. She is now working on computational simulation of signal transduction systems and on thermophilic bacteria project. Kenji Satou, Ph.D.: He is Associate Professor of School of Knowledge Science at Japan Advanced Institute of Science and Technology. He received B.S., M.E. and Ph.D. degrees from Kyushu University, in 1987, 1989 and 1995 respectively. For each degree, he majored in computer engineering. His research interests have progressed from deductive database application through data mining to Grid computing and natural language processing. His current field of research is bioinformatics. He prefers set-oriented manner of thinking, and usually wonders how he can construct an intelligent-looking system based on large amount of heterogeneous data and computer resources.     

A grid-oriented genetic algorithm framework for bioinformatics

In this paper, we propose a framework for enabling for researchers of genetic algorithms (GAs) to easily develop GAs running on the Grid, named “Grid-Oriented Genetic algorithms (GOGAs)”, and actually “Gridify” a GA for estimating genetic networks, which is being developed by our group, in order to examine the usability of the proposed GOGA framework. We also evaluate the scalability of the “Gridified” GA by applying it to a five-gene genetic network estimation problem on a grid testbed constructed in our laboratory. Hiroaki Imade: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2001. He received the M.S. degree in information systems from the Graduate School of Engineering, The University of Tokushima in 2003. He is now in Doctoral Course of Graduate School of Engineering, The University of Tokushima. His research interests include evolutionary computation. He currently researches a framework to easily develop the GOGA models which efficiently work on the grid. Ryohei Morishita: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2002. He is now in Master Course of Graduate School of Engineering, The University of Tokushima, Tokushima. His research interest is evolutionary computation. He currently researches GA for estimating genetic networks. Isao Ono, Ph.D.: He received his B.S. degree from the Department of Control Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 1994. He received Ph.D. of Engineering at Tokyo Institute of Technology, Yokohama, in 1997. He worked as a Research Fellow from 1997 to 1998 at Tokyo Institute of Technology, and at University of Tokushima, Tokushima, Japan, in 1998. He worked as a Lecturer from 1998 to 2001 at University of Tokushima. He is now Associate Professor at University of Tokushima. His research interests include evolutionary computation, scheduling, function optimization, optical design and bioinformatics. He is a member of JSAI, SCI, IPSJ and OSJ. Norihiko Ono, Ph.D.: He received his B.S. M.S. and Ph.D. of Engineering in 1979, 1981 and 1986, respectively, from Tokyo Institute of Technology. From 1986 to 1989, he was Research Associate at Faculty of Engineering, Hiroshima University. From 1989 to 1997, he was an associate professor at Faculty of Engineering, University of Tokushima. He was promoted to Professor in the Department of Information Science and Intelligent Systems in 1997. His current research interests include learning in multi-agent systems, autonomous agents, reinforcement learning and evolutionary algorithms. Masahiro Okamoto, Ph.D.: He is currently Professor of Graduate School of Systems Life Sciences, Kyushu University, Japan. He received his Ph.D. degree in Biochemistry from Kyushu University in 1981. His major research field is nonlinear numerical optimization and systems biology. His current research interests cover system identification of nonlinear complex systems by using evolutional computer algorithm of optimization, development of integrated simulator for analyzing nonlinear dynamics and design of fault-tolerant routing network by mimicking metabolic control system. He has more than 90 peer reviewed publications.     

Calculating accumulations

Theaccumulation strategy consists of generalizing a function over an algebraic data structure by inclusion of an extra parameter, anaccumulating parameter, for reusing and propagating intermediate results. However, there remain two major difficulties in this accumulation strategy. One is to determinewhere andwhen to generalize the original function. The other, surprisingly not yet receiving its worthy consideration, is how to manipulate accumulations. To overcome these difficulties, we propose to formulate accumulations ashigher order catamorphisms, and provide several general transformation rules for calculating accumulations (i.e., finding and manipulating accumulations) bycalculation-based (rather than a search-based) program transformation methods. Some examples are given for illustration. Zhenjiang Hu, Dr.Eng.: He is an Assistant Professor in Information Engineering at the University of Tokyo. He received his BS and MS in Computer Science from Shanghai Jiao Tong University in 1988 and 1990 respectively, and his Dr. Eng. degree in Information Engineering from the University of Tokyo in 1996. His current research concerns programming languages, functional programming, program transformation, and parallel processing. Hideya Iwasaki, Dr.Eng.: He is an Associate Professor in Information Engineering at the University of Tokyo. He received the M.E. degree in 1985, the Dr. Eng. degree in 1988 from the University of Tokyo. His research interests are list processing languages, functional languages, parallel processing, and constructive algorithmics. Masato Takeichi, Dr.Eng.: He is Professor in Mathematical Engineering and Information Engineering at the University of Tokyo since 1993. After graduation from the University of Tokyo, he joined the faculty at the University of Electro-Communications in Tokyo before he went back to work at the University of Tokyo in 1987. His research concerns the design and implementation of functional programming languages, and calculational program transformation systems.     

Computation of Peak Output for Inputs Restricted in L2 and L∞ Norms Using Finite Difference Schemes and Convex Optimization

Control systems designed by the principle of matching gives rise to problems of evaluating the peak output. This paper proposes a practical method for computing the peak output of linear time-invariant and non-anticipative systems for a class of possible sets that are characterized with many bounding conditions on the two- and/or the infinity-norms of the inputs and their derivatives. The original infinite-dimensional convex optimization problem is approximated as a large-scale convex programme defined in a Euclidean space, which are associated with sparse matrices and thus can be solved efficiently in practice. The numerical results show that the method performs satisfactorily, and that using a possible set with many bounding conditions can help to reduce the design conservatism and thereby yield a better match.