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.
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