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: Prof. Seppo J. Ovaska
Title: Computationally Intelligent Hybrid Systems: The Fusion of Soft Computing and Hard Computing

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.

Keynote Speaker: Professor Seppo J. Ovaska
Title: Computationally Intelligent Hybrid Systems: The Fusion of Soft Computing and Hard Computing

E-mail: seppo.ovaska@tkk.fi
Helsinki University of Technology
Faculty of Electronics, Communications, and Automation

Abstract: The concept of Fusion of Soft Computing and Hard Computing has gained growing recognition during the past few years. Soft computing is known as a complementary set of computationally intelligent techniques, such as neural networks, fuzzy systems, and evolutionary computation. On the other hand, hard computing is a heterogeneous set of traditional computing techniques. Now that our understanding of soft computing is maturing, the next synthesis must come in understanding how to combine soft-computing and hard-computing methodologies to generate synergistic improvements. In essence, the immediate challenge is to understand how to collectively allocate these techniques to create hybrid methods that are more effective than either alone. Over the next decade, the fusion of soft and hard computing will play an increasingly important role in the development of computationally intelligent systems for aerospace, electric power industry, automotive engineering, and numerous other application areas. The principal aim is to develop computationally intelligent hybrid systems that are straightforward to analyze, their behavior and stability could be highly predictable, and the computational burden would be no more than moderate. These goals are particularly important in autonomous real-time applications.
In this keynote, we will first introduce a multi-dimensional categorization scheme for fusion structures. Five qualitative criteria are defined to cover various aspects of the fusion of soft computing and hard computing: (1) The degree of interconnections of soft- and hard-computing constituents; (2) the topology of fusion structures; (3) the time frame when the fusion takes place; (4) the layer of a system architecture where the fusion takes place; and (5) the primary motivation for the application of fusion techniques. These criteria will help us to characterize fusion schemes, thus, facilitating the discussion on the advantages and limitations of specific fusion approaches and supporting the development of novel fusion structures. In addition to the fundamentals of the fusion of soft computing and hard computing, we discuss the future research opportunities, such as interface sophistication beyond the current means, true symbiosis of soft and hard computing, as well as fusion implementations at different levels of system hierarchy. Finally, a carefully selected collection of fusion applications are presented and analyzed.


Bio: Seppo J. Ovaska received an M.Sc. degree in electrical engineering from the Tampere University of Technology, Finland, an Lic.Sc. degree in computer science and engineering from the Helsinki University of Technology, Finland, and a D.Sc. degree in electrical engineering from the Tampere University of Technology in 1980, 1987, and 1989, respectively.

He is a Professor in the Faculty of Electronics, Communications, and Automation at the Helsinki University of Technology. Before joining the Helsinki University of Technology in 1996, he was a Professor in the Department of Information Technology at the Lappeenranta University of Technology, Finland (1992–1996). From 1980 to 1992, he held engineering, research, and R&D management positions with Kone Elevators and Nokia Research Center, both in Finland and in the United States. He was a Visiting Scientist at the Muroran Institute of Technology, Japan, in the summer of 1999; at the Virginia Polytechnic Institute and State University, in the summers of 2000 and 2001; at the Utah State University, in the summers of 2002–2004; and at the University of Passau, Germany, in the summer of 2005. In the academic year of 2006–2007, he was a Visiting Professor of Electrical and Computer Engineering at the Utah State University. His current research interests are in computationally intelligent hybrid systems, evolutionary computation, artificial life, and artificial immune systems. During his career, he has published more than 230 peer-reviewed journal articles, conference papers, and book chapters. He edited the book “Computationally Intelligent Hybrid Systems: The Fusion of Soft Computing and Hard Computing” (Wiley – IEEE Press, 2004), and holds nine patents in the area of elevator systems and control.

Dr. Ovaska has served as an Associate Editor for the IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews (2004–2008); for the IEEE Transactions on Neural Networks (2005–2006); for the IEEE Transactions on Industrial Electronics (1999–2004); and for the IEEE Transactions on Instrumentation and Measurement (1996–1998). In 2001, he co-edited the special issue on “Industrial Innovations Using Soft Computing” for the Proceedings of the IEEE. He was the Founding General Chair of the IEEE Midnight-Sun Workshop on Soft Computing Methods in Industrial Applications (1999). In addition, he was the General Chair of the 5th Online World Conference on Soft Computing in Industrial Applications (2000). Dr. Ovaska is a recipient of two Outstanding Contribution Awards (2000 and 2002) and the Most Active SMC Technical Committee Award (2006) of the IEEE Systems, Man, and Cybernetics Society.