The influence of investor's behavioral biases on the usefulness of the Dual Moving Average Crossovers

The so called Dual Moving Average Crossovers are said to be useful signals for forecasting trends of stock prices, as one of the technical analysis methods. First, we examined the usefulness of these crossovers by using historical daily closing price data and tick by tick price data of Japanese stocks. The results revealed that these crossovers were useful as confirmatory signals for forecasting market trends. Second, we tried to identify the underlying reasons for the usefulness of the crossovers. A model, which followed the Efficient Market Hypothesis, was found to fail to generate the price fluctuation where the crossovers were useful. We then developed a model that incorporated investor's suspicion about current price validity and two famous behavioral biases: conservativeness and representativeness. We identified the mechanism that those crossovers were closely related to investor's suspicion and the behavioral biases. Kotaro Miwa: He is a Ph.D. candidate at the University of Tokyo. He is also a quantitative financial analyst and fund manager at Tokio Marine Asset Managements. He received his B.A. degree from the Faculty of Engineering at the University of Tokyo in 2001. He also received M.A. degree from the Department of Systems Science at the University of Tokyo in 2003. His current research interests include behavioral finance and financial engineering. Kazuhiro Ueda, Ph.D.: He is an associate professor at the University of Tokyo. He received his B.A. degree from the Faculty of Liberal Arts and Science at the University of Tokyo in 1988. He also received M.A. and Ph.D. degrees in cognitive science from the Department of Systems Science at the University of Tokyo in 1990 and 1993. His current research interests include cognitive analysis on scientific problem solving, adaptive human-machine interface, artificial market and behavioral finance and cognitive robotics.     

A metamodel for modeling system features and their refinement, constraint and interaction relationships

This paper presents a metamodel for modeling system features and relationships between features. The underlying idea of this metamodel is to employ features as first-class entities in the problem space of software and to improve the customization of software by explicitly specifying both static and dynamic dependencies between system features. In this metamodel, features are organized as hierarchy structures by the refinement relationships, static dependencies between features are specified by the constraint relationships, and dynamic dependencies between features are captured by the interaction relationships. A first-order logic based method is proposed to formalize constraints and to verify constraints and customization. This paper also presents a framework for interaction classification, and an informal mapping between interactions and constraints through constraint semantics. Hong Mei received the BSc and MSc degrees in computer science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1984 and 1987, respectively, and the PhD degree in computer science from the Shanghai Jiao Tong University in 1992. He is currently a professor of Computer Science at the Peking University, China. His current research interests include Software Engineering and Software Engineering Environment, Software Reuse and Software Component Technology, Distributed Object Technology, and Programming Language. He has published more than 100 technical papers. Wei Zhang received the BSc in Engineering Thermophysics and the MSc in Computer Science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1999 and 2002, respectively. He is currently a PhD student at the School of Electronics Engineering and Computer Science of the Peking University, China. His research interests include feature-oriented requirements modeling, feature-driven software architecture design and feature-oriented software reuse. Haiyan Zhao received both the BSc and the MSc degree in Computer Science from the Peking Univeristy, China, and the Ph.D degree in Information Engineering from the University of Tokyo, Japan. She is currently an associate professor of Computer Science at the Peking University, China. Her research interests include Software Reuse, Domain Engineering, Domain Specific Languange and Program Transformation.     

Circular attribute grammars with remote attribute references and their evaluators

Attribute grammars (AGs) are a suitable formalism for the development of language processing systems. However, for languages including unrestricted labeled jumps, such as “goto” in C, the optimizers in compilers are difficult to write in AGs. This is due to two problems that few previous researchers could deal with simultaneously, i.e., references of attribute values on distant nodes and circularity in attribute dependency. This paper proposescircular remote attribute grammars (CRAGs), an extension of AGs that allows (1) direct relations between two distant attribute instances through pointers referring to other nodes in the derivation tree, and (2) circular dependencies, under certain conditions including those that arise from remote references. This extension gives AG programmers a natural means of describing language processors and programming environments for languages that include any type of jump structure. We also show a method of constructing an efficient evaluator for CRAGs called amostly static evaluator. The performance of the proposed evaluator has been measured and compared with dynamic and static evaluators. Akira Sasaki: He is a research fellow of the Advanced Clinical Research Center in the Institute of Medical Science at the University of Tokyo. He received his BSc and MSc from Tokyo Institute of Technology, Japan, in 1994 and 1996, respectively. His research interests include programming languages, programming language processors and programming environments, especially compiler compilers, attribute grammars and systematic debugging. He is a member of the Japan Society for Software Science and Technology. Masataka Sassa, D.Sc.: He is Professor of Computer Science at Tokyo Institute of Technology. He received his BSc, MSc and DSc from the University of Tokyo, Japan, in 1970, 1972 and 1978, respectively. His research interests include programming languages, programming language processors and programming environments, currently he is focusing on compiler optimization, compiler infrastructure, attribute grammars and systematic debugging. He is a member of the ACM, IEEE Computer Society, Japan Society for Software Science and Technology, and Information Processing Society of Japan.     

A portable approach to dynamic optimization in run-time specialization

This paper proposes arun-time bytecode specialization (BCS) technique that analyzes programs and generates specialized programs at run-time in an intermediate language. By using an intermediate language for code generation, a back-end system canoptimize the specialized programs after specialization. The system uses Java virtual machine language (JVML) as the intermediate language, which allows the system to easily achieve practicalportability and to use existing sophisticated just-in-time (JIT) compilers as its back-end. The binding-time analysis algorithm is based on a type system, and covers a non-object-oriented subset of JVML. The specializer generates programs on a per-instruction basis, and can performmethod inlining at run-time. Our performance measurements show that a non-trivial application program specialized at run-time by BCS runs approximately 3–4 times faster than the unspecialized one. Despite the large overhead of JIT compilation of specialized code, we observed that the overall performance of the application can be improved. This paper is an extended version of “A Portable Approach to Generating Optimized Specialized Code”, inProceedings of Second Symposium on Programs as Data Objects (PADO-II), Lecture Notes in Computer Science, vol. 2053, pp. 138–154, Aarhus, Denmark, May 2001.²³) Hidehiko Masuhara, D.Sc.: He is an Assistant Professor at Department of Graphics and Computer Science, Graduate School of Arts and Sciences, University of Tokyo. He received his B.S., M.S. and D.Sc. degrees from Department of Information Science, University of Tokyo in 1992, 1994, and 1999, respectively. His research interests are in programming languages, especially in mechanisms to support flexible and efficient computation such as dynamic optimization and reflection. He received the best-paper award from Information Processing Society of Japan in 1996. Akinori Yonezawa, Ph.D.: He is a Professor of computer science at Department of Computer Science, University of Tokyo. He received Ph.D. in Computer Science from the Massachusetts Institute of Technology in 1977. His current major research interests are in the areas of concurrent/parallel computation models, programming languages, object-oriented computing, and distributed computing. He is the designer of an object-oriented concurrent language ABCL/1 and the editor of several books and served as an associate editor of ACM Transaction of Programming Languages and Systems (TOPLAS). Since 1998, he has been an ACM Fellow.     

Dynamic vehicle routing using genetic algorithms

Many difficult combinatorial optimization problems have been modeled as static problems. However, in practice, many problems are dynamic and changing, while some decisions have to be made before all the design data are known. For example, in the Dynamic Vehicle Routing Problem (DVRP), new customer orders appear over time, and new routes must be reconfigured while executing the current solution. Montemanni et al. [1] considered a DVRP as an extension to the standard vehicle routing problem (VRP) by decomposing a DVRP as a sequence of static VRPs, and then solving them with an ant colony system (ACS) algorithm. This paper presents a genetic algorithm (GA) methodology for providing solutions for the DVRP model employed in [1]. The effectiveness of the proposed GA is evaluated using a set of benchmarks found in the literature. Compared with a tabu search approach implemented herein and the aforementioned ACS, the proposed GA methodology performs better in minimizing travel costs. Franklin T. Hanshar is currently a M.Sc. student in the Department of Computing and Information Science at the University of Guelph, Ontario, Canada. He received a B.Sc. degree in Computer Science from Brock University in 2005. His research interests include uncertain reasoning, optimization and evolutionary computation. Beatrice Ombuki-Berman is currently an Associate Professor in the Department of Computer Science at Brock University, Ontario, Canada. She obtained a PhD and ME in Information Engineering from University of The Ryukyus, Okinawa, Japan in 2001 and 1998, respectively. She received a B.Sc. in Mathematics and Computer Science from Jomo Kenyatta University, Nairobi, Kenya. Her primary research interest is evolutionary computation and applied optimization. Other research interests include neural networks, machine learning and ant colony optimization.     

Kernel Projection Algorithm for Large-Scale SVM Problems

Support Vector Machine (SVM) has become a very effective method in statistical machine learning and it has proved that training SVM is to solve Nearest Point pair Problem (NPP) between two disjoint closed convex sets.Later Keerthi pointed out that it is difficult to apply classical excellent geometric algorithms directly to SVM and so designed a new geometric algorithm for SVM.In this article,a new algorithm for geometrically solving SVM,Kernel Projection Algorithm,is presented based on the theorem on fixed-points of projection mapping.This new algorithm makes it easy to apply classical geometric algorithms to solving SVM and is more understandable than Keerthi‘s.Experiments show that the new algorithm can also handle large-scale SVM problems.Geometric algorithms for SVM,such as Keerthi‘s algorithm,require that two closed convex sets be disjoint and otherwise the algorithms are meaningless.In this article,this requirement will be guaranteed in theory be using the theoretic result on universal kernel functions.     

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.     

A new method of embedded fourth order with four stages to study raster CNN simulation

A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, single layer/raster CNN array is implemented by incorporating the proposed technique. Simulation results have been obtained, and comparison has also been carried out to show the efficiency of the proposed numerical integration algorithm. The analytic expressions for local truncation error and global truncation error are derived. It is seen that the RK-embedded root mean square outperforms the RK-embedded Heronian mean and RK-embedded harmonic mean.     

RHiNET-2/SW: a high-throughput, compact network-switch using 8.8-gbit/s optical interconnection

We have developed a high-throughput, compact network switch (the RHiNET-2/SW) for a distributed parallel computing system. Eight pairs of 800-Mbit/s×12-channel optical interconnection modules and a CMOS ASIC switch are integrated on a compact circuit board. To realize high-throughput (64 Gbit/s) and low-latency network, the SW-LSI has a customized high-speed LVDS I/O interface, and a high-speed internal SRAM memory in a 784-pin BGA one-chip package. We have also developed device implementation technologies to overcome the electrical problems (loss and crosstalk) caused by such high integration. The RHiNET-2/SW system enables high-performance parallel processing in a distributed computing environment. Shinji Nishimura: He is a researcher in the Department of Network System at the Central Research Laboratory, Hitachi Ltd., at Tokyo. He obtained his bachelors degree in Electronics Engineering from the University of Tokyo in 1989, and his M.E. from the University of Tokyo in 1991. He joined a member of the Optical Interconnection Hitachi Laboratory from 1992. His research interests are in hardware technology for the optical interconnection technologies in the computer and communication systems. Katsuyoshi Harasawa: He is a Senior Enginner of Hitachi Communication Systems Inc. He obtained his bachelors degree in Electrical Engineering from Tokyo Denki University. He is a chief of development of the devices and systems for the optical telecommunication. He was engaged in Development of Optical Reciever and Transmitter module. He joined RWCP project from 1997. His research interests are in hardward technology for optical interconnection in distributed parallel computing system (RHiNET). Nobuhiro Matsudaira: He is a engineer in the Hitachi Communication Systems, Inc. He obtained his bachelors degree in Mercantile Marine Engineering from the Kobe University of Mercantile Marine in 1986. He was engaged in Development of Optical Reciever and Transmitter module at 2.4 Gbit/s to 10Gbit/s. He joined RWCP project from 1998. His reserch interests are in hardware technology for the optical interconnection technology in the computer and communication systems. Shigeto Akutsu: He is a staff in Hitachi Communication Systems Inc. He obtained his bachelors degree in Electronics from Kanagawa University, Japan in 1998. His research interests are hardware technology for the optical interconnection technology in the computer and communication systems. Tomohiro Kudoh, Ph.D.: He received Ph.D. degree from Keio University, Japan in 1992. He has been chief of the parallel and distributed architecture laboratory, Real World Computing Partnership since 1997. His research interests include the area of parallel processing and network for high performance computing. Hiroaki Nishi: He received B.E., M.E. from Keio University, Japan, in 1994, 1996, respectively. He joined Parallel & Distributed Architecture Laboratory, Real World Computing Partnership in 1999. He is currently working on his Ph.D. His research interests include area of interconnection networks. Hideharu Amano, Ph.D.: He received Ph.D. degree from Keio University, Japan in 1986. He is now an Associate Professor in the Department of Information and Computer Science, Keio University. His research interests include the area of parallel processing and reconfigurable computing.     

Calculating accumulations

Theaccumulation strategy consists of generalizing a function over an algebraic data structure by inclusion of an extra parameter, anaccumulating parameter, for reusing and propagating intermediate results. However, there remain two major difficulties in this accumulation strategy. One is to determinewhere andwhen to generalize the original function. The other, surprisingly not yet receiving its worthy consideration, is how to manipulate accumulations. To overcome these difficulties, we propose to formulate accumulations ashigher order catamorphisms, and provide several general transformation rules for calculating accumulations (i.e., finding and manipulating accumulations) bycalculation-based (rather than a search-based) program transformation methods. Some examples are given for illustration. Zhenjiang Hu, Dr.Eng.: He is an Assistant Professor in Information Engineering at the University of Tokyo. He received his BS and MS in Computer Science from Shanghai Jiao Tong University in 1988 and 1990 respectively, and his Dr. Eng. degree in Information Engineering from the University of Tokyo in 1996. His current research concerns programming languages, functional programming, program transformation, and parallel processing. Hideya Iwasaki, Dr.Eng.: He is an Associate Professor in Information Engineering at the University of Tokyo. He received the M.E. degree in 1985, the Dr. Eng. degree in 1988 from the University of Tokyo. His research interests are list processing languages, functional languages, parallel processing, and constructive algorithmics. Masato Takeichi, Dr.Eng.: He is Professor in Mathematical Engineering and Information Engineering at the University of Tokyo since 1993. After graduation from the University of Tokyo, he joined the faculty at the University of Electro-Communications in Tokyo before he went back to work at the University of Tokyo in 1987. His research concerns the design and implementation of functional programming languages, and calculational program transformation systems.     

GigaE PM: a high performance communication facility using a Gigabit Ethernet

A high performance communication facility, called theGigaE PM, has been designed and implemented for parallel applications on clusters of computers using a Gigabit Ethernet. The GigaE PM provides not only a reliable high bandwidth and low latency communication, but also supports existing network protocols such as TCP/IP. A reliable communication mechanism for a parallel application is implemented on the firmware on a NIC while existing network protocols are handled by an operating system kernel. A prototype system has been implemented using an Essential Communications Gigabit Ethernet card. The performance results show that a 58.3 μs round trip time for a four byte user message, and 56.7 MBytes/sec bandwidth for a 1,468 byte message have been achieved on Intel Pentium II 400 MHz PCs. We have implemented MPICH-PM on top of the GigaE PM, and evaluated the NAS parallel benchmark performance. The results show that the IS class S performance on the GigaE PM is 1.8 times faster than that on TCP/IP. Shinji Sumimoto: He is a Senior Researcher of Parallel and Distributed System Software Laboratory at Real World Computing Partnership, JAPAN. He received BS degree in electrical engineering from Doshisha University. His research interest include parallel and distributed systems, real-time systems, and high performance communication facilities. He is a member of Information Processing Society of Japan. Hiroshi Tezuka: He is a Senior Researcher of Parallel and Distributed System Software Laboratory at Real World Computing Partnership, JAPAN. His research interests include real-time systems and operating system kernel. He is a member of the Information Processing Society of Japan, and Japan Society for Software Science and Technology. Atsushi Hori, Ph.D.: He is a Senior Researcher of Parallel and Distributed System Software Laboratory at Real World Computing Partnership, JAPAN. His current research interests include parallel operating system. He received B.S. and M.S. degrees in Electrical Engineering from Waseda University, and received Ph.D. from the University of Tokyo. He worked as a researcher in Mitsubishi Research Institute from 1981 to 1992. Hiroshi Harada: He is a Senior Researcher of Parallel and Distributed System Software Laboratory at Real World Computing Partnership, JAPAN. His research interests include distributed/parallel systems and distributed shared memory. He received BS degree in physics from Science University of Tokyo. He is a member of ACM and Information Processing Society of Japan. Toshiyuki Takahashi: He is a Researcher at Real World Computing Partnership since 1998. He received his B.S. and M.S. from the Department of Information Sciences of Science University of Tokyo in 1993 and 1995. He was a student of the Information Science Department of the University of Tokyo from 1995 to 1998. His current interests are in meta-level architecture for programming languages and high-performance software technologies. He is a member of Information Processing Society of Japan. Yutaka Ishikawa, Ph.D.: He is the chief of Parallel and Distributed System Software Laboratory at Real World Computing Partnership, JAPAN. He is currently temporary retirement from Electrotechnical Laboratory, MITI. His research interests include distributed/parallel systems, object-oriented programming languages, and real-time systems. He received the B.S., M.S. and Ph.D degrees in electrical engineering from Keio University. He is a member of the IEEE Computer Society, ACM, Information Processing Society of Japan, and Japan Society for Software Science and Technology.     

The superstructure toward open bioinformatics grid

The grid design strongly depends on not only a network infrastructure but also a superstructure, that is, a social structure of virtual organizations where people trust each other, share resources and work together. Open Bioinformatics Grid (OBIGrid) is a grid aimed at building a cooperative bioinformatics environment for computer sicentists and biologists. In October 2003, OBIGrid consisted of 293 nodes with 492 CPUs provided by 27 sites at universities, laboratories and other enterprises, connected by a virtual private network over the Internet. So many organizations have participated because OBIGrid has been conscious of constructing a superstructure on a grid as well as a grid infrastructure. For the benefit of OBIGrid participants, we have developed a series of life science application services: an open bioinformatics environment (OBIEnv), a scalable genome database (OBISgd), a genome annotation system (OBITco), a biochemical network simulator (OBIYagns), and to name a few. Akihiko Konagaya, Dr.Eng.: He is Project Director of Bioinformatics Group, RIKEN Genomic Sciences Center. He received his B.S. and M.S. from Tokyo Institute of Technology in 1978 and 1980 in Informatics Science, and joined NEC Corporation in 1980, Japan Advanced Institute of Science and Technology in 1997, RIKEN GSC in 2003. His research covers wide area from computer architectures to bioinformatics. He has been much involved into the Open Bioinformatics Grid project since 2002. Fumikazu Konishi, Dr.Eng.: He is researcher at Bioinformatics Group, RIKEN Genomic Sciences Center since 2000. He received his M.S. (1996) and Ph.D. (2001) from Tokyo Metropolitan Institute of Technology. He served as an assistant in Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology since 2000. He also works in Structurome Research Group, RIKEN Harima Institute from 2001. His research interests include concurrent engineering, bioinformatics and the Grid. He has deeply affected to the design of OBIGrid. Mariko Hatakeyama, Ph.D.: She recieved her Ph.D. degree from Tokyo University of Agriculture and Technology. She is Research Scientist at Bioinformactis Group, RIKEN Genomic Sciences Center. Her research topics are: microbiology, enzymology and signal transduction of mammalian cells. She is now working on computational simulation of signal transduction systems and on thermophilic bacteria project. Kenji Satou, Ph.D.: He is Associate Professor of School of Knowledge Science at Japan Advanced Institute of Science and Technology. He received B.S., M.E. and Ph.D. degrees from Kyushu University, in 1987, 1989 and 1995 respectively. For each degree, he majored in computer engineering. His research interests have progressed from deductive database application through data mining to Grid computing and natural language processing. His current field of research is bioinformatics. He prefers set-oriented manner of thinking, and usually wonders how he can construct an intelligent-looking system based on large amount of heterogeneous data and computer resources.     

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.     

An algorithm for similar utterance section extraction for managing spoken documents

This paper proposes a new, efficient algorithm for extracting similar sections between two time sequence data sets. The algorithm, called Relay Continuous Dynamic Programming (Relay CDP), realizes fast matching between arbitrary sections in the reference pattern and the input pattern and enables the extraction of similar sections in a frame synchronous manner. In addition, Relay CDP is extended to two types of applications that handle spoken documents. The first application is the extraction of repeated utterances in a presentation or a news speech because repeated utterances are assumed to be important parts of the speech. These repeated utterances can be regarded as labels for information retrieval. The second application is flexible spoken document retrieval. A phonetic model is introduced to cope with the speech of different speakers. The new algorithm allows a user to query by natural utterance and searches spoken documents for any partial matches to the query utterance. We present herein a detailed explanation of Relay CDP and the experimental results for the extraction of similar sections and report results for two applications using Relay CDP. Yoshiaki Itoh has been an associate professor in the Faculty of Software and Information Science at Iwate Prefectural University, Iwate, Japan, since 2001. He received the B.E. degree, M.E. degree, and Dr. Eng. from Tokyo University, Tokyo, in 1987, 1989, and 1999, respectively. From 1989 to 2001 he was a researcher and a staff member of Kawasaki Steel Corporation, Tokyo and Okayama. From 1992 to 1994 he transferred as a researcher to Real World Computing Partnership, Tsukuba, Japan. Dr. Itoh's research interests include spoken document processing without recognition, audio and video retrieval, and real-time human communication systems. He is a member of ISCA, Acoustical Society of Japan, Institute of Electronics, Information and Communication Engineers, Information Processing Society of Japan, and Japan Society of Artificial Intelligence. Kazuyo Tanaka has been a professor at the University of Tsukuba, Tsukuba, Japan, since 2002. He received the B.E. degree from Yokohama National University, Yokohama, Japan, in 1970, and the Dr. Eng. degree from Tohoku University, Sendai, Japan, in 1984. From 1971 to 2002 he was research officer of Electrotechnical Laboratory (ETL), Tsukuba, Japan, and the National Institute of Advanced Science and Technology (AIST), Tsukuba, Japan, where he was working on speech analysis, synthesis, recognition, and understanding, and also served as chief of the speech processing section. His current interests include digital signal processing, spoken document processing, and human information processing. He is a member of IEEE, ISCA, Acoustical Society of Japan, Institute of Electronics, Information and Communication Engineers, and Japan Society of Artificial Intelligence. Shi-Wook Lee received the B.E. degree and M.E. degree from Yeungnam University, Korea and Ph.D. degree from the University of Tokyo in 1995, 1997, and 2001, respectively. Since 2001 he has been working in the Research Group of Speech and Auditory Signal Processing, the National Institute of Advanced Science and Technology (AIST), Tsukuba, Japan, as a postdoctoral fellow. His research interests include spoken document processing, speech recognition, and understanding.     

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.     

Trends of internet auctions and agent-mediated Web commerce

Electronic Commerce (EC) is a promising field for applying agent and Artificial Intelligence technologies. In this article, we give an overview of the trends of Internet auctions and agent-mediated Web commerce. We describe the theoretical backgrounds of auction protocols and introduce several Internet auction sites. Furthermore, we describe various activities aimed toward utilizing agent technologies in EC and the trends in standardization efforts on agent technologies. Makoto Yokoo, Ph.D.: He received the B.E. and M.E. degrees in electrical engineering, in 1984 and 1986, respectively, from the University of Tokyo, Japan, and the Ph.D. degree in information and communication engineering in 1995 from the University of Tokyo, Japan. He is currently a distinguished technical member in NTT Communication Science Laboratories, Kyoto, Japan. He was a visiting research scientist at the Department of Electrical Engineering and Computer Science, the University of Michigan, Ann Arbor, from 1990 to 1991. His current research interests include multi-agent systems, search, and constraint satisfaction. Satoru Fujita, D.Eng.: He received his B.E. and M.E. degrees in electronic engineering from the University of Tokyo in 1984 and 1986, respectively. He also received his D.Eng. from the University of Tokyo in 1989 for his research on context comprehension in natural language understanding. He joined NEC Corporation in 1989, and is now a principal researcher of Internet Systems Research Laboratories of NEC. He is engaged in research on mobile agents, distributed systems and Web services.     

A Power-Aware Branch Predictor by Accessing the BTB Selectively

Microarchitects should consider power consumption, together with accuracy, when designing a branch predictor, especially in embedded processors. This paper proposes a power-aware branch predictor, which is based on the gshare predictor, by accessing the BTB （Branch Target Buffer） selectively. To enable the selective access to the BTB, the PHT （Pattern History Table） in the proposed branch predictor is accessed one cycle earlier than the traditional PHT if the program is executed sequentially without branch instructions. As a side effect, two predictions from the PHT are obtained through one access to the PHT, resulting in more power savings. In the proposed branch predictor, if the previous instruction was not a branch and the prediction from the PHT is untaken, the BTB is not accessed to reduce power consumption. If the previous instruction was a branch, the BTB is always accessed, regardless of the prediction from the PHT, to prevent the additional delay/accuracy decrease. The proposed branch predictor reduces the power consumption with little hardware overhead, not incurring additional delay and never harming prediction accuracy. The simulation results show that the proposed branch predictor reduces the power consumption by 29-47%.     

An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems

In this paper we propose a new fast learning algorithm for the support vector machine (SVM). The proposed method is based on the technique of second-order cone programming. We reformulate the SVM's quadratic programming problem into the second-order cone programming problem. The proposed method needs to decompose the kernel matrix of SVM's optimization problem, and the decomposed matrix is used in the new optimization problem. Since the kernel matrix is positive semidefinite, the dimension of the decomposed matrix can be reduced by decomposition (factorization) methods. The performance of the proposed method depends on the dimension of the decomposed matrix. Experimental results show that the proposed method is much faster than the quadratic programming solver LOQO if the dimension of the decomposed matrix is small enough compared to that of the kernel matrix. The proposed method is also faster than the method proposed in (S. Fine and K. Scheinberg, 2001) for both low-rank and full-rank kernel matrices. The working set selection is an important issue in the SVM decomposition (chunking) method. We also modify Hsu and Lin's working set selection approach to deal with large working set. The proposed approach leads to faster convergence. Rameswar Debnath is a Ph.D candidate at the University of Electro-Communications, Tokyo, Japan and also a lecturer of the Computer Science & Engineering Discipline at Khulna University, Bangladesh. He received the bachelor's degree in computer science and engineering from Khulna University in 1997 and masters of engineering degree in communication and systems from the University of Electro-Communications in 2002. His research interests include support vector machines, artificial neural networks, pattern recognition, and image processing. Masakazu Muramatsu is an associate professor of the Department of Computer Science at the University of Electro-Communications, Japan. He received a bachelor's degree from the University of Tokyo in 1989, master's degree in engineering from University of Tokyo in 1991, and Ph.D from the Graduate University for Advanced Studies in 1994. He was an assistant professor of the Department of Mechanical Engineering at Sophia University from 1994 to 2000, when he moved to the current university. His research interests include mathematical programming, second-order cone programming and its application to machine learning. Haruhisa Takahashi was born in Shizuoka Prefecture Japan, on March 31, 1952. He graduated from the University of Electro-Communications. He received the Dr Eng. degree from Osaka University. He was a faculty member of the Department of Computer Science and Engineering at Toyohashi University of Technology from 1980 to 1986. Since 1986, he has been with the University of Electro-Communications where he is currently professor of the Department of Information and Communication Engineering. He was previously engaged in the fields of nonlinear network theory, queueing theory and performance evaluation of communication systems. His current research includes learning machines, artificial neural networks, and cognitive science.     

An information management system with the facility to support long-term creative thinking

Most previous creativity support systems sustain short-term temporal thinking that is separate from users’ daily activities. In this paper, we propose a system to support long-term idea-generation in daily life. The system consists of two subsystems: a management system for problems and ideas calledIdeaManager, and a personal information storage system callediBox. When information is registered in iBox, it searches related problems and ideas in IdeaManager and presents the results. Users then try to generate or enhance ideas for automatically retrieved problems or ideas using registered information as the hint. To evaluate and enhance our system, we carried out a six-week experiment. Based on the results, we give some proposals for future systems. Hirohito Shibata: He received his B.Sci. degree from Kanazawa University in 1992 and his M.Sci. degree from Osaka University in 1994. He was a software engineer at Fuji Xerox Co., Ld from 1994 to 2000. He is currently a doctoral student with Department of Advanced Interdisciplinary Studies, University of Tokyo. His research interests include human-computer interaction and computer support for creative activities. He is a member of Japanese Society for Artificial Intelligence (JSAI) and Japanese Cognitive Science Society (JCSS). Koichi Hori, D.Eng.: He received his B.Eng, M.Eng, and Dr.Eng. degrees in electronic engineering from the University of Tokyo in 1979, 1981, and 1984, respectively. In 1984, he joined National Institute of Japanese Literature, where he developed AI systems for literature studies. Since 1988, he has been with the University of Tokyo. He is currently a professor with Department of Advanced Interdisciplinary Studies, the University of Tokyo. From September 1989 to January 1990, he also held a visiting position at University of Compiegne, France. His current research interests include AI technology for supporting human creative activities, cognitive engineering and Intelligent CAD systems. He is a member of IEEE, ACM, IEICE, IPS J, JSAI, JSSST, and JCSS.