A Framework for the Generation of Adaptive Courses Based on Semantic Metadata

This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model.John Freddy Duitama received his M.Sc. degree in system engineering from the University of Antioquia -Colombia (South America). He is currently a doctoral candidate in the GET – Institut National des Télécommunications, Evry France. This work is sponsored by the University of Antioquia, where he is assistant professor.His research interest includes semantic web and web-based learning systems, educational metadata and learning objects.Bruno Defude received his Ph.D. in Computer Science from the University of Grenoble (I.N.P.G) in 1986. He is currently Professor in the Department of Computer Science at the GET - Institut National des Télécommunications, Evry France where he leads the SIMBAD project (Semantic Interoperability for MoBile and ADaptive applications).His major field of research interest is databases and semantic web, specifically personalized data access, adaptive systems, metadata, interoperability and semantic Peer-to-peer systems with elearning as a privileged application area.He is a member of ACM SIGMOD.Amel Bouzeghoub received a degree of Ph.D. in Computer Sciences at Pierre et Marie Curie University, France.In 2000, she joined the Computer Sciences Department of GET-INT (Institut National des Telecommunications) at Evry (France) as an associate professor.Her research interests include topics related to Web-based Learning Systems, Semantic Metadata for learning resources, Adaptive Learning Systems and Intelligent Tutoring Systems.Claire Lecocq received an Engineer Degree and a Ph.D. in Computer Sciences respectively in 1994 and 1999. In 1997, she joined the Computer Sciences Department at GET-INT (Institut National des Télécommunications) of Evry, France, as an associate professor. Her first research interests included spatial databases and visual query languages. She is now working on adaptive learning systems, particularly on semantic metadata and user models.     

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     

STAMP: A Model for Generating Adaptable Multimedia Presentations

The STAMP model addresses the dynamic generation of multimedia presentations in the domain of Multimedia Web-based Information Systems. STAMP allows the presentation of multimedia data obtained from XML compatible data sources by means of query. Assuming that the size and the nature of the elements of information provided by a data source is not known a priori, STAMP proposes templates which describe the spatial, temporal, navigational structuration of multimedia presentations whose content varies. The instantiation of a template is done with respect to the set of spatial and temporal constraints associated with the delivery context. A set of adaptations preserving the initial intention of the presentation is proposed.Ioan Marius Bilasco is a Ph.D. student at the University Joseph Fourier in Grenoble, France, since 2003. He received his BS degree in Computer Science form the University Babes Bolyai in Cluj-Napoca, Romania and his MS degree in Computer Science from the University Joseph Fourier in Grenoble, France. He joined the LSR-IMAG Laboratory in Grenoble in 2001. His research interests include adaptability in Web-based Information Systems, 3D multimedia data modelling and mobile communications.Jérôme Gensel is an Assistant Professor at the University Pierre Mendès France in Grenoble, France, since 1996. He received his Ph.D. in 1995 from the University of Grenoble for his work on Constraint Programming and Knowledge Representation in the Sherpa project at the French National Institute of Computer Sciences and Automatics (INRIA). He joined the LSR-IMAG Laboratory in Grenoble in 2001. His research interests include adaptability and cooperation in Web-based Information Systems, multimedia data (especially video) modeling, semi-structured and object-based knowledge representation and constraint programming.Marlène Villanova-Oliver is an Assistant Professor at the University Pierre Mendès France in Grenoble, France, since 2003. In 1999, she received her MS degree in Computer Science from the University Joseph Fourier of Grenoble and the European Diploma of 3rd cycle in Management and Technology of Information Systems (MATIS). She received her Ph.D. in 2002 from the National Polytechnic Institute of Grenoble (INPG). She is a member of the LSR-IMAG Laboratory in Grenoble since 1998. Her research interests include adaptability in Web-based Information Systems, user modeling, adaptable Web Services.     

Behavior of the Laplacian of Gaussian Extrema

This paper analyses the behavior in scale space of linear junction models (L, Y and X models), nonlinear junction models, and linear junction multi-models. The variation of the grey level is considered to be constant, linear or nonlinear in the case of linear models and constant for the other models. We are mainly interested in the extrema points provided by the Laplacian of the Gaussian function. Moreover, we show that for infinite models the Laplacian of the Gaussian at the corner point is not always equal to zero.Salvatore Tabbone received his Ph.D. in computer science from the Institut National Polytechnique de Lorraine (France) in 1994. He is currently an assistant professor at the University of Nancy2 (France) and a member of the QGAR research project on graphics recognition at the LORIA-INRIA research center. His research interests include computer vision, pattern recognition, content-based image retrieval, and document analysis and recognition.Laurent Alonso was a student of ENS Ulm from 1987 to 1991, he received the Ph.D. degree in Computer Science from the University of Paris XI, Orsay, France in 1992. From 1991 to 1995 he served as lecturer in the University of Nancy I (France). Actually, he is full researcher in INRIA (France). His research interests include realistic rendering, geometric algorithms and combinatorics.Djemel Ziou received the BEng Degree in Computer Science from the University of Annaba (Algeria) in 1984, and Ph.D. degree in Computer Science from the Institut National Polytechnique de Lorraine (INPL), France in 1991. From 1987 to 1993 he served as lecturer in several universities in France. During the same period, he was a researcher in the Centre de Recherche en Informatique de Nancy (CRIN) and the Institut National de Recherche en Informatique et Automatique (INRIA) in France. Presently, he is full Professor at the department of computer science at the University of Sherbrooke in Canada. He has served on numerous conference committees as member or chair. He heads the laboratory MOIVRE and the consortium CoRIMedia which he founded. His research interests include image processing, information retrieval, computer vision and pattern recognition.     

Towards the construction of distributed detection programs,with an application to distributed termination

Summary Methodological design of distributed programs is necessary if one is to master the complexity of parallelism. The class of control programs, whose purpose is to observe or detect properties of an underlying program, plays an important role in distributed computing. The detection of a property generally rests upon consistent evaluations of a predicate; such a predicate can be global, i.e. involve states of several processes and channels of the observed program. Unfortunately, in a distributed system, the consistency of an evaluation cannot be trivially obtained. This is a central problem in distributed evaluations. This paper addresses the problem of distributed evaluation, used as a basic tool for solution of general distributed detection problems. A new evaluation paradigm is put forward, and a general distributed detection program is designed, introducing the iterative scheme ofguarded waves sequence. The case of distributed termination detection is then taken to illustrate the proposed methodological design. Jean-Michel Hélary is currently professor of Computer Science at the University of Rennes, France. He received a first Ph.D. degree in Numerical Analysis in 1968, then another Ph.D. Degree in Computer Science in 1988. His research interests include distributed algorithms and protocols, specially the methodological aspects. He is a member of an INRIA research group working at IRISA (Rennes) on distributed algorithms and applications. Professor Jean-Michel Hélary has published several papers on these subjects, and is co-author of a book with Michel Raynal. He serves as a PC member in an international conference. Michel Raynal is currently professor of Computer Science at the University of Rennes, France. He received the Ph.D. degree in 1981. His research interests include distributed algorithms, operating systems, protocols and parallelism. He is the head of an INRIA research group working at IRISA (Rennes) on distributed algorithms and applications. Professor Michel Raynal has organized several international conferences and has served as a PC member in many international workshops, conferences and symposia. Over the past 9 years, he has written 7 books that constitute an introduction to distributed algorithms and distributed systems (among them: Algorithms for Mutual Exclusion, the MIT Press, 1986, and Synchronization and Control of Distributed Programs, Wiley, 1990, co-authored with J.M. Hélary). He is currently involved in two european Esprit projects devoted to large scale distributed systems.This work was supported by French Research Program C³ on Parallelism and Distributed ComputingAn extended abstract has been presented to ISTCS '92 [12]     

The CPR Model for Summarizing Video

Most past work on video summarization has been based on selecting key frames from videos. We propose a model of video summarization based on three important parameters: Priority (of frames), Continuity (of the summary), and non-Repetition (of the summary). In short, a summary must include high priority frames and must be continuous and non-repetitive. An optimal summary is one that maximizes an objective function based on these three parameters. We show examples of how CPR parameters can be computed and provide algorithms to find optimal summaries based on the CPR approach. Finally, we briefly report on the performance of these algorithms.Marat Fayzullin has received his PhD degree in Computer Science from the University of Maryland, College Park, in 2004. He has done research in Distributed Simulation Environments, Multimedia Database Algebras, and Automated Content Summarization. His topics of interest also include Mobile Agent Networks and Reasoning with Semantic Networks.V.S. Subrahmanian received his Ph.D. in Computer Science from Syracuse University in 1989. Since then, he has been on the faculty of the Computer Science Department at the University of Maryland, College Park, where he currently holds the rank of Professor. He also serves as Director of the University of Marylands Institute for Advanced Computer Studies (UMIACS) established by the State of Maryland in the mid-1980s to pursue interdisciplinary research involving IT. He received the NSF Young Investigator Award in 1993 and the Distinguished Young Scientist Award from the Maryland Academy of Science/Maryland Science Center in 1997. Prof. Subrahmanian is recognized for his work on nonmonotonic and probabilistic logics, inconsistency management in databases, database models views and inference, rule bases, heterogeneous databases, multimedia databases, and probabilistic databases. More recently, he has developed techniques to agentize legacy software, allowing multiple software modules to dynamically collaborate with each other to solve complex problems. He has edited two books, one on nonmonotonic reasoning (MIT Press) and one on multimedia databases (Springer). He has co-authored an advanced database textbook (Morgan Kaufman, 1997) and a book on heterogeneous software agents. He is the sole author of the best known textbook on multimedia databases (Morgan Kaufmann)—a second edition of this book is under preparation. Prof. Subrahmanian has given invited talks at numerous national and international conferences—in addition, he has served on numerous conference and funding panels, as well as on the program committees of numerous conferences. He has also chaired several conferences. Prof. Subrahmanian is or has previously been on the editorial board of IEEE Transactions on Knowledge and Data Engineering, Artificial Intelligence Communications, Multimedia Tools and Applications, Journal of Logic Programming, Annals of Mathematics and Artificial Intelligence, Distributed and Parallel Database Journal, and Theory and Practice of Logic Programming.Prof. Subrahmanian has served on DARPAs (Defense Advanced Research Projects Agency) Executive Advisory Council on Advanced Logistics and as an ad-hoc member of the US Air Force Science Advisory Board (2001).Antonio Picariello received the Laurea degree in Electronics Engineering from the University of Napoli, Italy, in 1991. In 1993 he joined the Istituto Ricerca Sui Sistimi Informatici Paralleli, The National Research Council, Napoli, Italy. He received a Ph.D. degree in Computer Science and Engineering in 1998 from the University of Naples Federico II. In 1999, he joined the Dipartimento di Informatica e Sistemistica, University of Napoli Federico II, Italy, and is currently an Associate Professor of Data Base. He has been active in the field of Computer Vision, Medical Image Processing and Pattern Recognition, Object-Oriented models for image processing, Multimedia Data Base and Information Retrieval. His current research interests lie in Knowledge Extraction and Management, Multimedia Integration and Image and Video databases. He is a member of the International Association of Pattern Recognition.Maria Luisa Sapino has got her master degree and Ph.D. in Computer Science at the University of Torino, where shes currently Associate Professor. She initially worked in the area of logic programming and artificial intelligence, specifically interested in the semantics of negation in logic programming, and in the abductive extensions of logic programs. Her current research interests include heterogeneous and multimedia databases, in particular similarity based information retrieval, and modeling and querying multimedia presentations. She has been serving as a reviewer for several international conferences and journals.     

Radio-Triggered Wake-Up for Wireless Sensor Networks

Power management is an important technique to prolong the lifespan of sensor networks. Many power management protocols employ wake-up/sleep schedules, which are often complicated and inefficient. We present power management schemes that eliminate such wake-up periods unless the node indeed needs to wake up. This type of wake-up capability is enabled by a new radio-triggered hardware component inspired by the observation that the wake-up radio signal contains enough energy to trigger a wake-up process. We evaluate the potential power saving in terms of the lifespan of a sensor network application, using experimental data and SPICE circuit simulations. Comparing the result with always-on and rotation-based power management schemes, we find the radio-triggered scheme saves 98% of the energy used in the always-on scheme, and saves over 70% of the energy used in the rotation-based scheme. Consequently, the lifespan increases from 3.3 days (always-on) or 49.5 days (rotation-based) to 178 days (radio-triggered). Furthermore, a store-energy technique can extend operating distance from 10 feet to 22 feet, or even longer if longer latency is acceptable. Wake-up efficiency is evaluated in NS-2 simulations, which show that radio-triggered wake-up has fewer failures, shorter latency, and consistently larger sensing laxity than rotation based wake-up. We also present amplification and radio-triggered IDs which can further enhance performance.Lin Gu is a Ph.D. student at University of Virginia. His current research area is in wireless sensor networks, focusing on OS kernel services and energy efficient hardware and architecture support. Before joining to UVa, he got M.S. degree from Peking University and B.S. in Computer Science from Fudan University.John A. Stankovic is the BP America Professor in the Computer Science Department at the University of Virginia. He recently served as Chair of the department, completing two terms. He is a Fellow of both the IEEE and the ACM. He also won the IEEE Real-Time Systems Technical Committees Award for Outstanding Technical Contributions and Leadership. Professor Stankovic also serves on the Board of Directors of the Computer Research Association. Before joining the University of Virginia, Professor Stankovic taught at the University of Massachusetts where he won an outstanding scholar award. He has also held visiting positions in the Computer Science Departmentat Carnegie-Mellon University, at INRIA in France, and Scuola Superiore S. Anna in Pisa, Italy. He was the Editor-in-Chief for the IEEE Transactions on Distributed and Parallel Systems and is a co-editor-in-chief for the Real-Time Systems Journal. His research interests are in distributed computing, real-time systems, operating systems, and wireless sensor networks. Prof. Stankovic received his Ph.D. from Brown University.     

Naming symmetric processes using shared variables

Summary Implementations of inter-process communication and synchronization in distributed systems usually rely on the existence of unique ids for the processes. We consider the problem of generating such ids for identical processes in a shared-variable system. A randomized protocol that assigns distinct ids to the processes within an expected polynomial number of rounds using a polynomial number of boolean atomic variables is presented. Ömer Eeciolu obtained his Ph.D. degree in mathematics from the University of California, San Diego in 1984. At present he is an Associate Professor in the Computer Science department of the University of California, Santa Barbara, where he has been on the faculty since 1985. His principal areas of research are parallel algorithms, bijective and enumerative combinatorics, and combinatorial algorithms. His current interest in parallel algorithms involve approximation and numerical techniques on distributed memory systems while his combinatorial interests center around computational geometry, bijective methods, and ranking algorithms for combinatorial structures. Ambuj K. Singh is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara. He received a Ph.D. in Computer Science from the University of Texas at Austin in 1989, an M.S. in Computer Science from Iowa State University in 1984, and a B. Tech. from the Indian Institute of Technology at Kharagpur in 1982. His research interests are in the areas of adaptive resource allocation, concurrent program development, and distributed shared memory.Work supported in part by NSF grants CCR-9008628 and CCR-9223094     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

Global Control of Robotic Highway Safety Markers: A Real-time Solution

This paper presents the design and implementation of a real-time solution for the global control of robotic highway safety markers. Problems addressed in the system are: (1) poor scalability and predictability as the number of markers increases, (2) jerky movement of markers, and (3) misidentification of safety markers caused by objects in the environment.An extensive analysis of the system and two solutions are offered: a basic solution and an enhanced solution. They are built respectively upon two task models: the periodic task model and the variable rate execution (VRE) task model. The former is characterized by four static parameters: phase, period, worst case execution time and relative deadline. The latter has similar parameters, but the parameter values are allowed to change at arbitrary times.The use of real-time tasks and scheduling techniques solve the first two problems. The third problem is solved using a refined Hough transform algorithm and a horizon scanning window. The approach decreases the time complexity of traditional implementations of the Hough transform with only slightly increased storage requirements.Supported, in part, by grants from the National Science Foundation (CCR-0208619 and CNS-0409382) and the National Academy of Sciences Transportation Research Board-NCHRP IDEA Program (Project #90).Jiazheng Shi received the B.E. and M.E. degrees in electrical engineering from Beijing University of Posts and Telecommunications in 1997 and 2000, respectively. In 2000, he worked with the Global Software Group, Motorola Inc. Currently, he is a Ph.D. candidate in the Computer Science and Engineering Department at the University of Nebraska–Lincoln. His research interests are automated human face recognition, image processing, computer vision, approximate theory, and linear system optimization.Steve Goddard is a J.D. Edwards Associate Professor in the Department of Computer Science & Engineering at the University of Nebraska–Lincoln. He received the B.A. degree in computer science and mathematics from the University of Minnesota (1985). He received the M.S. and Ph.D. degrees in computer science from the University of North Carolina at Chapel Hill (1995, 1998).His research interests are embedded, real-time and distributed systems with emphases in high assurance systems engineering and real-time, rate-based scheduling theory.Anagh Lal received a B.S. degree in Computer Science from the University of Mumbai (Bombay), Mumbai, in 2001. He is currently a graduate research assistant at the University of Nebraska–Lincoln working on a M.S. in Computer Science, and a member of the ConSystLab. His research interests lie in Databases, Constraint Processing and Real Time Systems. Anagh will be graduating soon and is looking for positions at research institutions.Jason Dumpert received a B.S. degree in electrical engineering from the University of Nebraska–Lincoln in 2001. He received a M.S. degree in electrical engineering from the University of Nebraska-Lincoln in 2004. He is currently a graduate research assistant at the University of Nebraska-Lincoln working on a Ph.D. in biomedical engineering. His research interests include mobile robotics and surgical robotics.Shane M. Farritor is an Associate Professor in the University of Nebraska–Lincolns Department of Mechanical Engineering. His research interests include space robotics, surgical robotics, biomedical sensors, and robotics for highway safety. He holds courtesy appointments in both the Department of Surgery and the Department of Orthopaedic Surgery at the University of Nebraska Medical Center, Omaha. He serves of both the AIAA Space Robotics and Automation technical committee and ASME Dynamic Systems and Control Robotics Panel. He received M.S. and Ph.D. degrees from M.I.T.     

Distributed election in complete networks

An improved version of Afek and Gafni's synchronous algorithm for distributed election in complete networks is given and anO(n) expected message complexity is shown. M.Y. Chan received her Ph.D. in 1988 from the University of Hong Kong, and her M.S. and B.A. degrees in computer science from the University of California, San Diego in 1980 and 1981, respectively. She is currently an Assistant Professor at the University of Texas at Dallas. Francis Y.L. Chin (S71-M76-SM85) received the B.Sc. degree in engineering science from the University of Toronto, Toronto, Canada, in 1972, and the M.S., M.A., and Ph.D. degrees in electrical engineering and computer science from Princeton University, New Jersey, in 1974, 1975, and 1976, respectively. Since 1975, he has taught at the University of Maryland, Baltimore Country, University of California, San Diego, University of Alberta, and Chinese University of Hong Kong. He is currently Head of the Department of Computer Science, University of Hong Kong. He has served as a program co-chairman of the 1988 International Conference on Computer Processing of Chinese and Oriental Languages (Toronto) and the International Computer Science Conference '88 (Hong Kong). His current research interests include algorithm design and analysis, parallel and distributed computing.     

A new method for implementing moment functions in a CMOS retina

We present in this paper a new method for implementing geometric moment functions in a CMOS retina. The principle is based on the similarity between geometric moment equations and the measurement of the correlation value between an image to analyze and a range of grey levels. The latter is approximated by a binary image called mask using a dithering algorithm in order to reduce hardware implementation cost. The correlation product between the mask and the image under analysis gives an approximated value of the geometric moment with an error less than 1% of the exact value. Finally, the results obtained by our approach have been applied to an object localization application and the localization error due to the approximated moment values reported. Olivier Aubreton was born in Vichy on August 31, 1973. He obtained the agrégation examination in June 2000 and received the D.E.A. degree (equivalent to a master degree) in image processing in June 2001. He is currently a lecturer working towards a Ph. D. degree at Laboratory LE2I in the IUT of Le Creusot in Burgundy. His research interests include the design, development implementation, and testing of silicon retinas for pattern matching and pattern recognition. Lew F.C. Lew Yan Voon received his Ph.D. degree in Computer Aided Design of VLSI circuits from Montpellier University, France, in March 1992. Since September 1993, he has been first assistant professor and then associate professor at the University of Burgundy. His research interests lie in the field of pattern recognition and in the design of silicon retinas in standard CMOS technology for real-time inspection by machine vision. Bernard Lamalle was born in Autun on May 1, 1946. He obtained the Ph.D. degree in 1973 from the Université de Bourgogne in Dijon. During 1980 to 2000 he has been Maître de conférences at the IUT of Le Creusot in Bourgogne. He joined the image processing team of laboratory Le2i in 1992. Since 2000, he has been appointed full professor of the University of Bourgogne. His field of interest is principally the study and design of silicon retinas dedicated to industrial control. He has in charge some industrial contracts in the field of quality control by artificial vision and he holds two patents in the field of image processing and smart sensors. Guy Cathébras was born in Uzès, France, in 1961. He received the French engineer degree from the Ecole Nationale Supérieure de l'Electronique et de ses Applications, Cergy, France, in 1984 and the Diplôme de Doctorat de l'Université de Montpellier, France, in 1990. Since 1992 he is an assistant professor of microelectronics at the Institut des Sciences de l'Ingénieur de Montpellier. His current research interests include the design of imagers and silicon retinas using standard CMOS technologies.     

Efficient emulation of single-hop radio network with collision detection on multi-hop radio network with no collision detection

Summary This paper presents an efficient randomized emulation ofsingle-hop radio networkwith collision detection onmulti-hop radio networkwithout collision detection. Each step of the single-hop network is emulated by rounds of the multi-hop network and succeeds with probability 1–. (n is the number of processors,D the diameter and the maximum degree). It is shown how to emulate any polynomial algorithm such that the probability of failure remains . A consequence of the emulation is an efficient randomized algorithm for choosing a leader in a multi-hop network. Reuven Bar-Yehuda was born in Iran, on July 17th 1951. Received B.A., M.Sc., and D.Sc. in Computer Science from the Technion — Israel Institute of Technology, Haifa, Israel, in 1978, 1980, and 1983, respectively. He is currently a Senior Lecturer of Computer Science at the Technion. From 1984 to 1986, he was a visiting assistant professor in the Computer Science Dept. at the Duke Univesity His research interests include computational geometry, VLSI, graph algorithms and distributed algorithms. Oded Goldreich was born in Tel-Aviv, Israel, on February 4th 1957. Received B.A., M.Sc., and D.Sc. in Computer Science from the Technion — Israel Institute of Technology, Haifa, Israel, in 1980, 1982, and 1983, respectively. He is currently an Associate Professor of Computer Science at the Technion. From 1983 to 1986, he was a postdoctoral fellow at MIT's Laboratory for Computer Science. His research interests include cryptography and related areas, relation between randomness and algorithms, and distributed computation. Alon Itai was born in Scotland, on December 12th 1946. Received B.Sc. in Mathematics from the Hebrew University in Jerusalem in 1969. M.Sc., and Ph.D. in Computer Science from the Weizmann Institute of Science, Rehovot, Israel in 1971 and 1976. He is currently an Associate Professor of Computer Science at the Technion. His research interests include randomized and distributed algorithms, computational learning theory and performance evaluation.The second author was partially supported by grant No. 86-00301 from the United States—Israel Bi-national Science Foundation BSF), Jerusalem, Israel.     

Segmentation of stick text based on sub connected area analysis

A new stick text segmentation method based on the sub connected area analysis is introduced in this paper.The foundation of this method is the sub connected area representation of text image that can represent all connected areas in an image efficiently.This method consists mainly of four steps:sub connected area classification,finding initial boundary following point,finding optimal segmentation point by boundary tracing,and text segmentaton.This method is similar to boundary analysis method but is more efficient than boundary analysis.     

Block cipher based on reversible cellular automata

We propose a new encryption algorithm relying on reversible cellular automata (CA). The behavior complexity of CA and their parallel nature makes them interesting candidates for cryptography. The proposed algorithm belongs to the class of symmetric key systems. Marcin Seredynski: He is a Ph.D. student at University of Luxembourg and Polish Academy of Sciences. He received his M.S. in 2004 from Faculty of Electronics and Information Technology in Warsaw University of Technology. His research interests include cryptography, cellular automata, nature inspired algorithms and network security. Currently he is working on intrusion detection algorithms for ad-hoc networks. Pascal Bouvry, Ph.D.: He earned his undergraduate degree in Economical & Social Sciences and his Master degree in Computer Science with distinction (’91) from the University of Namur, Belgium. He went on to obtain his Ph.D. degree (’94) in Computer Science with great distinction at the University of Grenoble (INPG), France. His research at the IMAG laboratory focussed on Mapping and scheduling task graphs onto Distributed Memory Parallel Computers. Next, he performed post-doctoral researches on coordination languages and multi-agent evolutionary computing at CWI in Amsterdam. He gained industrial experience as manager of the technology consultant team for FICS in the banking sector (Brussels, Belgium). Next, he worked as CEO and CTO of SDC (Ho Chi Minh city, Vietnam) in the telecom, semi-conductor and space industry. After that, He moved to Montreal Canada as VP Production of Lat45 and Development Director for MetaSolv Software in the telecom industry. He is currently serving as Professor in the group of Computer Science and Communications (CSC) of the Faculty of Sciences, Technology and Communications of Luxembourg University and he is heading the Intelligent & Adaptive Systems lab. His current research interests include: ad-hoc networks & grid-computing, evolutionary algorithms and multi-agent systems.     

CCMPerf: A Benchmarking Tool for CORBA Component Model Implementations

Commercial off-the-shelf (COTS) middleware is now widely used to develop distributed real-time and embedded (DRE) systems. DRE systems are themselves increasingly combined to form systems of systems that have diverse quality of service (QoS) requirements. Earlier generations of COTS middleware, such as Object Request Brokers (ORBs) based on the CORBA 2.x standard, did not facilitate the separation of QoS policies from application functionality, which made it hard to configure and validate complex DRE applications. The new generation of component middleware, such as the CORBA Component Model (CCM) based on the CORBA 3.0 standard, addresses the limitations of earlier generation middleware by establishing standards for implementing, packaging, assembling, and deploying component implementations.There has been little systematic empirical study of the performance characteristics of component middleware implementations in the context of DRE systems. This paper therefore provides four contributions to the study of CCM for DRE systems. First, we describe the challenges involved in benchmarking different CCM implementations. Second, we describe key criteria for comparing different CCM implementations using key black-box and white-box metrics. Third, we describe the design of our CCMPerf benchmarking suite to illustrate test categories that evaluate aspects of CCM implementation to determine their suitability for the DRE domain. Fourth, we use CCMPerf to benchmark CIAO implementation of CCM and analyze the results. These results show that the CIAO implementation based on the more sophisticated CORBA 3.0 standard has comparable DRE performance to that of the TAO implementation based on the earlier CORBA 2.x standard.Arvind S. Krishna is a PhD student in the Electrical Engineering and Computer Science Department at Vanderbilt University and a member of the Institute for Software Integrated Systems. He received his MA in management from the Brila Institute for Technology and Science (BITS), Pilani, India and his MS in computer science from University of California, Irvine. His research interests include patterns, real-time Java technologies for Real-Time Corba, model-integrated QA techniques, and tools for partial evaluation and specialization of middleware. He is a student member of the IEEE and ACM. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Balachandran Natarajan is a senior staff engineer at the Institute for Software Integrated Systems and a PhD student in electrical engineering and computer science at Vanderbilt University. His research focuses on applying patterns, optimization principles, and frameworks to build high-performance, dependable, and real-time distributed systems. He received his MS in computer science from Washington University. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Aniruddha Gokhale is an assistant professor in the Electrical Engineering and Computer Science Department at Vanderbilt University and a senior research scientist at the Institute for Software Integrated Systems. His research focuses on real-time component middleware optimizations, distributed systems and networks, model-driven software synthesis applied to component middleware-based distributed systems, and distributed resource management. He received his PhD in computer science from Washington University. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Douglas C. Schmidt is a professor in the Electrical Engineering and Computer Science Department at Vanderbilt University and a senior research scientist at the Institute for Software Integrated Systems. His research interests include patterns, optimization techniques, and empirical analyses of software frameworks and domain-specific modeling environments that facilitate the development of distributed real-time and embedded middleware and applications running over high-speed networks and embedded system interconnects. He received his PhD in information and computer science at the University of California, Irvine. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Nanbor Wang is a Research Scientist in the Distributed Technologies Group at the Tech-X Corporation in Boulder, Colorado. He received M.S. and Ph.D. degrees in Computer Science from Washington University in St. Louis, Missouri. While working for his degree, he also worked as a Research Associate in the Center of Distributed Object Computing in the Department of Computer Science where he conducted research on design, implementation and analysis of object-oriented and component-based techniques for development of distributed systems and management of extra-functional concerns. Dr. Wangs work currently focuses on developing and applying middleware techniques, such as CORBA and Grid Computing, for enabling distributed and parallel scientific applications, such as, distributed data analysis, remote visualization and collaboration, and, work-flow management for large-scale scientific applications.Gautam H. Thaker was born in Amdavad, India, in 1955. He holds a BSEE (75) and MSEE (77) from Clemson University, Clemson, SC. He spent the 85-86 academic year at M.I.T. as a visiting researcher. His research interests include analysis, design, construction and validation of real-time, command and control systems. In particular he has focused on interactions between operating systems, networking protocols, and middleware technologies.     

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

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

Privacy-preserving SVM classification

Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. What is required is distributed knowledge discovery that is sensitive to this problem. The key is to obtain valid results, while providing guarantees on the nondisclosure of data. Support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. It is based on solid theoretical foundations and has wide practical application. This paper proposes a privacy-preserving solution for support vector machine (SVM) classification, PP-SVM for short. Our solution constructs the global SVM classification model from data distributed at multiple parties, without disclosing the data of each party to others. Solutions are sketched out for data that is vertically, horizontally, or even arbitrarily partitioned. We quantify the security and efficiency of the proposed method, and highlight future challenges. Jaideep Vaidya received the Bachelor’s degree in Computer Engineering from the University of Mumbai. He received the Master’s and the Ph.D. degrees in Computer Science from Purdue University. He is an Assistant Professor in the Management Science and Information Systems Department at Rutgers University. His research interests include data mining and analysis, information security, and privacy. He has received best paper awards for papers in ICDE and SIDKDD. He is a Member of the IEEE Computer Society and the ACM. Hwanjo Yu received the Ph.D. degree in Computer Science in 2004 from the University of Illinois at Urbana-Champaign. He is an Assistant Professor in the Department of Computer Science at the University of Iowa. His research interests include data mining, machine learning, database, and information systems. He is an Associate Editor of Neurocomputing and served on the NSF Panel in 2006. He has served on the program committees of 2005 ACM SAC on Data Mining track, 2005 and 2006 IEEE ICDM, 2006 ACM CIKM, and 2006 SIAM Data Mining. Xiaoqian Jiang received the B.S. degree in Computer Science from Shanghai Maritime University, Shanghai, 2003. He received the M.C.S. degree in Computer Science from the University of Iowa, Iowa City, 2005. Currently, he is pursuing a Ph.D. degree from the School of Computer Science, Carnegie Mellon University. His research interests are computer vision, machine learning, data mining, and privacy protection technologies.     

Using visual and text features for direct marketing on multimedia messaging services domain

Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.