Evolutionary fusion of a multi-classifier system for efficient face recognition

In this paper an evolutionary classifier fusion method inspired by biological evolution is presented to optimize the performance of a face recognition system. Initially, different illumination environments are modeled as multiple contexts using unsupervised learning and then the optimized classifier ensemble is searched for each context using a Genetic Algorithm (GA). For each context, multiple optimized classifiers are searched; each of which are referred to as a context based classifier. An evolutionary framework comprised of a combination of these classifiers is then applied to optimize face recognition as a whole. Evolutionary classifier fusion is compared with the simple adaptive system. Experiments are carried out using the Inha database and FERET database. Experimental results show that the proposed evolutionary classifier fusion method gives superior performance over other methods without using evolutionary fusion. Recommended by Guest Editor Daniel Howard. This work was supported by INHA UNIVERSITY Research Grant. Zhan Yu received the B.E. degree in Software Engineering from Xiamen University, China, in 2008. He is currently a master student in Intelligent Technology Lab, Computer and Information Department, Inha University, Korea. He has research interests in image processing, pattern recognition, computer vision, machine learning and statistical inference and computating. Mi Young Nam received the B.Sc. and M.Sc. degrees in Computer Science from the University of Silla Busan, Korea in 1995 and 2001 respectively and the Ph.D. degree in Computer Science & Engineering from the University of Inha, Korea in 2006. Currently, She is Post-Doctor course in Intelligent Technology Laboratory, Inha University, Korea. She’s research interest includes biometrics, pattern recognition, computer vision, image processing. Suman Sedai received the M.S. degree in Software Engineering from Inha University, China, in 2008. He is currently a Doctoral course in Western Australia University, Australia. He has research interests in image processing, pattern recognition, computer vision, machine learning. Phill Kyu Rhee received the B.S. degree in Electrical Engineering from the Seoul University, Seoul, Korea, the M.S. degree in Computer Science from the East Texas State University, Commerce, TX, and the Ph.D. degree in Computer Science from the University of Louisiana, Lafayette, LA, in 1982, 1986, and 1990 respectively. During 1982–1985 he was working in the System Engineering Research Institute, Seoul, Korea as a research scientist. In 1991 he joined the Electronic and Telecommunication Research Institute, Seoul, Korea, as a Senior Research Staff. Since 1992, he has been an Associate Professor in the Department of Computer Science and Engineering of the Inha University, Incheon, Korea and since 2001, he is a Professor in the same department and university. His current research interests are pattern recognition, machine intelligence, and parallel computer architecture. dr. rhee is a Member of the IEEE Computer Society and KISS (Korea Information Science Society).     

A noise robust gait representation: Motion energy image

Gait-based human identification aims to discriminate individuals by the way they walk. A unique advantage of gait as a biometric is that it requires no subject contact and is easily acquired at a distance, which stands in contrast to other biometric techniques involving face, fingerprints, iris, etc. This paper proposes a new gait representation called motion energy image (MEI). Compared with other gait features, MEI is more robust against noise that can be included in binary gait silhouette images due to various factors. The effectiveness of the proposed method for gait recognition is demonstrated using experiments performed on the NLPR database. Recommended by Editorial Board member Jang Myung Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. Grant Number: R11-2002-105-09002-0 (2009). Heesung Lee received the B.S. and M.S. degrees in Electrical and Electronic Engineering, from Yonsei University, Seoul, Korea, in 2003 and 2005, respectively. He is currently a Ph.D. candidate of Dept. of Electrical and Electronic Engineering at Yonsei University. His current research interests include computational intelligence, pattern recognition, biometrics, and neural network. Sungjun Hong received the B.S. degrees in Electrical and Electronic Engineering and Computer Science, from Yonsei University, Seoul, Korea, in 2005. He is a graduate student of the combined master’s and doctoral degree programs at Yonsei University. He has studied machine learning, biometrics and optimization Imran Fareed Nizami received the B.S. degree from University of Engg. & Tech. Taxila, Pakistan and the M.S. degree in the Electrical and Electronic Engineering from Yonsei University, Seoul, Korea. He is currently a senior lecturer in Bahria University, Islamabad, Pakistan. His research interests include biometrics, gait recognition, Bayesian and neural networks. Euntai Kim received the B.S. (with top honors), M.S. and Ph.D. degrees in Electronic Engineering from Yonsei University, Seoul, Korea, in 1992, 1994, and 1999, respectively. From 1999 to 2002, he was a Full-time Lecturer with the Department of Control and Instrumentation Engineering at Hankyong National University, Gyeonggi-do, Korea. Since 2002, he has been with the School of Electrical and Electronic Engineering at Yonsei University, where he is currently an associate professor. He was a Visiting Scholar with the University of Alberta, Edmonton, Canada, and the Berkeley Initiative in Soft Computing (BISC), UC Berkeley, USA, in 2003 and 2008, respectively. His current research interests include computational intelligence and machine learning and their application to intelligent service robots, unmanned vehicles, home networks, biometrics, and evolvable hardware.     

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.     

Finite-horizon scheduling of radar dwells with online template construction

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon. Sathish Gopalakrishnan is a visting scholar in the Department of Computer Science, University of Illinois at Urbana-Champaign, where he defended his Ph.D. thesis in December 2005. He received an M.S. in Applied Mathematics from the University of Illinois in 2004 and a B.E. in Computer Science and Engineering from the University of Madras in 1999. Sathish’s research interests concern real-time and embedded systems, and the design of large-scale reliable systems. He received the best student paper award for his work on radar dwell scheduling at the Real-Time Systems Symposium 2004. Marco Caccamo graduated in computer engineering from the University of Pisa in 1997 and received the Ph.D. degree in computer engineering from the Scuola Superiore S. Anna in 2002. He is an Assistant Professor of the Department of Computer Science at the University of Illinois. His research interests include real-time operating systems, real-time scheduling and resource management, wireless sensor networks, and quality of service control in next generation digital infrastructures. He is recipient of the NSF CAREER Award (2003). He is a member of ACM and IEEE. Chi-Sheng Shih is currently an assistant professor at the Graduate Institute of Networking and Multimedia and Department of Computer Science and Information Engineering at National Taiwan University since February 2004. He received the B.S. in Engineering Science and M.S. in Computer Science from National Cheng Kung University in 1993 and 1995, respectively. In 2003, he received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His main research interests are embedded systems, hardware/software codesign, real-time systems, and database systems. Specifically, his main research interests focus on real-time operating systems, real-time scheduling theory, embedded software, and software/hardware co-design for system-on-a-chip. Chang-Gun Lee received the B.S., M.S. and Ph.D. degrees in computer engineering from Seoul National University, Korea, in 1991, 1993 and 1998, respectively. He is currently an Assistant Professor in the Department of Electrical Engineering, Ohio State University, Columbus. Previously, he was a Research Scientist in the Department of Computer Science, University of Illinois at Urbana-Champaign from March 2000 to July 2002 and a Research Engineer in the Advanced Telecomm. Research Lab., LG Information & Communications, Ltd. from March 1998 to February 2000. His current research interests include real-time systems, complex embedded systems, QoS management, and wireless ad-hoc networks. Chang-Gun Lee is a member of the IEEE Computer Society. Lui Sha graduated with the Ph.D. degree from Carnegie-Mellon University in 1985. He was a Member and then a Senior Member of Technical Staff at Software Engineering Institute (SEI) from 1986 to 1998. Since Fall 1998, he has been a Professor of Computer Science at the University of Illinois at Urbana Champaign, and a Visiting Scientist of the SEI. He was the Chair of IEEE Real Time Systems Technical Committee from 1999 to 2000, and has served on its Executive Committee since 2001. He was a member of National Academy of Science’s study group on Software Dependability and Certification from 2004 to 2005, and is an IEEE Distinguished Visitor (2005 to 2007). Lui Sha is a Fellow of the IEEE and the ACM.     

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).     

Automated music video generation using multi-level feature-based segmentation

We show how to create a music video automatically, using computable characteristics of the video and music to promote coherent matching. We analyze the flow of both music and video, and then segment them into sequences of near-uniform flow. We extract features from the both video and music segments, and then find matching pairs. The granularity of the matching process can be adapted by extending the segmentation process to several levels. Our approach drastically reduces the skill required to make simple music videos.

Scheduling real-time requests in on-demand data broadcast environments

On-demand broadcast is an attractive data dissemination method for mobile and wireless computing. In this paper, we propose a new online preemptive scheduling algorithm, called PRDS that incorporates urgency, data size and number of pending requests for real-time on-demand broadcast system. Furthermore, we use pyramid preemption to optimize performance and reduce overhead. A series of simulation experiments have been performed to evaluate the real-time performance of our algorithm as compared with other previously proposed methods. The experimental results show that our algorithm substantially outperforms other algorithms over a wide range of workloads and parameter settings. The work described in this paper was partially supported by grants from CityU (Project No. 7001841) and RGC CERG Grant No. HKBU 2174/03E. This paper is an extended version of the paper “A preemptive scheduling algorithm for wireless real-time on-demand data broadcast” that appeared in the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications. Victor C. S. Lee received his Ph.D. degree in Computer Science from the City University of Hong Kong in 1997. He is now an Assistant Professor in the Department of Computer Science of the City University of Hong Kong. Dr. Lee is a member of the ACM, the IEEE and the IEEE Computer Society. He is currently the Chairman of the IEEE, Hong Kong Section, Computer Chapter. His research interests include real-time data management, mobile computing, and transaction processing. Xiao Wu received the B.Eng. and M.S. degrees in computer science from Yunnan University, Kunming, China, in 1999 and 2002, respectively. He is currently a Ph.D. candidate in the Department of Computer Science at the City University of Hong Kong. He was with the Institute of Software, Chinese Academy of Sciences, Beijing, China, between January 2001 and July 2002. From 2003 to 2004, he was with the Department of Computer Science of the City University of Hong Kong, Hong Kong, as a Research Assistant. His research interests include multimedia information retrieval, video computing and mobile computing. Joseph Kee-Yin NG received a B.Sc. in Mathematics and Computer Science, a M.Sc. in Computer Science, and a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in the years 1986, 1988, and 1993, respectively. Prof. Ng is currently a professor in the Department of Computer Science at Hong Kong Baptist University. His current research interests include Real-Time Networks, Multimedia Communications, Ubiquitous/Pervasive Computing, Mobile and Location- aware Computing, Performance Evaluation, Parallel and Distributed Computing. Prof. Ng is the Technical Program Chair for TENCON 2006, General Co-Chair for The 11th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2005), Program Vice Chair for The 11th International Conference on Parallel and Distributed Systems (ICPADS 2005), Program Area-Chair for The 18th & 19th International Conference on Advanced Information Networking and Applications (AINA 2004 & AINA 2005), General Co-Chair for The International Computer Congress 1999 & 2001 (ICC’99 & ICC’01), Program Co-Chair for The Sixth International Conference on Real-Time Computing Systems and Applications (RTCSA’99) and General Co-Chair for The 1999 and 2001 International Computer Science Conference (ICSC’99 & ICSC’01). Prof. Ng is a member of the Editorial Board of Journal of Pervasive Computing and Communications, Journal of Ubiquitous Computing and Intelligence, Journal of Embedded Computing, and Journal of Microprocessors and Microsystems. He is the Associate Editor of Real-Time Systems Journal and Journal of Mobile Multimedia. He is also a guest editor of International Journal of Wireless and Mobile Computing for a special issue on Applications, Services, and Infrastructures for Wireless and Mobile Computing. Prof. Ng is currently the Region 10 Coordinator for the Chapter Activities Board of the IEEE Computer Society, and is the Coordinator of the IEEE Computer Society Distinguished Visitors Program (Asia/Pacific). He is a senior member of the IEEE and has been a member of the IEEE Computer Society since 1991. Prof. Ng has been an Exco-member (1993–95), General Secretary (1995–1997), Vice-Chair (1997–1999), Chair (1999–2001) and the Past Chair of the IEEE, Hong Kong Section, Computer Chapter. Prof. Ng received the Certificate of Appreciation for Services and Contribution (2004) from IEEE Hong Kong Section, the Certificate of Appreciation for Leadership and Service (2000–2001) from IEEE Region 10 and the IEEE Meritorious Service Award from IEEE Computer Society at 2004. He is also a member of the IEEE Communication Society, ACM and the Founding Member for the Internet Society (ISOC)-Hong Kong Chapter.     

Proofs of a set of hybrid let-polymorphic type inference algorithms

We present a generalized let-polymorphic type inference algorithm, prove that any of its instances is sound and complete with respect to the Hindley/Milner let-polymorphic type system, and find a condition on two instance algorithms so that one algorithm should find type errors earlier than the other. By instantiating the generalized algorithm with different parameters, we can obtain not only the two opposite algorithms (the bottom-up standard algorithmW and the top-down algorithmM) but also other hybrid algorithms which are used in real compilers. Such instances’ soudness and completeness follow automatically, and their relative earliness in detecting type-errors is determined by checking a simple condition. The set of instances of the generalized algorithm is a superset of those used in the two most popular ML compilers: SML/NJ and OCaml. This work is supported by Creative Research Initiatives of the Korean Ministry of Science and Technology National Creative Research Initiative Center, http://ropas.kaist.ac.kr Work done while the third author was associated with Korea Advanced Institute of Science and Technology Hyunjun Eo: He is a Ph.D. candidate in the Department of Computer Science at KAIST (Korea Advanced Institute of Science and Technology). He recieved his bachelor’s degree and master’s degree in Computer Science from KAIST in 1996 and 1998, respectively. His research interest has been on static program analysis, fixpoint iteration algorithm and higher-order and typed languages. From fall 1998, he has been a research assistant of the National Creative Research Initiative Center for Research on Program Analysis System. He is currently working on developing a tool for automatic generation of program analyzer. Oukseh Lee: He is a Ph.D. candidate in the Department of Computer Science at KAIST (Korea Advanced Institute of Science and Technology). He received his bachelor’s and master’s degree in Computer Science from KAIST in 1995 and 1997, respectively. His research interest has been on static program analysis, type system, program language implementation, higher-order and typed languages, and program verification. From 1998, he has been a research assistant of the National Creative Research Initiative Center for Research on Program Analysis System. He is currently working on compile-time analyses and verification for the memory behavior of programs. Kwangkeun Yi, Ph.D.: His research interest has been on semanticbased program analysis and systems application of language technologies. After his Ph.D. from University of Illinois at Urbana-Champaign he joined the Software Principles Research Department at Bell Laboratories, where he worked on various static analysis approaches for higher-order and typed programming languages. For 1995 to 2003 he was a faculty member in the Department of Computer Science, Korea Advanced Institute of Science and Technology. Since fall 2003, he has been a faculty member in the School of Computer Science and Engineering, Seoul National University.     

S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches. Chunming Hu is a research staff in the Institute of Advanced Computing Technology at the School of Computer Science and Engineering, Beihang University, Beijing, China. He received his B.E. and M.E. in Department of Computer Science and Engineering in Beihang University. He received the Ph.D. degree in School of Computer Science and Engineering of Beihang University, Beijing, China, 2005. His research interests include peer-to-peer and grid computing; distributed systems and software architectures. Yanmin Zhu is a Ph.D. candidate in the Department of Computer Science, Hong Kong University of Science and Technology. He received his B.S. degree in computer science from Xi’an Jiaotong University, Xi’an, China, in 2002. His research interests include grid computing, peer-to-peer networking, pervasive computing and sensor networks. He is a member of the IEEE and the IEEE Computer Society. Jinpeng Huai is a Professor and Vice President of Beihang University. He serves on the Steering Committee for Advanced Computing Technology Subject, the National High-Tech Program (863) as Chief Scientist. He is a member of the Consulting Committee of the Central Government’s Information Office, and Chairman of the Expert Committee in both the National e-Government Engineering Taskforce and the National e-Government Standard office. Dr. Huai and his colleagues are leading the key projects in e-Science of the National Science Foundation of China (NSFC) and Sino-UK. He has authored over 100 papers. His research interests include middleware, peer-to-peer (P2P), grid computing, trustworthiness and security. Yunhao Liu received his B.S. degree in Automation Department from Tsinghua University, China, in 1995, and an M.A. degree in Beijing Foreign Studies University, China, in 1997, and an M.S. and a Ph.D. degree in computer science and engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include peer-to-peer computing, pervasive computing, distributed systems, network security, grid computing, and high-speed networking. He is a senior member of the IEEE Computer Society. Lionel M. Ni is chair professor and head of the Computer Science and Engineering Department at Hong Kong University of Science and Technology. Lionel M. Ni received the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, Indiana, in 1980. He was a professor of computer science and engineering at Michigan State University from 1981 to 2003, where he received the Distinguished Faculty Award in 1994. His research interests include parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of the IEEE and the IEEE Computer Society, he has chaired many professional conferences and has received a number of awards for authoring outstanding papers.     

Static extensivity analysis for λ-definable functions over lattices

We employ a static analysis to examine the extensivity (∀x:x≤f(x)) of functions defined over lattices in a λ-calculus augmented with lattice operations. The need for such a verification procedure has arisen in our work on a generator system (called Zoo) of static program-analyzers. The input to Zoo is a static analysis specification that consists of lattice definitions and function definitions over the lattices. Once the extensivity of the functions is ascertained, the generated analyzer is guaranteed to terminate when the lattices have finite-heights. The extensivity analysis consists of a sound syntax-driven deductive rules whose satisfiability check is done by a constraint solving procedure. Hyunjun Eo: He is a Ph.D. candidate of Computer Science Dept. at KAIST (Korea Advanced Institute of Science and Technology). He received his B.S. and M.S. in Computer Science from KAIST in 1996 and 1998, respectively. For 1998–2003, he was a research assistant of the National Creative Research Initiative Center for Research On Program Analysis System. His research interest has been on static program analysis, program logics, and higher-order and typed languages. He is currently working on developing a tool for automatic generation of program analyzers. Kwangkeun Yi, Ph.D.: His research interest has been on semantic-based program analysis and systems application of language technologies. After his Ph.D. from University of Illinois at Urbana-Champaign he joined the Software Principles Research Department at Bell Laboratories, where he worked on various static analysis approaches for higher-order and typed programming languages. For 1995–2003, he was a faculty member in the Department of Computer Science, Korea Advanced Institute of Science and Technology. Since Fall 2003, he has been a faculty member in the School of Computer Science and Engineering, Seoul National University. Kwang-Moo Choe, Ph.D.: He is a professor of Computer Science at Korea Advanced Institute of Science and Technology. He received his B.S. from Seoul National University in 1976, and his M.S. and Ph.D. from Korea Advanced Institute of Science and Technology in 1978 and 1984, respectively. For 1985–1986, he was a technical staff of AT&T Bell Labs at Murray Hill. His research interest is formal language theory, parallel evaluation of logic programs, and optimizing compilers.     

A classification method using a hybrid genetic algorithm combined with an adaptive procedure for the pool of ellipsoids

This paper presents a hybrid classification method that utilizes genetic algorithms (GAs) and adaptive operations of ellipsoidal regions for multidimensional pattern classification problems with continuous features. The classification method fits a finite number of the ellipsoidal regions to data pattern by using hybrid GAs, the combination of local improvement procedures and GAs. The local improvement method adaptively expands, rotates, shrinks, and/or moves the ellipsoids while each ellipsoid is separately handled with a fitness value assigned during the GA operations. A set of significant features for the ellipsoids are automatically determined in the hybrid GA procedure by introducing “don’t care” bits to encode the chromosomes. The performance of the method is evaluated on well-known data sets and a real field classification problem originated from a deflection yoke production line. The evaluation results show that the proposed method can exert superior performance to other classification methods such as k nearest neighbor, decision trees, or neural networks. Ki K. Lee received the B.S. degree from Han Yang University, Seoul, Korea in 1994, and the M.S. and Ph.D. degrees in industrial engineering from Korea Advanced Institute Science and Technology (KAIST), Daejeon, Korea in 1996 and 2005, respectively. From 2001 to 2004, he was a senior research engineer in telecommunication systems laboratory of LG Electronics Inc. Since 2005, he has been an assistant professor in the School of Management at Inje University, Kimhae, Korea. His research interests include intelligent decision support systems, soft computing, and pattern recognition. Wan C. Yoon received the B.S. degree from Seoul National University, Korea in 1977, the M.S. degree from KAIST, Korea in 1979, and the Ph.D. degree in industrial and systems engineering from Georgia Institute of Technology in 1987. He is professor of the Department of Industrial Engineering at KAIST, Korea. His research interests include application of artificial intelligence, human decision-making and aiding, information systems, and joint intelligent systems. Dong H. Baek received the B.S. degree from Han Yang University, Seoul, Korea in 1992, and the M.S. and Ph.D. degrees in industrial engineering from Korea Advanced Institute Science and Technology (KAIST), Daejeon, Korea in 1994 and 1999, respectively. He is an assistant professor in management information systems at department of business administration, Hanyang University, Korea. His research interests include management information systems, system engineering, and machine learning.     

MFR (Multipurpose Field Robot) for installing construction materials

The objective of the study was to propose a MFR (Multipurpose Field Robot) in hazardous operation environments. This system combines a basic system composed of a multi-DOF (Degree Of Freedom) manipulator and a mobile platform with an additional module for construction, national defense and emergency-rescue. According to an additional module type combined with a basic system, it can be used in a various fields. In this study, we describe a prototype of construction robot which helps a human operator handle easily construction materials in case of using the cooperation system on construction site. This study introduces an additional module for construction and a robot control algorithm for a HRC (Human-Robot Cooperation). In addition, it proposes a novel construction method to install construction materials with robot on construction site. Seung Yeol Lee received the B.S. degree from the Department of Mechanical Engineering, Myungji University, Seoul, Korea in 2002, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 2005. He is a Ph.D. degree candidate from the Department of Mechanical Engineering, Hanyang University, Seoul, Korea. From 2003, He is currently a visiting researcher in the Research Institute of Technology, Construction Group at the Samsung Corporation, Korea conducting the design and implementation of construction robot and automation system for construction project. His research interests include design, control, and application of construction robots, field robotic systems and ergonomic design of robotic systems. He is a member of the Korea Society of Mechanical Engineers, Architectural Institute of Korea, and Ergonomics Society of Korea. Yong Seok Lee received the B.S. degree from the Department of Precision Mechanical Engineering, Kunsan national University, Kunsan, Korea in 2002, and the M.S. degree from the Department of Precision Mechanical Engineering, Hanyang University, Seoul, Korea in 2005. Currently, he is the Post Master in Hanyang University, Korea. His major interests include design and kinematic/dynamic analysis on multi-purpose field robots and service robots. He is a member of the Architectural Institute of Korea. Bum Seok Park received the B.S. degree from the Department of Mechanical Engineering, Hanyang University, Ansan, Kyung-gi Do, Korea in 1993, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 1998. He is a Ph.D. from the Department of Mechatronics System Engineering, Hanyang University, Seoul, Korea From 2006. He is currently the post-doctor in Hanyang University, Korea. His major interests include embedded robot control system on multi-purpose field robot and service robot. He is a member of the Korea Society of Mechanical Engineers, Korean Society of Machine Tool Engineers. Sang Heon Lee graduated with the B.S. degree in Precision Mechanical Engineering from Hanyang University, Seoul, Korea in 1992. He received the M.S. degree in Precision Engineering from KAIST, Taejon, Korea in 1994 and the Ph.D. degree in Mechanical Engineering from KAIST in 2001. Currently, he is a senior researcher in Samsung Corporation, Korea. His major interests include the kinematic/dynamic analysis on multi-body system, application of field robots, and automation in construction. ChangSoo Han received the B.S. degree from the Department of Mechanical Engineering, Seoul National University Technology, Seoul, Korea in 1983, and the M.S. and Ph.D. degrees from the Department of Mechanical Engineering, University of Texas at Austin, in 1985 and 1989, respectively. From May 1988 to September 1989, he was a Research Assistant, Robotics Lab in Mechanical Engineering about manufacturing of the high resolution micro manipulator module. In March 1990, he joined Hanyang University, Ansan, Kyungki-Do, Korea as a Professor, Department of Mechanical Engineering. From March 1993 to February 1995, he was a Vice President, The Research Institute of Engineering & Technology of the Hanyang University. From August 1996 to July 1997, he was a Visiting Professor, Univ. of California at Berkeley. From September 1997 to February 1999, he was a Director, Hanyang Business Incubator. In August 2000, he joined a Branch President, The Korean Society of Mechanical Engineers. In January 2002, he joined a Committee Member, The Korean Society of Mechanical Engineers. From January 2001 to December 2001, he was an International Cooperation Director, The Institute of Control, Automation and Systems, Korea. His research interests include design, control, and application of robot, automation systems, and advanced vehicle.     

Game theory basis for control of long-lived lunar/planetary surface robots

Current and future NASA robotic missions to planetary surfaces are tending toward longer duration and are becoming more ambitious for rough terrain access. For a higher level of autonomy in such missions, the rovers will require behavior that must also adapt to declining health and unknown environmental conditions. The MER (Mars Exploration Rovers) called Spirit and Opportunity have both passed 600 days of life on the Martian surface, with extensions to 1000 days and beyond depending on rover health. Changes in navigational planning due to degradation of the drive motors as they reach their lifetime are currently done on Earth for the Spirit rover. The upcoming 2009 MSL (Mars Science Laboratory) and 2013 AFL (Astrobiology Field Laboratory) missions are planned to last 300–500 days, and will possibly involve traverses on the order of multiple kilometers over challenging terrain. This paper presents a unified coherent framework called SMART (System for Mobility and Access to Rough Terrain) that uses game theoretical algorithms running onboard a planetary surface rover to safeguard rover health during rough terrain access. SMART treats rover motion, task planning, and resource management as a Two Person Zero Sum Game (TPZSG), where the rover is one player opposed by the other player called “nature” representing uncertainty in sensing and prediction of the internal and external environments. We also present preliminary results of some field studies. Terry Huntsberger is a Principal Member of the Technical Staff in the Advanced Robotic Controls Group at NASA’s Jet Propulsion Laboratory in Pasadena, CA, where he is the Manager for numerous tasks in the areas of multi-robot control systems, and rover systems for access to high risk terrain. He is an Adjunct Professor and former Director of the Intelligent Systems Laboratory in the Department of Computer Science at the University of South Carolina. His research interests include behavior-based control, computer vision, neural networks, wavelets, and biologically inspired system design. Dr. Huntsberger has published over 120 technical articles in these and associated areas. He received his PhD in Physics in 1978 from the University of South Carolina. He is a member of SPIE, ACM, IEEE Computer Society, and INNS. Abhijit Sengupta is a Senior Member of Engineering Staff in the Advanced Concepts and Architecture Group of the Jet Propulsion Laboratory in Pasadena, California. His research interest includes distributed architecture, algorithm design and fault-tolerant computing and he has more than 100 publications in these and other related areas. Prior to joining JPL in 2001, he was a Professor in the Department of Computer Science and Engineering at the University of South Carolina. He received his Ph.D. in 1976 in Electronic Engineering from the University of Calcutta.     

Adaptive group scheduling mechanism using mobile agents in peer-to-peer grid computing environment

Peer-to-peer grid computing is an attractive computing paradigm for high throughput applications. However, both volatility due to the autonomy of volunteers (i.e., resource providers) and the heterogeneous properties of volunteers are challenging problems in the scheduling procedure. Therefore, it is necessary to develop a scheduling mechanism that adapts to a dynamic peer-to-peer grid computing environment. In this paper, we propose a Mobile Agent based Adaptive Group Scheduling Mechanism (MAAGSM). The MAAGSM classifies and constructs volunteer groups to perform a scheduling mechanism according to the properties of volunteers such as volunteer autonomy failures, volunteer availability, and volunteering service time. In addition, the MAAGSM exploits a mobile agent technology to adaptively conduct various scheduling, fault tolerance, and replication algorithms suitable for each volunteer group. Furthermore, we demonstrate that the MAAGSM improves performance by evaluating the scheduling mechanism in Korea@Home. SungJin Choi is a Ph.D. student in the Department of Computer Science and Engineering at Korea University. His research interests include mobile agent, peer-to-peer computing, grid computing, and distributed systems. Mr. Choi received a M.S. in computer science from Korea University. He is a student member of the IEEE. MaengSoon Baik is a senior research member at the SAMSUNG SDS Research & Develop Center. His research interests include mobile agent, grid computing, server virtualization, storage virtualization, and utility computing. Dr. Baik received a Ph.D. in computer science from Korea University. JoonMin Gil is a professor in the Department of Computer Science Education at Catholic University of Daegu, Korea. His recent research interests include grid computing, distributed and parallel computing, Internet computing, P2P networks, and wireless networks. Dr. Gil received his Ph.D. in computer science from Korea University. He is a member of the IEEE and the IEICE. SoonYoung Jung is a professor in the Department of Computer Science Education at Korea University. His research interests include grid computing, web-based education systems, database systems, knowledge management systems, and mobile computing. Dr. Jung received his Ph.D. in computer science from Korea University. ChongSun Hwang is a professor in the Department of Computer Science and Engineering at Korea University. His research interests include distributed systems, distributed algorithms, and mobile computing. Dr. Hwang received a Ph.D. in statistics and computer science from the University of Georgia.     

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.     

Privacy-preserving SVM classification

Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. What is required is distributed knowledge discovery that is sensitive to this problem. The key is to obtain valid results, while providing guarantees on the nondisclosure of data. Support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. It is based on solid theoretical foundations and has wide practical application. This paper proposes a privacy-preserving solution for support vector machine (SVM) classification, PP-SVM for short. Our solution constructs the global SVM classification model from data distributed at multiple parties, without disclosing the data of each party to others. Solutions are sketched out for data that is vertically, horizontally, or even arbitrarily partitioned. We quantify the security and efficiency of the proposed method, and highlight future challenges. Jaideep Vaidya received the Bachelor’s degree in Computer Engineering from the University of Mumbai. He received the Master’s and the Ph.D. degrees in Computer Science from Purdue University. He is an Assistant Professor in the Management Science and Information Systems Department at Rutgers University. His research interests include data mining and analysis, information security, and privacy. He has received best paper awards for papers in ICDE and SIDKDD. He is a Member of the IEEE Computer Society and the ACM. Hwanjo Yu received the Ph.D. degree in Computer Science in 2004 from the University of Illinois at Urbana-Champaign. He is an Assistant Professor in the Department of Computer Science at the University of Iowa. His research interests include data mining, machine learning, database, and information systems. He is an Associate Editor of Neurocomputing and served on the NSF Panel in 2006. He has served on the program committees of 2005 ACM SAC on Data Mining track, 2005 and 2006 IEEE ICDM, 2006 ACM CIKM, and 2006 SIAM Data Mining. Xiaoqian Jiang received the B.S. degree in Computer Science from Shanghai Maritime University, Shanghai, 2003. He received the M.C.S. degree in Computer Science from the University of Iowa, Iowa City, 2005. Currently, he is pursuing a Ph.D. degree from the School of Computer Science, Carnegie Mellon University. His research interests are computer vision, machine learning, data mining, and privacy protection technologies.     

Development of the multi-functional indoor service robot PSR systems

This paper discusses the development of the multi-functional indoor service robot PSR (Public Service Robots) systems. We have built three versions of PSR systems, which are the mobile manipulator PSR-1 and PSR-2, and the guide robot Jinny. The PSR robots successfully accomplished four target service tasks including a delivery, a patrol, a guide, and a floor cleaning task. These applications were defined from our investigation on service requirements of various indoor public environments. This paper shows how mobile-manipulator typed service robots were developed towards intelligent agents in a real environment. We identified system integration, multi-functionality, and autonomy considering environmental uncertainties as key research issues. Our research focused on solving these issues, and the solutions can be considered as the distinct features of our systems. Several key technologies were developed to satisfy technological consistency through the proposed integration scheme. Woojin Chung was born in Seoul, Korea, in 1970. He received the B.S. at the department of mechanical design and production engineering, Seoul National University in 1993. He received the M.S. degree in 1995 and Ph.D degree in 1998 at the department of Mechano-Informatics, the University of Tokyo. He was a senior research scientist at the Korea Institute of Science and Technology from 1998 to 2005. He joined the department of mechanical engineering, Korea University in 2005 as an assistant professor. He received an excellent paper award from the Robotics Society of Japan in 1996 and a best transactions paper award from the IEEE robotics and automation society in 2002. His research interests include the design and control of nonholonomic underactuated mechanical systems, trailer system design and control, mobile robot navigation, a dexterous robot hand and a system integration of intelligent robots. He is a member of the IEEE, the robotics society of Japan, the institute of control, automation and systems engineers and the Korea robotics society. Gunhee Kim received the B.S. and M.S. degrees at the department of mechanical engineering, Korea Advanced Institute of Science and Technology (KAIST), Korea, in 1999 and 2001, respectively. He was a research scientist in Intelligent Robotics Research Center, at Korea Institute of Science and Technology (KIST), Korea, from 2001 to 2006. Currently, he is a graduate student in the Robotics Institute, Carnegie Mellon University. His research interests include computer vision, artificial intelligence, mobile robot navigation, and discrete event systems. He is a member of the IEEE. Munsang Kim received the B.S. and M.S degree in Mechanical Engineering from the Seoul National University in 1980 and 1982 respectively and the Dr.-Ing. degree in Robotics from the Technical University of Berlin, Germany in 1987. Since 1987 he has been working as a research scientist at Korea Institute of Science and Technology. He has led the Intelligent Robotics Research Center since 2000 and became the director of the “Intelligent Robot—The Frontier 21 Program” since Oct. 2003. His current research interests are design and control of novel mobile manipulation systems, haptic device design and control, and sensor application to intelligent robots.     

Image hiding scheme using modulus function and optimal substitution table

The simple least-significant-bit (LSB) substitution technique is the easiest way to embed secret data in the host image. To avoid image degradation of the simple LSB substitution technique, Wang et al. proposed a method using the substitution table to process image hiding. Later, Thien and Lin employed the modulus function to solve the same problem. In this paper, the proposed scheme combines the modulus function and the optimal substitution table to improve the quality of the stego-image. Experimental results show that our method can achieve better quality of the stego-image than Thien and Lin’s method does. The text was submitted by the authors in English. Chin-Shiang Chan received his BS degree in Computer Science in 1999 from the National Cheng Chi University, Taipei, Taiwan and the MS degree in Computer Science and Information Engineering in 2001 from the National Chung Cheng University, ChiaYi, Taiwan. He is currently a Ph.D. student in Computer Science and Information Engineering at the National Chung Cheng University, Chiayi, Taiwan. His research fields are image hiding and image compression. Chin-Chen Chang received his BS degree in applied mathematics in 1977 and his MS degree in computer and decision sciences in 1979, both from the National Tsing Hua University, Hsinchu, Taiwan. He received his Ph.D. in computer engineering in 1982 from the National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at the National Chiao Tung University. From 1983–1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he has worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a Fellow of IEEE, a Fellow of IEE and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression. Yu-Chen Hu received his Ph.D. degree in Computer Science and Information Engineering from the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan in 1999. Dr. Hu is currently an assistant professor in the Department of Computer Science and Information Engineering, Providence University, Sha-Lu, Taiwan. He is a member of the SPIE society and a member of the IEEE society. He is also a member of the Phi Tau Phi Society of the Republic of China. His research interests include image and data compression, information hiding, and image processing.     

A QoS-Enabled Transmission Scheme for MPEG Video Streaming

While MPEG is the de facto encoding standard for video services, online video streaming service is becoming popular over the open network such as the Internet. As the performance of open network is non-predictable and uncontrollable, the tuning of the quality of service (QoS) for on-line video streaming services is difficult. In order to provide better QoS for the delivery of videos, there are proposals of new encoding formats or new transmission protocols for on-line video streaming. However, these results are not compatible with popular video players or network protocols and hence these approaches are so far not very successful. We use another approach which tries to by-pass these problems. We designed a QoS Tuning Scheme and a QoS-Enabled Transmission Scheme for transmitting MPEG videos from video servers to clients. According to the traffic characteristics between the video server and each individual client, the QoS Tuning Scheme tunes the QoS to be delivered to each individual client on the fly. Furthermore, our QoS-Enabled Transmission Scheme can be applied over any protocol, such as HTTP which is the most popular protocol over the open network. With our transmission scheme, bandwidth can be better utilized by reducing transmitted frames which would have missed their deadlines and would eventually be discarded by the clients. This is achieved by sending frames according to their impact on the QoS in the playback under the allowed throughput. With these schemes, users can enjoy video streaming through their favorite video players and with the best possible QoS. In order to facilitate the real time QoS tuning, a metric, QoS-GFS, is developed. This QoS-GFS is extended from the QoS-Index, another metric which has taken human perspective in the measurement of video quality. Hence QoS-GFS is better than the common metrics which measures QoS by means of rate of transmission of bytes or MPEG frames. We designed and implemented a middleware to perform empirical tests of the proposed transmission scheme and QoS tuning scheme. Experiment results show that our schemes can effectively enhance the QoS for online MPEG video streaming services. The work reported in this paper was supported in part by the RGC Earmarked Research Grant under RGC HKBU 2074/01E, and by the FRG under FRG 00-01/I. Joseph Kee-Yin Ng received a B.Sc. in Mathematics and Computer Science, a M.Sc. in Computer Science, and a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in the years 1986, 1988, and 1993, respectively. Dr. Ng is currently an associate professor in the Department of Computer Science at Hong Kong Baptist University. His current research interests includes Real-Time Networks, Multimedia Communications, Ubiquitous/Pervasive Computing, Mobile and Location-aware Computing, Performance Evaluation, Parallel and Distributed Computing. Dr. Ng is the Technical Program Chair for TENCON 2006, General Chair for The 11th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2005), Program Vice Chair for The 11th International Conference on Parallel and Distributed Systems (ICPADS 2005), Program Area-Chair for The 18th & 19th International Conference on Advanced Information Networking and Applications (AINA 2004 & AINA 2005) and he had served as the General Co-Chair for The International Computer Congress 1999 & 2001 (ICC'99 & ICC'01), the Program Co-Chair for The Sixth International Conference on Real-Time Computing Systems and Applications (RTCSA'99) and the General Co-Chair for The 1999 and 2001 International Computer Science Conference (ICSC'99 & ICSC'01). Dr. Ng is a member of the Editorial Board of Journal of Pervasive Computing and Communications, Associate Editor of Real-Time Systems Journal and Journal of Mobile Multimedia. He is a guest editor of International Journal of Wireless and Mobile Computing for a special issue on Applications, Services, and Infrastructures for Wireless and Mobile Computing. Dr. Ng is currently the Region 10 Coordinator for the Chapter Activities Board of the IEEE Computer Society, and is the Coordinator of the IEEE Computer Society Distinguished Visitors Program (Asia/Pacific). He is a senior member of the IEEE and has been a member of the IEEE Computer Society since 1991. Dr. Ng has been an exco-member (1993–95), General Secretary (1995–1997), Vice-Chair (1997–1999), Chair (1999–2001) and is the immediate past Chairman of the IEEE, Hong Kong Section, Computer Chapter. Dr. Ng received the Certificate of Appreciation for Leadership and Service (2000–2001) from IEEE Region 10 and the IEEE Meritorious Service Award from IEEE Computer Society at 2004. He is also a member of the IEEE Communication Society, and ACM. Karl R.P.H. Leung received his Ph.D. from The University of Hong Kong. He is currently a Principal Lecturer in the Department of Information and Communications Technology at the Hong Kong Institute of Vocational Education (IVE). He is the founder of the Compuware Software Testing Laboratory in the IVE with a donation from the Compuware Asia Pacific Co. Ltd. His research areas include: domain modeling, mission critical software engineering methodology, secure workflow systems, GSM-based location estimation, and QoS of MPEG streaming. He is a Senior Member of the IEEE and IEEE Computer Society, and has held major office of the IEEE Hong Kong Section Computer Chapter. While he was the chairman in 1998, the Chapter won the IEEE Most Outstanding Computer Society Chapter Award. He is also a Chartered Engineer of Engineering Council (UK), a Chartered Information Systems Engineer of British Computer Society (UK), an Engineer of Hong Kong Institution of Engineers, Registered Professional Engineer (Information) of Hong Kong Engineers Registration Board, and a member of ACM, BCS, ACS, HKIE and HKCS. Calvin Kin Cheung Hui received a B.Sc. (First Class Honours) in Computer Science, and a M.Phil. degree in Computer Science from Hong Kong Baptist University in the years 1999, and 2002, respectively. Mr. Hui's research interests includes Real-Time Networks, VoD Systems, Video Streaming, Multimedia Communication, and Distributed Systems Performance Evaluation.