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1.
Masayuki Ishinishi Yuhsuke Koyama Hiroshi Deguchi Hajime Kita 《New Generation Computing》2005,23(1):43-56
Management of telecommunication network requires quick, continuous and decentralized allocation of network bandwidth to various
sorts of demands. So as to achieve the efficient network resource allocation, this paper describes a market-based model combining
futures market with the agent-based approach. That is, utilization time is divided into many timeslots, and futures markets
in hereafter use of bandwidth are opened. In our model, all market participants (software agents) observe only market prices
and decide to buy or sell bandwidth trying to maximize their utilities over time so that they can secure enough network resources.
The authors discuss network resource allocation through simulation using the proposed model.
Masayuki Ishinishi, Ph.D.: He graduated from National Defense Academy in 1995 and 2000. He received the B.E. (1995) and M.E.(2000) degrees in computer
science from National Institution for Academic Degrees (NIAD). He received his Ph.D. degree from Tokyo Institute of Technology
in 2003. He has been a communications officer at Air Communications and Systems Wing in Japan Air Self-Defence Force (JASDF)
since 2003. His research interests include information assurance, agent-based modeling and simulation, multi-agent system
and market-based control. He is a member of IEEJ, IPSJ and JSAI.
Yuhsuke Koyama, Ph.D.: He received the B.Econ., M.Econ., and Ph.D. degrees in economics from Kyoto University, in 1996, 1998, 2002, respectively.
He has been a research associate of Tokyo Institute of Technology since 2002. His research field is evolutionary economics,
mathematical sociology and experimental economics. He is a member of JAFEE, JAMS, JASESS and JASAG.
Hiroshi Deguchi, Ph.D.: He received his Ph.D. degree in systems science from Tokyo Institute of Technology, in 1986. He also received the Dr. Econ.
degree from Kyoto University in 2001. He has been a Professor of Tokyo Institute of Technology since 2002. His research field
is evolutionary economics, computational organization theory, agent-based modeling, social system theory, gaming simulation,
and philosophy of science. He is a member of SICE, JAMS, IPSJ, PHSC, JASAG and JAFEE.
Hajime Kita, Ph.D.: He received the B.E., M.E., and Ph.D. degrees in electrical engineering from Kyoto University, in 1982, 1984, 1991, respectively.
He has been a Professor of Kyoto University since 2003, His research field is systems science/engineering, and his research
interests are evolutionary computation, neural networks and socio-economic analysis of energy systems, and agentbased modeling.
He is a member of IEEJ, IEICE, ISCIE, JNNS, JSER, ORSJ and SICE. 相似文献
2.
Chinese-English machine translation is a significant and challenging problem in information processing.The paper presents an interlingua-based Chinese-English natural language translation system(ICENT).It introduces the realization mechanism of Chinses language analysis,which contains syntactic parsing and semantic analyzing and gives the design of interlingua in details .Experimental results and system evaluation are given .The sesult is satisfying. 相似文献
3.
In modern VLSI technology, hundreds of thousands of arithmetic units fit on a 1cm^2 chip. The challenge is supplying them with instructions and data. Stream architecture is able to solve the problem well. However, the applications suited for typical stream architecture are limited. This paper presents the definition of regular stream and irregular stream, and then describes MASA (Multiple-morphs Adaptive Stream Architecture) prototype system which supports different execution models according to applications' stream characteristics. This paper first discusses MASA architecture and stream model, and then explores the features and advantages of MASA through mapping stream applications to hardware. Finally MASA is evaluated by ten benchmarks. The result is encouraging. 相似文献
4.
A new approach based on switched capacitor network to harmonic compensation for switching supplies is presented in the paper,The basic principle is discussed.SPICE simulation is applied to analyze the behaviour of the switched capacitor harmonic compensation part. 相似文献
5.
Constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns
to a smaller, more interesting, subset. Although a lot of work has been done with both these paradigms, there is still confusion
around the mining problem obtained by joining closed and constrained frequent patterns in a unique framework. In this paper,
we shed light on this problem by providing a formal definition and a thorough characterisation. We also study computational
issues and show how to combine the most recent results in both paradigms, providing a very efficient algorithm that exploits
the two requirements (satisfying constraints and being closed) together at mining time in order to reduce the computation
as much as possible.
Francesco Bonchi received his Ph.D. in computer science from the University of Pisa in December 2003, with the thesis “Frequent Pattern Queries:
Language and Optimizations”. Currently, he is a postdoc at the Institute of Information Science and Technologies (ISTI) of
the Italian National Research Council in Pisa, where he is a member of the Knowledge Discovery and Delivery Laboratory. He
has been a visiting fellow at the Kanwal Rekhi School of Information Technology, Indian Institute of Technology, Bombay (2000,
2001). His current research interests are data mining query language and Optimization, frequent pattern mining, privacy-preserving
data mining, bioinformatics. He is one of the teachers of a course on data mining held at the faculty of Economics at the
University of Pisa. He served as a referee at various national and international conferences on databases, data mining, logic
programming and artificial intelligence.
Claudio Lucchese received the Master Degree in Computer Science summa cum laude from Ca' Foscari University of Venice in October 2003. He is currently a Ph.D. student at the same university and Research
Associate at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council in Pisa,
where he is a member of the High Performance Computing Laboratory. He is mainly interested in frequent pattern mining, privacy-preserving
data mining, and data mining techniques for information retrieval. 相似文献
6.
Paola Mello Michela Milano Marco Gavanelli Evelina Lamma Massimo Piccardi Rita Cucchiara 《New Generation Computing》2001,19(4):339-367
*1 Constraint Satisfaction Problems (CSPs)17) are an effective framework for modeling a variety of real life applications and many techniques have been proposed for solving
them efficiently. CSPs are based on the assumption that all constrained data (values in variable domains) are available at
the beginning of the computation. However, many non-toy problems derive their parameters from an external environment. Data
retrieval can be a hard task, because data can come from a third-party system that has to convert information encoded with
signals (derived from sensors) into symbolic information (exploitable by a CSP solver). Also, data can be provided by the
user or have to be queried to a database.
For this purpose, we introduce an extension of the widely used CSP model, called Interactive Constraint Satisfaction Problem
(ICSP) model. The variable domain values can be acquired when needed during the resolution process by means of Interactive
Constraints, which retrieve (possibly consistent) information. A general framework for constraint propagation algorithms is
proposed which is parametric in the number of acquisitions performed at each step. Experimental results show the effectiveness
of the proposed approach. Some applications which can benefit from the proposed solution are also discussed.
This paper is an extended and revised version of the paper presented at IJCAI’99 (Stockholm, August 1999)4).
Paola Mello, Ph.D.: She received her degree in Electronic Engineering from University of Bologna, Italy, in 1982 and her Ph.D. degree in Computer
Science in 1989. Since 1994 she is full Professor. She is enrolled, at present, at the Faculty of Engineering of the University
of Bologna where she teaches Artificial Intelligence. Her research activity focuses around: programming languages, with particular
reference to logic languages and their extensions towards modular and object-oriented programming; artificial intelligence;
knowledge representation; expert systems. Her research has covered implementation, application and theoretical aspects and
is presented in several national and international publications. She took part to several national (Progetti Finalizzati e
MURST) and international (UE) research projects in the context of computational logic.
Michela Milano, Ph.D.: She is a Researcher in the Department of Electronics, Computer Science and Systems at the University of Bologna. From the
same University she obtained her master degree in 1994 and her Ph.D. in 1998. In 1999 she had a post-doc position at the University
of Ferrara. Her research focuses on Artificial Intelligence, Constraint Satisfaction and Constraint Programming. In particular,
she worked on using and extending the constraint-based paradigm for solving real-life problems such as scheduling, routing,
object recognition and planning. She has served on the program committees of several international conferences in the area
of Constraint Satisfaction and Programming, and she has served as referee in several related international journals.
Marco Gavanelli: He is currently a Ph.D. Student in the Department of Engineering at the University of Ferrara, Italy. He graduated in Computer
Science Engineering in 1998 at the University of Bologna, Italy. His research interest include Artificial Intelligence, Constraint
Logic Programming, Constraint Satisfaction and visual recognition. He is a member of ALP (the Association for Logic Programming)
and AI*IA (the Italian Association for Artificial Intelligence).
Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990.
Her research activity centers on logic programming languages, Artificial Intelligence and software engineering. She was co-organizers
of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th
Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Executive Committee
of the Italian Association for Artificial Intelligence (AI*IA). Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence and Fondations
of Computer Science.
Massimo Piccardi, Ph.D.: He graduated in electronic engineering at the University of Bologna, Italy, in 1991, where he received a Ph.D. in computer
science and computer engineering in 1995. He currently an assistant professor of computer science with the Faculty of Engineering
at the University of Ferrara, Italy, where he teaches courses on computer architecture and microprocessor systems. Massimo
Piccardi participated in several research projects in the area of computer vision and pattern recognition. His research interests
include architectures, algorithms and benchmarks for computer vision and pattern recognition. He is author of more than forty
papers on international scientific journals and conference proceedings. Dr. Piccardi is a member of the IEEE, the IEEE Computer
Society, and the International Association for Pattern Recognition — Italian Chapter.
Rita Cucchiara, Ph.D.: She is an associate professor of computer science at the Faculty of Engineering at the University of Modena and Reggio Emilia,
Italy, where she teaches courses on computer architecture and computer vision. She graduated in electronic engineering at
the University of Bologna, Italy, in 1989 and she received a Ph.D. in electronic engineering and computer science from the
same university in 1993. From 1993 to 1998 she been an assistant professor of computer science with the University of Ferrara,
Italy. She participated in many research projects, including a SIMD parallel system for vision in the context of an Italian
advanced research program in robotics, funded by CNR (the Italian National Research Council). Her research interests include
architecture and algorithms for computer vision and multimedia systems. She is author of several papers on scientific journals
and conference proceedings. She is member of the IEEE, the IEEE Computer Society, and the International Association for Pattern
Recognition — Italian Chapter. 相似文献
7.
Hidenori Kawamura Yasushi Okada Azuma Ohuchi Koichi Kurumatani 《New Generation Computing》2005,23(1):23-32
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. 相似文献
8.
PRIME: A Mass Spectrum Data Mining Tool for <Emphasis Type="Italic">De Nova</Emphasis> Sequencing and PTMs Identification
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De novo sequencing is one of the most promising proteomics techniques for identification of protein posttranslation modifications (PTMs) in studying protein regulations and functions. We have developed a computer tool PRIME for identification of b and y ions in tandem mass spectra, a key challenging problem in de novo sequencing. PRIME utilizes a feature that ions of the same and different types follow different mass-difference distributions to separate b from y ions correctly. We have formulated the problem as a graph partition problem. A linear integer-programming algorithm has been implemented to solve the graph partition problem rigorously and efficiently. The performance of PRIME has been demonstrated on a large amount of simulated tandem mass spectra derived from Yeast genome and its power of detecting PTMs has been tested on 216 simulated phosphopeptides. 相似文献
9.
Evelina Lamma Fabrizio Riguzzi Sergio Storari Paola Mello Anna Nanetti 《New Generation Computing》2003,21(2):123-133
A huge amount of data is daily collected from clinical microbiology laboratories. These data concern the resistance or susceptibility
of bacteria to tested antibiotics. Almost all microbiology laboratories follow standard antibiotic testing guidelines which
suggest antibiotic test execution methods and result interpretation and validation (among them, those annually published by
NCCLS2,3). Guidelines basically specify, for each species, the antibiotics to be tested, how to interpret the results of tests and
a list of exceptions regarding particular antibiotic test results. Even if these standards are quite assessed, they do not
consider peculiar features of a given hospital laboratory, which possibly influence the antimicrobial test results, and the
further validation process.
In order to improve and better tailor the validation process, we have applied knowledge discovery techniques, and data mining
in particular, to microbiological data with the purpose of discovering new validation rules, not yet included in NCCLS guidelines,
but considered plausible and correct by interviewed experts. In particular, we applied the knowledge discovery process in
order to find (association) rules relating to each other the susceptibility or resistance of a bacterium to different antibiotics.
This approach is not antithetic, but complementary to that based on NCCLS rules: it proved very effective in validating some
of them, and also in extending that compendium. In this respect, the new discovered knowledge has lead microbiologists to
be aware of new correlations among some antimicrobial test results, which were previously unnoticed. Last but not least, the
new discovered rules, taking into account the history of the considered laboratory, are better tailored to the hospital situation,
and this is very important since some resistances to antibiotics are specific to particular, local hospital environments.
Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990.
Her research activity centers on logic programming languages, artificial intelligence and agent-based programming. She was
co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992,
and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Italian
Association for Artificial Intelligence (AI*IA), associated with ECCAI. Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence
and Fondations of Computer Science.
Fabrizio Riguzzi, Ph.D.: He is Assistant Professor at the Department of Engineering of the University of Ferrara, Italy. He received his Laurea from
the University of Bologna in 1999. He joined the Department of Engineering of the University of Ferrara in 1999. He has been
a visiting researcher at the University of Cyprus and at the New University of Lisbon. His research interests include: data
mining (and in particular methods for learning from multirelational data), machine learning, belief revision, genetic algorithms
and software engineering.
Sergio Storari: He got his degree in Electrical Engineering at the University of Ferrara in 1998. His research activity centers on artificial
intelligence, knowledge-based systems, data mining and multi-agent systems. He is a member of the Italian Association for
Artificial Intelligence (AI*IA), associated with ECCAI. Currently, he is attending the third year of Ph.D. course about “Study and application of Artificial
Intelligence techniques for medical data analysis” at DEIS University of Bologna.
Paola Mello, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1982, and her Ph.D. in Computer Science in 1988.
Her research activity centers on knowledge representation, logic programming, artificial intelligence and knowledge-based
systems. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna
in February 1992, and of the 6th Italian Congress on Artificial Intelligence, Held in Bologna in September 1999. She is a
member of the Italian Association for Artificial Intelligence (AI*IA), associated with ECCAI. Currently, she is Full Professor at the University of Bologna, where she teaches Artificial Intelligence
and Fondations of Computer Science.
Anna Nanetti: She got a degree in biologics sciences at the University of Bologna in 1974. Currently, she is an Academic Recearcher in
the Microbiology section of the Clinical, Specialist and Experimental Medicine Department of the Faculty of Medicine and Surgery,
University of Bologna. 相似文献
10.
Singularity analysis in an important subject of the geometric constraint satisfaction problem.In this paper,three kinds of singularities are described and corresponding identifcation methods are presented for both under0constrained systems and over-constrained systems,Another special but common singularity for under-constrained geometric systems,pseudo-singularity,is analyzed.Pseudo-singularity is caused by a variety of constraint mathching of under-constrained systems and can be removed by improving constraint distribution.To avoid pseudo-singularity and decide redundant constraints adaptively,a differentiaiton algorithm is proposed in the paper.Its corrctness and effciency have been validated through its practical applications in a 2D/3D geometric constraint solver CBA. 相似文献
11.
A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes. 相似文献
12.
Wilfred W. Li Robert W. Byrnes Jim Hayes Adam Birnbaum Vicente M. Reyes Atif Shahab Coleman Mosley Dmitry Pekurovsky Greg B. Quinn Ilya N. Shindyalov Henri Casanova Larry Ang Fran Berman Peter W. Arzberger Mark A. Miller Philip E. Bourne 《New Generation Computing》2004,22(2):127-136
The ongoing global effort of genome sequencing is making large scale comparative proteomic analysis an intriguing task. The
Encyclopedia of Life (EOL; http://eol.sdsc.edu) project aims to provide current functional and structural annotations for
all available proteomes, a computational challenge never seen before in biology. Using an integrative genome annotation pipeline
(iGAP), we have produced 3D models and functional annotations for more than 100 proteomes thus far. This process is greatly
facilitated by grid compute resources, and especially by the development of grid application execution environment. AppLeS
(Application-Level Scheduling) Parameter Sweep Template (APST) has been adopted by the EOL project as a mediator to grid middleware.
APST has made the annotation process much more efficient, highly automated and scalable. Currently we are building a domain-specific
bioinformatics workflow management system (BWMS) on top of APST, which further streamlines grid deployment of life science
applications. With these developments in mind, we discuss some common problems and expectations of grid computing for high
throughput proteomics.
Henri Casanova, Ph.D.: He is an adjunct Professor of Computer Science and Engineering at the University of California, San Diego (UCSD), a Research
Scientist at the San Diego Supercomputer Center, and the founder and director of the Grid Research and Development Laboratory
(GRAIL) at UCSD. His research interests are in the area of parallel, distributed, Grid and Internet computing. He obtained
his B.S. from the Ecole Nationale Supérieure d’Electronique, d’Electrotechnique, d’Informatique et d’Hydraulique de Toulouse,
France in 1993, his M.S. from the Université Paul Sabatier, Toulouse, France in 1994, and his Ph.D. from the University of
Tennessee, Knoxville in 1998.
Francine Berman, Ph.D.: She is a Professor and High Performance Computing Endowed Chair at U.C. San Diego, Director of the San Diego Supercomputer
Center and a Fellow of the ACM. Her research over two decades has focused on High Performance and Grid Computing, in particular
in the areas of programming environments, adaptive middleware, scheduling and performance prediction. She has served on numerous
editorial boards, steering committees, and program and conference committees in the areas of Parallel and Grid computing.
She is one of the Principal Investigators of the NSF-supported TeraGrid, and directs NSF’s National Partnership for Advanced
Computing Infrastructure (NPACI).
Peter Arzberger, Ph.D.: He is the Director of Life Sciences Initiatives, University of California San Diego, Director of the National Biomedical
Computation Resource (http://nbcr.ucsd.edu), funded by the National Center of Research Resource of NIH and the Chair of the
Pacific Rim Application and Grid Middleware Assembly (http://www.pragma-grid.edu), an organization of 20 institutions around
the pacific rim whose mission is to establish sustained collaborations and to advance the use of grid technologies in applications.
He serves on the US National CODATA Committee and the National Advisory Board of the US Long Term Ecological Research. His
hobby is working on Lloyds.
Mark A. Miller, Ph.D.: He is Program Coordinator for the Integrative BioSciences Program at San Diego Supercomputer Center. He received his Ph.D.
in Biochemistry from Purdue University in 1984. His research interests have slowly moved towards computer driven analyses
and quantitative biology, and culminated in managing the BioInformatics Core of the Joint Center for Structural Biology where
he helped to plan and implement the informatics solutions for high throughput crystallography. He is currently working on
the specification, design and deployment of tools to enable biology research.
Philip Bourne, Ph.D.: He is a Professor of Pharmacology at the University of California, San Diego and co-director of the Protein Data Bank (PDB).
He is immediate past President of the International Society for Computational Biology, an Associate Editor of Bioinformatics
and on the Editorial Board of several other journals. He received his B.Sc. and Ph.D. in chemistry at the Flinders University,
South Australia. His research interests include bioinformatics, particularly structural bioinformatics. This implies algorithms,
metalanguages, biological databases, biological query languages and visualization with special interest in cell signaling
and apoptosis. Major projects ongoing in the Bourne Lab include the PDB, Encyclopedia of Life (EOL), Systematic Protein Annotation
and Modeling (SPAM), and the Tree of Life. Bourne’s personal interests include fishing, tennis, squash, walking, skiing, sports
cars, motor bikes and writing. 相似文献
13.
This paper is devtoed to a new algebraic modelling approach to distributed problem-solving in multi-agent systems(MAS),which is featured by a unified framework for describing and treating social behaviors,social dynamics and social intelligence.A coneptual architecture of algebraic modelling is presented.The algebraic modelling of typical social be-haviors,social situation and social dynamics is discussed in the context of distributed problem-solving in MAS .The comparison and simulation on distributed task allocations and resource assignments in MAS show more advantages of the algebraic approach than other conventional methods. 相似文献
14.
We introduce in this paper four classes of P transducers: arbitrary, initial, isolated arbitrary, isolated and initial. The
first two classes are universal, they can compute the same word functions as Turing machines, the latter two are incomparable
with finite state sequential transducers, generalized or not. We study the effect of the composition, and show that iteration
increases the power of these latter classes, also leading to a new characterization of recursively enumerable languages. The
“Sevilla carpet” of a computation is defined for P transducers, giving a representation of the control part for these P transducers.
Gabriel Ciobanu, Ph.D.: He has graduated from the Faculty of Mathematics, “A.I.Cuza” University of Iasi, and received his Ph.D. from the same university.
He is a senior researcher at the Institute of Computer Science of the Romanian Academy. He has wide-ranging interests in computing
including distributed systems and concurrency, computational methods in biology, membrane computing, and theory of programming
(semantics, formal methods, logics, verification). He has published around 90 papers in computer science and mathematics,
a book on programming semantics and a book on network programming. He is a co-editor of three volumes. He has visited various
universities in Europe, Asia, and North America, giving lectures and invited talks. His webpage is http://www.info.uaic.ro/gabriel
Gheorghe Păun, Ph.D.: He has graduated from the Faculty of Mathematics, University of Bucharest, in 1974 and received his Ph.D. from the same university
in 1977. Curently he works as senior researcher in the Institute of Mathematics of the Romanian Academy, as well as a Ramon
y Cajal researcher in Sevilla University, Spain. He has repeatedly visited numerous universities in Europe, Asia, and North
America. His main research areas are formal language theory and its applications, computational linguistics, DNA computing,
and membrane computing (a research area initiated by him). He has published over 400 research papers (collaborating with many
researchers worldwide), has lectured at over 100 universities, and gave numerous invited talks at recognized international
conferences. He has published 11 books in mathematics and computer science, has edited about 30 collective volumes, and also
published many popular science books and books on recreational mathematics (games). He is on the editorial boards of fourteen
international journals in mathematics, computer science, and linguistics, and was/is involved in the program/steering/organizing
commitees for many recognized conferences and workshops. In 1997 he was elected a member of the Romanian Academy.
Gheorghe Ştefănescu, Ph.D.: He received his B.Sc./M.Sc./Ph.D. degrees in Computer Science from the University of Bucharest. Currently, he is a Professor
of Computer Science at the University of Bucharest and a Senior Fellow at the National University of Singapore. Previously,
he was a researcher at the Institute of Mathematics of the Romanian Academy and has held visiting positions in The Netherlands,
Germany, and Japan. His current research focuses on formal methods in computer science, particularly on process and network
algebras, formal methods for interactive, real-time, and object-oriented systems. Some of his results may be found in his
book on “Network Algebra,” Springer, 2000. 相似文献
15.
This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic
(land-cover) maps. We present a Structure Matching algorithm that combines Gentner’s structuremapping theory with an attributematching process. We use structure matching to solve geometric analogy problems that involve manipulating attribute information, such
as colors and patterns. Structure matching is also used to creatively interpret topographic (land-cover) maps, adding a wealth
of semantic knowledge and providing a far richer interpretation of the raw data. We return to the geometric proportional analogies,
identify alternate attribute matching processes that are required to solve different categories of problems. Finally, we assess
some implications for computationally creative and inventive models.
Diarmuid P. O’Donoghue, Ph.D.: He received his B.Sc. and M.Sc. from University College Cork in 1988 and 1990, and his Ph.D. from University College Dublin.
He has been a lecturer at the Department of Computer Science NUI Maynooth since 1996 and is also an associate of the National
Centre for Geocomputation. His interests are in artificial intelligence, analogical reasoning, topology, and qualitative spatial
reasoning.
Amy Bohan, B.Sc, M.Sc.: She received her B.Sc. from the National University of Ireland, Maynooth in 2000. She received her M.Sc. in 2003 from University
College Dublin where she also recently completed her Ph.D. She is a member of the Cognitive Science society. Her interests
are in cognitive science, analogical argumentation, geometric proportional analogies and computational linguistics.
Prof. Mark T. Keane: He is Chair of Computer Science and Associate Dean of Science at University College Dublin. He is also Director of ICT, at
Science Foundation Ireland. Prof. Keane has made significant contributions in the areas of analogy, case-based reasoning and
creativity. He has published over 100 publications, including 16 books, that are cited widely. He is co-author of a Cognitive
Science textbook, written with Mike Eysenck (University of London) that has been translated into Portuguese, Hungarian, Italian
and Chinese and is now entering its fifth edition. Prof. Keane is a fellow of ECCAI (European Co-ordinating Committee on Artificial
Intelligence) and received the Special Award for Merit from the Psychology Society of Ireland, for his work on human creativity. 相似文献
16.
Bounded Slice-line Grid (BSG) is an elegant representation of block placement, because it is very intuitionistic and has the advantage of handling various placement constraints. However, BSG has attracted little attention because its evaluation is very time-consuming. This paper proposes a simple algorithm independent of the BSG size to evaluate the BSG representation in O(nloglogn) time, where n is the number of blocks. In the algorithm, the BSG-rooms are assigned with integral coordinates firstly, and then a linear sorting algorithm is applied on the BSG-rooms where blocks are assigned to compute two block sequences, from which the block placement can be obtained in O(n log logn) time. As a consequence, the evaluation of the BSG is completed in O(nloglogn) time, where n is the number of blocks. The proposed algorithm is much faster than the previous graph-based O(n^2) algorithm. The experimental results demonstrate the efficiency of the algorithm. 相似文献
17.
Jose-Jesus Fernandez Jose-Roman Bilbao-Castro Roberto Marabini Jose-Maria Carazo Inmaculada Garcia 《New Generation Computing》2005,23(1):101-112
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. 相似文献
18.
Chance discovery and scenario analysis 总被引:1,自引:0,他引:1
Scenario analysis is often used to identify possible chance events. However, no formal, computational theory yet exists for
scenario analysis. In this paper, we commence development of such a theory by defining a scenario in an argumentation context,
and by considering the question of when two scenarios are the same.
Peter McBurney, Ph.D.: He is a lecturer in the Department of Computer Science at the University of Liverpool, UK. He has a first degree in Pure
Mathematics and Statistics from the Australian National University, Canberra, and a Ph.D in Artificial Intelligence from the
University of Liverpool. His Ph.D research concerned the design of protocols for rational interaction between autonomous software
agents, and he has several publications in this area. Prior to completing his Ph.D he worked as a consultant to major telecommunications
network operating companies, primarily in mobile and satellite communications, where his work involved strategic marketing
programming.
Simon Parsons, Ph.D.: He is currently visiting the Sloan School of Management at Massachusetts Institute of Technology (MIT) and is a Visiting
Professor at the University of Liverpool, UK. He holds a first degree in Engineering from Cambridge University, and an MSc
and Ph.D in Artificial Intelligence from the University of London. In 1998, he was awarded the Young Engineer Achievement
Medal of the British Institution of Electrical Engineers (IEE), the largest professional engineering society in Europe. He
has published 4 books and over 100 articles on autonomous agents and multi-agent systems, uncertainty formalisms, risk and
decision-making. 相似文献
19.
Potential field method to navigate several mobile robots 总被引:2,自引:1,他引:2
Saroj Kumar Pradhan Dayal Ramakrushna Parhi Anup Kumar Panda Rabindra Kumar Behera 《Applied Intelligence》2006,25(3):321-333
Navigation of mobile robots remains one of the most challenging functions to carry out. Potential Field Method (PFM) is rapidly
gaining popularity in navigation and obstacle avoidance applications for mobile robots because of its elegance. Here a modified
potential field method for robots navigation has been described. The developed potential field function takes care of both
obstacles and targets. The final aim of the robots is to reach some pre-defined targets. The new potential function can configure
a free space, which is free from any local minima irrespective of number of repulsive nodes (obstacles) in the configured
space. There is a unique global minimum for an attractive node (target) whose region of attraction extends over the whole
free space. Simulation results show that the proposed potential field method is suitable for navigation of several mobile
robots in complex and unknown environments.
Saroj Kumar Pradhan is faculty of Mechanical Engineering Department with N.I.T., Hamirpur, HP, India. He has received his B.E. degree in Mechanical
Engineering from Utkal University and M.E. in Machine Design and Analysis from NIT Rourkela. He has published more than 17
technical papers in international journals and conference proceedings. His areas of research include mobile robots navigation
and vibration of multilayred beams.
Dayal R. Parhi is working as Assistant Professor at NIT Rourkela, India. He has obtained his first Ph.D. degree in “Mobile Robotics” from
United Kingdom and Second Ph.D. in “Mechanical Vibration” from India. He has visited CMU, USA as a “Visiting Scientist” in
the field of “Mobile Robotics”. His main areas of current research are “Robotics” and “Mechanical Vibration”. He is supervising
five Ph.D. students in the fields of Robotics and Vibration. Email: dayalparhi@yahoo.com.
Anup Kumar Panda Received his M.Tech degree from IIT, Kharagpur in 1993 and Ph.D. degree from Utkal University in 2001. He is currently an
assistant professor in the Department of Electrical Engineering at National Institute of Technology, Rourkela, India. His
areas of research include robotics, Machine Drives, harmonics and power quality. He has published more than 30 technical papers
in journals and conference proceedings. He is now involved in two R&D projects funded by Government of India.
R. K. Behera is a Senior Lecturer of Mechanical Engineering at National Institute of Technology, Rourkela, India. He has been working
as lecturer for more than 10 years. He obtained his BE degree from IGIT, Sarang, of Utkal University. He obtained his ME and
Ph.D degrees, both in the field of mechanical engineering from NIT Rourkela. 相似文献
20.
This paper investigates a preemptive semi-online scheduling problem on m identical parallel machines where m = 2,3. It is assumed that all jobs have their processing times in between p and rp (p > 0, r≥1). The goal is to minimize the makespan. Best possible algorithms are designed for any r≥1 when m = 2,3. 相似文献