Looking briefly back, and then forward...

Pradip Bose recalls economic and technical changes in the hardware sector of the computer industry over his four years as Editor in Chief of IEEE Micro. As he took office in 2003, the frequency wars characteristic of single-core processor designs had barely started giving way to a new trend of multicore chips, now firmly established. Bose looks ahead to challenges brought by multicore chips and anticipates the proliferation of a wide variety of ultra-power-efficient, high-performance processor chips that cater to specialized markets: Finally, Bose introduces IEEE Micro's new Editor in Chief, David Albonesi.     

From the Editor in Chief: Welcome A-Board

IEEE Micro Editor in Chief David H. Albonesi welcomes six new emmbers to teh IEEE Micro Editorial Board and previews this general interest issue.     

Intelligent Systems in a Connected World

Incoming IEEE Intelligent Systems Editor in Chief Fei-Yue Wang thanks Editor in Chief Emeritus Jim Hendler for his service to the magazine and welcomes Hsinchun Chen director of the Artificial Intelligence Lab at the University of Arizona to the editorial staff. As the new editor in chief, Wang outlines his vision to make IS the Science of AI, following in the footsteps of Hendler's vision to make the magazine the Nature of AI. He also discusses the need to recruit young, up and coming researching to the magazine's editorial staff and plans to add interesting new departments such as one on Cyber-Physical Systems. Wang also wants to follow through on promoting the magazine in China, Japan, and Korea.     

Agents Redux

Editor in Chief James Hendler comments on responses he received about his essay "Where Are All the Intelligent Agents?" in the May/June issue.     

Grasping the Torch

New Editor in Chief Roy Want, "grasping the torch" Mahadev Satyanarayanan handed to him, outlines the magazine's mission, offers a taste of things to come, and reveals his resolutions.     

The Seeds of Inspiration

What are some of the seeds of inspiration for pervasive computing research? For Editor in Chief Roy Want, it's his fascination with gadgets, tendency to shop for electronic odds and ends, and interest in turning fictional devices into reality—all of which relate to hacking, the topic of this special issue.     

El Tour de Verano

Editor in Chief Fei-Yue Wang describes his astonishingly full summer tour of intelligent-systems-related conferences, panels, meetings, and lectures, which took him numerous times across the Pacific Ocean—to locations in China, Singapore, India, Canada, and the US.     

Building from a Solid Foundation

With a sharper focus on serving problem solvers, IT Pro enters its eighth year with a reaffirmed pledge to offer an eclectic mix of solid information. In his introductory letter, new Editor in Chief Arnold Bragg shares some recent findings from an October 2005 subscriber survey and outlines the magazine’s upcoming topics, themes, and threads.     

DH-26 HANDHELD ENCRYPTION MACHINE

In 1915 First Lt. Joseph O. Maubourgne, later MG Maugorne and Chief Signal Officer, 1937–1941, presents a simple substitution cipher challenge to the Army Signal School. He proposes a test to determine if his new cryptosystem should replace the Cipher Disk and Playfair Cipher then in use.     

The Challenge of Finding Intelligent Agents

In the last issue, Editor in Chief James Hendler asked, "Where are all the intelligent agents?" Here, several readers offer answers.     

An Introduction to High-Level Synthesis

Editor's note:High-level synthesis raises the design abstraction level and allows rapid generation of optimized RTL hardware for performance, area, and power requirements. This article gives an overview of state-of-the-art HLS techniques and tools.—Tim Cheng, Editor in Chief     

Mining frequent patterns with the pattern tree

Mining frequent patterns with a frequent pattern tree (FP-tree in short) avoids costly candidate generation and repeatedly occurrence frequency checking against the support threshold. It therefore achieves much better performance and efficiency than Apriori-like algorithms. However, the database still needs to be scanned twice to get the FP-tree. This can be very time-consuming when new data is added to an existing database because two scans may be needed for not only the new data but also the existing data. In this research we propose a new data structure, the pattern tree (P-tree in short), and a new technique, which can get the P-tree through only one scan of the database and can obtain the corresponding FP-tree with a specified support threshold. Updating a P-tree with new data needs one scan of the new data only, and the existing data does not need to be re-scanned. Our experiments show that the P-tree method outperforms the FP-tree method by a factor up to an order of magnitude in large datasets. A preliminary version of this paper has been published in theProceedings of the 2002 IEEE International Conference on Data Mining (ICDM ’02), 629–632. Hao Huang: He is pursuing his Ph.D. degree in the Department of Computer Science at the University of Virginia. His research interests are Gird Computing, Data Mining and their applications in Bioinformatics. He received his M.S. in Computer Science from Colorado School of Mines in 2001. Xindong Wu, Ph.D.: He is Professor and Chair of the Department of Computer Science at the University of Vermont, USA. He holds a Ph.D. in Artificial Intelligence from the University of Edinburgh, Britain. His research interests include data mining, knowledge-based systems, and Web information exploration. He has published extensively in these areas in various journals and conferences, including IEEE TKDE, TPAMI, ACM TOIS, IJCAI, AAAI, ICML, KDD, ICDM, and WWW. Dr. Wu is the Executive Editor (January 1, 1999-December 31, 2004) and an Honorary Editor-in-Chief (starting January 1, 2005) of Knowledge and Information Systems (a peer-reviewed archival journal published by Springer), the founder and current Steering Committee Chair of the IEEE International Conference on Data Mining (ICDM), a Series Editor of the Springer Book Series on Advanced Information and Knowledge Processing (AI&KP), and the Chair of the IEEE Computer Society Technical Committee on Computational Intelligence (TCCI). He served as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering (TKDE) between January 1, 2000 and December 31, 2003, and is the Editor-in-Chief of TKDE since January 1, 2005. He is the winner of the 2004 ACM SIGKDD Service Award. Richard Relue, Ph.D.: He received his Ph.D. in Computer Science from the Colorado School of Mines in 2003. His research interests include association rules in data mining, neural networks for automated classification, and artificial intelligence for robot navigation. He has been an Information Technology consultant since 1992, working with Ball Aerospace and Technology, Rational Software, Natural Fuels Corporation, and Western Interstate Commission for Higher Education (WICHE).     

Polynomial-time learning of elementary formal systems

An elementary formal system (EFS) is a logic program consisting of definite clauses whose arguments have patterns instead of first-order terms. We investigate EFSs for polynomial-time PAC-learnability. A definite clause of an EFS is hereditary if every pattern in the body is a subword of a pattern in the head. With this new notion, we show that H-EFS(m, k, t, r) is polynomial-time learnable, which is the class of languages definable by EFSs consisting of at mostm hereditary definite clauses with predicate symbols of arity at mostr, wherek andt bound the number of variable occurrences in the head and the number of atoms in the body, respectively. The class defined by all finite unions of EFSs in H-EFS(m, k, t, r) is also polynomial-time learnable. We also show an interesting series ofNC-learnable classes of EFSs. As hardness results, the class of regular pattern languages is shown not polynomial-time learnable unlessRP=NP. Furthermore, the related problem of deciding whether there is a common subsequence which is consistent with given positive and negative examples is shownNP-complete. Satoru Miyano, Dr. Sci.: He is a Professor in Human Genome Center at the University of Tokyo. He obtained B.S. in 1977, M.S. in 1979, and Dr. Sci. degree all in Mathematics from Kyushu University. His current interests include bioinformatics, discovery science, computational complexity, computational learning. He has been organizing Genome Informatics Workshop Series since 1996 and has served for the chair/member of the program committee of many conferences in the area of Computer Science and Bioinformatics. He is on the Editorial Board of Theoretical Computer Science and the Chief Editor of Genome Informatics Series. Ayumi Shinohara, Dr. Sci.: He is an Associate Professor in the Department of Informatics at Kyushu University. He obtained B.S. in 1988 in Mathematics, M.S. in 1990 in Information Systems, and Dr. Sci. degree in 1994 all from Kyushu University. His current interests include discovery science, bioinformatics, and pattern matching algorithms. Takeshi Shinohara, Dr. Sci.: He is a Professor in the Department of Artificial Intelligence at Kyushu Institute of Technology. He obtained his B.S. in Mathematics from Kyoto University in 1980, and his Dr. Sci. degree from Kyushu University in 1986. His research interests are in Computational/Algorithmic Learning Theory, Information Retrieval, and Approximate Retrieval of Multimedia Data.     

Tradeoff and Sensitivity Analysis in Software Architecture Evaluation Using Analytic Hierarchy Process

Software architecture evaluation involves evaluating different architecture design alternatives against multiple quality-attributes. These attributes typically have intrinsic conflicts and must be considered simultaneously in order to reach a final design decision. AHP (Analytic Hierarchy Process), an important decision making technique, has been leveraged to resolve such conflicts. AHP can help provide an overall ranking of design alternatives. However it lacks the capability to explicitly identify the exact tradeoffs being made and the relative size of these tradeoffs. Moreover, the ranking produced can be sensitive such that the smallest change in intermediate priority weights can alter the final order of design alternatives. In this paper, we propose several in-depth analysis techniques applicable to AHP to identify critical tradeoffs and sensitive points in the decision process. We apply our method to an example of a real-world distributed architecture presented in the literature. The results are promising in that they make important decision consequences explicit in terms of key design tradeoffs and the architecture's capability to handle future quality attribute changes. These expose critical decisions which are otherwise too subtle to be detected in standard AHP results. Liming Zhu is a PHD candidate in the School of Computer Science and Engineering at University of New South Wales. He is also a member of the Empirical Software Engineering Group at National ICT Australia (NICTA). He obtained his BSc from Dalian University of Technology in China. After moving to Australia, he obtained his MSc in computer science from University of New South Wales. His principle research interests include software architecture evaluation and empirical software engineering. Aybüke Aurum is a senior lecturer at the School of Information Systems, Technology and Management, University of New South Wales. She received her BSc and MSc in geological engineering, and MEngSc and PhD in computer science. She also works as a visiting researcher in National ICT, Australia (NICTA). Dr. Aurum is one of the editors of “Managing Software Engineering Knowledge”, “Engineering and Managing Software Requirements” and “Value-Based Software Engineering” books. Her research interests include management of software development process, software inspection, requirements engineering, decision making and knowledge management in software development. She is on the editorial boards of Requirements Engineering Journal and Asian Academy Journal of Management. Ian Gorton is a Senior Researcher at National ICT Australia. Until Match 2004 he was Chief Architect in Information Sciences and Engineering at the US Department of Energy's Pacific Northwest National Laboratory. Previously he has worked at Microsoft and IBM, as well as in other research positions. His interests include software architectures, particularly those for large-scale, high-performance information systems that use commercial off-the-shelf (COTS) middleware technologies. He received a PhD in Computer Science from Sheffield Hallam University. Dr. Ross Jeffery is Professor of Software Engineering in the School of Computer Science and Engineering at UNSW and Program Leader in Empirical Software Engineering in National ICT Australia Ltd. (NICTA). His current research interests are in software engineering process and product modeling and improvement, electronic process guides and software knowledge management, software quality, software metrics, software technical and management reviews, and software resource modeling and estimation. His research has involved over fifty government and industry organizations over a period of 15 years and has been funded from industry, government and universities. He has co-authored four books and over one hundred and twenty research papers. He has served on the editorial board of the IEEE Transactions on Software Engineering, and the Wiley International Series in Information Systems and he is Associate Editor of the Journal of Empirical Software Engineering. He is a founding member of the International Software Engineering Research Network (ISERN). He was elected Fellow of the Australian Computer Society for his contribution to software engineering research.     

Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

In this paper, we present a new method for fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. The proposed method considers the centroid points and the standard deviations of generalized trapezoidal fuzzy numbers for ranking generalized trapezoidal fuzzy numbers. We also use an example to compare the ranking results of the proposed method with the existing centroid-index ranking methods. The proposed ranking method can overcome the drawbacks of the existing centroid-index ranking methods. Based on the proposed ranking method, we also present an algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can overcome the drawbacks of the one we presented in [7]. Shi-Jay Chen was born in 1972, in Taipei, Taiwan, Republic of China. He received the B.S. degree in information management from the Kaohsiung Polytechnic Institute, Kaohsiung, Taiwan, and the M.S. degree in information management from the Chaoyang University of Technology, Taichung, Taiwan, in 1997 and 1999, respectively. He received the Ph.D. degree at the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, in October 2004. His research interests include fuzzy systems, multicriteria fuzzy decisionmaking, and artificial intelligence. Shyi-Ming Chen was born on January 16, 1960, in Taipei, Taiwan, Republic of China. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. From August 1987 to July 1989 and from August 1990 to July 1991, he was with the Department of Electronic Engineering, Fu-Jen University, Taipei, Taiwan. From August 1991 to July 1996, he was an Associate Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1996 to July 1998, he was a Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1998 to July 2001, he was a Professor in the Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Since August 2001, he has been a Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was a Visiting Scholar in the Department of Electrical Engineering and Computer Science, University of California, Berkeley, in 1999. He was a Visiting Scholar in the Institute of Information Science, Academia Sinica, Republic of China, in 2003. He has published more than 250 papers in referred journals, conference proceedings and book chapters. His research interests include fuzzy systems, information retrieval, knowledge-based systems, artificial intelligence, neural networks, data mining, and genetic algorithms. Dr. Chen has received several honors and awards, including the 1994 Outstanding Paper Award o f the Journal of Information and Education, the 1995 Outstanding Paper Award of the Computer Society of the Republic of China, the 1995 and 1996 Acer Dragon Thesis Awards for Outstanding M.S. Thesis Supervision, the 1995 Xerox Foundation Award for Outstanding M.S. Thesis Supervision, the 1996 Chinese Institute of Electrical Engineering Award for Outstanding M.S. Thesis Supervision, the 1997 National Science Council Award, Republic of China, for Outstanding Undergraduate Student's Project Supervision, the 1997 Outstanding Youth Electrical Engineer Award of the Chinese Institute of Electrical Engineering, Republic of China, the Best Paper Award of the 1999 National Computer Symposium, Republic of China, the 1999 Outstanding Paper Award of the Computer Society of the Republic of China, the 2001 Institute of Information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the 2001 Outstanding Talented Person Award, Republic of China, for the contributions in Information Technology, the 2002 Institute of information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, the 2002 Chinese Fuzzy Systems Association Best Thesis Award for Outstanding M.S. Thesis Supervision, the 2003 Outstanding Paper Award of the Technological and Vocational Education Society, Republic of China, the 2003 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision, the 2005 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 Taiwan Fuzzy Systems Association Award for Outstanding Ph.D. Dissertation Supervision, and the 2006 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision. Dr. Chen is currently the President of the Taiwanese Association for Artificial Intelligence (TAAI). He is a Senior Member of the IEEE, a member of the ACM, the International Fuzzy Systems Association (IFSA), and the Phi Tau Phi Scholastic Honor Society. He was an administrative committee member of the Chinese Fuzzy Systems Association (CFSA) from 1998 to 2004. He is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics - Part C, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Editorial Board Member of the International Journal of Applied Intelligence, an Editor of the New Mathematics and Natural Computation Journal, an Associate Editor of the International Journal of Fuzzy Systems, an Editorial Board Member of the International Journal of Information and Communication Technology, an Editorial Board Member of the WSEAS Transactions on Systems, an Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics, an Associate Editor of the WSEAS Transactions on Computers, an Editorial Board Member of the International Journal of Computational Intelligence and Applications, an Editorial Board Member of the Advances in Fuzzy Sets and Systems Journal, an Editor of the International Journal of Soft Computing, an Editor of the Asian Journal of Information Technology, an Editorial Board Member of the International Journal of Intelligence Systems Technologies and Applications, an Editor of the Asian Journal of Information Management, an Associate Editor of the International Journal of Innovative Computing, Information and Control, and an Editorial Board Member of the International Journal of Computer Applications in Technology. He was an Editor of the Journal of the Chinese Grey System Association from 1998 to 2003. He is listed in International Who's Who of Professionals, Marquis Who's Who in the World, and Marquis Who's Who in Science and Engineering.     

A powertype-based metamodelling framework

Software development methodologies may be described in the context of an underpinning metamodel, but the precise mechanisms that permit them to be defined in terms of their metamodels are usually difficult to explain and do not cover all needs. For example, it is difficult to devise a way that allows the definition of properties of the elements that compose the methodology and, at the same time, of the entities (such as work products) created when the methodology is applied. This article introduces a new approach to constructing metamodels and deriving methodologies from them based on the concept of powertype. It combines key advantages of other metamodelling approaches and allows the seamless integration of process, modelling and documentational aspects of methodologies. With this approach, both methodology components and project entities can be described directly by the same metamodel. Cesar Gonzalez-Perez is a post-doctoral research fellow at the Faculty of Information Technology at UTS, where he works in object- and agent- oriented methodologies and metamodelling. Cesar is the author of over 40 publications and has led 12 successful software development projects. Cesar has previously worked in archaeology as well as biology, both in industry and academe. Cesar is the founder and former technical director of Neco, a company based in Spain specialising in software development support services, which include the deployment and use of the OPEN/Metis methodological framework at small and mid-sized organisations. Brian Henderson-Sellers is Director of the Centre for Object Technology Applications and Research and Professor of Information Systems at University of Technology, Sydney (UTS). He is author of eleven books on object technology and is well-known for his work in OO methodologies (MOSES, COMMA, OPEN, OOSPICE) and in OO metrics and, more recently, in agent-oriented methodologies. Brian has been Regional Editor of Object-Oriented Systems, a member of the editorial board of Object Magazine/Component Strategies and Object Expert for many years and is currently on the editorial board of Journal of Object Technology and Software and Systems Modelling. He is Editor of the International Journal on Agent-Oriented Software Engineering. He was the Founder of the Object-Oriented Special Interest Group of the Australian Computer Society (NSW Branch) and Chairman of the Computerworld Object Developers' Awards committee for ObjectWorld 94 and 95 (Sydney). He is a frequent, invited speaker at international OT conferences. In 1999, he was voted number 3 in the Who's Who of Object Technology (Handbook of Object Technology, CRC Press, Appendix N). He is a member of the Review Panel for the OMG's Software Process Engineering Model (SPEM) standards initiative and a member of the UML2.0 review team. In July 2001, Professor Henderson-Sellers was awarded a Doctor of Science (DSc) from the University of London for his research contributions in object-oriented methodologies.     

Tracking the activity of participants in a meeting

A vision system suitable for a smart meeting room able to analyse the activities of its occupants is described. Multiple people were tracked using a particle filter in which samples were iteratively re-weighted using an approximate likelihood in each frame. Trackers were automatically initialised and constrained using simple contextual knowledge of the room layout. Person–person occlusion was handled using multiple cameras. The method was evaluated on video sequences of a six person meeting. The tracker was demonstrated to outperform standard sampling importance re-sampling. All meeting participants were successfully tracked and their actions were recognised throughout the meeting scenarios tested.H. Nait Charif was funded by UK EPSRC Grant GR/R27419/01. Hammadi Nait Charif was born in Tinghir, Ouarzazat, Morocco on 25 December 1965. He received his Master of Engineering (Ingenieur d'Etat Diploma) in electrical engineering in 1990 and after a short-term job with the Ministry of Telecommunication, was appointed lecturer at Mohamed I University in 1991. He was a Monbusho visiting research fellow at Chiba University, Japan (1994–1995) where he received his PhD in 1998. He was an Assistant Professor and then an Associate Professor in electrical engineering at Mohamed I University (1998–2001). In 1999, he was a Fulbright Visiting Assistant Professor at Michigan State University. At the University of Dundee he has worked on the EPSRC project “Advanced Sensors for Supportive Environments for Elderly”. His research interests include image processing, computer vision and neural networks. Stephen McKenna is a Senior Lecturer at the University of Dundee. He graduated BSc (Hons) in Computer Science from the University of Edinburgh and PhD from the University of Dundee (1994). He has held post-doctoral research positions at Queen Mary, University of London and Tecnopolis Csata, Italy and has been a visiting researcher at BT Labs and George Mason University. Funders of his research include EPSRC, BBSRC and MRC. He has served on international program committees and is an Associate Editor of the journal Machine Vision and Applications. He co-authored the book “Dynamic Vision” and has published 75 articles on computer vision and pattern recognition. His research interests include the application of computer vision, imaging and machine learning to intelligent human–computer interaction, monitoring, surveillance, medicine and biology.     

Periodic use of time-varying state feedbacks for the receding horizon control of bilinear systems

This paper provides a receding horizon control method for SISO bilinear systems in the presence input constraints. Periodically-invariant sets are derived for a bilinear system with respect to a series of time-varying state feedback gains. The dual-mode control strategy is adopted and the periodically-invariant sets are used as target invariant sets. The state feedback gains used to define the target invariant sets are also used to render degrees of freedom to steer the current state into the target set. The region of attraction for the proposed algorithm is enlarged significantly with an extension of the horizon of periodicity while the on-line. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. This project is conducted through the Practical Application Project of Advanced Microsystems Packaging Program of Seoul Technopark, funded by the Ministry of Knowledge Economy. Young Il Lee was born in Korea in 1963. He received his B.Sc., M.S. and Ph.D. in Control and Instrumentation from Seoul National University. He is currently a Professor of the Dept. of Control and Instrumentation, Seoul National University of Technology. He spent two years at Oxford University as a Visiting Research Fellow. Basil Kouvaritakis was born in Athens, Greece in 1948. He was awarded First-Class Honours in Electrical Engineering from the Manchester Institute of Science and Technology, where he also received his Master and Doctorate. He is currently a Professor in Engineering at the Department of Engineering Science and a Tutorial Fellow at St Edmund Hall, Oxford University. Mark Cannon was born in England in 1971. He received M.Eng. and D.Phil. degrees from Oxford University and S.M. from Massachusetts Institute of Technology. He is currently a University Lecturer in Engineering and Fellow of St. Peter’s College, Oxford University.     

Retracted and replaced: Software component composition: a subdomain‐based testing foundation

The following article from Software Testing, Verification and Reliability, Software component composition: a subdomain‐based testing foundation by Dick Hamlet published online on 14 June 2007 in Wiley InterScience ( www.interscience.wiley.com ), has been retracted by agreement between the author, the journal Editor‐in‐Chief Jeff Offutt and John Wiley & Sons, Ltd. The retraction has been agreed because the article was not ready for publication and an early version without revisions was published in error. Replacement article DOI: 10.1002/stvr.376 . Copyright © 2007 John Wiley & Sons, Ltd.