Relational semantics for locally nondeterministic programs

Introducing nondeterministic operators in a conventional deterministic language gives rise to various semantic difficulties. One of the problems is that there has been no semantic domain that is wholly satisfactory for denoting nondeterministic programs. In this paper, we propose an approach based on relational algebra. We divide the semantics of a nondeterministic program into two parts. The first part concerns the angelic aspect of programs and the second part concerns the demonic aspect of programs. Because each semantic function used in these parts is monotonic with respect to an ordering on relations, the existence of the fixed points of recursively defined nondeterministic programs is ensured. Liangwei Xu: His research interests are computational model, program transformation and derivation methodology. He received the B. E. degree from Shanghai Jiao Tong University in 1982 and the M.E. degree from University of Tokyo in 1992. He currently joins Mathematical Systems Institute Inc. Masato Takeichi, Dr. Eng.: He is a Professor of Department of Mathematical Engineering. Graduate School of Engineering, University of Tokyo. His research interests are functional programming, language implementation and constructive algorithmics. Hideya Iwasaki, Dr. Eng.: He is an Associate Professor of Faculty of Technology, Tokyo University of Agriculture and Technology. He received the M.E. degree in 1985, the Dr. Eng. degree in 1988 from University of Tokyo. His research interests are list processing languages, functional languages, parallel processing, and constructive algorithmics.     

FNS,CFNS and HEIV: A Unifying Approach

Estimation of parameters from image tokens is a central problem in computer vision. FNS, CFNS and HEIV are three recently developed methods for solving special but important cases of this problem. The schemes are means for finding unconstrained (FNS, HEIV) and constrained (CFNS) minimisers of cost functions. In earlier work of the authors, FNS, CFNS and a core version of HEIV were applied to a specific cost function. Here we extend the approach to more general cost functions. This allows the FNS, CFNS and HEIV methods to be placed within a common framework. Wojciech Chojnacki is a professor of mathematics in the Department of Mathematics and Natural Sciences at Cardinal Stefan Wyszyski University in Warsaw. He is concurrently a senior research fellow in the School of Computer Science at the University of Adelaide working on a range of problems in computer vision. His research interests include differential equations, mathematical foundations of computer vision, functional analysis, and harmonic analysis. He is author of over 70 articles on pure mathematics and machine vision, and a member of the Polish Mathematical Society. Michael J. Brooks holds the Chair in Artificial Intelligence within the University of Adelaides School of Computer Science, which he heads. He is also leader of the Image Analysis Program within the Cooperative Research Centre for Sensor Signal and Information Processing, based in South Australia. His research interests include structure from motion, self-calibration, metrology, statistical vision-parameter estimation, and video surveillance and analysis. He is author of over 100 articles on vision, actively involved in a variety of commercial applications, an Associate Editor of the International Journal of Computer Vision, and a Fellow of the Australian Computer Society. Anton van den Hengel is a senior lecturer in the School of Computer Science within the University of Adelaide. He is also leader of the Video Surveillance and Analysis Project within the Cooperative Research Centre for Sensor Signal and Information Processing. His research interests include structure from motion, parameter estimation theory, and commercial applications of computer vision. Darren Gawley graduated with first class honours from the School of Computer Science at the University of Adelaide. He holds a temporary lectureship at the same University, and is currently finalising his PhD in the field of computer vision.This revised version was published online in June 2005 with correction to CoverDate     

An agent architecture for strategy-centric adaptive QoS control in flexible videoconference system

In this paper, we propose an agent architecture to improve flexibility of a videoconference system with strategy-centric adaptive QoS (Quality of Service) control mechanism. The proposed architecture realizes more flexibility by changing their QoS control strategies dynamically. To switch the strategies, system considers the properties of problems occurred on QoS and status of problem solving process. This architecture is introduced as a part of knowledge base of agent that deals with cooperation between software module of videoconference systems. We have implemented the mechanism, and our prototype system shows its capability of flexible problem solving against the QoS degradation, along with other possible problems within the given time limitation. Thus we confirmed that the proposed architecture can improve its flexibility of a videoconference system compared to traditional systems. Takuo Suganuma, Dr.Eng.: He is a research associate of Research Institute of Electrical Communication of Tohoku University. He received a Dr.Eng. degree from Chiba Institute of Technology in 1997. His research interests include agent-based computing and design methodology for distributed systems. He is a member of IPSJ, IEICE and IEEE. SungDoke Lee: He is a Ph.D. Student in the Graduate School of Information Sciences in Tohoku University. He received his MEng degree at Chonbuk National University, Korea in 1991. His research interests include Flexible Network and Knowledge of Agent. Tetsuo Kinoshita, Dr.Eng.: He is an associate professor of Research Institute of Electrical Communication of Tohoku University. He received a Dr.Eng. degree in information engineering from Tohoku University, Japan. His research interests include knowledge engineering, cooperative distributed processing and agent-based computing. He received the the IPSJ Best Paper Award in 1997, etc. He is a member of IPSJ, IEICE, JSAI, AAAI, ACM and IEEE. Norio Shiratori, Dr.Eng.: After receiving his Dr.Eng degree at Tohoku University, he joined the Research Institute of Electrical Communication of Tohoku University in 1977, and is now a professor at the same University. He has been engaged in research on distributed processing system, and flexible intelligent network. He received the 25th Anniversary of IPSJ Memorial Prize-Winning Paper Award in 1985, the 6th Telecommunications Advancement Foundation Incorporation Award in 1991, the Best Paper Award of ICOIN-9 in 1994, the IPSJ Best Paper Award in 1997, etc. He has been named a Fellow of the IEEE for his contributions to the field of computer communication networks.     

Music composition by interaction between human and computer

This paper aims at constructing a music composition system that composes music by the interaction between human and a computer. Even users without special musical knowledge can compose 16-bar musical works with one melody part and some backing parts using this system. The interactive Genetic Algorithm is introduced to music composition so that users’ feeling toward music is reflected in the composed music. One chromosome corresponds to 4-bar musical work information. Users participate in music composition by evaluating composed works after GA operators such as crossover, mutation, virus infection are applied to chromosomes based on the evaluation results. From the experimental results, it is found that the users’ evaluation values become high over the progress of generations. That is, the system can compose 16-bar musical works reflecting users’ feeling. Muneyuki Unehara: He received his M.S. in Engineering in 2002 from Institute of Science and Engineering, University of Tsukuba. Currently, he is a Ph.D. candidate of Graduate School of Systems and Information Engineering, University of Tsukuba. His research interests include the construction of intelligent systems by considering soft computing techniques and human interface. Takehisa Onisawa, Ph.D.: He received Dr.Eng. in Systems Science in 1986 from Tokyo Institute of Technology. Currently, he is a Professor in the Graduate School of Systems and Information Engineering, University of Tsukuba. His research interests include applications of soft computing techniques to human centered systems thinking. He is a member of IEEE and IFSA.     

Stability of nonlinear hybrid dynamical systems with time delay via sum of squares decomposition

Considering an infinite number of eigenvalues for time delay systems, it is difficult to determine their stability. We have developed a new approach for the stability test of time delay nonlinear hybrid systems. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are found, stability’s analysis of the system is straight-forward. In this paper both delay-independent and delay-dependent stability tests are proposed, based on the construction of appropriate Lyapunov-Krasovskii functionals. The methodology is based on the sum of squares decomposition of multivariate polynomials and the algorithmic construction is achieved through the use of semidefinite programming. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be computationally infeasible to solve. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Finally simulation results show the correctness and validity of the designed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors wish to express their thanks to Dr. A. Papachristodoulou and Dr. M. Peet for their helpful comments and suggestions. Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received the B.S. degree in Electrical Engineering from University of Tabriz in 1998 and the M.Sc. degree in Control Engineering from University of Tabriz in 2001. He received the Ph.D. degree in Control Engineering from University of Tabriz in 2007. He is now an Assistant Professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include Hybrid dynamical systems, Stability of systems, Time delay systems, Robot path planning. Sohrab Khanmohammadi received the B.S. degree in Industrial Engineering from Sharif University, Iran in 1977 and the M.Sc. degree in Automatic from University Paul Sabatie, France in 1980 and the Ph.D. degree in Automatic from National University, ENSAE, France in 1983. He is now a Professor of Electrical Engineering at University of Tabriz. His research interests are Fuzzy control, Artificial Intelligence applications in control and simulation on industrial systems and human behavior. Gasem Alizadeh was born in Tabriz, Iran in 1967. He received the B.S. degree in Electrical Engineering from Sharif University, Iran in 1990 and the M.Sc. degree from Khajeh Nasir Toosi University, Iran in 1993 and the Ph.D. degree in Electrical Engineering from Tarbiat Modarres University, Iran in 1998. From 1998, he is a Member of University of Tabriz in Iran. His research interests are robust and optimal control, guidance, navigation and adaptive control. Ali Aghagolzadeh was born in Babol, Iran. He received the B.S. degree in Electrical Engineering in 1985 from University of Tabriz, Tabriz, Iran, and the M.Sc. degree in Electrical Engineering in 1988 from the Illinois Institute of Technology, Chicago, IL. He also attended the School of Electrical Engineering at Purdue University in August 1998 where he was also employed as a part-time research assistant and received the Ph.D. degree in 1991. He is currently an Associate Professor of Electrical Engineering at University of Tabriz, Tabriz, Iran. His research interests include digital signal and image processing, image coding and communication, computer vision, and image analysis.     

A Framework for Design Tradeoffs

Designs almost always require tradeoffs between competing design choices to meet system requirements. We present a framework for evaluating design choices with respect to meeting competing requirements. Specifically, we develop a model to estimate the performance of a UML design subject to changing levels of security and fault-tolerance. This analysis gives us a way to identify design solutions that are infeasible. Multi-criteria decision making techniques are applied to evaluate the remaining feasible alternatives. The method is illustrated with two examples: a small sensor network and a system for controlling traffic lights. Dr. Anneliese Amschler Andrews is Professor and Chair of the Department of Computer Science at the University of Denver. Before that she was the Huie Rogers Endowed Chair in Software Engineering at Washington State University. Dr. Andrews is the author of a text book and over 130 articles in the area of Software Engineering, particularly software testing and maintenance. Dr. Andrews holds an MS and PhD from Duke University and a Dipl.-Inf. from the Technical University of Karlsruhe. She served as Editor-in-Chief of the IEEE Transactions on Software Engineering. She has also served on several other editorial boards including the IEEE Transactions on Reliability, the Empirical Software Engineering Journal, the Software Quality Journal, the Journal of Information Science and Technology, and the Journal of Software Maintenance. She was Director of the Colorado Advanced Software Institute from 1995 to 2002. CASI's mission was to support technology transfer research related to software through collaborations between industry and academia. Ed Mancebo studied software engineering at Milwaukee School of Engineering and computer science at Washington State University. His masters thesis explored applying systematic decision making methods to software engineering problems. He is currently a software developer at Amazon.com. Dr. Per Runeson is a professor in software engineering at Lund University, Sweden. His research interests include methods to facilitate, measure and manage aspects of software quality. He received a PhD from Lund University in 1998 and has industrial experience as a consulting expert. He is a member of the editorial board of Empirical Software Engineering and several program committees, and currently has a senior researcher position funded by the Swedish Research Council. Robert France is currently a Full Professor in the Department of Computer Science at Colorado State University. His research interests are in the area of Software Engineering, in particular formal specification techniques, software modeling techniques, design patterns, and domain-specific modeling languages. He is an Editor-in-Chief of the Springer journal on Software and System Modeling (SoSyM), and is a Steering Committee member and past Steering Committee Chair of the MoDELS/UML conference series. He was also a member of the revision task forces for the UML 1.x standards.     

Synthesising surface matching algorithms using the correspondence framework

Computer vision tasks such as registration, modeling and object recognition, are becoming increasingly useful in industry. Each of these applications employs correspondence algorithms to compute accurate mappings between partially overlapping surfaces. In industry, it is essential to select an appropriate correspondence algorithm for a given surface matching task. A correspondence framework has recently been proposed to assist in the selection and creation of correspondence algorithms for these tasks. This paper demonstrates how to use the correspondence framework to create a new surface matching algorithm, which uses stages of an existing model matching algorithm. The efficiency with which the new algorithm is created using the correspondence frame work is emphasized. In addition, results show that the new algorithm is both robust and efficient. The text was submitted by the authors in English. Birgit Maria Planitz, born in 1978, received B. Engineering (Hons) degree at the Queensland University of Technology (QUT) in Brisbane, Australia (2001). Dr. Planitz then continued her studies at QUT, enrolling in a PhD. The PhD was in the field of computer vision, specializing in three-dimensional surface matching. Dr. Planitz graduated from her postraduate degree in 2005, with two major journal publications, six conference papers and a technical report. She is currently working for the e-Health Research Centre/CSIRO ICT Centre. Dr. Planitz is a member of the Australia Pattern Recognition Society. Anthony John Maeder, born 1958, graduated with B. Science (Hons) from University of Witwatersrand in 1980 and M. Science from the University of Natal in 1982. He was awarded his PhD in 1992 by Monash University. Dr. Maeder is currently the Research Director, E-Health Research Centre/CSIRO ICT Centre and Adjunct Professor, Faculty of Health Sciences, University of Queensland. His research areas include digital image processing, image and video compression, medical imaging, computer graphics and visualization. Dr. Maeder has 200 publications consisting of 10 monographs and proceedings, 20 journal papers and 180 conference papers. He is a fellow of the Institution of Engineers Australia; a member of IEEE, ACM, ACS, HISA; a member of SPIE International Technical Committee for Medical Imaging; and a member of national executive committee of the Australian Pattern Recognition Society. John Alan Williams, born in 1973, was awarded his PhD from the Queensland University of Technology (QUT), Australia, in 2001. He was previously awarded undergraduate degrees in Electronic Engineering and Information Technology (Hons), also from QUT, in 1995. He is currently employed at the School of ITEE at The University of Queensland, Brisbane, Australia, where he holds the position of Research Fellow. Dr. William’s research interests include reconfigurable computing and realtime embedded systems, as well as 3D computer vision and imaging. He has authored 5 refereed journal publications and more than 20 refereed conference publications, and has recently edited the Proceedings of the 2004 IEEE International Conference on Field Programmable Technology. He has been a member of the IEEE for eight years.     

Balance control of a biped robot using camera image of reference object

This paper presents a new balance control scheme for a biped robot. Instead of using dynamic sensors to measure the pose of a biped robot, this paper uses only the visual information of a specific reference object in the workspace. The zero moment point (ZMP) of the biped robot can be calculated from the robot’s pose, which is measured from the reference object image acquired by a CCD camera on the robot’s head. For balance control of the biped robot a servo controller uses an error between the reference ZMP and the current ZMP, estimated by Kalman filter. The efficiency of the proposed algorithm has been proven by the experiments performed on both flat and uneven floors with unknown thin obstacles. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Jae-Bok Song. This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD). This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA(Institute for Information Technology Advancement) (IITA-2008-C1090-0803-0006). Sangbum Park received the B.S. and M.S. degrees from Electronic Engineering of Soongsil University, Seoul, Korea, in 2004 and 2006 respectively. He has been with School of Electronic Engineering, Soongsil University since 2006, where he is currently pursuing a Ph.D. His current research interests include biped walking robot, robotics vision. Youngjoon Han received the B.S., M.S. and Ph.D. degrees in Electronic Engineering from Soongsil University, Seoul, Korea, in 1996, 1998, and 2003, respectively. He is currently an Assistant Professor in the School of Electornic Engineering at Soongsil University. His research interests include robot vision system, and visual servo control. Hernsoo Hahn received the B.S. and M.S. degrees in Electronic Engineering at Soongsil University and Younsei University, Korea in 1982 and 1983 respectively. He received the Ph.D. degree in Computer Engineering from University of Southern California in 1991, and became an Assistant Professor at the School Electroncis Engneering in Soongsil University in 1992. Currently, he is a Professor. His research interests include application of vision sensors to mobile robots and measurement systems.     

Public opinion channel for communities in the information age

In this paper, we propose as a new challenge a public opinion channel which can provide a novel communication medium for sharing and exchanging opinions in a community. Rather than simply developing a means of investigating public opinion, we aim at an active medium that can facilitate mutual understanding, discussion, and public opinion formation. First, we elaborate the idea of public opinion channels and identify key issues. Second, we describe our first step towards the goal using the talking virtualized egos metaphor. Finally, we discuss a research agenda towards the goal. Toyoaki Nishida, Dr.Eng.: He is a professor of Department of Information and Communication Engineering, School of Engineering, The University of Tokyo. He received the B.E., the M.E., and the Doctor of Engineering degrees from Kyoto University in 1977, 1979, and 1984 respectively. His research centers on artificial intelligence in general. His current research focuses on community computing and support systems, including knowledge sharing, knowledge media, and agent technology. He has been leading the Breakthrough 21 Nishida Project, sponsored by Ministry of Posts and Telecommunications, Japan, aiming at understanding and assisting networked communities. Since 1997, he is a trustee for JSAI (Japanese Society for Artificial Intelligence), and serves as the program chair of 1999 JSAI Annual Convention. He is an area editor (intelligent systems) of New Generation Computing and an editor of Autonomous Agents and Multiagent Systems. Nobuhiko Fujihara, Ph.D.: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E., the M.E., and the Ph.D. in Human Sciences degrees from Osaka University in 1992, 1994, and 1998 respectively. He has a cognitive psychological background. His current research focuses on: (1) cognitive psychological analysis of human behavior in a networked community, (2) investigation of information comprehension process, (3) assessment and proposition of communication tools in networking society. Shintaro Azechi: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E. and the M.E. of Human Sciences degrees from Osaka University in 1994 and 1996 respectively. He is a Doctoral Candidate of Graduate School of Human Sciences, Osaka University. His current researches focus on (1) human behavior in networking community (2) social infomation process in human mind (3) development of acessment technique for communication tools in networkingsociety. His approach is from social psychological view. Kaoru Sumi, Dr.Eng.: She is a Researcher of Breakthrough 21 Nishida Project. She received her Bachelor of Science at School of Physics, Science University of Tokyo. She received her Master of Systems Management at Graduate School of Systems Management, The university of Tsukuba. She received her Doctor of engineering at Graduate School of Engineering, The University of Tokyo. Her research interests include knowledge-based systems, creativity supporting systems, and their applications for facilitating human collaboration. She is a member of the Information Processing Society of Japan (IPSJ), the Japanese Society for Artificial Intelligence (JSAI). Hiroyuki Yano, Dr.Eng.: He is a senior research official of Kansai Advanced Research Center, Communications Research Laboratory, Ministry of Posts and Telecommunications. He received the B.E., the M.E., and the Doctor of Engineering degrees from Tohoku University in 1986, 1988, and 1993 respectively. His interests of research include cognitive mechanism of human communications. His current research focuses on discourse structure, human interface, and dialogue systems for human natural dialogues. He is a member of the Japanese Society for Artificial Intelligence, the Association for Natural Language Processing, and the Japanese Cognitive Science Society. Takashi Hirata: He is a doctor course student in Graduate School of Information Scienc at Nara Institute of Science and Technology (NAIST). He received a master of engineering from NAIST in 1998. His research interest is knowledge media and knowledge sharing. He is a member of Information Processing Society of Japan (IPSJ), Japan Association for Artificial Intelligence (JSAI) and The Institute of Systems, Control and Information Engineers (ISCIE).     

Geo-located image categorization and location recognition

Image categorization is undoubtedly one of the most recent and challenging problems faced in Computer Vision. The scientific literature is plenty of methods more or less efficient and dedicated to a specific class of images; further, commercial systems are also going to be advertised in the market. Nowadays, additional data can also be attached to the images, enriching its semantic interpretation beyond the pure appearance. This is the case of geo-location data that contain information about the geographical place where an image has been acquired. This data allow, if not require, a different management of the images, for instance, to the purpose of easy retrieval from a repository, or of identifying the geographical place of an unknown picture, given a geo-referenced image repository. This paper constitutes a first step in this sense, presenting a method for geo-referenced image categorization, and for the recognition of the geographical location of an image without such information available. The solutions presented are based on robust pattern recognition techniques, such as the probabilistic Latent Semantic Analysis, the Mean Shift clustering and the Support Vector Machines. Experiments have been carried out on a couple of geographical image databases: results are actually very promising, opening new interesting challenges and applications in this research field. The article is published in the original. Marco Cristani received the Laurea degree in 2002 and the Ph.D. degree in 2006, both in Computer Science from the University of Verona, Verona, Italy. He was a visiting Ph.D. student at the Computer Vision Lab, Institute for Robotics and Intelligent Systems School of Engineering (IRIS), University of Southern California, Los Angeles, in 2004–2005. He is now an Assistant Professor with the Department of Computer Science, University of Verona, working with the Vision, Image Processing and Sounds (VIPS) Lab. His main research interests include statistical pattern recognition, generative modeling via graphical models, and non-parametric data fusion techniques, with applications on surveillance, segmentation and image and video retrieval. He is the author of several papers in the above subjects and a reviewer for several international conferences and journals. Alessandro Perina received the BD and MS degrees in Information Technologies and Intelligent and Multimedia Systems from the University of Verona, Verona, Italy, in 2004 and 2006, respectively. He is currently a Ph.D. candidate in the Computer Science Department at the University of Verona. His research interests include computer vision, machine learning and pattern recognition. He is a student member of the IEEE. Umberto Castellani is Ricercatore (i.e., Research Assistant) of Department of Computer Science at University of Verona. He received his Dottorato di Ricerca (Ph.D.) in Computer Science from the University of Verona in 2003 working on 3D data modelling and reconstruction. During his Ph.D., he had been Visiting Research Fellow at the Machine Vision Unit of the Edinburgh University, in 2001. In 2007 he has been an Invited Professor for two months at the LASMEA laboratory in Clermont-Ferrand, France. In 2008, he has been Visiting Researcher for two months at the PRIP laboratory of the Michigan State University (USA). His main research interests concern the processing of 3D data coming from different acquisition systems such as 3D models from 3D scanners, acoustic images for the vision in underwater environment, and MRI scans for biomedical applications. The addressed methodologies are focused on the intersections among Machine Learning, Computer Vision and Computer Graphics. Vittorio Murino received the Laurea degree in electronic engineering in 1989 and the Ph.D. degree in electronic engineering and computer science in 1993, both from the University of Genoa, Genoa, Italy. He is a Full Professor with the Department of Computer Science, University of Verona. From 1993 to 1995, he was a Postdoctoral Fellow in the Signal Processing and Understanding Group, Department of Biophysical and electronic Engineering, University of Genoa, where he supervised of research activities on image processing for object recognition and pattern classification in underwater environments. From 1995 to 1998, he was an Assistant Professor of the Department of Mathematics and Computer Science, University of Udine, Udine, Italy. Since 1998, he has been with the University of Verona, where he founded and is responsible for the Vision, Image processing, and Sound (VIPS) Laboratory. He is scientifically responsible for several national and European projects and is an Evaluator for the European Commission of research project proposals related to different scientific programmes and frameworks. His main research interests include computer vision and pattern recognition, probabilistic techniques for image and video processing, and methods for integrating graphics and vision. He is author or co-author of more than 150 papers published in refereed journals and international conferences. Dr. Murino is a referee for several international journals, a member of the technical committees for several conferences (ECCV, ICPR, ICIP), and a member of the editorial board of Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics, Pattern Analysis and Applications and Electronic Letters on Computer Vision and Image Analysis (ELCVIA). He was the promotor and Guest Editor off our special issues of Pattern Recognition and is a Fellow of the IAPR.     

A New Parallel Differential Method for Optical Flow Estimation

Optical flow estimation is a recurrent problem in several disciplines and assumes a primary importance in a number of applicative fields such as medical imaging [12], computer vision [6], productive process control [4], etc. In this paper, a differential method for optical flow evaluation is being presented. It employs a new error formulation that ensures a more than satisfactory image reconstruction in those points which are free of motion discontinuity. A dynamic scheme of brightness-sample processing has been used to regularise the motion field. A technique based on the concurrent processing of sequences with multiple pairs of images has also been developed for improving detection and resolution of mobile objects on the scene, if they exist. This approach permits to detect motions ranging from a fraction of a pixel to a few pixels per frame. Good results, even on noisy sequences and without the need of a filtering pre-processing stage, can be achieved. The intrinsic method structure can be exploited for favourable implementation on multi-processor systems with a scalable degree of parallelism. Several sequences, some with noise and presenting various types of motions, have been used for evaluating the performances and the effectiveness of the method. Carmelo Lodato received his Dr. Ing. Degree in Civil Engineering from the University of Palermo, Italy, in 1987. He is Researcher at the High Performance Computing and Networking Institute (ICAR) of the Italian National Research Council (CNR). His current research interests include computer vision, image processing, motion analysis, optimization and stochastic algorithms. Salvatore Lopes received his Dr. Ing. Degree (summa com laude) in Nuclear Engineering from the University of Palermo, Italy, in 1988. He is Researcher at the High Performance Computing and Networking Institute (ICAR) of the Italian National Research Council (CNR). His current research interests include computer vision, image processing, motion analysis, optimization and stochastic algorithms.     

Constraining and summarizing association rules in medical data

Association rules are a data mining technique used to discover frequent patterns in a data set. In this work, association rules are used in the medical domain, where data sets are generally high dimensional and small. The chief disadvantage about mining association rules in a high dimensional data set is the huge number of patterns that are discovered, most of which are irrelevant or redundant. Several constraints are proposed for filtering purposes, since our aim is to discover only significant association rules and accelerate the search process. A greedy algorithm is introduced to compute rule covers in order to summarize rules having the same consequent. The significance of association rules is evaluated using three metrics: support, confidence and lift. Experiments focus on discovering association rules on a real data set to predict absence or existence of heart disease. Constraints are shown to significantly reduce the number of discovered rules and improve running time. Rule covers summarize a large number of rules by producing a succinct set of rules with high-quality metrics. Carlos Ordonez received a degree in applied mathematics (actuarial sciences) and an MS degree in computer science, both from the UNAM University, Mexico, in 1992 and 1996, respectively. He got a PhD degree in computer science from the Georgia Institute of Technology, USA, in 2000. Dr. Ordonez currently works for Teradata (NCR) conducting research on database and data mining technology. He has published more than 20 research articles and holds three patents. Norberto Ezquerra obtained his undergraduate degree in mathematics and physics from the University of South Florida, and his doctoral degree from Florida State University, USA. He is an associate professor at the College of Computing at the Georgia Institute of Technology and an adjunct faculty member in the Emory University School of Medicine. His research interests include computer graphics, computer vision in medicine, AI in medicine, modeling of physically based systems, medical informatics and telemedicine. He is associate editor of the IEEE Transactions on Medical Imaging Journal, and a member of the American Medical Informatics Association and the IEEE Engineering in Medicine Biology Society. Cesar A. Santana received his MD degree in 1984 from the Institute of Medical Science, in Havana, Cuba. In 1988, he finished his residency training in internal medicine, and in 1991, completed a fellowship in nuclear medicine in Havana, Cuba. Dr. Santana received a PhD in nuclear cardiology in 1996 from the Department of Cardiology of the Vall d' Hebron University Hospital in Barcelona, Spain. Dr. Santana is an assistant professor at the Emory University School of Medicine and conducts research in the Radiology Department at the Emory University Hospital.     

Information gathering and searching approaches on the Web

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

Research in moisture transport through one and two-layered porous composites

1 Introduction Moisture transport or general mass transport is a typical phenomenon that widely exists in porous ma- terials such as soil, construction or porous industrial materials. It is always accompanied with heat transfer and also a?ects temperature variation. A good under- standing of the mechanism of moisture transport pro- cesses is very important in various science areas such as soil science and agriculture, construction industry and chemical engineering[1]. For example, a success- f…     

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.     

Oscillation amplitude-controlled resonant accelerometer design using a reference tracking automatic gain control

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project ST·IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the Korea Foundation for International Cooperation of Science & Technology(KICOS) through a grant provided by the Korean Ministry of Education, Science & Technology(MEST) in 2008 (No. K20601000001). Authors also thank to Dr. B.-L. Lee for the help in structure manufacturing. Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, navigation filter, and intelligent vehicle systems. Chang-Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems. Jungkeun Park is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University. Dr. Park received the Ph.D. in Electrical Engineering and Computer Science from the Seoul National University in 2004. His current research interests include embedded real-time systems design, real-time operating systems, distributed embedded real-time systems and multimedia systems. Joon Goo Park is an Assistant Professor of the Department of Electronic Engineering at Gyung Book National University, Korea. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2001. His research interests include mobile navigation and adaptive control.     

Agent-based Drivers’ Information Assistance System

“Drivers’ Information Assistance System (DIA system)” is an ITS (Intelligent Transport Systems) application framework that provides agent-based information assistance to drivers through car navigation systems or on-board PCs. DIA system enables flexible information retrieval over the Internet using intelligent mobile agent, and incorporates a high-speed event delivery facility that makes real-time information service possible. The goal of the system is to provide up to the minute information and services related to driver needs, such as parking lot vacancy information. Crucial to making this a practical operation is the agent-based ability to access the network while the vehicle is in motion. Masanori Hattori: He is a research engineer in the Computer & Network Systems Laboratory, Corporate Research & Development Center, Toshiba Corporation. His research interests are network computing, human interface, and agent technologies especially in mobile agents, intelligent agents, and physical agents. He received the B.E. and M.E. from the Kyushu University. Naoki Kase: He received the M.S. in computer science from the Keio University, Japan. His research interests are mobile agent and its applications. He has developed an intelligent mobile agent system and its applications on ITS (Intelligent Transport Systems) field. Akihiko Ohsuga, Dr. Eng.: He is a senior research scientist at the Computer & Network Systems Laboratory in Toshiba Corporation. Dr. Ohsuga received a B.S. degree in mathematics from Sophia University in 1981 and a Dr. Eng. degree in electrical engineering from Waseda University in 1995. He joined Toshiba Corporation in 1981, worked with the ICOT (institute for New Generation Computer Technology) involved in the Fifth Generation Computer System project from 1985 to 1989. His research interests include agent technologies, formal specification & verification, and automated theorem proving. Shinichi Honiden, Dr.Eng.: He is a chief specialist of Government Division, Toshiba Corporation. He received the B.S., M.S., and Dr. Eng. degrees in electrical engineering from Waseda University, Tokyo, Japan, in 1976, 1978, and 1986, respectively. Since 1978, he has been with Toshiba Corporation. His research interests include software engineering and artificial intelligence. In these fields, he is the author or coauthor of ten textbooks and has published over 80 technical papers.     

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

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

A Semantic Web data retrieval implementation with an adaptive model for supporting agent decision structures

This paper proposes an adaptive learning approach that yields decision models that can be applied by a transactions agent. This model can learn effectively with a variety of data distributions. This research uses the Semantic Web as a data access approach. The Semantic Web is a method that sellers can use to publish semantically meaningful information on Websites so automated applications can reliably access that information. We implemented a Semantic Web composed of 30 vendors’ Web pages and a spider to search those pages to obtain product and vendor information. This information was used to train a learning agent, which then provided a decision model to a transaction agent. James Hansen is J. Owen Cherrington Professor in the Information Systems Department of the Marriott School of Management at Brigham Young University. He is an associate editor for IEEE Intelligent Systems and Information Systems Frontiers. His research is in machine learning and planning as model checking. James B. McDonald is Professor of Economics at Brigham Young University. His research interests are in econometrics and quantitative methods. He has recently published in Econometrica, Journal of the American Statistical Association, Management Science, and Journal of Business Conan C. Albrecht is a professor of Information Systems at Brigham Young University. He teaches classes in enterprise development, middleware, and business programming. Conan researches computer-based fraud detection techniques, ecommerce platforms, and online group dynamics. He has published articles on fraud detection and information theory in The Journal of Forensic Accounting, The Journal of Accounting, The Communications of the ACM, Decision Support Systems, Information and Management, and other academic and professional outlets. Conan is currently working on an open source framework for computer-based fraud detection. The core of this research is detectlets, which encode background and detection information for specific fraud schemes. He is researching with the United Nations and the World Bank to use detectlets to prevent and detect fraud in third world countries. In the next few years, he hopes the system will serve as the foundation of a large, online repository of detectlets about all types of fraud. Douglas L. Dean is an Associate Professor at the Marriott School of Management at Brigham Young University. He is also research coordinator for the Rollins Center for E-business. He received his Ph.D. in MIS from the University of Arizona in 1995. Dr. Dean’s research interests include electronic commerce technology and strategy, online communities, requirements analysis, and collaborative tools and methods. His work has been published in Management Science, Journal of Management Information Systems, Information and Management, The DATA BASE for Advances in Information Systems, Communications of the AIS, Expert Systems with Applications, Group Decision and Negotiation, and IEEE Transactions on Systems, Man, and Cybernetics. Bonnie Brinton Anderson is the LeAnn Albrecht Fellow and an Assistant Professor in the Information Systems Department of the Marriott School at Brigham Young University (Provo, UT). She received her Ph.D. from Carnegie Mellon University. Dr. Anderson has published in Decision Support Systems; IEEE Transactions on Systems, Man, and Cybernetics; Communications of the ACM; Journal of Accountancy, among others. She researches in the areas of knowledge management, information systems security, and intelligent agents.