Toward a real-world knowledge medium: Building a guidance system for exhibition tours

We propose a notion of a real-world knowledge medium by presenting our ongoing project to build a guidance system for exhibition tours. In order to realize a knowledge medium usable in the real world, we focus on the context-awareness of users and their environments. Our system is a personal mobile assistant that provides visitors touring exhibitions with information based on their spatial/temporal locations and individual interests. We also describe an application of knowledge sharing used in the actual exhibition spaces. Yasuyuki Sumi, Ph.D.: He has been a researcher at ATR Media Integration & Communications Research Laboratories since 1995. His research interests include knowledge-based systems, creativity supporting systems, and their applications for facilitating human collaboration. He received his B. Eng. degree from Waseda University in 1990, and M. Eng. and D. Eng. degrees in information engineering from the University of Tokyo in 1992 and 1995, respectively. He is a member of Institutes of Electronics, Information and Communication Engineers (IEICE) of Japan, the Information Processing Society of Japan (IPSJ), the Japanese Society for Artificial Intelligence (JSAI), and American Association for Artificial Intelligence (AAAI). Kenji Mase, Ph.D.: He received the B.S. degree in Electrical Engineering and the M.S. and Ph.D. degrees in Information Engineering from Nagoya University in 1979, 1981 and 1992 respectively. He has been with ATR (Advanced Telecommunications Research Institute) Media Integration & Communications Research Laboratories since 1995 and is currently the head of Department 2. He joined the Nippon Telegraph and Telephone Corporation (NTT) in 1981 and had been with the NTT Human Interface Laboratories. He was a visiting researcher at the Media Laboratory, MIT in 1988–1989. His research interests include image sequence processing of human actions, computer graphics, computer vision, artificial intelligence and their applications for computer-aided communications and human-machine interfaces. He is a member of the Information Processing Society of Japan (IPSJ), Institutes of Electronics, Information and Communication Engineers (IEICE) of Japan and IEEE Computer Society.     

Event-based operational semantics and a consistency result for real-time concurrent processes with action refinement

In this paper an event-based operational interleaving semantics is proposed for real-time processes,for which action refinement and a denotational true concurrency semantics are developed and defined in terms of timed event structures. The authors characterize the timed event traces that are generated by the operational semantics in a denotational way, and show that this operational semantics is consistent with the denotational semantics in the sense that they generate the same set of timed event traces, thereby eliminating the gap between the true concurrency and interleaving semantics.     

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.     

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.     

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.     

Efficient algorithms for optimistic crash recovery

Summary Recovery from transient processor failures can be achieved by using optimistic message logging and checkpointing. The faulty processorsroll back, and some/all of the non-faulty processors also may have to roll back. This paper formulates the rollback problem as a closure problem. A centralized closure algorithm is presented together with two efficient distributed implementations. Several related problems are also considered and distributed algorithms are presented for solving them. S. Venkatesan received the B. Tech. and M. Tech degrees from the Indian Institute of Technology, Madras in 1981 and 1983, respectively and the M.S. and Ph.D. degrees in Computer Science from the University of Pittsburgh in 1985 and 1988. He joined the University of Texas at Dallas in January 1989, where he is currently an Assistant Professor of Computer Science. His research interests are in fault-tolerant distributed systems, distributed algorithms, testing and debugging distributed programs, fault-tolerant telecommunication networks, and mobile computing. Tony Tony-Ying Juang is an Associate Professor of Computer Science at the Chung-Hwa Polytechnic Institute. He received the B.S. degree in Naval Architecture from the National Taiwan University in 1983 and his M.S. and Ph.D. degrees in Computer Science from the University of Texas at Dallas in 1989 and 1992, respectively. His research interests include distributed algorithms, fault-tolerant distributed computing, distributed operating systems and computer communications.This research was supported in part by NSF under Grant No. CCR-9110177 and by the Texas Advanced Technology Program under Grant No. 9741-036     

Fast multicast on multistage interconnection networks using multi-head worms

1IntroductionMulticastcommunication,whichreferstothedeliveryofamessagefromasinglesourcenodetoanumberofdestinationnodes,isfrequentlyusedindistributed-memoryparallelcomputersystemsandnetworks[1].Efficientimplementationofmulticastcommunicationiscriticaltotheperformanceofmessage-basedscalableparallelcomputersandswitch-basedhighspeednetworks.Switch-basednetworksorindirectnetworks,basedonsomevariationsofmultistageiDterconnectionnetworks(MINs),haveemergedasapromisingnetworkajrchitectureforconstruct…     

An Optimum Placement Search Algorithm Based on Extended Corner Block List

A non-slicing approach,Corner Block List(CBL),has been presented recently.Since CBL only can represent floorplans without empty rooms,the algorithm based on CBL cannot get the optimum placement.In this paper,an extended corner block list,ECBLλ,is proposed.It can represent non-slicing floorplan including empty rooms.Based on the optimum solution theorem of BSG(bounded-sliceline grid),it is proved that the solution space of ECBLn,where n is the number of blocks,contains the optimum block placement with the minimum area.A placement algorithm based on ECBLλ,whose solution space can be controlled by setting λ,the extending ratio,is completed.Whenλ is set as n,the algorithm based on ECBLn is the optimum placement search algorithm.Experiments show that λ has a reasonable constant range for building block layout problem,so the algorithm can translate an ECBLλ representation to its corresponding placement in O(n) time,Experimental results on MCNC benchmarks show promising performance with 7% improvement in wire length and 2% decrease in dead space over algorthms based on CBL.Meanwhile,compared with other algorithms,the proposed algorithm can get better results with less runtime.     

A Transactional Asynchronous Replication Scheme for Mobile Database Systems

In mobile database systems,mobility of users has a significant impact on data replication.As a result,the various replica control protocols that exist today in traditional distributed and multidatabase environments are no longer suitable To solve this problem,a new mobile database replication scheme,the Transaction-Level Result-Set Propagation(TLRSP)model,is put forward in this paper,The conflict dectction and resolution strategy based on TLRSP is discussed in detail,and the implementation algorithm is proposed,In order to compare the performance of the TLRSP model with that of other mobile replication schemes,we have developed a detailde simulation model.Experimantal results show that the TLRSP model provides an effcient support for replicated mobile database systems by reducing reprocessing overhead and maintaining database consistency.     

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

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

A New Challenge for Applying Time Series Metrics Data to Software Quality Estimation

In typical software development, a software reliability growth model (SRGM) is applied in each testing activity to determine the time to finish the testing. However, there are some cases in which the SRGM does not work correctly. That is, the SRGM sometimes mistakes quality for poor quality products. In order to tackle this problem, we focussed on the trend of time series data of software defects among successive testing phases and tried to estimate software quality using the trend. First, we investigate the characteristics of the time series data on the detected faults by observing the change of the number of detected faults. Using the rank correlation coefficient, the data are classified into four kinds of trends. Next, with the intention of estimating software quality, we investigate the relationship between the trends of the time series data and software quality. Here, software quality is defined by the number of faults detected during six months after shipment. Finally, we find a relationship between the trends and metrics data collected in the software design phase. Using logistic regression, we statistically show that two review metrics in the design and coding phase can determine the trend. Sousuke Amasakireceived the B.E. degree in Information and Computer Sciences from Okayama Prefectural University, Japan, in 2000 and the M.E. degree in Information and Computer Sciences from Graduate School of Information Science and Technology, Osaka University, Japan, in 2003. He has been in Ph.D. course of Graduate School of Information Science and Technology at Osaka University. His interests include the software process and the software quality assurance technique. He is a student member of IEEE and ACM. Takashi Yoshitomireceived the B.E. degree in Information and Computer Sciences from Osaka University, Japan, in 2002. He has been working for Hitachi Software Engineering Co., Ltd. Osamu Mizunoreceived the B.E., M.E., and Ph.D. degrees in Information and Computer Sciences from Osaka University, Japan, in 1996, 1998, and 2001, respectively. He is an Assistant Professor of the Graduate School of Information Science and Technology at Osaka University. His research interests include the improvement technique of the software process and the software risk management technique. He is a member of IEEE. Yasunari Takagireceived the B.E. degree in Information and Computer Science, from Nagoya Institute of Technology, Japan, in 1985. He has been working for OMRON Corporation. He has been also in Ph.D. course of Graduate School of Information Science and Technology at Osaka University since 2002. Tohru Kikunoreceived the B.E., M.Sc., and Ph.D. degrees in Electrical Engineering from Osaka University, Japan, in 1970, 1972, and 1975, respectively. He joined Hiroshima University from 1975 to 1987. Since 1990, he has been a Professor of the Department of Information and Computer Sciences at Osaka University. His research interests include the analysis and design of fault-tolerant systems, the quantitative evaluation of software development processes, and the design of procedures for testing communication protocols. He is a member of IEEE and ACM.     

A Novel Computer Architecture to Prevent Destruction by Viruses

In today‘s Internet computing world,illegal activities by crackers pose a serious threat to computer security.It is well known that computer viruses,Trojan horses and other intrusive programs may cause sever and often catastrophic consequences. This paper proposes a novel secure computer architecture based on security-code.Every instruction/data word is added with a security-code denoting its security level.External programs and data are automatically addoed with security-code by hadware when entering a computer system.Instruction with lower security-code cannot run or process instruction/data with higher security level.Security-code cannot be modified by normal instruction.With minor hardware overhead,then new architecture can effectively protect the main computer system from destruction or theft by intrusive programs such as computer viruses.For most PC systems it includes an increase of word-length by 1 bit on register,the memory and the hard disk.     

Program transformation system based on generalized partial computation

Generalized Partial Computation (GPC) is a program transformation method utilizing partial information about input data, abstract data types of auxiliary functions and the logical structure of a source program. GPC uses both an inference engine such as a theorem prover and a classical partial evaluator to optimize programs. Therefore, GPC is more powerful than classical partial evaluators but harder to implement and control. We have implemented an experimental GPC system called WSDFU (Waseda Simplify-Distribute-Fold-Unfold). This paper demonstrates the power of the program transformation system as well as its theorem prover and discusses some future works. Yoshihiko Futamura, Ph.D.: He is Professor of Department of Information and Computer Science and the director of the Institute for Software Production Technology (ISPT) of Waseda University. He received his BS in mathematics from Hokkaido University in 1965, MS in applied mathematics from Harvard University in 1972 and Ph.D. degree from Hokkaido University in 1985. He joined Hitachi Central Research Laboratory in 1965 and moved to Waseda University in 1991. He was a visiting professor of Uppsala University from 1985 to 1986 and a visiting scholar of Harvard University from 1988 to 1989. Automatic generation of computer programs and programming methodology are his main research fields. He is the inventor of the Futamura Projections in partial evaluation and ISO8631 PAD (Problem Analysis Diagram). Zenjiro Konishi: He is a visiting lecturer of Institute for Software Production Technology, Waseda University. He received his M. Sc. degree in mathematics from Waseda University in 1995. His research interests include automated theorem proving. He received JSSST Takahashi Award in 2001. He is a member of JSSST and IPSJ. Robert Glück, Ph.D., Habil.: He is an Associate Professor of Computer Science at the University of Copenhagen. He received his Ph.D. and Habilitation (venia docendi) from the Vienna University of Technology in 1991 and 1997. He was research assistant at the City University of New York and received twice the Erwin-Schrodinger-Fellowship of the Austrian Science Foundation (FWF). After being an Invited Fellow of the Japan Society for the Promotion of Science (JSPS), he is now funded by the PRESTO21 program for basic research of the Japan Science and Technology Corporation (JST) and located at Waseda University in Tokyo. His main research interests are advanced programming languages, theory and practice of program transformation, and metaprogramming.     

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

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

SATCHMOREBID: SATCHMO(RE) with BIDirectional relevancy

SATCHMORE was introduced as a mechanism to integrate relevancy testing with the model-generation theorem prover SATCHMO. This made it possible to avoid invoking some clauses that appear in no refutation, which was a major drawback of the SATCHMO approach. SATCHMORE relevancy, however, is driven by the entire set of negative clauses and no distinction is accorded to the query negation. Under unfavorable circumstances, such as in the presence of large amounts of negative data, this can reduce the efficiency of SATCHMORE. In this paper we introduce a further refinement of SATCHMO called SATCHMOREBID: SATCHMORE with BIDirectional relevancy. SATCHMOREBID uses only the negation of the query for relevancy determination at the start. Other negative clauses are introduced on demand and only if a refutation is not possible using the current set of negative clauses. The search for the relevant negative clauses is performed in a forward chaining mode as opposed to relevancy propagation in SATCHMORE which is based on backward chaining. SATCHMOREBID is shown to be refutationally sound and complete. Experiments on a prototype SATCHMOREBID implementation point to its potential to enhance the efficiency of the query answering process in disjunctive databases. Donald Loveland, Ph.D.: He is Emeritus Professor of Computer Science at Duke University. He received his Ph.D. in mathematics from New York University and taught at NYU and CMU prior to joining Duke in 1973. His research in automated deduction includes defining the model elimination proof procedure and the notion of linear resolution. He is author of one book and editor/co-editor of two other books on automated theorem proving. He has done research in the areas of algorithms, complexity, expert systems and logic programming. He is an AAAI Fellow, ACM Fellow and winner of the Herbrand Award in Automated Reasoning. Adnan H. Yahya, Ph.D.: He is an associate professor at the Department of Electrical Engineering, Birzeit University, Palestine. He received his Diploma and PhD degrees from St. Petersburg Electrotechnical University and Nothwestern University in 1979 and 1984 respectively. His research interests are in Artificial Intelligence in general and in the areas of Deductive Databases, Logic Programming and Nonmonotonic Reasoning in particular. He had several visiting appointments at universities and research labs in the US, Germany, France and the UK. Adnan Yahya is a member of the ACM, IEEE and IEEE Computer Society.     

Some impossibility results in interprocess synchronization

Summary In this paper we construct a formal specification of the problem of synchronizing asynchronous processes under strong fairness. We prove that strong interaction fairness is impossible for binary (and hence for multiway) interactions and strong process fairness is impossible for multiway interactions. Yih-Kuen Tsay received his B.S. degree form National Taiwan University in 1984 and his M.S. degree from UCLA in 1989. He is currently a Ph.D. candidate in the UCLA Computer Science Department. His research interests include distributed algorithms, fault-tolerant systems, and specification and verification of concurrent programs. Rajive L. Bagrodia received the B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay in 1981 and the M.A. and Ph.D. degrees in Computer Science from the University of Texas at Austin in 1983 and 1987 respectively. He is currently an Assistant Professor in the Computer Science Department at UCLA. His research interests include parallel languages, distributed algorithms, parallel simulation and software design methodologies. He was selected as a 1991 Presidential Young Investigator by NSF.This research was partially supported by NSF PYI Award number ASC9157610 and by ONR under grant N00014-91-J1605     

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.     

BCL—3：Aigh Performance Basic Communication Protocol for Commodity Superserver DAWNING—3000

This paper introduces the design and implemetation of BCL-3,a high performance low-level communication software running on a cluster of SMPs(CLUMPS) called DAWNING-3000,BCL-3 provides flexible and sufficient functionality to fulfill the communication requirements of fundamental system software developed for DAWNING-3000 while guaranteeing security,scalability,and reliability,Important features of BCL-3 are presented in the paper,including special support for SMP and heterogeneous network environment,semiuser-level communication,reliable and ordered data transfer and scalable flow control,The performance evaluation of BCL-3 over Myrinet is also given.     

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

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

Learning Horn definitions: Theory and an application to planning

A Horn definition is a set of Horn clauses with the same predicate in all head literals. In this paper, we consider learning non-recursive, first-order Horn definitions from entailment. We show that this class is exactly learnable from equivalence and membership queries. It follows then that this class is PAC learnable using examples and membership queries. Finally, we apply our results to learning control knowledge for efficient planning in the form of goal-decomposition rules. Chandra Reddy, Ph.D.: He is currently a doctoral student in the Department of Computer Science at Oregon State University. He is completing his Ph.D. on June 30, 1998. His dissertation is entitled “Learning Hierarchical Decomposition Rules for Planning: An Inductive Logic Programming Approach.” Earlier, he had an M. Tech in Artificial Intelligence and Robotics from University of Hyderabad, India, and an M.Sc.(tech) in Computer Science from Birla Institute of Technology and Science, India. His current research interests broadly fall under machine learning and planning/scheduling—more specifically, inductive logic programming, speedup learning, data mining, and hierarchical planning and optimization. Prasad Tadepalli, Ph.D.: He has an M.Tech in Computer Science from Indian Institute of Technology, Madras, India and a Ph.D. from Rutgers University, New Brunswick, USA. He joined Oregon State University, Corvallis, as an assistant professor in 1989. He is now an associate professor in the Department of Computer Science of Oregon State University. His main area of research is machine learning, including reinforcement learning, inductive logic programming, and computational learning theory, with applications to classification, planning, scheduling, manufacturing, and information retrieval.