Keynotes
Keynote Speaker: Prof. Yuzuru Tanaka
Title: Proximity-based ad hoc Federation among Smart Objects and its Applications

Keynote Speaker: Prof. Yukio Ohsawa
Title: Chance Discovery as Value Sensing by Data based Meta Cognition

Keynote Speaker: Prof. Hisao Ishibuchi
Title: Evolutionary Multiobjective Optimization and Multiobjective Fuzzy System Design 

Keynote Speaker: Professor Yuzuru Tanaka
Title: Proximity-based ad hoc Federation among Smart Objects and its Applications

E-mail: tanaka@meme.hokudai.ac.jp
Meme Media Laboratory, Hokkaido University
Sapporo, 060-8628 Japan

Abstract: Information system environments today are rapidly expanding their scope of subject resources, their geographical distribution, their reorganization, and their advanced utilization. Currently, this expansion is understood only through its several similar but different aspects, and referred to by several different stereotyped terms such as ubiquitous computing, pervasive computing, mobile computing, and sensor networks. No one has clearly defined this expansion as a whole. It is so complex and has extremely versatile potentialities. In such an expanded information environment, some resources are accessible through the Web, while others are accessible only through peer-to-peer ad hoc networks. Any advanced utilization of some of these resources needs a way to select them, and a way to make them interoperable with each other to perform a desired function. 

This talk focuses on the ad hoc federation of intellectual resources on smart objects, and first reviews our formal model of autonomic proximity-based federation among smart objects including both physical smart objects with wireless network connectivity and virtual smart objects such as services on the Web. Then it proposes some application frameworks based on this model. Smart objects here denote computing devices such as RFID tag chips, smart chips with sensors and/or actuators that are embedded in pervasive computing environments such as home, office, and social infrastructure environments, mobile PDAs, intelligent electronic appliances, embedded computers, and access points with network servers. 

Our model hides any details on how functions of each smart object are implemented, and focuses on abstract level modeling of its federation interface. Each smart object is modeled as a set of ports, each of which represents an I/O interface for a function of this smart object to interoperate with some function of another smart object. Here, we consider the matching of service-requesting queries and service-providing capabilities that are respectively represented as service-requesting ports and service-providing ports, instead of the matching of a service requesting message with a service-providing message. 

In the preceding research studies, federation mechanisms were described in the codes that define the behaviors of participating smart objects, and were not separated from these codes to be discussed independently from them. Our abstract model allows us to discuss both the matching mechanism for federation and complex federation among smart objects in terms of a simple mathematical model. Applications can be described from the view point of their federation structures. This enables us to extract a common substructure from applications sharing the same typical federation scenario. Such an extracted substructure may work as an application framework for this federation scenario. 

This talk shows how our formal model of federation enables us to describe application frameworks not only for stereotyped applications such as location-transparent service continuation but also novel applications using glue objects and confederators.

Bio: Yuzuru Tanaka is a professor at the Department of Computer Science, Graduate School of Information Science and Technology, Hokkaido University, and the director of Meme Media Laboratory, Hokkaido University. He is also a professor of National Institute of Informatics. His research areas covered multiprocessor architectures, database schema-design theory, hardware algorithms for searching and sorting, multiport memory architectures, database machine architectures, full text search of document image files, and automatic cut detection in movies and full video search. His current research areas cover meme media architectures, knowledge federation frameworks, and their application to e-Science based on meme media application frameworks such as database and Web visualization frameworks and virtual experiment environment frameworks. He worked as a board member of Japanese Society for Artificial Intelligence (1991-1994), a councilor of Japanese Society for Artificial Intelligence (1995- ), a board member of Information Processing Society of Japan (1995-1996, 1999-2000, 2008-), an associate member of Japanese Academy of Science (2006- ), and an advisory board member of NTT Research Laboratory (2004- )... He is currently involved in EU’s Integrated Project ACGT (Advancing Clinico-Genomic Trials on Cancer).

Keynote Speaker: Professor Yukio Ohsawa
Title: Chance Discovery as Value Sensing by Data based Meta Cognition

E-mail: ohsawa@sys.t.u-tokyo.ac.jp
Dept. Systems Innovation, School of Engineering,
The University of Tokyo, 113-8656 Japan

Abstract: Value-sensing means to feel associated with the content of one's awareness. This concept has been defined in the literature of educational psychology, as a particular dimension of human awareness. It is meaningful to extend this concept to the aspect of creativity in business. The "value" here can be dealt with as a new variable which business workers create from their interaction with the dynamic
environment, on which they intentionally and sub-intentionally redesign the market sustainably. Data mining and data visualization can provide useful tools for aiding
marketers'/designers' sensitivity of emerging values of consumers/users.  This leads to the finding of essential scenarios corresponding to useful strategies for the
designing and marketing of products.

Bio: Yukio Ohsawa is an associate professor in the School of Engineering, The University of Tokyo.  He received Ph.D in Communication and Information Engineering from The University of Tokyo. He worked also for School of Engineering Science in Osaka University (research associate, 1995-1999), Graduate School of
Business Sciences in University of Tsukuba (associate professor, 1999-2005), and Japan Science and Technology Corporation (JST researcher, 2000-2003). He initiated the research area of Chance Discovery, defined "discovery of events significant for decision making" in 1999, and series of international meetings (conference sessions and workshops), e.g., the fall symposium of the American
Association of Artificial Intelligence (2001). He edited the first book on "Chance Discovery" (2003) and "Chance Discoveries in Real World Decision Making" (2003) published by Springer Verlag, and special issues in international and Japanese (domestic) journals. Chance discovery is growing: Journal issues has been published from the international journals, e.g., Journal of Contingencies and Crisis Management (2001), New Generation Computing (2003), New Mathematics and Natural Computing (2005), and from Journal on Soft Computing in conjunction with the special issue on Web Intelligence (2006), etc, and new books are appearing. He is in the editorial board the Japanese Society of AI and the planning board of New Generation Computing, and is the TC chair of IEEE-SMC technical committee of Information Systems for Design & Marketing. 

Keynote Speaker: Professor Hisao Ishibuchi
Title: Evolutionary Multiobjective Optimization and Multiobjective Fuzzy System Design 

E-mail: hisaoi@cs.osakafu-u.ac.jp
Department of Computer Science and Intelligent Systems
Osaka Prefecture University, Sakai, Osaka, Japan
http://www.ie.osakafu-u.ac.jp/~hisaoi/ci_lab_e/personal/ishibuchi  

Abstract: In his talk, Prof. Ishibuchi will present his research on Evolutionary Multiobjective Optimization (EMO) and Multiobjective Fuzzy System Design. His talk is divided into two parts. The first part is on EMO algorithms. First he will introduce some basic concepts in multiobjective optimization such as Pareto dominance and Pareto optimality. Next he will explain common features of well-known EMO algorithms such as NSGA-II and SPEA. Then he will show difficulties in the handling of many-objective problems by EMO algorithms. After that, he will explain some approaches to the scalability improvement of EMO algorithms to many-objective problems. In the second part of his talk, the focus shall be on the application of EMO algorithms to the design of fuzzy rule-based systems. First he will introduce the concept of accuracy-complexity tradeoff in the design of fuzzy rule-based systems. Next he will explain an EMO approach to multiobjective fuzzy system design. In his approach, the accuracy of fuzzy rule-based systems is maximized while their complexity is minimized. An EMO algorithm is used to search for non-dominated fuzzy rule-based systems with respect to accuracy maximization and complexity minimization. Then he will demonstrate through computation experiments on some classification problems that a large number of non-dominated fuzzy rule-based classifiers can be obtained along the accuracy-complexity tradeoff surface by a single run of his EMO approach. Finally he will suggest some future research issues in multiobjective genetic fuzzy systems. 
  
Bio: Professor Hisao Ishibuchi was born in Japan in 1963. He received the BS and MS degrees in precision mechanics from Kyoto University, Japan, in 1985 and 1987, respectively. He received the Ph. D. degree from Osaka Prefecture University, Japan, in 1992. Since 1987, he has been with Osaka Prefecture University, Japan, where he was a research associate (1987-1993), an assistant professor (1993), and an associate professor (1994-1999). He is currently a professor since 1999. He is also the Head of Computational Intelligence Research Center, Osaka Prefecture University. 

His research interests include evolutionary multiobjective optimization, fuzzy rule-based classifiers, multiobjective genetic fuzzy systems, data mining, and multi-agent systems. He received GECCO 2004 Best Paper Award in the Genetic Algorithm Track, ISIS 2005 Outstanding Paper Award, EFS 2006 Best Runner-Up Paper Award, HIS-NCEI 2006 Best Paper Award, GECCO 2007 Competition First Prize, and JSPS PRIZE from the Japan Society for the Promotion of Science. 

He is the Fuzzy Systems Technical Committee Chair of IEEE Computational Intelligence Society, and a Vice-President of Japan Society for Fuzzy Theory and Intelligent Informatics. He is also an associate editor of IEEE Trans. on Fuzzy Systems, IEEE Trans. on Evolutionary Computation, IEEE Trans. on Systems, Man, and Cybernetics: Part B, Mathware & Soft Computing, International Journal of Computational Intelligence Research, and International Journal of Metaheuristics. He was the Area Chair in the Hybrid Systems Area in IJCNN 1997 and FUZZ-IEEE 1998, a Technical Co-Chair of FUZZ-IEEE 2006, and a Program Co-Chair of EMO 2007, and will serve as the Program Chair for CEC 2010.