A grid-oriented genetic algorithm framework for bioinformatics

In this paper, we propose a framework for enabling for researchers of genetic algorithms (GAs) to easily develop GAs running on the Grid, named “Grid-Oriented Genetic algorithms (GOGAs)”, and actually “Gridify” a GA for estimating genetic networks, which is being developed by our group, in order to examine the usability of the proposed GOGA framework. We also evaluate the scalability of the “Gridified” GA by applying it to a five-gene genetic network estimation problem on a grid testbed constructed in our laboratory. Hiroaki Imade: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2001. He received the M.S. degree in information systems from the Graduate School of Engineering, The University of Tokushima in 2003. He is now in Doctoral Course of Graduate School of Engineering, The University of Tokushima. His research interests include evolutionary computation. He currently researches a framework to easily develop the GOGA models which efficiently work on the grid. Ryohei Morishita: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2002. He is now in Master Course of Graduate School of Engineering, The University of Tokushima, Tokushima. His research interest is evolutionary computation. He currently researches GA for estimating genetic networks. Isao Ono, Ph.D.: He received his B.S. degree from the Department of Control Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 1994. He received Ph.D. of Engineering at Tokyo Institute of Technology, Yokohama, in 1997. He worked as a Research Fellow from 1997 to 1998 at Tokyo Institute of Technology, and at University of Tokushima, Tokushima, Japan, in 1998. He worked as a Lecturer from 1998 to 2001 at University of Tokushima. He is now Associate Professor at University of Tokushima. His research interests include evolutionary computation, scheduling, function optimization, optical design and bioinformatics. He is a member of JSAI, SCI, IPSJ and OSJ. Norihiko Ono, Ph.D.: He received his B.S. M.S. and Ph.D. of Engineering in 1979, 1981 and 1986, respectively, from Tokyo Institute of Technology. From 1986 to 1989, he was Research Associate at Faculty of Engineering, Hiroshima University. From 1989 to 1997, he was an associate professor at Faculty of Engineering, University of Tokushima. He was promoted to Professor in the Department of Information Science and Intelligent Systems in 1997. His current research interests include learning in multi-agent systems, autonomous agents, reinforcement learning and evolutionary algorithms. Masahiro Okamoto, Ph.D.: He is currently Professor of Graduate School of Systems Life Sciences, Kyushu University, Japan. He received his Ph.D. degree in Biochemistry from Kyushu University in 1981. His major research field is nonlinear numerical optimization and systems biology. His current research interests cover system identification of nonlinear complex systems by using evolutional computer algorithm of optimization, development of integrated simulator for analyzing nonlinear dynamics and design of fault-tolerant routing network by mimicking metabolic control system. He has more than 90 peer reviewed publications.     

Behavioural notions for elementary net systems

We study the relationships between a number of behavioural notions that have arisen in the theory of distributed computing. In order to sharpen the under-standing of these relationships we apply the chosen behavioural notions to a basic net-theoretic model of distributed systems called elementary net systems. The behavioural notions that are considered here are trace languages, non-sequential processes, unfoldings and event structures. The relationships between these notions are brought out in the process of establishing that for each elementary net system, the trace language representation of its behaviour agrees in a strong way with the event structure representation of its behaviour. M. Nielsen received a Master of Science degree in mathematics and computer science in 1973, and a Ph.D. degree in computer science in 1976 both from Aarhus University, Denmark. He has held academic positions at Department of Computer Science, Aarhus University, Denmark since 1976, and was visiting researcher at Computer Science Department, University of Edinburgh, U.K., 1977–79, and Computer Laboratory, Cambridge University, U.K., 1986. His research interest is in the theory of distributed computing. Grzegorz Rozenberg received a master of engineering degree from the Department of Electronics (section computers) of the Technical University of Warsaw in 1964 and a Ph.D. in mathematics from the Institute of Mathematics of the Polish Academy of Science in 1968. He has held acdeemic positions at the Institute of Mathematics of the Polish Academy of Science, the Department of Mathematics of Utrecht University, the Department of Computer Science at SUNY at Buffalo, and the Department of Mathematics of the University of Antwerp. He is currently Professor at the Department of Computer Science of Leiden University and Adjoint Professor at the Department of Computer Science of the University of Colorado at Boulder. His research interests include formal languages and automata theory, theory of graph transformations, and theory of concurrent systems. He is currently President of the European Association for Theoretical Computer Science (EATCS). P.S. Thiagarajan received the Bachelor of Technology degree from the Indian Institute of Technology, Madras, India in 1970. He was awarded the Ph.D. degree by Rice University, Houston Texas, U.S.A, in 1973. He has been a Research Associate at the Massachusetts Institute of Technology, Cambridge a Staff Scientist at the Geosellschaft für Mathematik und Datenverarbeitung, St. Augustin, a Lektor at Århus University, Århus and an Associate Professor at the Institute of Mathematical Sciences, Madras. He is currently a Professor at the School of Mathematics, SPIC Science Foundation, Madras. He research intest is in the theory of distributed computing.     

A challenge towards next-generation research infrastructure for advanced life science

Recently, life scientists have expressed a strong need for computational power sufficient to complete their analyses within a realistic time as well as for a computational power capable of seamlessly retrieving biological data of interest from multiple and diverse bio-related databases for their research infrastructure. This need implies that life science strongly requires the benefits of advanced IT. In Japan, the Biogrid project has been promoted since 2002 toward the establishment of a next-generation research infrastructure for advanced life science. In this paper, the Biogrid strategy toward these ends is detailed along with the role and mission imposed on the Biogrid project. In addition, we present the current status of the development of the project as well as the future issues to be tackled. Haruki Nakamura, Ph.D.: He is Professor of Protein Informatics at Institute for Protein Research, Osaka University. He received his B.S., M.A. and Ph.D. from the University of Tokyo in 1975, 1977 and 1980 respectively. His research field is Biophysics and Bioinformatics, and has so far developed several original algorithms in the computational analyses of protein electrostatic features and folding dynamics. He is also a head of PDBj (Protein Data Bank Japan) to manage and develop the protein structure database, collaborating with RCSB (Research Collaboratory for Structural Bioinformatics) in USA and MSD-EBI (Macromolecular Structure Database at the European Bioinformatics Institute) in EU. Susumu Date, Ph.D.: He is Assistant Professor of the Graduate School of Information Science and Technology, Osaka University. He received his B.E., M.E. and Ph.D. degrees from Osaka University in 1997, 2000 and 2002, respectively. His research field is computer science and his current research interests include application of Grid computing and related information technologies to life sciences. He is a member of IEEE CS and IPSJ. Hideo Matsuda, Ph.D.: He is Professor of the Department of Bioinformatic Engineering, the Graduate School of Information Science and Technology, Osaka University. He received his B.S., M.Eng. and Ph.D. degrees from Kobe University in 1982, 1984 and 1987 respectively. For M.Eng. and Ph.D. degrees, he majored in computer science. His research interests include computational analysis of genomic sequences. He has been involved in the FANTOM (Functional Annotation of Mouse) Project for the functional annotation of RIKEN mouse full-length cDNA sequences. He is a member of ISCB, IEEE CS and ACM. Shinji Shimojo, Ph.D.: He received M.E. and Ph.D. degrees from Osaka University in 1983 and 1986 respectively. He was an Assistant Professor with the Department of Information and Computer Sciences, Faculty of Engineering Science at Osaka University from 1986, and an Associate Professor with Computation Center from 1991 to 1998. During the period, he also worked as a visiting researcher at the University of California, Irvine for a year. He has been Professor with Cybermedia Center (then Computation Center) at Osaka University since 1998. His current research work focus on a wide variety of multimedia applications, peer-to-peer communication networks, ubiquitous network systems and Grid technologies. He is a member of ACM, IEEE and IEICE.     

Information gathering and searching approaches on the Web

The information accessible through the Internet is increasing explosively as the Web is getting more and more widespread. In this situation, the Web is indispensable information resource for both of information gathering and information searching. Though traditional information retrieval techniques have been applied to information gathering and searching in the Web, they are insufficient for this new form of information source. Fortunately some Al techniques can be straightforwardly applicable to such tasks in the Web, and many researchers are trying this approach. In this paper, we attempt to describe the current state of information gathering and searching technologies in the Web, and the application of AI techniques in the fields. Then we point out limitations of these traditional and AI approaches and introduce two aapproaches: navigation planning and a Mondou search engine for overcoming them. The navigation planning system tries to collect systematic knowledge, rather than Web pages, which are only pieces of knowledge. The Mondou search engine copes with the problems of the query expansion/modification based on the techniques of text/web mining and information visualization. Seiji Yamada, Dr. Eng.: He received the B.S., M.S. and Ph.S. degrees in control engineering and artificial intelligence from Osaka University, Osaka, Japan, in 1984, 1986 and 1989, respectively. From 1989 to 1991, he served as a Research Associate in the Department of Control Engineering at Osaka University. From 1991 to 1996, he served as a Lecturer in the Institute of Scientific and Industrial Research at Osaka University. In 1996, he joined the Department of Computational Intelligence and Systems Science at Tokyo Institute of Technology, Yokohama, Japan, as an Associate Professor. His research interests include artificial intelligence, planning, machine learning for a robotics, intelligent information retrieval in the WWW, human computer interaction, He is a member of AAAI, IEEE, JSAI, RSJ and IEICE. Hiroyuki Kawano, Dr.Eng.: He is an Associate Professor at the Department of Systems Science, Graduate School of Informatics, Kyoto University, Japan. He obtained his B.Eng. and M.Eng. degrees in Applied Mathematics and Physics, and his Dr.Eng. degree in Applied Systems Science from Kyoto University. His research interests are in advanced database technologies, such as data mining, data warehousing, knowledge discovery and web search engine (Mondou). He has served on the program committees of several conferences in the areas of Data Base Systems, and technical committes of advanced information systems.     

A quantum algorithm using NMR computers to break secret-key cryptosystems

In this paper, we discuss quantum algorithms that, for a given plaintextm _o and a given ciphertextc _o, will find a secret key,k _o, satisfyingc _o=E(k _o,m _o), where an encryption algorithm,E, is publicly available. We propose a new algorithm suitable for an NMR (Nuclear Magnetic Resonance) computer based on the technique used to solve the counting problem. The complexity of, our algorithm decreases as the measurement accuracy of the NMR computer increases. We discuss the possibility that the proposed algorithm is superior to Grover’s algorithm based on initial experimental results. Kazuo Ohta, Dr.S.: He is Professor of Faculty of Electro-Communications at the University of Electro-Communications, Japan. He received B.S., M.S., and Dr. S. degrees from Waseda University, Japan, in 1977, 1979, and 1990, respectively. He was researcher of NTT (Nippon Telegraph and Telephone Corporation) from 1979 to 2001, and was visiting scientist of Laboratory for Computer Science e of MIT (Massachusetts Institute of Technology) in 1991–1992 and visiting Professor of Applied Mathematics of MIT in 2000. He is presently engaged in research on Information Security, and theoretical computer science. Dr. Ohta is a member of IEEE, the International Association for Cryptologic Research, the Institute of Electronics, Information and Communication Engineers and the Information Processing Society of Japan. Tetsuro Nishino,: He received the B.S., M.S. and, D.Sc. degrees in mathematics from Waseda University, in 1982, 1984, and 1991 respectively. From 1984 to 1987, he joined Tokyo Research Laboratory, IBM Japan. From 1987 to 1992, he was a Research Associate of Tokyo Denki University, and from 1992 to 1994, he was an Associate Professor of Japan Advanced Institute of Science and Technology, Hokuriku. He is presently an Associate Professor in the Department of Communications and Systems Engineering, the University of Electro-Communications. His main interests are circuit complexity theory, computational learning theory and quantum complexity theory. Seiya Okubo,: He received the B.Eng. and M.Eng. degrees from the University of Electro-Communications in 2000 and 2002, respectively. He is a student in Graduate School of Electro-Communications, the University of Electro-Communications. His research interests include quantum complexity theory and cryptography. Noboru Kunihiro, Ph.D.: He is Assistant Professor of the University of Electro-Communications. He received his B. E., M. E. and Ph. D. in mathematical engineering and information physics from the University of Tokyo in 1994, 1996 and 2001, respectively. He had been engaged in the research on cryptography and information security at NTT Communication Science Laboratories from 1996 to 2002. Since 2002, he has been working for Department of Information and Communication Engineering of the University of Elector-Communications. His research interests include cryptography, information security and quantum computations. He was awarded the SCIS’97 paper prize.     

LMI stability criterion with less variables for time-delay systems

Slack variables approach is an important technique for tackling the delay-dependent stability problem for systems with time-varying delay. In this paper, a new delay-dependent stability criterion is presented without introducing any slack variable. The technique is based on a simply integral inequality. The result is shown to be equivalent to some existing ones but includes the least number of variables. Thus, redundant selection and computation can be avoided so that the computational burden can be largely reduced. Numerical examples are given to illustrate the effectiveness of the proposed stability conditions. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors would like to thank the Associate Editor and the Reviewers for their very helpful comments and suggestions. This work was supported in part by the Funds for Creative Research Groups of China under Grant 60821063, by the State Key Program of National Natural Science of China under Grant 60534010, by the Funds of National Science of China under Grant 60674021, 60774013, 60774047, National 973 Program of China under Grant No. 2009CB320604, and by the Funds of Ph.D. program of MOE, China under Grant 20060145019 and the 111 Project B08015. Xun-Lin Zhu received the B.S. degree in Applied Mathematics from Information Engineering Institute, Zhengzhou, China, in 1986, the M.S. degree in basic mathematics from Zhengzhou University, Zhengzhou, China, in 1989, and the Ph.D. degree in Control Theory and Engineer-ing from Northeastern University, Shenyang, China, in 2008. Currently, he is an Associate Professor at Zhengzhou University of Light Industry, Zhengzhou, China. His research interests include neural networks and networked control systems. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, non-fragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society. Tao Li was born in 1979. He is now pursuing a Ph.D. degree in Research Institute of Automation Southeast University, China. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Chong Lin received the B.Sci and M.Sci in Applied Mathematics from the Northeastern University, China, in 1989 and 1992, respectively, and the Ph.D in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore, in 1999. He was a Research Associate with the University of Hong Kong in 1999. From 2000 to 2006, he was a Research Fellow with the National University of Singapore. He is currently a Profesor with the Institute of Complexity Science, Qingdao University, China. His current research interests are mainly in the area of systems analysis and control. Lei Guo was born in 1966. He received the Ph.D. degree in Control Engineering from Southeast University (SEU), PR China, in 1997. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now he is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. He also holds a Visiting Professor position in the University of Manchester, UK and an invitation fellowship in Okayama University, Japan. His research interests include robust control, stochastic systems, fault detection, filter design, and nonlinear control with their applications.     

Efficient algorithms for NMR quantum computers with small qubits

The security of the RSA cryptosystems is based on the difficulty of factoring a large composite integer. In 1994, Shor showed that factoring a large composite is executable in polynomial time if we use a quantum Turing machine. Since this algorithm is complicated, straightforward implementations seem impractical judging from current technologies. In this paper, we propose simple and efficient algorithms for factoring and discrete logarithm problem based on NMR quantum computers. Our algorithms are easier to implement if we consider NMR quantum computers with small qubits. A part of this work was done while both authors were with NTT Communication Science Laboratories. Noboru Kunihiro, Ph.D.: He is Assistant Professor of the University of Electro-Communications. He received his B.E., M.E. and Ph.D. in mathematical engineering and information physics from the University of Tokyo in 1994, 1996 and 2001, respectively. He had been engaged in the research on cryptography and information security at NTT Communication Science Laboratories from 1996 to 2002. Since 2002, he has been working for Department of Information and Communication Engineering of the University of Elector-Communications. His research interest includes cryptography, information security and quantum computations. He was awarded the SCIS’97 paper prize. Shigeru Yamashita, Ph.D.: Associate Professor of Graduate School of Information Science, Nara Institute of Science and Technology, Nara 630-0192, Japan. He received his B.E., M.E. and Ph.D. degrees in information science from Kyoto University, Kyoto, Japan, in 1993, 1995 and 2001, respectively. His research interests include new type of computer architectures and quantum computation. He received the 2000 IEEE Circuits and Systems Society Transactions on Computer-Aided Design of Integrated Circuits and Systems Best Paper Award.     

Two fusion predictors for discrete-time linear systems with different types of observations

New fusion predictors for linear dynamic systems with different types of observations are proposed. The fusion predictors are formed by summation of the local Kalman filters/predictors with matrix weights depending only on time instants. The relationship between fusion predictors is established. Then, the accuracy and computational efficiency of the fusion predictors are demonstrated on the first-order Markov process and the GMTI model with multisensor environment. Recommended by Editorial Board member Lucy Y. Pao under the direction of Editor Young Il Lee. This work was partially supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MOST), No. R01-2007-000-20227-0 and the Center for Distributed Sensor Network at GIST. Ha-Ryong Song received the B.S. degree in Control and Instrumentation Engineering from the Chosun University, Korea, in 2006, the M.S. degree in School of Information and Mechatronics from the Gwangju Institute of Science and Technology, Korea, in 2007. He is currently a Ph.D. candidate in Gwangju Institute of Science and Technology. His research interests include estimation, target tracking systems, data fusion, nonlinear filtering. Moon-Gu Jeon received the B.S. degree in architectural engineering from the Korea University, Korea in 1988. He then received both the M.S. and Ph.D. degrees in computer science and scientific computation from the University of Minnesota in 1999 and 2001, respectively. Currently, he is an Associate Professor at the School of Information and Mechatronics of the Gwangju Institute of Science and Technology (GIST). His current research interests are in machine learning and pattern recognition and evolutionary computation. Tae-Sun Choi received the B.S. degree in Electrical Engineering from the Seoul National University, Seoul, Korea, in 1976, the M.S. degree in Electrical Engineering from the Korea Advanced Institute of Science and Technology, Seoul, Korea, in 1979, and the Ph.D. degree in Electrical Engineering from the State University of New York at Stony Brook, in 1993. He is currently a Professor in the School of Information and Mechatronics at Gwangju Institute of Science and Technology, Korea. His research interests include image processing, machine/robot vision, and visual communications. Vladimir Shin received the B.Sc. and M.Sc. degrees in Applied Mathematics from Moscow State Aviation Institute, in 1977 and 1979, respectively. In 1985 he received the Ph.D. degree in Mathematics at the Institute of Control Science, Russian Academy of Sciences, Moscow. He is currently an Associate Professor at Gwangju Institute of Science and Technology, South Korea. His research interests include estimation, filtering, tracking, data fusion, stochastic control, identification, and other multidimensional data processing methods.     

A Fuzzy set based approach to generalized landscape theory of aggregation

In this paper, we firstly reformulate the landscape theory of aggregation (Axelrod and Bennett, 1993) in terms of an optimization problem, and then straightforwardly propose a fuzzy-set-theoretic based extension for it. To illustrate efficiency of the proposal, we make a simulation with the proposed framework for the international alignment of the Second World War in Europe. It is shown that the obtained results are essentially comparable to those given by the original theory. Consequently, the fuzzy-set-theoretic based extension of landscape theory can allow us to analyze a wide variety of aggregation processes in politics, economics, and society in a more flexible manner. Shigemasa Suganuma: He received the M.S. degree in knowledge science from Japan Advanced Institute of Science and Technology,, Ishikawa, Japan in 2000. He currently takes a doctor's course in School of Knowledge Science, Japan Advanced Institute of Science and Technology (JAIST). His research interest includes agent based simulation and its application to social and political concerns, industry and environmental behavior. Van-Nam Huynh, Ph.D.: He received the B.S. in Mathematics (1990) and Ph.D. (1999) from University of Quinhon, Vietnam and Institute of Information Technology, Vietnam Academy of Science and Technology, respectively. From April 2001 to March 2002, he was a postdoctoral fellow awarded by INOUE Foundation for Science at JAIST. He is currently a Research Associate in School of Knowledge Science, JAIST, Japan. His current research interests include fuzzy logic and approximate reasoning, uncertainty formalisms in knowledge-based systems, decision making. Yoshiteru Nakamori, Ph.D.: He received the B.S., M.S., and Ph.D. degrees all in applied mathematics and physics from Kyoto University, Kyoto, Japan. He is currently a Professor in School of Knowledge Science, JAIST. His research interests include development of modeling methodology based on hard as well as soft data, and support systems for soft thinking around hard data. Shouyang Wang, Ph.D.: He received the Ph.D. degree in Operations Research from Chinsese Academy of Sciences (CAS), Beijing in 1986. He is currently a Bairen distinguished professor of Management Science at Academy of Mathematics and Systems Sciences of CAS and a Lotus chair professor of Hunan University in Changsha. He is the editor-in-chief or a co-editor of 12 journals. He has published 120 journal articles. His current research interest includes decision analysis, system engineering and knowledge management.     

Efficient discovery of optimal word-association patterns in large text databases

We study efficient discovery of proximity word-association patterns, defined by a sequence of strings and a proximity gap, from a collection of texts with the positive and the negative labels. We present an algorithm that finds alld-stringsk-proximity word-association patterns that maximize the number of texts whose matching agree with their labels. It runs in expected time complexityO(k ^d−1n log ^d n) and spaceO(k ^d−1n) with the total lengthn of texts, if texts are uniformly random strings. We also show that the problem to find one of the best word-association patterns with arbitrarily many strings in MAX SNP-hard. Shinichi Shimozono, Ph.D.: He is an Associate Professor of the Department of Artificial Intelligence at Kyushu Institute of Technology Iizuka, Japan. He obtained the B.S. degree in Physics from Kyushu University, awarded M.S. degree from Graduate School of Information Science in Kyushu University, and his Dr. Sci. degree in 1996 from Kyushu University. His research interests are primarily in the design and analysis of algorithms for intractable problems. Hiroki Arimura, Ph.D.: He is an Associate Professor of the Department of Informatics at Kyushu University, Fukuoka, Japan. He is also a researcher with Precursory Research for Embryonic Science and Technology, Japan Science and Technology Corporation (JST) since 1999. He received the B.S. degree in 1988 in Physics, the M.S. degree in 1979 and the Dr.Sci. degree in 1994 in Information Systems from Kyushu University. His research interests include data mining, computational learning theory, and inductive logic programming. Setsuo Arikawa, Ph.D.: He is a Professor of the Department of Informatics and the Director of University Library at Kyushu University, Fukuoka, Japan. He received the B.S. degree in 1964, the M.S. degree in 1966 and the Dr.Sci. degree in 1969 all in Mathematics from Kyushu University. His research interests include Discovery Science, Algorithmic Learning Theory, Logic and Inference/Reasoning in AI, Pattern Matching Algorithms and Library Science. He is the principal investigator of the Discovery Science Project sponsored by the Grant-in Aid for Scientific Research on Priority Area from the Ministry of ESSC, Japan.     

Generation of templates for low-resolution text recognition using a hypothesis graph

We propose a recognition method of character-string images captured by portable digital cameras. A challenging task in character-string recognition is the segmentation of characters. In the proposed method, a hypothesis graph is used for recognition-based segmentation of the character-string images. The hypothesis graph is constructed by the subspace method, using eigenvectors as conditionally elastic templates. To obtain these templates, a generation-based approach is introduced in the training stage. Various templates are generated to cope with low-resolution. We have experimentally proved that the proposed scheme achieves high recognition performance even for low-resolution character-string images. The text was submitted by the authors in English. Hiroyuki Ishida. Received his B.S. and M.S. degrees from the Department of Information Engineering and from the Graduate School of Information Science, respectively, at Nagoya University. He is currently pursuing a Ph.D. in Information Science at Nagoya University. Ichiro Ide. Received his B.S. degree from the Department of Electronic Engineering, his M.S. degree from the Department of Information Engineering, and his Ph.D. from the Department of Electrical Engineering at the University of Tokyo. He is currently an Associate Professor in the Graduate School of Information Science at Nagoya University. Tomokazu Takahashi. Received his B.S. degree from the Department of Information Engineering at Ibaraki University, and his M.S. and Ph.D. from the Graduate School of Science and Engineering at Ibaraki University. His research interests include computer graphics and image recognition. Hiroshi Murase. Received his B.S., M.S., and Ph.D. degrees from the Graduate School of Electrical Engineering at Nagoya University. He is currently a Professor in the Graduate School of Information Science at Nagoya University. He received the Ministry Award from the Ministry of Education, Culture, Sports, Science and Technology in Japan in 2003. He is a Fellow of the IEEE.     

InfoFilter: Supporting quality of service for fresh information delivery

With the explosive growth of the Internet and World Wide Web comes a dramatic increase in the number of users that compete for the shared resources of distributed system environments. Most implementations of application servers and distributed search software do not distinguish among requests to different web pages. This has the implication that the behavior of application servers is quite unpredictable. Applications that require timely delivery of fresh information consequently suffer the most in such competitive environments. This paper presents a model of quality of service (QoS) and the design of a QoS-enabled information delivery system that implements such a QoS model. The goal of this development is two-fold. On one hand, we want to enable users or applications to specify the desired quality of service requirements for their requests so that application-aware QoS adaptation is supported throughout the Web query and search processing. On the other hand, we want to enable an application server to customize how it should respond to external requests by setting priorities among query requests and allocating server resources using adaptive QoS control mechanisms. We introduce the Infopipe approach as the systems support architecture and underlying technology for building a QoS-enabled distributed system for fresh information delivery. Ling Liu, Ph.D.: She is an associate professor at the College of Computing, Georgia Institute of Technology. She received her Ph.D. from Tilburg University, The Netherlands in 1993. Her research interests are in the area of large-scale data intensive systems and its applications in distributed, mobile, multimedia, and Internet computing environments. Her work has focused on systems support for creating, searching, manipulating, and monitoring streams of information in wide area networked information systems. She has published more than 70 papers in internal journals or international conferences, and has served on more than 20 program committees in the area of data engineering, databases, and knowledge and information management. Calton Pu, Ph. D.: He is a Professor and John P. Imlay, Jr. Chair in Software at the College of Computing, Georgia Institute of Technology. Calton received his Ph.D. from University of Washington in 1986. He leads the Infosphere expedition project, which is building the system software to support the next generation information flow applications. Infosphere research includes adaptive operating system kernels, communications middleware, and distributed information flow applications. His past research included operating system projects such as Synthetix and Microfeedback, extended transaction projects such as Epsilon Serializability, and Internet data management. He has published more than 125 journal and conference papers, and served on more than 40 program committees. Karsten Schwan, Ph.D.: He is a professor in the College of Computing at the Georgia Institute of Technology. He received the M.Sc. and Ph.D. degrees from Carnegie-Mellon University in Pittsburgh, Pennsylvania. He directs the IHPC project for high performance cluster computing at Georgia Tech. His current research addresses the interactive nature of modern high performance applications (i.e., online monitoring and computational steering), the development of efficient and object-based middleware, the operating system support for distributed and parallel programs, and the online configuration of applications for distributed real-time applications and for communication protocols. Jonathan Walpole, Ph.D.: He is a Professor in the Computer Science and Engineering Department at oregon Graduate Institute of Science and Technology. He received his Ph.D. in Computer Science from Lancaster University, U.K. in 1987. His research interests are in the area of adaptive systems software and its application in distributed, mobile, multimedia computing environments. His work has focused on quality of service specification, adaptive resource management and dynamic specialization for enhanced performance, survivability and evolvability of large software systems, and he has published extensively in these areas.     

Shape Estimation from Support and Diameter Functions

We address the problem of reconstructing a planar shape from a finite number of noisy measurements of its support function or its diameter function. New linear and non-linear algorithms are proposed, based on the parametrization of the shape by its Extended Gaussian Image. This parametrization facilitates a systematic statistical analysis of the problem via the Cramér-Rao lower bound (CRLB), which provides a fundamental lower bound on the performance of estimation algorithms. Using CRLB, we also generate confidence regions which conveniently display the effect of parameters like eccentricity, scale, noise, and measurement direction set, on the quality of the estimated shapes, as well as allow a performance analysis of the algorithms. Supported in part by U.S. National Science Foundation grants CCR-9984246 and DMS-0203527. Amyn Poonawala received the B.E. degree from the University of Mumbai, India, in 2001, and the M.S. degree from the University of California, Santa Cruz (UCSC), in 2004, both in computer engineering. He is currently pursuing the Ph.D. degree in computer engineering at UCSC. His technical interests include statistical signal and image processing and inverse problems in microlithography. Peyman Milanfar received the B.S. degree in electrical engineering/mathematics from the University of California, Berkeley, in 1988, and the S.M., E.E., and Ph.D. degrees in electrical engineering from the Massachusetts Institute of Technology, in 1990, 1992, and 1993, respectively. Until 1999, he was a Senior Research Engineer at SRI International, Menlo Park, CA. He is currently Associate Professor of Electrical Engineering at the University of California, Santa Cruz. He was a Consulting Assistant Professor of computer science at Stanford University from 1998-2000, and a visiting Associate Professor there in 2002. His technical interests are in statistical signal and image processing, and inverse problems. He won a National Science Foundation CAREER award in 2000, was associate editor for the IEEE Signal Processing Letters from 1998 to 2001, and is a Senior member of the IEEE. Richard Gardner holds B.Sc. and Ph.D. degrees in mathematics from University College London and was awarded a D.Sc. degree from the University of London in 1988 for contributions to measure theory and convex geometry. He has held positions at universities and research institutions in several countries and has been Professor of Mathematics at Western Washington University since 1991. He founded geometric tomography, an area of geometric inverse problems involving data concerning sections by and projections on lines or planes, and published a book on the subject in 1995.     

Towards a Smarter Meeting Record—Capture and Access of Meetings Revisited

Multimedia records of meetings contain a rich amount of project information. However, finding detailed information in a meeting record can be difficult because there is no structural information other than time to aid navigation. In this paper we survey and discuss various ways of indexing meeting records by categorizing existing approaches along multiple dimensions. We then introduce the notion of creating indices based upon user interaction with domain-specific artifacts. As an example to illustrate the use of domain-specific artifacts to create meaningful pointers into the meeting record, we describe capture and access in a prototype system that supports general meeting artifacts. Werner Geyer is a Research Staff Member at the IBM T.J. Watson Research Lab in Cambridge, Massachusetts, in the Collaborative User Experience Group (CUE). He is leading research projects in the areas of activity-centric collaboration, ad hoc collaboration, and virtual meetings. His research focuses on the intersections of egocentric vs. public, informal vs. formal, unstructured vs. structured types of collaboration. Before joining CUE, Werner was a Post Doc at IBM Research in New York where he worked on new web-based team support technologies and on capture and access of distributed meetings. He holds a Ph.D. in Computer Science from the University of Mannheim, Germany. He also earned a M.S. in Information Technology, which combines Computer Science and Business Administration, from the University of Mannheim. Heather Richter is an Assistant Professor in the Department of Software and Information Systems at the University of North Carolina at Charlotte. She received her Ph.D. in Computer Science from the Georgia Institute of Technology in 2005, and her B.S. in Computer Science from Michigan State University in 1995. Her research interests are in the areas of Human Computer Interaction, Computer Supported Cooperative Work, Ubiquitous Computing, and Software Engineering. Gregory D. Abowd is an Associate Professor in the College of Computing at the Georgia Institute of Technology. He leads the Ubiquitous Computing Research Group in examining issues involved in building and evaluating ubiquitous computing applications that impact our everyday lives. Dr. Abowd initiated, and now co-directs, the Aware Home Research Initiative at Georgia Tech. He is an Associate Editor for the Human Computer Interaction Journal and the IEEE Pervasive Computing Magazine. He received a B.S. in Mathematics in 1986 from the University of Notre Dame and the degrees of M.Sc. in 1987 and D.Phil in 1991 in Computation from Oxford University.     

On the suitability of Biological structure determination by electron microscopy to Grid Computing

The present contribution describes a potential application of Grid Computing in Bioinformatics. High resolution structure determination of biological specimens is critical in BioSciences to understanding the biological function. The problem is computational intensive. Distributed and Grid Computing are thus becoming essential. This contribution analyzes the use of Grid Computing and its potential benefits in the field of electron microscope tomography of biological specimens. Jose-Jesus Fernandez, Ph.D.: He received his M.Sc. and Ph.D. degrees in Computer Science from the University of Granada, Spain, in 1992 and 1997, respectively. He was a Ph.D. student at the Bio-Computing unit of the National Center for BioTechnology (CNB) from the Spanish National Council of Scientific Research (CSIC), Madrid, Spain. He became an Assistant Professor in 1997 and, subsequently, Associate Professor in 2000 in Computer Architecture at the University of Almeria, Spain. He is a member of the supercomputing-algorithms research group. His research interests include high performance computing (HPC), image processing and tomography. Jose-Roman Bilbao-Castro: He received his M.Sc. degree in Computer Science from the University of Almeria in 2001. He is currently a Ph.D. student at the BioComputing unit of the CNB (CSIC) through a Ph.D. CSIC-grant in conjuction with Dept. Computer Architecture at the University of Malaga (Spain). His current research interestsinclude tomography, HPC and distributed and grid computing. Roberto Marabini, Ph.D.: He received the M.Sc. (1989) and Ph.D. (1995) degrees in Physics from the University Autonoma de Madrid (UAM) and University of Santiago de Compostela, respectively. He was a Ph.D. student at the BioComputing Unit at the CNB (CSIC). He worked at the University of Pennsylvania and the City University of New York from 1998 to 2002. At present he is an Associate Professor at the UAM. His current research interests include inverse problems, image processing and HPC. Jose-Maria Carazo, Ph.D.: He received the M.Sc. degree from the Granada University, Spain, in 1981, and got his Ph.D. in Molecular Biology at the UAM in 1984. He left for Albany, NY, in 1986, coming back to Madrid in 1989 to set up the BioComputing Unit of the CNB (CSIC). He was involved in the Spanish Ministry of Science and Technology as Deputy General Director for Research Planning. Currently, he keeps engaged in his activities at the CNB, the Scientific Park of Madrid and Integromics S.L. Immaculada Garcia, Ph.D.: She received her B.Sc. (1977) and Ph.D. (1986) degrees in Physics from the Complutense University of Madrid and University of Santiago de Compostela, respectively. From 1977 to 1987 she was an Assistant professor at the University of Granada, from 1987 to 1996 Associate professor at the University of Almeria and since 1997 she is a Full Professor and head of Dept. Computer Architecture. She is head of the supercomputing-algorithms research group. Her research interest lies in HPC for irregular problems related to image processing, global optimization and matrix computation.     

A framework for protein structure prediction on the grid

The large number of protein sequences, provided by genomic projects at an increasing pace, constitutes a challenge for large scale computational studies of protein structure and thermodynamics. Grid technology is very suitable to face this challenge, since it provides a way to access the resources needed in compute and data intensive applications. In this paper, we show the procedure to adapt to the Grid an algorithm for the prediction of protein thermodynamics, using the GridWay tool. GridWay allows the resolution of large computational experiments by reacting to events dynamically generated by both the Grid and the application. Eduardo Huedo, Ph.D.: He is a Computer Engineer (1999) and Ph.D. in Computer Architecture (2004) by the Universidad Complutense de Madrid (UCM). He is Scientist in the Advanced Computing Laboratory at Centro de Astrobiología (CSIC-INTA), associated to NASA Astrobiology Institute. He had one appointment in 2000 as a Summer Student in High Performance Computing and Applied Mathematics at ICASE (NASA Langley Research Center). His research areas are Performance Management and Tuning, High Performance Computing and Grid Technology. Ugo Bastolla, Ph.D.: He received his degree and Ph.D. in Physics in Rome University, with L. Peliti and G. Parisi respectively. He was interested from the beginning in biologically motivated problems, therefore, studied models of Population Genetics, Boolean Networks, Neural Networks, Statistical Mechanics of Polymers, Ecological and Biodiversity. His main research interest is constituted by studies of protein folding thermodynamics and evolution. Thereby, he set up an effective energy function allowing prediction of protein folding thermodynamics, and applied it to protein structure prediction, to simulate protein evolution and to analyze protein sequences from a thermodynamical point of view. He is currently in the Bioinformatic Unit of the Centro de Astrobiología of Madrid. Rubén S. Montero, Ph.D.: He received his B.S. in Physics (1996), M.S in Computer Science (1998) and Ph.D. in Computer Architecture (2002) from the Universidad Complutense de Madrid (UCM). He is Assistant Professor of Computer Architecture and Technology at UCM since 1999. He has held several research appointments at ICASE (NASA Langley Research Center), where he worked on computational fluid dynamics, parallel multigrid algorithms and Cluster computing. Nowadays, his research interests lie mainly in Grid Technology, in particular in adaptive scheduling, adaptive execution and distributed algorithms. Ignacio M. Llorente, Ph.D.: He received his B.S. in Physics (1990), M.S in Computer Science (1992) and Ph.D. in Computer Architecture (1995) from the Universidad Complutense de Madrid (UCM). He is Executive M.B.A. by Instituto de Empresa since 2003. He is Associate Professor of Computer Architecture and Technology in the Department of Computer Architecture and System Engineering at UCM and Senior Scientist at Centro de Astrobiología (CSIC-INTA), associated to NASA Astrobiology Institute. He has held several appointments since 1997 as a Consultant in High Performance Computing and Applied Mathematics at ICASE (NASA Langley Research Center). His research areas are Information Security, High Performance Computing and Grid Technology.     

Variational Image Binarization and its Multi-Scale Realizations

A variational approach for image binarization is discussed in this paper. The approach is based on the interpolation of surface. This interpolation is computed using edge points as interpolating points and minimizing an energy functional which interpolates a smooth threshold surface. A globally convergent Sequential Relaxation Algorithm (SRA) is proposed for solving the optimization problem. Moreover, our algorithm is also formulated in a multi-scale framework. The performance of our method is demonstrated on a variety of real and synthetic images and compared with traditional techniques. Examples show that our method gives promising results.This research is partially supported by HKBU Faculty Research Grant FRG/02-03/II-04 and NSF of China Grant. C.S. Tong received a BA degree in Mathematics and a Ph.D. degree (on Mathematical Modelling of Intermolecular Forces) both from Cambridge University. After graduation, he joined the Signal and Image Processing division of GEC-Marconis Hirst Research Centre as a Research Scientist, working on image restoration and fractal image compression. He then moved to the Department of Mathematics at Hong Kong Baptist University in 1992, becoming Associate Professor since 2002.He is a member of the IEEE, a Fellow of the Institute of Mathematics and Its Application, and a Chartered Mathematician. His current research interests include image processing, fractal image compression, and neural networks. Yongping Zhang received the M. S. degree from Department of Mathematics at Shaanxi Normal University, Xian, China, in 1988 and received the Ph.D. degree from The Institute of Artificial Intelligence and Robotics at Xian Jiaotong University, Xian, China, in 1998.In 1988 he joined Department of Mathematics at Shaanxi Normal University, where he became Associate Professor in July 1987. He held postdoctoral position at Northwestern Polytechnic University during the 1999–2000 academic years. Currently he is a research associate in the Bioengineering Institute at the University of Auckland, New Zealand. His research interests are in Computer Vision and Pattern Recognition, and include Wavelets, Neural Networks, PDE methods and variational methods for image processing. Nanning Zheng received the M.S. degree from Xian Jiaotong University, Xian, China, in 1981 and the Ph.D. degree from Keio University, Japan, in 1985. He is an academician of Chinese Engineer Academy, and currently a Professor at Xian Jiaotong University. His research interest includes Signal Processing, Machine Vision and Image Processing, Pattern Recognition and Virtual Reality.This revised version was published online in June 2005 with correction to CoverDate     

A study on effects of market systems in an artificial market

In an artificial market approach with multi-agent systems, the static equilibrium concept is often used in market systems to approximate continuous market auctions. However, differences between the static equilibrium concept and continuous auctions have not been discussed in the context of an artificial market study. In this paper, we construct an artificial market model with both of them, namely, the Itayose and Zaraba method, and show simple characteristic differences between these methods based on computer simulations. The result indicates the further need to model the market system by studying artificial markets. Hidenori Kawamura, Ph.D.: He received Ph.D. degree from Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University, Japan in 2000. He is currently an instructor in Graduate School of Information Science and Technology, Hokkaido University, Japan. His research interests include multiagent systems, mass user support, artificial intelligence, complex systems, and tourism informatics. He is a member of IPSJ, JSAI, IEICE, ORSJ, JSTI and AAAI. Yasushi Okada, Ph.D.: He is a master course student in Graduate School of Engineering, Hokkaido University, Japan. He studies multiagent systems. Azuma Ohuchi, Ph.D.: He received his Ph.D. degree in 1974 from Hokkaido University. He is currently the professor in Graduate School of Information Science and Technology, Hokkaido University Japan. His research interstes include systems information engineering, artificial intelligence, complex systems, tourism informatics and medical systems. He is a member of the IPSJ, JSAI, IEEJ, ORSJ, Soc. Contr. Eng., Jap. OR Soc., Soc. Med. Informatics, Hosp. Manag., JSTI and IEEE-SMC. Koichi Kurumatani, Ph.D.: He received his Ph.D. Degree in 1989 from The University of Tokyo. He is currently a leader of Multiagent Research Team in Cyber Assist Research Center (CARC), National Institute of Advanced Industrial Science and Technology (AIST), Japan. His research interests include multiagent systems and mass user support. He is a member of JSAI, IPSJ, JSTI and AAAI.