Central pattern generator parameter search for a biped walking robot using nonparametric estimation based Particle Swarm Optimization

A parameter search for a Central Pattern Generator (CPG) for biped walking is difficult because there is no methodology to set the parameters and the search space is broad. These characteristics of the parameter search result in numerous fitness evaluations. In this paper, nonparametric estimation based Particle Swarm Optimization (NEPSO) is suggested to effectively search the parameters of CPG. The NEPSO uses a concept experience repository to store a previous position and the fitness of particles in a PSO and estimated best position to accelerate a convergence speed. The proposed method is compared with PSO variants in numerical experiments and is tested in a three dimensional dynamic simulator for bipedal walking. The NEPSO effectively finds CPG parameters that produce a gait of a biped robot. Moreover, NEPSO has a fast convergence property which reduces the evaluation of fitness in a real environment. Recommended by Editorial Board member Euntai Kim under the direction of Editor Jae-Bok Song. Jeong-Jung Kim received the B.S. degree in Electronics and Information Engineering from Chonbuk National University in 2006 and the M.S. degree in Robotics from Korea Advanced Institute of Science and Technology in 2008. He is currently working toward a Ph.D. at the Korea Advanced Institute of Science and Technology. His research interests include biologically inspired robotics and machine learning. Jun-Woo Lee received the B.S. degree in Electronics, Electrical and Communication Engineering from Pusan National University in 2007. He is currently working toward an M.S. in the Korea Advanced Institute of Science and Technology. His research interests include swarm intelligence and machine learning. Ju-Jang Lee was born in Seoul, Korea, in 1948. He received the B.S. and M.S. degrees from Seoul National University, Seoul, Korea, in 1973 and 1977, respectively, and the Ph.D. degree in Electrical Engineering from the University of Wisconsin, in 1984. From 1977 to 1978, he was a Research Engineer at the Korean Electric Research and Testing Institute, Seoul. From 1978 to 1979, he was a Design and Processing Engineer at G. T. E. Automatic Electric Company, Waukesha, WI. For a brief period in 1983, he was the Project Engineer for the Research and Development Department of the Wisconsin Electric Power Company, Milwaukee. He joined the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, in 1984, where he is currently a Professor. In 1987, he was a Visiting Professor at the Robotics Laboratory of the Imperial College Science and Technology, London, U.K. From 1991 to 1992, he was a Visiting Scientist at the Robotics Department of Carnegie Mellon University, Pittsburgh, PA. His research interests are in the areas of intelligent control of mobile robots, service robotics for the disabled, space robotics, evolutionary computation, variable structure control, chaotic control systems, electronic control units for automobiles, and power system stabilizers. Dr. Lee is a member of the IEEE Robotics and Automation Society, the IEEE Evolutionary Computation Society, the IEEE Industrial Electronics Society, IEEK, KITE, and KISS. He is also a former President of ICROS in Korea and a Counselor of SICE in Japan. He is a Fellow of SICE and ICROS. He is an Associate Editor of IEEE Transactions on Industrial Electronics and IEEE Transactions on Industrial Informatics.     

A motion compensated lifting wavelet codec for 3D video coding

A motion compensated lifting (MCLIFT) ramework for the 3D wavelet video coding is proposed in this paper,By using bi-directional motion compensation in each lifting step of the temporal direction,the video frames are effectively de-correlated,With the proper entropy coding and bit-stream packaging schemes,the MCLIFT wavelet video coder is scalable at frame rate and quality level .Experimental results show that the MCLIFT video coder outperforms the 3D wavelet video coder without motion by an average of 0.9-1.3dB,and outperforms MPEG-4 coder by an average of 0.2-0.6dB.     

A control-design-based solution to robotic ecology: Autonomy of achieving cooperative behavior from a high-level astronaut command

In this paper, we propose a cooperative control strategy for a group of robotic vehicles to achieve the specified task issued from a high-level astronaut command. The problem is mathematically formulated as designing the cooperative control for a general class of multiple-input-multiple-output (MIMO) dynamical systems in canonical form with arbitrary but finite relative degrees such that the outputs of the overall system converge to the explicitly given steady state. The proposed cooperative control for individual vehicle only need to use the sensed and communicated outputs information from its local neighboring vehicles. No fixed leader and time-invariant communication networks are assumed among vehicles. Particularly, a set of less-restrictive conditions on the connectivity of the sensor/communication networks are established, under which it is rigorously proven by using the newly found nice properties of the convergence of sequences of row stochastic matrices that the cooperative objective of the overall system can be achieved. Simulation results for a group of vehicles achieving a target and surrounding a specified object in formation are provided to support the proposed approach in this paper. Jing Wang received his B.S. degree and Ph.D. degree in control theory and control engineering, both from Central South University of Technology, China, in 1992 and 1997, respectively. He was a Postdoctoral Research Fellow at the Institute of Computing Technology, Chinese Academy of Sciences, from 1997 to 1999, and at the National University of Singapore, Singapore, from 1999 to 2002. Since March 2002, he has been with School of Electrical and Computer Science of University of Central Florida and now is a research assistant professor. He is the co-recipient of Best Theoretical Paper Award in 2002 at the 4th World Congress on Intelligent Control and Automation, Shanghai, China. His current research interests include cooperative control of multi-robot systems, nonlinear controls, robot control and motion planning, trajectory optimization, and control applications. He is a Member of IEEE and AIAA. Zhihua Qu received his Ph.D. degree in electrical engineering from the Georgia Institute of Technology in 1990. Since then, he has been with the University of Central Florida. Currently, he is a Professor in the Department of Electrical and Computer Engineering. His main research interests are nonlinear systems, robust and adaptive control designs, and robotics. He has published a number of papers in these areas and is the author of two books, Robust Control of Nonlinear Uncertain Systems by Wiley Interscience and Robust Tracking Control of Robotic Manipulators by IEEE Press. He is presently serving as an Associate Editor for Automatica and for International Journal of Robotics and Automation. He is a senior member of IEEE. Curtis M. Ihlefeld has been an electronics engineer for the National Aeronautics and Space Administration at the Kennedy Space Center since 1989. He is currently a member of the Kennedy Space Center Applied Physics Lab and has performed embedded processor systems design and control systems design for numerous Kennedy Space Center laboratories including the NASA Analytical Chemistry Lab, Optical Instrumentation Lab, Transducers Lab, and Data Acquisition Lab. Current projects include a control system design for a Lunar chemistry experiment that searches for water on the moon’s surface, a control system design and image processing tool set for space shuttle engine compartment photography, and a control system and image processing tool set for a space shuttle window defect measurement system. Presently he is performing research in the control of electroactive polymers. He holds an MS degree in electrical engineering from the University of Central Florida, and the title of his thesis was Application of Lyapunov Based Sensor Fault Detection in a Reverse Water Gas Shift Generator. He has one published conference proceedings paper and one journal article in the area of nonlinear fault tolerant control. Richard A. Hull received his B.S. in Engineering Science and Mechanics from the University of Florida, 1972, his M.S. and Ph.D. in Electrical Engineering from the University of Central Florida in 1993 and 1996, respectively. He has served as a Guidance and Control System Engineer in the Aerospace Industry for over 30 years, working for Lockheed Martin, Coleman Aerospace, McDonnell Douglas, and Boeing companies. He is currently a Principal Engineer in the Advanced Concepts Business Unit of Science Applications International Corporation (SAIC). He was a former recipient of the U.S. Air Force Laboratory Graduate Fellowship in Guidance and Control, and formerly served as Vice-Chairman of the Lockheed Martin Corporate Technical Focus Group for Guidance, Navigation and Control. His expertise and experience includes synthesis, simulation and analysis of guidance and control systems for hypersonic interceptor missiles, exo-atmospheric space vehicles, supersonic turbo-jets, space launch vehicle rockets, and high performance fighter aircraft. He is also a principal investigator for research in nonlinear robust control design methods, cooperative control of multiple platforms, and genetic algorithm design methods for aerospace applications. He has authored or co-authored over twenty conference and journal articles in the fields of nonlinear or cooperative control. He is a member of Institute of Electrical and Electronics Engineers (IEEE), a senior member of American Institute of Aeronautics and Astronautics (AIAA) and a member of the IEEE Control System Society. He has served as an Associate Editor of the Conference Editorial Board for the IEEE Control System Society since 1998, and is an adjunct professor and member of the graduate advisory council in Electrical Engineering for the Florida Institute of Technology (FIT).     

Catch the moment: maintaining closed frequent itemsets over a data stream sliding window

This paper considers the problem of mining closed frequent itemsets over a data stream sliding window using limited memory space. We design a synopsis data structure to monitor transactions in the sliding window so that we can output the current closed frequent itemsets at any time. Due to time and memory constraints, the synopsis data structure cannot monitor all possible itemsets. However, monitoring only frequent itemsets will make it impossible to detect new itemsets when they become frequent. In this paper, we introduce a compact data structure, the closed enumeration tree (CET), to maintain a dynamically selected set of itemsets over a sliding window. The selected itemsets contain a boundary between closed frequent itemsets and the rest of the itemsets. Concept drifts in a data stream are reflected by boundary movements in the CET. In other words, a status change of any itemset (e.g., from non-frequent to frequent) must occur through the boundary. Because the boundary is relatively stable, the cost of mining closed frequent itemsets over a sliding window is dramatically reduced to that of mining transactions that can possibly cause boundary movements in the CET. Our experiments show that our algorithm performs much better than representative algorithms for the sate-of-the-art approaches. Yun Chi is currently a Ph.D. student at the Department of Computer Science, UCLA. His main areas of research include database systems, data mining, and bioinformatics. For data mining, he is interested in mining labeled trees and graphs, mining data streams, and mining data with uncertainty. Haixun Wang is currently a research staff member at IBM T. J. Watson Research Center. He received the B.S. and the M.S. degree, both in computer science, from Shanghai Jiao Tong University in 1994 and 1996. He received the Ph.D. degree in computer science from the University of California, Los Angeles in 2000. He has published more than 60 research papers in referred international journals and conference proceedings. He is a member of the ACM, the ACM SIGMOD, the ACM SIGKDD, and the IEEE Computer Society. He has served in program committees of international conferences and workshops, and has been a reviewer for some leading academic journals in the database field. Philip S. Yureceived the B.S. Degree in electrical engineering from National Taiwan University, the M.S. and Ph.D. degrees in electrical engineering from Stanford University, and the M.B.A. degree from New York University. He is with the IBM Thomas J. Watson Research Center and currently manager of the Software Tools and Techniques group. His research interests include data mining, Internet applications and technologies, database systems, multimedia systems, parallel and distributed processing, and performance modeling. Dr. Yu has published more than 430 papers in refereed journals and conferences. He holds or has applied for more than 250 US patents.Dr. Yu is a Fellow of the ACM and a Fellow of the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery in Data. He is a member of the IEEE Data Engineering steering committee and is also on the steering committee of IEEE Conference on Data Mining. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001–2004), an editor, advisory board member and also a guest co-editor of the special issue on mining of databases. He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he will be serving as the general chairman of 2006 ACM Conference on Information and Knowledge Management and the program chairman of the 2006 joint conferences of the 8th IEEE Conference on E-Commerce Technology (CEC' 06) and the 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE' 06). He was the program chairman or co-chairs of the 11th IEEE International Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, the 2nd IEEE International Workshop on Research Issues on Data Engineering:Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases, and the 2nd IEEE International Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chairman of the 14th IEEE International Conference on Data Engineering and the general co-chairman of the 2nd IEEE International Conference on Data Mining. He has received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 84th plateau of Invention Achievement Awards. He received an Outstanding Contributions Award from IEEE International Conference on Data Mining in 2003 and also an IEEE Region 1 Award for “promoting and perpetuating numerous new electrical engineering concepts" in 1999. Dr. Yu is an IBM Master Inventor. Richard R. Muntz is a Professor and past chairman of the Computer Science Department, School of Engineering and Applied Science, UCLA. His current research interests are sensor rich environments, multimedia storage servers and database systems, distributed and parallel database systems, spatial and scientific database systems, data mining, and computer performance evaluation. He is the author of over one hundred and fifty research papers.Dr. Muntz received the BEE from Pratt Institute in 1963, the MEE from New York University in 1966, and the Ph.D. in Electrical Engineering from Princeton University in 1969. He is a member of the Board of Directors for SIGMETRICS and past chairman of IFIP WG7.3 on performance evaluation. He was a member of the Corporate Technology Advisory Board at NCR/Teradata, a member of the Science Advisory Board of NASA's Center of Excellence in Space Data Information Systems, and a member of the Goddard Space Flight Center Visiting Committee on Information Technology. He recently chaired a National Research Council study on “The Intersection of Geospatial Information and IT” which was published in 2003. He was an associate editor for the Journal of the ACM from 1975 to 1980 and the Editor-in-Chief of ACM Computing Surveys from 1992 to 1995. He is a Fellow of the ACM and a Fellow of the IEEE.     

Zikimi: A Case Study in Micro Kernel Design for Multimedia Applications

Due to recent rapid deployment of Internet Appliances and PostPC products, the importance of developing lightweight embedded operating system is being emphasized more. In this article, we like to present the details of design and implementation experience of low cost embedded system, Zikimi, for multimedia data processing. We use the skeleton of existing Linux operating system and develop a micro-kernel to perform a number of specific tasks efficiently and effectively. Internet Appliances and PostPC products usually have very limited amount of hardware resources to execute very specific tasks. We carefully analyze the system requirement of multimedia processing device. Weremove the unnecessary features, e.g. virtual memory, multitasking, a number of different file systems, and etc. The salient features of Zikimi micro kernel are (i) linear memory system and (ii) user level control of I/O device. The result of performance experiment shows that LMS (linear memory system) of Zikimi micro kernel achieves significant performance improvement on memory allocationagainst legacy virtual memory management system of Linux. By exploiting the computational capability of graphics processor and its local memory, we achieve 2.5 times increase in video processing speed. Supported by KOSEF through Statistical Research Center for Complex Systems at Seoul National University. Funded by Faculty Research Institute Program 2001, Sahmyook University, Korea. Sang-Yeob Lee received his B.S. and M.S degree from Hanyang University, seoul, Korea in 1995. He is currently working towards the Ph.D. degree in Devision of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. Since 1998, he has been on the faculty of Information Management System at Sahmyook university, Seoul, Korea. His research interests include robot vision systems, pattern recognition, Multimedia systems. He is a member of IEEE. Youjip Won received the B.S and M.S degree in Computer Science from the Department of Computer Science, Seoul National University, Seoul, Korea in 1990 and 1992, respectively and the Ph.D. in Computer Science from the University of Minnesota, Minneapolis in 1997. After finishing his Ph.D., He worked as Server Performance Analysts at Server Architecture Lab., Intel Corp. Since 1999, he has been on the board of faculty members in Division of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. His current research interests include Multimedia Systems, Internet Technology, Database and Performance Modeling and Analysis. He is a member of ACM and IEEE. Whoi-Yul Kim received his B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea in 1980. He received his M.S. from Pennsylvania State University, University Park, in 1983 and his Ph.D. from Purdue University, West Lafayette, in 1989, both in Electrical Engineering. From 1989 to 1994, he was with the Erick Jonsson School of Engineering and Computer Science at the University of Texas at Dallas. Since 1994, he has been on the faculty of Electronic Engineering at Hanyang University, Seoul, Korea. He has been involved with research development of various range sensors and their use in robot vision systems. Recently, his work has focused on content-based image retrieval system. He is a member of IEEE.     

Modeling semantics in composite Web service requests by utility elicitation

When meeting the challenges in automatic and semi-automatic Web service composition, capturing the user’s service demand and preferences is as important as knowing what the services can do. This paper discusses the idea of semantic service requests for composite services, and presents a multi-attribute utility theory (MAUT) based model of composite service requests. Service requests are modeled as user preferences and constraints. Two preference structures, additive independence and generalized additive independence, are utilized in calculating the expected utilities of service composition outcomes. The model is also based on an iterative and incremental scheme meant to better capture requirements in accordance with service consumers’ needs. OWL-S markup vocabularies and associated inference mechanism are used as a means to bring semantics to service requests. Ontology conceptualizations and language constructs are added to OWL-S as uniform representations of possible aspects of the requests. This model of semantics in service requests enables unambiguous understanding of the service needs and more precise generation of the desired compositions. An application scenario is presented to illustrate how the proposed model can be applied in the real business world. Qianhui Althea Liang received her Ph.D from the Department of Electrical and Computer Engineering, University of Florida in 2004. While pursuing her Ph.D, she was a member of Database Systems Research and Development Center at the University of Florida. She received both her bachelor’s and master’s from the Department of Computer Science and Engineering, Zhejiang University, China. She joined the School of Information Systems at Singapore Management University, Singapore, as an assistant professor in 2005. Her major research interests are service composition, dynamic service discovery, multimedia Web services, and applied artificial intelligence. Jen-Yao Chung received the M.S. and Ph.D degrees in computer science from the University of Illinois at Urbana-Champaign. Currently, he is the senior manager for Engineering and Technology Services Innovation, where he was responsible for identifying and creating emergent solutions. He was Chief Technology Officer for IBM Global Electronics Industry. Before that, he was program director for IBM Institute for Advanced Commerce Technology office. He is the co-founder of IEEE technical committee on e-Commerce (TCEC). He has served as general chair and program chair for many international conferences, most recently he served as the steering committee chair for the IEEE International Conference on e-Commerce Technology (CEC06) and general chair for the IEEE International Conference on e-Business Engineering (ICEBE06). He has authored or coauthored over 150 technical papers in published journals or conference proceedings. He is a senior member of the IEEE and a member of ACM. Miller is founding Dean of the School of Information Systems (SIS) at Singapore Management University, and also serves as Practice Professor of Information Systems. Since 2003, he has led efforts to launch and establish the undergraduate, graduate and professional programs of the SIS. Immediately prior to joining SMU, Dr. Miller served as Chief Architect Executive for the Business Consulting Services unit of IBM Global Services in Asia Pacific. He held prior industry appointments with Fujitsu Network Systems, and with RWD Technologies. Dr. Miller started his professional career as an Assistant Professor at Carnegie Mellon University, conducting research and teaching related to Computer-Integrated Manufacturing and Robotics applications and impacts. He has a Bachelors of Engineering Degree in Systems Engineering (Magna Cum Laude) from the University of Pennsylvania and a Masters of Science in Statistics and a Ph.D in Engineering and Public Policy from Carnegie Mellon University.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

Automatic model-based 3D object recognition by combining feature matching with tracking

We propose a vision-based robust automatic 3D object recognition, which provides object identification and 3D pose information by combining feature matching with tracking. For object identification, we propose a robust visual feature and a probabilistic voting scheme. An initial object pose is estimated using correlations between the model image and the 3D CAD model, which are predefined, and the homography, byproduct of the identification. In tracking, a Lie group formalism is used for robust and fast motion computation. Experimental results show that object recognition by the proposed method improves the recognition range considerably. Sungho Kim received the B.S. degree in Electrical Engineering from Korea University, Korea in 2000 and the M.S. degree in Electrical Engineering and Computer Science from Korea Advanced Institute of Science and Technology, Korea in 2002. He is currently pursuing his Ph.D. at the latter institution, concentrating on 3D object recognition and tracking. In So Kweon received the Ph.D. degree in robotics from Carnegie Mellon University, Pittsburgh, PA, in 1990. Since 1992, he has been a Professor of Electrical Engineering at KAIST. His current research interests include human visual perception, object recognition, real-time tracking, vision-based mobile robot localization, volumetric 3D reconstruction, and camera calibration. He is a member of the IEEE, and Korea Robotics Society (KRS).     

Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

In this paper, we present a new method for fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. The proposed method considers the centroid points and the standard deviations of generalized trapezoidal fuzzy numbers for ranking generalized trapezoidal fuzzy numbers. We also use an example to compare the ranking results of the proposed method with the existing centroid-index ranking methods. The proposed ranking method can overcome the drawbacks of the existing centroid-index ranking methods. Based on the proposed ranking method, we also present an algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can overcome the drawbacks of the one we presented in [7]. Shi-Jay Chen was born in 1972, in Taipei, Taiwan, Republic of China. He received the B.S. degree in information management from the Kaohsiung Polytechnic Institute, Kaohsiung, Taiwan, and the M.S. degree in information management from the Chaoyang University of Technology, Taichung, Taiwan, in 1997 and 1999, respectively. He received the Ph.D. degree at the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, in October 2004. His research interests include fuzzy systems, multicriteria fuzzy decisionmaking, and artificial intelligence. Shyi-Ming Chen was born on January 16, 1960, in Taipei, Taiwan, Republic of China. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. From August 1987 to July 1989 and from August 1990 to July 1991, he was with the Department of Electronic Engineering, Fu-Jen University, Taipei, Taiwan. From August 1991 to July 1996, he was an Associate Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1996 to July 1998, he was a Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1998 to July 2001, he was a Professor in the Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Since August 2001, he has been a Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was a Visiting Scholar in the Department of Electrical Engineering and Computer Science, University of California, Berkeley, in 1999. He was a Visiting Scholar in the Institute of Information Science, Academia Sinica, Republic of China, in 2003. He has published more than 250 papers in referred journals, conference proceedings and book chapters. His research interests include fuzzy systems, information retrieval, knowledge-based systems, artificial intelligence, neural networks, data mining, and genetic algorithms. Dr. Chen has received several honors and awards, including the 1994 Outstanding Paper Award o f the Journal of Information and Education, the 1995 Outstanding Paper Award of the Computer Society of the Republic of China, the 1995 and 1996 Acer Dragon Thesis Awards for Outstanding M.S. Thesis Supervision, the 1995 Xerox Foundation Award for Outstanding M.S. Thesis Supervision, the 1996 Chinese Institute of Electrical Engineering Award for Outstanding M.S. Thesis Supervision, the 1997 National Science Council Award, Republic of China, for Outstanding Undergraduate Student's Project Supervision, the 1997 Outstanding Youth Electrical Engineer Award of the Chinese Institute of Electrical Engineering, Republic of China, the Best Paper Award of the 1999 National Computer Symposium, Republic of China, the 1999 Outstanding Paper Award of the Computer Society of the Republic of China, the 2001 Institute of Information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the 2001 Outstanding Talented Person Award, Republic of China, for the contributions in Information Technology, the 2002 Institute of information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, the 2002 Chinese Fuzzy Systems Association Best Thesis Award for Outstanding M.S. Thesis Supervision, the 2003 Outstanding Paper Award of the Technological and Vocational Education Society, Republic of China, the 2003 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision, the 2005 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 Taiwan Fuzzy Systems Association Award for Outstanding Ph.D. Dissertation Supervision, and the 2006 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision. Dr. Chen is currently the President of the Taiwanese Association for Artificial Intelligence (TAAI). He is a Senior Member of the IEEE, a member of the ACM, the International Fuzzy Systems Association (IFSA), and the Phi Tau Phi Scholastic Honor Society. He was an administrative committee member of the Chinese Fuzzy Systems Association (CFSA) from 1998 to 2004. He is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics - Part C, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Editorial Board Member of the International Journal of Applied Intelligence, an Editor of the New Mathematics and Natural Computation Journal, an Associate Editor of the International Journal of Fuzzy Systems, an Editorial Board Member of the International Journal of Information and Communication Technology, an Editorial Board Member of the WSEAS Transactions on Systems, an Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics, an Associate Editor of the WSEAS Transactions on Computers, an Editorial Board Member of the International Journal of Computational Intelligence and Applications, an Editorial Board Member of the Advances in Fuzzy Sets and Systems Journal, an Editor of the International Journal of Soft Computing, an Editor of the Asian Journal of Information Technology, an Editorial Board Member of the International Journal of Intelligence Systems Technologies and Applications, an Editor of the Asian Journal of Information Management, an Associate Editor of the International Journal of Innovative Computing, Information and Control, and an Editorial Board Member of the International Journal of Computer Applications in Technology. He was an Editor of the Journal of the Chinese Grey System Association from 1998 to 2003. He is listed in International Who's Who of Professionals, Marquis Who's Who in the World, and Marquis Who's Who in Science and Engineering.     

A study of the model and algorithms for handling location-dependent continuous queries

Advances in wireless and mobile computing environments allow a mobile user to access a wide range of applications. For example, mobile users may want to retrieve data about unfamiliar places or local life styles related to their location. These queries are called location-dependent queries. Furthermore, a mobile user may be interested in getting the query results repeatedly, which is called location-dependent continuous querying. This continuous query emanating from a mobile user may retrieve information from a single-zone (single-ZQ) or from multiple neighbouring zones (multiple-ZQ). We consider the problem of handling location-dependent continuous queries with the main emphasis on reducing communication costs and making sure that the user gets correct current-query result. The key contributions of this paper include: (1) Proposing a hierarchical database framework (tree architecture and supporting continuous query algorithm) for handling location-dependent continuous queries. (2) Analysing the flexibility of this framework for handling queries related to single-ZQ or multiple-ZQ and propose intelligent selective placement of location-dependent databases. (3) Proposing an intelligent selective replication algorithm to facilitate time- and space-efficient processing of location-dependent continuous queries retrieving single-ZQ information. (4) Demonstrating, using simulation, the significance of our intelligent selective placement and selective replication model in terms of communication cost and storage constraints, considering various types of queries. Manish Gupta received his B.E. degree in Electrical Engineering from Govindram Sakseria Institute of Technology & Sciences, India, in 1997 and his M.S. degree in Computer Science from University of Texas at Dallas in 2002. He is currently working toward his Ph.D. degree in the Department of Computer Science at University of Texas at Dallas. His current research focuses on AI-based software synthesis and testing. His other research interests include mobile computing, aspect-oriented programming and model checking. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China, in 1996, and a Master's Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the Ph.D. degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu's research interests include distributed systems, wireless communications, mobile computing, and reliability and performance analysis. His Ph.D. research work focuses on the dependent and secure data replication and placement issues in network-centric systems. Latifur R. Khan has been an Assistant Professor of Computer Science department at University of Texas at Dallas since September 2000. He received his Ph.D. and M.S. degrees in Computer Science from University of Southern California (USC) in August 2000 and December 1996, respectively. He obtained his B.Sc. degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, in November of 1993. Professor Khan is currently supported by grants from the National Science Foundation (NSF), Texas Instruments, Alcatel, USA, and has been awarded the Sun Equipment Grant. Dr. Khan has more than 50 articles, book chapters and conference papers focusing in the areas of database systems, multimedia information management and data mining in bio-informatics and intrusion detection. Professor Khan has also served as a referee for database journals, conferences (e.g. IEEE TKDE, KAIS, ADL, VLDB) and he is currently serving as a program committee member for the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD2005), ACM 14th Conference on Information and Knowledge Management (CIKM 2005), International Conference on Database and Expert Systems Applications DEXA 2005 and International Conference on Cooperative Information Systems (CoopIS 2005), and is program chair of ACM SIGKDD International Workshop on Multimedia Data Mining, 2004. Farokh Bastani received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay, and the M.S. and Ph.D. degrees in Computer Science from the University of California, Berkeley. He is currently a Professor of Computer Science at the University of Texas at Dallas. Dr. Bastani's research interests include various aspects of the ultrahigh dependable systems, especially automated software synthesis and testing, embedded real-time process-control and telecommunications systems and high-assurance systems engineering. Dr. Bastani was the Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE). He is currently an emeritus EIC of IEEE-TKDE and is on the editorial board of the International Journal of Artificial Intelligence Tools, the International Journal of Knowledge and Information Systems and the Springer-Verlag series on Knowledge and Information Management. He was the program cochair of the 1997 IEEE Symposium on Reliable Distributed Systems, 1998 IEEE International Symposium on Software Reliability Engineering, 1999 IEEE Knowledge and Data Engineering Workshop, 1999 International Symposium on Autonomous Decentralised Systems, and the program chair of the 1995 IEEE International Conference on Tools with Artificial Intelligence. He has been on the program and steering committees of several conferences and workshops and on the editorial boards of the IEEE Transactions on Software Engineering, IEEE Transactions on Knowledge and Data Engineering and the Oxford University Press High Integrity Systems Journal. I-Ling Yen received her B.S. degree from Tsing-Hua University, Taiwan, and her M.S. and Ph.D. degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at University of Texas at Dallas. Dr. Yen's research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce and self-stabilising systems. She has published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Cochair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She has also served as a guest editor for a theme issue of IEEE Computer devoted to high-assurance systems.     

CPU load shedding for binary stream joins

We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept ofselective processing for load shedding. We allow stream tuples to be stored in the windows and shed excessive CPU load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. We support such dynamic selective processing through three forms of runtimeadaptations: adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. Our load shedding approach enables us to integrateutility-based load shedding withtime correlation-based load shedding. Indexes are used to further speed up the execution of stream joins. Experiments are conducted to evaluate our adaptive load shedding in terms of output rate and utility. The results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams. Bugra Gedik received the B.S. degree in C.S. from the Bilkent University, Ankara, Turkey, and the Ph.D. degree in C.S. from the College of Computing at the Georgia Institute of Technology, Atlanta, GA, USA. He is with the IBM Thomas J. Watson Research Center, currently a member of the Software Tools and Techniques Group. Dr. Gedik's research interests lie in data intensive distributed computing systems, spanning data-centric peer-to-peer overlay networks, mobile and sensor-based distributed data management systems, and distributed data stream processing systems. His research focus is on developing system-level architectures and techniques to address scalability problems in distributed continual query systems and applications. He is the recipient of the ICDCS 2003 best paper award. He has served in the program committees of several international conferences, such as ICDE, MDM, and CollaborateCom. Kun-Lung Wu received the B.S. degree in E.E. from the National Taiwan University, Taipei, Taiwan, the M.S. and Ph.D. degrees in C.S. both from the University of Illinois at Urbana-Champaign. He is with the IBM Thomas J. Watson Research Center, currently a member of the Software Tools and Techniques Group. His recent research interests include data streams, continual queries, mobile computing, Internet technologies and applications, database systems and distributed computing. He has published extensively and holds many patents in these areas. Dr. Wu is a Senior Member of the IEEE Computer Society and a member of the ACM. He is the Program Co-Chair for the IEEE Joint Conference on e-Commerce Technology (CEC 2007) and Enterprise Computing, e-Commerce and e-Services (EEE 2007). He was an Associate Editor for the IEEE Trans. on Knowledge and Data Engineering, 2000–2004. He was the general chair for the 3rd International Workshop on E-Commerce and Web-Based Information Systems (WECWIS 2001). He has served as an organizing and program committee member on various conferences. He has received various IBM awards, including IBM Corporate Environmental Affair Excellence Award, Research Division Award, and several Invention Achievement Awards. He received a best paper award from IEEE EEE 2004. He is an IBM Master Inventor. Philip S. Yu received the B.S. Degree in E.E. from National Taiwan University, the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University. He is with the IBM Thomas J. Watson Research Center and currently manager of the Software Tools and Techniques group. His research interests include data mining, Internet applications and technologies, database systems, multimedia systems, parallel and distributed processing, and performance modeling. Dr. Yu has published more than 430 papers in refereed journals and conferences. He holds or has applied for more than 250 US patents. Dr. Yu is a Fellow of the ACM and a Fellow of the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery in Data. He is a member of the IEEE Data Engineering steering committee and is also on the steering committee of IEEE Conference on Data Mining. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001–2004), an editor, advisory board member and also a guest co-editor of the special issue on mining of databases. He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he will be serving as the general chair of 2006 ACM Conference on Information and Knowledge Management and the program chair of the 2006 joint conferences of the 8th IEEE Conference on E-Commerce Technology (CEC' 06) and the 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE' 06). He was the program chair or co-chairs of the 11th IEEE Intl. Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, the 2nd IEEE Intl. Workshop on Research Issues on Data Engineering: Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases, and the 2nd IEEE Intl. Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chair of the 14th IEEE Intl. Conference on Data Engineering and the general co-chair of the 2nd IEEE Intl. Conference on Data Mining. He has received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 84th plateau of Invention Achievement Awards. He received an Outstanding Contributions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE Region 1 Award for “promoting and perpetuating numerous new electrical engineering concepts” in 1999. Dr. Yu is an IBM Master Inventor. Ling Liu is an associate professor at the College of Computing at Georgia Tech. There, she directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining research issues and technical challenges in building large scale distributed computing systems that can grow without limits. Dr. Liu and the DiSL research group have been working on various aspects of distributed data intensive systems, ranging from decentralized overlay networks, exemplified by peer to peer computing, data grid computing, to mobile computing systems and location based services, sensor network computing, and enterprise computing systems. She has published over 150 international journal and conference articles. Her research group has produced a number of software systems that are either open sources or directly accessible online, among which the most popular ones are WebCQ and XWRAPElite. Dr. Liu is currently on the editorial board of several international journals, including IEEE Transactions on Knowledge and Data Engineering, International Journal of Very large Database systems (VLDBJ), International Journal of Web Services Research, and has chaired a number of conferences as a PC chair, a vice PC chair, or a general chair, including IEEE International Conference on Data Engineering (ICDE 2004, ICDE 2006, ICDE 2007), IEEE International Conference on Distributed Computing (ICDCS 2006), IEEE International Conference on Web Services (ICWS 2004). She is a recipient of IBM Faculty Award (2003, 2006). Dr. Liu's current research is partly sponsored by grants from NSF CISE CSR, ITR, CyberTrust, a grant from AFOSR, an IBM SUR grant, and an IBM faculty award.     

Nonlinear adaptive decentralized stabilization control for multimachine power systems

This paper presents a decentralized adaptive backstepping controller to dampen oscillations and improve the transient stability to parametric uncertainties in multimachine power systems. The proposed design on the i ^th synchronous generator uses only local information and operates without the need for remote signals from the other generators. The design of the nonlinear controller is based on a modified fourth-order nonlinear model of a synchronous generator, and the automatic voltage regulator model is considered so as to decrease the steady state voltage error. The construction of both the control law and the associated Lyapunov function is systematically designed within the design methodology. A 3-machine power system is used to demonstrate the effectiveness of the proposed controller over two other controllers, namely a conventional damping controller (power system stabilizer) and one designed using the feedback linearization techniques. Recommended by Editorial Board member Gang Tao under the direction of Editor Jae Weon Choi. This work was supported by the Korea Electrical Engineering and Science Research Institute, which is funded by Ministry of Commerce, Industry and Energy. Shan-Ying Li received the B.S. degrees in Computer Science and M.S. degree in Electrical Engineering from Northeast DianLi University, China, in 1997 and 2002, respectively. She obtained the Ph.D. degree in Electrical Engineering from Seoul National University, Korea, in 2008. She is a Post Doctor in North China Electric Power Research Institute, North China Grid Co., Ltd., China. Her research interests are in the areas of advanced control and stability applications on power systems. Sang-Seung Lee received the M.S.E.E. and Ph.D. degrees in Electrical Engineering at Seoul National University. Currently, he is with Power System Research Division of KESRI, Seoul National University, Korea. His interest areas are nonlinear/adaptive control theory, North-East Asia power system interconnection, distributed/small generation, distributed transmission/distribution load flow algorithm, regional/local energy system, PSS (power system stabilizer), and RCM (Reliability Centered Maintenance). Yong Tae Yoon was born in Korea on April 20, 1971. He received the B.S. degree, M.Eng. and Ph.D. degrees from M.I.T., USA in 1995, 1997, and 2001, respectively. Currently, he is an Assistant Professor in the School of Electrical Engineering and Computer Science at Seoul National University, Korea. His special field of interest includes electric power network economics, power system reliability, and the incentive regulation of independent transmission companies. Jong-Keun Park received the B.S. degree in Electrical Engineering from Seoul National University, Seoul, Korea in 1973 and the M.S. and Ph.D. degrees in Electrical Engineering from The University of Tokyo, Japan in 1979 and 1982, respectively. He is currently a Professor of School of Electrical Engineering, Seoul National University. In 1992, he attended as a Visiting Professor at Technology and Policy Program and Laboratory for Electromagnetic and Electronic Systems, Massachusetts Institute of Technology. He is a Senior Member of the IEEE, a Fellow of the IEE, and a Member of Japan Institute of Electrical Engineers (JIEE).     

Test Resource Partitioning Based on Efficient Response Compaction for Test Time and Tester Channels Reduction

This paper presents a test resource partitioning technique based on an efficient response compaction design called quotient compactor(q-Compactor). Because q-Compactor is a single-output compactor, high compaction ratios can be obtained even for chips with a small number of outputs. Some theorems for the design of q-Compactor are presented to achieve full diagnostic ability, minimize error cancellation and handle unknown bits in the outputs of the circuit under test (CUT). The q-Compactor can also be moved to the load-board, so as to compact the output response of the CUT even during functional testing. Therefore, the number of tester channels required to test the chip is significantly reduced. The experimental results on the ISCAS ‘89 benchmark circuits and an MPEG 2 decoder SoC show that the proposed compactionscheme is very efficient.     

Fast Surface Segmentation Guided by User Input Using Implicit Extension of Minimal Paths

We introduce a novel implicit approach for single object segmentation in 3D images. The boundary surface of this object is assumed to contain two or more known curves (the constraining curves), given by an expert. The aim of our method is to find the desired surface by exploiting the information given in the supplied curves as much as possible. We use a cost potential which penalizes image regions of low interest (for example areas of low gradient). In order to avoid local minima, we introduce a new partial differential equation and use its solution for segmentation. We show that the zero level set of this solution contains the constraining curves as well as a set of paths joining them. These paths globally minimize an energy which is defined from the cost potential. Our approach, although conceptually different, can be seen as an implicit extension to 3D of the minimal path framework already known for 2D image segmentation. As for this previous approach, and unlike other variational methods, our method is not prone to local minima traps of the energy. We present a fast implementation which has been successfully applied to 3D medical and synthetic images. Roberto Ardon graduated from the Ecole Centrale Paris in 2001 with a major in applied mathematics, obtained his master degree in image processing from the Ecole Normale Supérieure de Cachan in the same year and his Ph.D. degree in applied mathematics from the University Paris-Dauphine in 2005. Currently he is a research scientist in Philips Medical Systems Research Paris. His research interests include calculus of variations mainlly focused on medical image processing. Laurent D. Cohen was at Ecole Normale Superieure Ulm in Paris from 1981 to 1985. He received Master's and Ph.D. degrees in Applied Mathematics from Paris 6 in 1983 and 1986. From 1985 to 1987, he was member at the Computer Graphics and Image Processing group at Schlumberger Palo Alto Research, California and Schlumberger Montrouge Research, and remained consultant there for a few years afterwards. He began working with INRIA, France in 1988, mainly with the medical image understanding group Epidaure. Since 1990, he is Research Scholar (Charge then Directeur de Recherche) with CNRS in the Applied Mathematics and Image Processing group at CEREMADE, University Paris-Dauphine. His research interests and teaching at the university are applications of variational methods and Partial Differential Equations to Image Processing and Computer Vision, like deformable models, minimal paths, surface reconstruction, Image registration, Image segmentation and restoration. He obtained CS 2002 Prize for Image and Signal Processing. He has been member in program committees for boards for about 20 international conferences. Anthony Yezzi obtained his Ph.D. in 1997 through the Department of Electrical Engineering at the University of Minnesota. After completing a postdoctoral research position in the Laboratory for Information and Decision Systems (LIDS) at Massacusetts Institute of Technology, he joined the faculty of the School of Electrical and Computer Engineering at Georgia Institute of Technology in 1999 where he currently holds the position of Associate Professor. Prof. Yezzi has also consulted for a number of medical imaging companies including GE, Picker, and VTI, and has been an IEEE member since 1999. His research lies primarily within the fields of image processing and computer vision. He has worked on a variety of problems including image denoising, edge-detection, segmentation and grouping, shape analysis, multi-frame stereo reconstruction, tracking, and registration. Some central themes of his research include curve and surface evolution theory, differential geometry, and partial differential equations.     

Best-Effort Patching for Multicast True VoD Service

A multicast Video-on-Demand (VoD) system allows clients to share a server stream by batching their requests, and hence, improves channel utilization. However, it is very difficult to equip such a VoD system with full support for interactive VCR functions which are important to a growing number of Internet applications. In order to eliminate service (admission) latency, patching was proposed to enable an existing multicast session to dynamically add new clients, and requests can be served without delay if patching channels are available. A true VoD (TVoD) service should support not only zero-delay client admission but also continuous VCR-like interactivity. However, the conventional patching is only suitable for admission control. We propose a new patching scheme, called Best-Effort Patching (BEP), that offers a TVoD service in terms of both request admission and VCR interactivity. Moreover, by using a novel dynamic merging algorithm, BEP significantly improves the efficiency of TVoD interactivity, especially for popular videos. We also model and evaluate the efficiency of the dynamic merging algorithm. It is shown that BEP outperforms the conventional TVoD interaction protocols.Huadong Ma received the B.S. degree in Mathematics from Henan Normal University in 1984, the M.S. degree in Computer Science from Shenyang Institute of Computing Technology, Chinese Academy of Science (CAS) in 1990 and the Ph.D. degree in Computer Science from Institute of Computing Technology, CAS, in 1995.He is a Professor with the School of Computer Science & Technology, Beijing University of Posts and Telecommunications, China. He visited UNU/IIST as research fellow in 1998 and 1999, respectively. From 1999 to 2000, he held a visiting position in the Real-Time Computing Laboratory in the Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor. His current research focuses on multimedia, networking, e-commerce and computergraphics, and he has published over 70papers and 3 books on these fields. He is member of IEEE and ACM.Kang G. Shin received the B.S. degree in Electronics Engineering from Seoul National University, Korea, in 1970, and both the M.S. and Ph.D. degrees in Electrical Engineering from Cornell University, Ithaca, New York in 1976 and 1978, respectively.He is the Kevin and Nancy OConnor Professor of Computer Scienceand Founding Director of the Real-Time Computing Laboratory in the Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor. His current research focuses on QoS-sensitive networking and computing as well as on embedded real-time OS, middleware and applications, all with emphasis on timeliness and dependability. He has supervised the completion of 49 Ph.D. theses, and authored/coauthored over 600 technical papers and numerous book chapters in the areas of distributed real-time computing and control, computer networking, fault-tolerant computing, and intelligent manufacturing. Dr. Shin is Fellow of IEEE and ACM, and member of the Korean Academy of Engineering.Weibiao Wu received the Ph.D. degree in statistics from the University of Michigan, Ann Arbor in 2001. He is currently an Assistant professor of statistics at the University of Chicago. His research interests include probabilistic network modelling and simulation, data-base compression, asymptotic theory and statistical inference of stochastic processes.     

Forms and theories of communication: from multimedia to Kansei Mediation

In this paper we describe a form of communication that could be used for lifelong learning as contribution to cultural computing. We call it Kansei Mediation. It is a multimedia communication concept that can cope with non-verbal, emotional and Kansei information. We introduce the distinction between the concepts of Kansei Communication and Kansei Media. We then develop a theory of communication (i.e. Kansei Mediation) as a combination of both. Based on recent results from brain research the proposed concept of Kansei Mediation is developed and discussed. The biased preference towards consciousness in established communication theories is critically reviewed and the relationship to pre- and unconscious brain processes explored. There are two tenets of the Kansei Mediation communication theory: (1) communication based on connected unconciousness, and (2) Satori as the ultimate form of experience. Ryohei Nakatsu received the B.S. (1969), M.S. (1971) and Ph.D. (1982) degrees in electronic engineering from Kyoto University. After joining NTT in 1971, he mainly worked on speech recognition technology. He joined ATR (Advanced Telecommunications Research Institute) as the president of ATR Media Integration & Communications Research Laboratories (1994–2002). From the spring of 2002 he is full professor at School of Science and Technology, Kwansei Gakuin University in Sanda (Japan). At the same time he established a venture company, Nirvana Technology Inc., and became the president of the company. In 1978, he received Young Engineer Award from the Institute of Electronics, Information and Communication Engineers Japan (IEICE-J). In 1996, he received the best paper award from the IEEE International Conference on Multimedia. In 1999, 2000 and 2001, he was awarded Telecom System Award from Telecommunication System Foundation and the best paper award from Virtual Reality Society of Japan. In 2000, he got the best paper award from Artificial Intelligence Society of Japan. He is a fellow of the IEEE and the Institute of Electronics, Information and Communication Engineers Japan (IEICE-J), a member of the Acoustical Society of Japan, Information Processing Society of Japan, and Japanese Society for Artificial Intelligence. Matthias Rauterberg received the B.S. in psychology (1978) at the University of Marburg (Germany), the B.S. in philosophy (1981) and computer science (1983), the M.S. in psychology (1981) and computer science (1985) at the University of Hamburg (Germany), and the Ph.D. in computer science (1995) at the University of Zurich (Switzerland). He was a senior lecturer for ‘usability engineering’ in computer science and industrial engineering at the Swiss Federal Institute of Technology (ETH) in Zurich. He was the head of the Man–Machine Interaction research group (MMI) of the Institute for Hygiene and Applied Physiology (IHA) from the Department of Industrial Engineering at the ETH, Zurich. Since 1998, he is a fulltime professor for ‘human communication technology’ at the Department of Industrial Design at the Technical University Eindhoven (The Netherlands), and also since 2004, he is appointed as a visiting professor at the Kwansei Gakuin University (Japan). He received the German GI-HCI award for the best Ph.D. in 1997 and the Swiss Technology Award together with Martin Bichsel for the BUILD-IT system in 1998. Since 2005, he is elected as a member of the Cream of Science in The Netherlands. Ben Salem received the Dip.Arch. (1987) at the Ecole Polytechnique d'Architecture et d'Urbanisme EPAU (Algiers), the M.Arch. (1993) at the School of Architectural Studies of the University of Sheffield (UK), and the Ph.D. in electronics (2003) at the Department of Electronic and Electrical Engineering, University of Sheffield (UK). Since 2001, he is director of Polywork Ltd. (UK). Since 2003. he has a PostDoc position at the Department of Industrial Design of the Technical University Eindhoven (The Netherlands).     

Fast training for object recognition with structure-from-motion

In this paper we present a system for statistical object classification and localization that applies a simplified image acquisition process for the learning phase. Instead of using complex setups to take training images in known poses, which is very time-consuming and not possible for some objects, we use a handheld camera. The pose parameters of objects in all training frames that are necessary for creating the object models are determined using a structure-from-motion algorithm. The local feature vectors we use are derived from wavelet multiresolution analysis. We model the object area as a function of 3D transformations and introduce a background model. Experiments made on a real data set taken with a handheld camera with more than 2500 images show that it is possible to obtain good classification and localization rates using this fast image acquisition method. The text was submitted by the authors in English. Marcin Grzegorzek, born in 1977, obtained his Master’s Degree in Engineering from the Silesian University of Technology Gliwice (Poland) in 2002. Since December 2002 he has been a PhD candidate and member of the research staff of the Chair for Pattern Recognition at the University of Erlangen-Nuremberg, Germany. His fields are 3D object recognition, statistical modeling, and computer vision. He is an author or coauthor of seven publications. Michael Reinhold, born in 1969, obtained his degree in Electrical Engineering from RWTH Aachen University, Germany, in 1998. Later, he received a Doctor of Engineering from the University of Erlangen-Nuremberg, Germany, in 2003. His research interests are statistical modeling, object recognition, and computer vision. He is currently a development engineer at Rohde & Schwarz in Munich, Germany, where he works in the Center of Competence for Digital Signal Processing. He is an author or coauthor of 11 publications. Ingo Scholz, born in 1975, graduated in computer science at the University of Erlangen-Nuremberg, Germany, in 2000 with a degree in Engineering. Since 2001 he has been working as a research staff member at the Institute for Pattern Recognition of the University of Erlangen-Nuremberg. His main research focuses on the reconstruction of light field models, camera calibration techniques, and structure from motion. He is an author or coauthor of ten publications and member of the German Gesellschaft für Informatik (GI). Heinrich Niemann obtained his Electrical Engineering degree and Doctor of Engineering degree from Hannover Technical University, Germany. He worked with the Fraunhofer Institut für Informationsverarbeitung in Technik und Biologie, Karlsruhe, and with the Fachhochschule Giessen in the Department of Electrical Engineering. Since 1975 he has been a professor of computer science at the University of Erlangen-Nuremberg, where he was dean of the engineering faculty of the university from 1979 to 1981. From 1988 to 2000, he was head of the Knowledge Processing research group at the Bavarian Research Institute for Knowledge-Based Systems (FORWISS). Since 1998, he has been a spokesman for a “special research area” with the name of “Model-Based Analysis and Visualization of Complex Scenes and Sensor Data” funded by the German Research Foundation. His fields of research are speech and image understanding and the application of artificial intelligence techniques in these areas. He is on the editorial board of Signal Processing, Pattern Recognition Letters, Pattern Recognition and Image Analysis, and the Journal of Computing and Information Technology. He is an author or coauthor of seven books and about 400 journal and conference contributions, as well as editor or coeditor of 24 proceedings volumes and special issues. He is a member of DAGM, ISCA, EURASIP, GI, IEEE, and VDE and an IAPR fellow.     

Design, analysis, and implementation of an agent driven pull-based distributed video-on-demand system

The problem of employing multiple servers to serve a pool of clients on a network based multimedia service is addressed. We have designed and practically implemented a prototype system employing multiple servers to render a long duration movie to the customers. We have employed a multiple server retrieval strategy proposed in the literature [39] to realize this system. In the system, server coordination, client behavior and service facilities are completely controlled by an Agent based approach in which we have used the recent Jini technology. Several issues, ranging from data retrieval from individual server, behavior of the underlying network infrastructure, to client management and resource (client buffers) management, are considered in this implementation. We describe in detail our experiences in this complete design process of every module in the software architecture, its purpose, and working style. Further, the system is shown to be robust amidst unpredictable failures, i.e., in the event of server crashes. The load balancing capability is built-in as a safe guard measure to assure a continuous presentation. We present a comprehensive discussion on the software architecture to realize this working system and present our experiences. A system comprising a series of Pentium III PCs on a fast Ethernet network is built as a test-bed. Through this prototype, a wider scope of research challenges ahead are highlighted as possible extensions. Bharadwaj Veeravalli Member, IEEE & IEEE-CS, received his BSc in Physics, from Madurai-Kamaraj Uiversity, India in 1987, Master's in Electrical Communication Engineering from Indian Institute of Science, Bangalore, India in 1991 and PhD from Department of Aerospace Engineering, Indian Institute of Science, Bangalore, India in 1994. He did his post-doctoral research in the Department of Computer Science, Concordia University, Montreal, Canada, in 1996. He is currently with the Department of Electrical and Computer Engineering, Computer and Information Engineering (CIE) division, at The National University of Singapore, Singapore, as a tenured Associate Professor. His main stream research interests include, Multiprocessor systems, Cluster/Grid computing, Scheduling in parallel and distributed systems, Bioinformatics & Computational Biology, and Multimedia computing. He is one of the earliest researchers in the field of divisible load theory. He has published over 75 papers in high-quality International Journals and Conferences. He had secured several externally funded projects. He has co-authored three research monographs in the areas of Parallel and Distributed Systems, Distributed Databases, and Multimedia systems, in the years 1996, 2003, and 2005, respectively. He had guest edited a special issue on Cluster/Grid Computing for IJCA, USA journal in 2004. He has been recently invited to contribute to Multimedia Encyclopedia, Kluwer Academic Publishers, 2005. He is currently serving the Editorial Board of IEEE Transactions on Computers, IEEE Transactions on SMC-A and International Journal of Computers & Applications, USA, as an Associate Editor. He had served as a program committee member and as a session chair in several International Conferences. Long Chen received the B.E. degree in Electrical Engineering and M.E. degree in Electrical Engineering from the Northwestern Polytechnic University, P. R. China, in 1998 and 2001, respectively, and the M.E. degree in Computer Engineering from the National University of Singapore, Singapore, in 2004. He is currently a Ph.D. candidate at the Department of Electrical and Computer Engineering, the University of Delaware, United States. His research interests include multimedia systems, distributed system, network security, and computer architecture.     

LMI-based H ∞ synchronization of second-order neutral master-slave systems using delayed output feedback control

The H _∞ synchronization problem of the master and slave structure of a second-order neutral master-slave systems with time-varying delays is presented in this paper. Delay-dependent sufficient conditions for the design of a delayed output-feedback control are given by Lyapunov-Krasovskii method in terms of a linear matrix inequality (LMI). A controller, which guarantees H _∞ synchronization of the master and slave structure using some free weighting matrices, is then developed. A numerical example has been given to show the effectiveness of the method. The simulation results illustrate the effectiveness of the proposed methodology. Recommended by Editorial Board member Bin Jiang under the direction of Editor Jae Weon Choi. This research has been partially funded by the German Research Foundation (DFG) as part of the Collaborative Research Center 637 ‘Autonomous Cooperating Logistic Processes: A Paradigm Shift and its Limitations’ (SFB 637). This work was supported in part by the National Natural Science Foundation of China (60504008), by the Research Fund for the Doctoral Program of Higher Education of China (20070213084), by the Fok Ying Tung Education Foundation (111064). Hamid Reza Karimi born in 1976, received the B.Sc. degree in Power Systems Engineering from Sharif University of Technology in 1998 and M.Sc. and Ph.D. degrees both in Control Systems Engineering from University of Tehran in 2001 and 2005, respectively. From 2006 to 2007, he was a Post-doctoral Research Fellow of the Alexander-von-Humboldt Stiftung with both Technical University of Munich and University of Bremen in Germany. He held positions as Assistant Professor at the Department of Electrical Engineering of the University of Tehran in Iran, Senior Research Fellow in the Centre for Industrial Mathematics of the University of Bremen in Germany and Research Fellow of Juan de la Cierva program at the Department of Electronics, Informatics and Automation of the University of Girona in Spain before he was appointed as an Associate Professor in Control Systems at the Faculty of Technology and Science of the University of Agder in Norway in April 2009. His research interests are in the areas of nonlinear systems, networked control systems, robust filter design and vibration control of flexible structures with an emphasis on applications in engineering. Dr. Karimi was the recipient of the German Academic Awards (DAAD Award) from 2003 to 2005 and was a recipient of the Distinguished Researcher Award from University of Tehran in 2001 and 2005. He received the Distinguished PhD Award of the Iranian President in 2005 and the Iranian Students Book Agency’s Award for Outstanding Doctoral Thesis in 2007. He also received first rank of Juan de la Cierva research program in the field of Electrical, Electronic and Automation Engineering in Spain in 2007. Huijun Gao was born in Heilongjiang Province, China, in 1976. He received the M.S. degree in Electrical Engineering from Shenyang University of Technology, Shengyang, China, in 2001 and the Ph.D. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2005. He was a Research Associate with the Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, from November 2003 to August 2004. From October 2005 to September 2007, he carried out his postdoctoral research with the Department of Electrical and Computer Engineering, University of Alberta, Canada, supported by an Alberta Ingenuity Fellowship and an Honorary Izaak Walton Killam Memorial Postdoctoral Fellowship. Since November 2004, he has been with Harbin Institute of Technology, where he is currently a Professor. His research interests include network-based control, robust control/filter theory, model reduction, time-delay systems, multidimensional systems, and their engineering applications. Dr. Gao is an Associate Editor for the IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics, the Journal of Intelligent and Robotics Systems, the Circuits, System and Signal Processing etc. He serves on the Editorial Board of the International Journal of Systems Science, the Journal of the Franklin Institute etc. He was the recipient of the University of Alberta Dorothy J. Killam Memorial Postdoctoral Fellow Prize in 2005 and was a corecipient of the National Natural Science Award of China in 2008. He was a recipient of the National Outstanding Youth Science Fund in 2008 and the National Outstanding Doctoral Thesis Award in 2007. He was an outstanding reviewer for IEEE Transactions on Automatic Control and Automatica in 2008 and 2007 respectively, and an appreciated reviewer for IEEE Transactions on Signal Processing in 2006.