From eager to lazy constrained data acquisition: A general framework

^*1 Constraint Satisfaction Problems (CSPs)¹⁷⁾ are an effective framework for modeling a variety of real life applications and many techniques have been proposed for solving them efficiently. CSPs are based on the assumption that all constrained data (values in variable domains) are available at the beginning of the computation. However, many non-toy problems derive their parameters from an external environment. Data retrieval can be a hard task, because data can come from a third-party system that has to convert information encoded with signals (derived from sensors) into symbolic information (exploitable by a CSP solver). Also, data can be provided by the user or have to be queried to a database. For this purpose, we introduce an extension of the widely used CSP model, called Interactive Constraint Satisfaction Problem (ICSP) model. The variable domain values can be acquired when needed during the resolution process by means of Interactive Constraints, which retrieve (possibly consistent) information. A general framework for constraint propagation algorithms is proposed which is parametric in the number of acquisitions performed at each step. Experimental results show the effectiveness of the proposed approach. Some applications which can benefit from the proposed solution are also discussed. This paper is an extended and revised version of the paper presented at IJCAI’99 (Stockholm, August 1999)⁴⁾. Paola Mello, Ph.D.: She received her degree in Electronic Engineering from University of Bologna, Italy, in 1982 and her Ph.D. degree in Computer Science in 1989. Since 1994 she is full Professor. She is enrolled, at present, at the Faculty of Engineering of the University of Bologna where she teaches Artificial Intelligence. Her research activity focuses around: programming languages, with particular reference to logic languages and their extensions towards modular and object-oriented programming; artificial intelligence; knowledge representation; expert systems. Her research has covered implementation, application and theoretical aspects and is presented in several national and international publications. She took part to several national (Progetti Finalizzati e MURST) and international (UE) research projects in the context of computational logic. Michela Milano, Ph.D.: She is a Researcher in the Department of Electronics, Computer Science and Systems at the University of Bologna. From the same University she obtained her master degree in 1994 and her Ph.D. in 1998. In 1999 she had a post-doc position at the University of Ferrara. Her research focuses on Artificial Intelligence, Constraint Satisfaction and Constraint Programming. In particular, she worked on using and extending the constraint-based paradigm for solving real-life problems such as scheduling, routing, object recognition and planning. She has served on the program committees of several international conferences in the area of Constraint Satisfaction and Programming, and she has served as referee in several related international journals. Marco Gavanelli: He is currently a Ph.D. Student in the Department of Engineering at the University of Ferrara, Italy. He graduated in Computer Science Engineering in 1998 at the University of Bologna, Italy. His research interest include Artificial Intelligence, Constraint Logic Programming, Constraint Satisfaction and visual recognition. He is a member of ALP (the Association for Logic Programming) and AI^*IA (the Italian Association for Artificial Intelligence). Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990. Her research activity centers on logic programming languages, Artificial Intelligence and software engineering. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Executive Committee of the Italian Association for Artificial Intelligence (AI^*IA). Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence and Fondations of Computer Science. Massimo Piccardi, Ph.D.: He graduated in electronic engineering at the University of Bologna, Italy, in 1991, where he received a Ph.D. in computer science and computer engineering in 1995. He currently an assistant professor of computer science with the Faculty of Engineering at the University of Ferrara, Italy, where he teaches courses on computer architecture and microprocessor systems. Massimo Piccardi participated in several research projects in the area of computer vision and pattern recognition. His research interests include architectures, algorithms and benchmarks for computer vision and pattern recognition. He is author of more than forty papers on international scientific journals and conference proceedings. Dr. Piccardi is a member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter. Rita Cucchiara, Ph.D.: She is an associate professor of computer science at the Faculty of Engineering at the University of Modena and Reggio Emilia, Italy, where she teaches courses on computer architecture and computer vision. She graduated in electronic engineering at the University of Bologna, Italy, in 1989 and she received a Ph.D. in electronic engineering and computer science from the same university in 1993. From 1993 to 1998 she been an assistant professor of computer science with the University of Ferrara, Italy. She participated in many research projects, including a SIMD parallel system for vision in the context of an Italian advanced research program in robotics, funded by CNR (the Italian National Research Council). Her research interests include architecture and algorithms for computer vision and multimedia systems. She is author of several papers on scientific journals and conference proceedings. She is member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter.     

ASIP-based reconfigurable architectures for power-efficient and real-time image/video processing

To meet both flexibility and performance requirements, particularly when implementing high-end real-time image/video processing algorithms, the paper proposes to combine the application specific instruction-set processor (ASIP) paradigm with the reconfigurable hardware one. As case studies, the design of partially reconfigurable ASIP (r-ASIP) architectures is presented for two classes of algorithms with widespread diffusion in image/video processing: motion estimation and retinex filtering. Design optimizations are addressed at both algorithmic and architectural levels. Special processor concepts used to trade-off performance versus flexibility and to enable new features of post-fabrication configurability are shown. Silicon implementation results are compared to known ASIC, DSP or reconfigurable designs; the proposed r-ASIPs stand for their better performance–flexibility figures in the respective algorithmic class.

A Method for Computing the Number of Iterations in Data Dependent Loops

This paper addresses the problem of loop iteration number estimation, applied to linear loops. This is important to statically put an upper bound on the execution time of real-time systems and implement timing constraint verification. In our approach, matrix calculation is applied to derive the analytical equation that holds the number of iterations as a solution, and it is proved that such solution is related to a zero of an exponential function of the eigenvalues. So, the number of iterations turns out to be an implicit variable of the equation, which can be easily exactly calculated for loops depending on few free variables. Francesco Curatelli received the degree in Electronic Engineering and the Ph.D. degree in Microelectronics from the University of Genova, Italy. During the years 1980-85 he worked as a design engineer at Elsag Inc., Genova. Since 1985 he has been working at the Microelectronics group of the Department of Biophysical and Electronic Engineering (DIBE) at the University of Genova, initially as Research assistant and, since 1992, as Professor in Electronics. His research activities concern the study and development of algorithms and design tools for real-time systems, HCI and assistive technology. He is the author of more than 80 papers published in journals, conference proceedings, and books. Leonardo Mangeruca received his master and PhD degrees in Electrical Engineering and Computer Science from the University of Genoa, Italy, between 1995 and 1998. In 1999 he joined PARADES, Roma, Italy, directed by Prof. A.L. Sangiovanni-Vincentelli, where he focused on research activities in System Level Design and Advanced Architectures for Embedded Systems. His interests include formal models and methods for system design, distributed systems, fault-tolerant architectures, embedded software, real-time scheduling. He is involved in numerous cooperations with international research institutions and represents PARADES in several European Projects.     

Finite-horizon scheduling of radar dwells with online template construction

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon. Sathish Gopalakrishnan is a visting scholar in the Department of Computer Science, University of Illinois at Urbana-Champaign, where he defended his Ph.D. thesis in December 2005. He received an M.S. in Applied Mathematics from the University of Illinois in 2004 and a B.E. in Computer Science and Engineering from the University of Madras in 1999. Sathish’s research interests concern real-time and embedded systems, and the design of large-scale reliable systems. He received the best student paper award for his work on radar dwell scheduling at the Real-Time Systems Symposium 2004. Marco Caccamo graduated in computer engineering from the University of Pisa in 1997 and received the Ph.D. degree in computer engineering from the Scuola Superiore S. Anna in 2002. He is an Assistant Professor of the Department of Computer Science at the University of Illinois. His research interests include real-time operating systems, real-time scheduling and resource management, wireless sensor networks, and quality of service control in next generation digital infrastructures. He is recipient of the NSF CAREER Award (2003). He is a member of ACM and IEEE. Chi-Sheng Shih is currently an assistant professor at the Graduate Institute of Networking and Multimedia and Department of Computer Science and Information Engineering at National Taiwan University since February 2004. He received the B.S. in Engineering Science and M.S. in Computer Science from National Cheng Kung University in 1993 and 1995, respectively. In 2003, he received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His main research interests are embedded systems, hardware/software codesign, real-time systems, and database systems. Specifically, his main research interests focus on real-time operating systems, real-time scheduling theory, embedded software, and software/hardware co-design for system-on-a-chip. Chang-Gun Lee received the B.S., M.S. and Ph.D. degrees in computer engineering from Seoul National University, Korea, in 1991, 1993 and 1998, respectively. He is currently an Assistant Professor in the Department of Electrical Engineering, Ohio State University, Columbus. Previously, he was a Research Scientist in the Department of Computer Science, University of Illinois at Urbana-Champaign from March 2000 to July 2002 and a Research Engineer in the Advanced Telecomm. Research Lab., LG Information & Communications, Ltd. from March 1998 to February 2000. His current research interests include real-time systems, complex embedded systems, QoS management, and wireless ad-hoc networks. Chang-Gun Lee is a member of the IEEE Computer Society. Lui Sha graduated with the Ph.D. degree from Carnegie-Mellon University in 1985. He was a Member and then a Senior Member of Technical Staff at Software Engineering Institute (SEI) from 1986 to 1998. Since Fall 1998, he has been a Professor of Computer Science at the University of Illinois at Urbana Champaign, and a Visiting Scientist of the SEI. He was the Chair of IEEE Real Time Systems Technical Committee from 1999 to 2000, and has served on its Executive Committee since 2001. He was a member of National Academy of Science’s study group on Software Dependability and Certification from 2004 to 2005, and is an IEEE Distinguished Visitor (2005 to 2007). Lui Sha is a Fellow of the IEEE and the ACM.     

Discovering validation rules from microbiological data

A huge amount of data is daily collected from clinical microbiology laboratories. These data concern the resistance or susceptibility of bacteria to tested antibiotics. Almost all microbiology laboratories follow standard antibiotic testing guidelines which suggest antibiotic test execution methods and result interpretation and validation (among them, those annually published by NCCLS^2,3). Guidelines basically specify, for each species, the antibiotics to be tested, how to interpret the results of tests and a list of exceptions regarding particular antibiotic test results. Even if these standards are quite assessed, they do not consider peculiar features of a given hospital laboratory, which possibly influence the antimicrobial test results, and the further validation process. In order to improve and better tailor the validation process, we have applied knowledge discovery techniques, and data mining in particular, to microbiological data with the purpose of discovering new validation rules, not yet included in NCCLS guidelines, but considered plausible and correct by interviewed experts. In particular, we applied the knowledge discovery process in order to find (association) rules relating to each other the susceptibility or resistance of a bacterium to different antibiotics. This approach is not antithetic, but complementary to that based on NCCLS rules: it proved very effective in validating some of them, and also in extending that compendium. In this respect, the new discovered knowledge has lead microbiologists to be aware of new correlations among some antimicrobial test results, which were previously unnoticed. Last but not least, the new discovered rules, taking into account the history of the considered laboratory, are better tailored to the hospital situation, and this is very important since some resistances to antibiotics are specific to particular, local hospital environments. Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990. Her research activity centers on logic programming languages, artificial intelligence and agent-based programming. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Italian Association for Artificial Intelligence (AI^*IA), associated with ECCAI. Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence and Fondations of Computer Science. Fabrizio Riguzzi, Ph.D.: He is Assistant Professor at the Department of Engineering of the University of Ferrara, Italy. He received his Laurea from the University of Bologna in 1999. He joined the Department of Engineering of the University of Ferrara in 1999. He has been a visiting researcher at the University of Cyprus and at the New University of Lisbon. His research interests include: data mining (and in particular methods for learning from multirelational data), machine learning, belief revision, genetic algorithms and software engineering. Sergio Storari: He got his degree in Electrical Engineering at the University of Ferrara in 1998. His research activity centers on artificial intelligence, knowledge-based systems, data mining and multi-agent systems. He is a member of the Italian Association for Artificial Intelligence (AI^*IA), associated with ECCAI. Currently, he is attending the third year of Ph.D. course about “Study and application of Artificial Intelligence techniques for medical data analysis” at DEIS University of Bologna. Paola Mello, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1982, and her Ph.D. in Computer Science in 1988. Her research activity centers on knowledge representation, logic programming, artificial intelligence and knowledge-based systems. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, Held in Bologna in September 1999. She is a member of the Italian Association for Artificial Intelligence (AI^*IA), associated with ECCAI. Currently, she is Full Professor at the University of Bologna, where she teaches Artificial Intelligence and Fondations of Computer Science. Anna Nanetti: She got a degree in biologics sciences at the University of Bologna in 1974. Currently, she is an Academic Recearcher in the Microbiology section of the Clinical, Specialist and Experimental Medicine Department of the Faculty of Medicine and Surgery, University of Bologna.     

Feasibility Analysis of Real-Time Periodic Tasks with Offsets

The problem of feasibility analysis of asynchronous periodic task sets, where tasks can have an initial offset, is known to be co-NP-complete in the strong sense. A sufficient pseudo-polynomial test has been proposed by Baruah, Howell and Rosier, which consists in analyzing the feasibility of the corresponding synchronous task set (i.e. all offsets are set equal to 0). If the test gives a positive result, then the original asynchronous task set is feasible; else, no definitive answer can be given. In many cases, this sufficient test is too pessimistic, i.e. it gives no response for many feasible task sets.In this paper, we present a new sufficient pseudo-polynomial test for asynchronous periodic task sets. Our test reduces the pessimism by explicitely considering the offsets in deriving a small set of critical arrival patterns. We show, trough a set of extensive simulations, that our test outperforms the previous sufficient test.Rodolfo Pellizzoni received the Laurea degree in Computer Engineering from the Università di Pisa and the Diploma degree from the Scuola Superiore SantAnna, in 2004. He is presently a Ph.D. student in the Department of Computer Science at the University of Illinois at Urbana-Champaign. His main research interests are in real-time operating systems, scheduling theory and resource-allocation in distributed and multiprocessor systems.Giuseppe Lipari graduated in Computer Engineering at the University of Pisa in 1996, and received the Ph.D. degree in Computer Engineering from Scuola Superiore SantAnna in 2000. During 1999, he was a visiting student at University of North Carolina at Chapel Hill, collaborating with professor S.K. Baruah and professor K. Jeffay on real-time scheduling. Currently, he is assistant professor of Operating Systems with Scuola Superiore SantAnna. His main research activities are in real-time scheduling theory and its application to real-time operating systems, soft real-time systems for multimedia applications and component-based real-time systems.     

Belief revision via Lamarckian evolution

We present a system for performing belief revision in a multi-agent environment. The system is called GBR (Genetic Belief Revisor) and it is based on a genetic algorithm. In this setting, different individuals are exposed to different experiences. This may happen because the world surrounding an agent changes over time or because we allow agents exploring different parts of the world. The algorithm permits the exchange of chromosomes from different agents and combines two different evolution strategies, one based on Darwin’s and the other on Lamarck’s evolutionary theory. The algorithm therefore includes also a Lamarckian operator that changes the memes of an agent in order to improve their fitness. The operator is implemented by means of a belief revision procedure that, by tracing logical derivations, identifies the memes leading to contradiction. Moreover, the algorithm comprises a special crossover mechanism for memes in which a meme can be acquired from another agent only if the other agent has “accessed” the meme, i.e. if an application of the Lamarckian operator has read or modified the meme. Experiments have been performed on the η-queen problem and on a problem of digital circuit diagnosis. In the case of the η-queen problem, the addition of the Lamarckian operator in the single agent case improves the fitness of the best solution. In both cases the experiments show that the distribution of constraints, even if it may lead to a reduction of the fitness of the best solution, does not produce a significant reduction. Evelina Lamma, Ph.D.: She is Full Professor at the University of Ferrara. She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990. Her research activity centers on extensions of logic programming languages and artificial intelligence. She was coorganizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. Currently, she teaches Artificial Intelligence and Fondations of Computer Science. Fabrizio Riguzzi, Ph.D.: He is Assistant Professor at the Department of Engineering of the University of Ferrara, Italy. He received his Laurea from the University of Bologna in 1995 and his Ph.D. from the University of Bologna in 1999. He joined the Department of Engineering of the University of Ferrara in 1999. He has been a visiting researcher at the University of Cyprus and at the New University of Lisbon. His research interests include: data mining (and in particular methods for learning from multirelational data), machine learning, belief revision, genetic algorithms and software engineering. Luís Moniz Pereira, Ph.D.: He is Full Professor of Computer Science at Departamento de Informática, Universidade Nova de Lisboa, Portugal. He received his Ph.D. in Artificial Intelligence from Brunel University in 1974. He is the director of the Artificial Intelligence Centre (CENTRIA) at Universidade Nova de Lisboa. He has been elected Fellow of the European Coordinating Committee for Artificial Intelligence in 2001. He has been a visiting Professor at the U. California at Riverside, USA, the State U. NY at Stony Brook, USA and the U. Bologna, Italy. His research interests include: knowledge representation, reasoning, learning, rational agents and logic programming.     

QoS Management Through Adaptive Reservations

Reservation based (RB) scheduling is a class of scheduling algorithms that is well-suited for a large class of soft real-time applications. They are based on a bandwidth abstraction, meaning that a task is given the illusion of executing on a dedicated slower processor. In this context, a crucial design issue is deciding the bandwidth that each task should receive. The point we advocate is that, in presence of large fluctuations on the computation requirements of the tasks, it can be a beneficial choice to dynamically adapt the bandwidth based on QoS measurements and on the subsequent application of feedback control (adaptive reservations).In this paper, we present two novel contributions to this research area. First, we propose three new control algorithms inspired to the ideas of stochastic control. Second, we present a flexible and modular software architecture for adaptive reservations. An important feature of this architecture is that it is realised by means of a minimally invasive set of modifications to the Linux kernel.This work has been partially supported by the European OCERA IST-2001-35102 and RECSYS IST-2001-32515 projects.Luca Abeni is a Ph.D. in Computer Engineering at the Scuola Superiore SantAnna of Pisa (Italy). He graduated in Computer Engineering at the University of Pisa in 1998, and received a Ph.D. in Computer Engineering at the Scuola SuperioreS. Anna of Pisa in 2002. During 2000 he was a visiting student at the Carnegie Mellon University (Pittsburgh, PA), working with Prof. Ragunathan Rajkumar on resource reservation algorithms for real-time kernels. During 2001 he was a visiting student a Oregon Graduate Institute (Portland, OR) working with Prof. Jonathan Walpole on the support for time-sensitive applications in the Linux kernel. He has been working in Broadsat S.R.L. since 2003, developing audio/video streaming solutions and IPTV applications.Tommaso Cucinotta got the degree in Computer Engineering at the University of Pisa (Italy) in 2000. He got the Ph.D. inComputer Engineering at the Scuola Superiore SantAnna(SSSA) of Pisa in 2004 with a thesis titled Issues in authentication by means of smart-card devices. He held a course on cryptography in the International Master on Software Engineering organized at SSSA in 2002 and 2004. At the moment, he cooperates in research activities at the Scuola Superiore S. Anna in the areas of computer security and Quality of Service control for soft real-time systems.Giuseppe Lipari graduated in Computer Engineering at the University of Pisa in 1996, and received the Ph.D. degree in Computer Engineering from Scuola Superiore SantAnna in 2000. During 1999, he was avisiting student at University of North Carolina at Chapel Hill, collaborating with professor S.K. Baruah and professor K. Jeffay on real-time scheduling. Currently, he is assistant professor of Operating Systems with Scuola Superiore SantAnna. His main research activities are in real-time scheduling theory and its application to real-time operating systems, soft real-time systems for multimedia applications and component-based real-time systems.Luca Marzario is a Ph.D. student in Computer Engineering at the Scuola Superiore S. Anna of Pisa, Italy. In 2002, he graduated in Computer Engineering at University of Pisa. His main research interest include real-time systems scheduling, aperiodic service mechanism, feedback-scheduling, QoS in multimedia systems, Linux kernel and Real Time Linux executives (RTAI, RTLinux).Luigi Palopoli graduated in Control Engineering at the University of Pisa in 1998 and received his Ph.D. degree in Computer Engineering in 2002 from the Scuola Superiore S. Anna, Pisa. During 2001 he was a visiting scholar at the Department of EECS, University of California at Berkeley, where he worked on design techniques for real-time controllers under the supervision of Professor Alberto Sangiovanni-Vincentelli. He is currently Assistant Professor at the Scuola Superiore S. Anna (Pisa). His main research activities include Quality of Service control, control of systems under communication and computation constraints and design of embedded systems.     

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.     

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.     

LMI stability criterion with less variables for time-delay systems

Slack variables approach is an important technique for tackling the delay-dependent stability problem for systems with time-varying delay. In this paper, a new delay-dependent stability criterion is presented without introducing any slack variable. The technique is based on a simply integral inequality. The result is shown to be equivalent to some existing ones but includes the least number of variables. Thus, redundant selection and computation can be avoided so that the computational burden can be largely reduced. Numerical examples are given to illustrate the effectiveness of the proposed stability conditions. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors would like to thank the Associate Editor and the Reviewers for their very helpful comments and suggestions. This work was supported in part by the Funds for Creative Research Groups of China under Grant 60821063, by the State Key Program of National Natural Science of China under Grant 60534010, by the Funds of National Science of China under Grant 60674021, 60774013, 60774047, National 973 Program of China under Grant No. 2009CB320604, and by the Funds of Ph.D. program of MOE, China under Grant 20060145019 and the 111 Project B08015. Xun-Lin Zhu received the B.S. degree in Applied Mathematics from Information Engineering Institute, Zhengzhou, China, in 1986, the M.S. degree in basic mathematics from Zhengzhou University, Zhengzhou, China, in 1989, and the Ph.D. degree in Control Theory and Engineer-ing from Northeastern University, Shenyang, China, in 2008. Currently, he is an Associate Professor at Zhengzhou University of Light Industry, Zhengzhou, China. His research interests include neural networks and networked control systems. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, non-fragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society. Tao Li was born in 1979. He is now pursuing a Ph.D. degree in Research Institute of Automation Southeast University, China. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Chong Lin received the B.Sci and M.Sci in Applied Mathematics from the Northeastern University, China, in 1989 and 1992, respectively, and the Ph.D in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore, in 1999. He was a Research Associate with the University of Hong Kong in 1999. From 2000 to 2006, he was a Research Fellow with the National University of Singapore. He is currently a Profesor with the Institute of Complexity Science, Qingdao University, China. His current research interests are mainly in the area of systems analysis and control. Lei Guo was born in 1966. He received the Ph.D. degree in Control Engineering from Southeast University (SEU), PR China, in 1997. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now he is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. He also holds a Visiting Professor position in the University of Manchester, UK and an invitation fellowship in Okayama University, Japan. His research interests include robust control, stochastic systems, fault detection, filter design, and nonlinear control with their applications.     

A notion of passivity for switched systems with state-dependent switching

A passivity concept for switched systems with state-dependent switching is presented. Each subsystem has a storage function to describe the “energy” stored in the subsystem. The passivity property of a switched system is given in terms of multiple storage functions. Each storage function is allowed to grow on the “switched on” time sequence but the total growth is bounded by a certain function. Stability is inferred from passivity and asymptotic stability is achieved under further assumptions of a detectivity property of a local form and boundedness of the total change of some storage function on its inactive intervals. A state-dependent switching law that renders the system passive is also designed.     

A Simple Robotic System for Neurorehabilitation

In the recent past, several researchers have shown that important variables in relearning motor skills and in changing the underlying neural architecture after stroke are the quantity, duration, content, and intensity of training sessions. Unfortunately, when traditional therapy is provided in a hospital or rehabilitation center, the patient is usually seen for few hours a week. Robot-mediated therapies could improve this situation but even if interesting results have been achieved by several groups, the use of robot-mediated therapy has not become very common in clinical practice. This is due to many different reasons (e.g., the “technophobia” of some clinicians, the need for more extensive clinical trials) but one of the more important is the cost and the complexity of these devices which make them difficult to be purchased and used in all the clinical centers. The aim of this work was to verify the possibility of improving motor recovery of hemiparetic subjects by using a simple mechatronic system. To achieve this goal, our system (named “MEchatronic system for MOtor recovery after Stroke” (MEMOS)) has been designed with the aim of using mainly “off-the-shelf products” with only few parts simply manufactured with standard technology, when commercial parts were not available. Moreover, the prototype has been developed taking into account the requirements related to the clinical applicability such as robustness and safety. The MEMOSsystem has been used during clinical trials with subjects affected by chronic hemiparesis (<6 months from the cerebrovascular accident). The results obtained during these experiments seem to showthat notwithstanding the simple mechatronic structure characterizing theMEMOSsystem, it is able to help chronic hemiparetics to reduce their level of impairment. Further clinical experiments with acute and chronic subjects will be carried out in order to confirm these preliminary findings. Moreover, experiments for tele-rehabilitation of patients will be also carried out. Silvestro Micera was born in Taranto, Italy, on August 31, 1972. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 1996, and the Ph.D. degree in biomedical engineering from the Scuola Superiore Sant'Anna, Pisa, Italy, in 2000. From 1998 to 2001, he was the Project Manager of the EU GRIP Project (ESPRIT LTR Project 26322, “An integrated system for the neuroelectrIic control of grasp in disabled persons”). During 1999, he was a Visiting Researcher at the Center for Sensory-Motor Interaction, Aalborg University. Since May 2000, he has been an Assistant Professor of Biomechanical Engineering at the Scuola Superiore Sant'Anna. He is currently involved in several projects on neuro-robotics and rehabilitation engineering. His research interests include the development of neuro-robotic systems (interfacing the central and peripheral nervous system with robotic artefacts) and the development of mechatronic and robotic systems for function restoration in disabled persons. Dr. Micera is an Associate Editor of the IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING and member of the IEEE Engineering in Medicine and Biology and Robotics and Automation Societies. M. Chiara Carrozza received the Laurea degree in physics from the University of Pisa, Pisa, Italy, in 1990. Since 2001, she has been an Associate Professor of biomedical robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. She is the co-cordinator of the Advanced Robotics Technology and Systems Laboratory where she is responsible for some national and international projects in the fields of biorobotics. Her research interests are in the fields of biorobotics (artificial hands, upper limb exoskeletons), rehabilitation engineering (neurorehabilitation, domotic, and robotic aids), and biomedical microengineering (microsensors, tactile sensors). She is an author of several scientific papers and international patents. Eugenio Guglielmelli received the Laurea degree and the PhD in electronics engineering from the University of Pisa, Italy, in 1991 and in 1995, respectively. He is currently Associate Professor of Bioengineering at Campus Bio-Medico University in Rome, Italy, where he teaches the courses of Bio-Mechatronics and of Rehabilitation Bioengineering, and where he also recently co-founded the new Research Laboratory of Biomedical Robotics & Electro-Magnetic Compatibility. He has been working in the field of biomedical robotics over the last fifteen years at Scuola Superiore Sant'Anna where he also served from 2002 to 2004 as the Head of the Advanced Robotics Technology & Systems Laboratory (ARTS Lab), founded by prof. Paolo Dario in 1991. His main current research interests are in the fields of novel theoretical and experimental approaches to human-centered robotics and to biomporphic control of mechatronic systems, and in their application to robot-mediated motor therapy, assistive robotics, neuro-robotics and neuro-developmental engineering. He serves in the Editorial Board of the International Journal on Applied Bionics and Biomechanics. He has been Guest Co-Editor of the Special Issue on Rehabilitation Robotics of the International Journal ‘Autonomous Robots’. He is member of the IEEE Robotics & Automation Society, of the IEEE Engineering in Medicine & Biology Society, of the Society for Neuroscience, and of the Association for the Advancement of Assistive Technology in Europe (AAATE). He served (2002–03) as the Secretary of the IEEE Robotics & Automation Society (RAS) and he is currently Co-chair of the RAS Technical Committee on Rehabilitation Robotics. He serves in the Programme Committees of several International Conferences, such as ICRA, IROS, ICAR, AIM, BIOROB and others. He was/is a member of the Organizing Committees of ICAR2003, IROS2004, IFAC/SYROCO2006 and ICRA2007. Giovanni Cappiello received the M.E. degree from the University of Pisa, Pisa, Italy. He is currently working towards the Ph.D. degree in robotics at the ARTS Lab of the Scuola Superiore Sant'Anna Pisa. He worked on the RTR IV Prosthetic Hand Project. Among his research interests are rehabilitation technologies, biomedical and surgical devices, osseointegration, and biomimetic artificial sensors. He is involved in the design of antropomorphic hands and arm and in the exploitation of compliant joints. Franco Zaccone was born in Policoro, Italy. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 2000. Since June 2000, he has been a Research Assistant at the Advanced Robotics Technologies and Systems Laboratory, Scuola Superiore Sant'Anna, Pisa. His research interests include the design of hardware systems for rehabilitation engineering and motion analysis. Cinzia Freschi was born in Caserta, Italy, on December 25, 1969. She received the University degree (Laurea) in computer engineering from the University of Pisa, Pisa, Italy, in 1998. Since 1998, she has been research assistant at the Advanced Robotics Technology and Systems Laboratory (ARTSLAB), Scuola Superiore Sant'Anna. Her research interests are in the filed of rehabilitation engineering and neuro-robotics. Roberto Colombo received the Dr. Eng. degree in electrical engineering from the Politecnico of Milano, Milan, Italy, in 1980. Since 1981, he has been a Research Engineer in the Bioengineering Department of the “Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. From 1998 to 2001, he was a Partner of the European Community project “Prevention of muscular disorders in operation of computer input devices (PROCID).” From 2001 to 2004, he was the Coordinator of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. His research interests include robot-aided neurorehabilitation, muscle tone and spasticity evaluation, muscle force and fatigue assessment, speech production mechanisms study, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. He has taught several national courses in the field of neurorehabilitation. He is the author of over 20 papers and the co-editor of one book on the subject of speech production mechanisms. Alessandra Mazzone received the degree (Diploma) in computer science, from the ITIS “Leonardo da Vinci,” Borgomanero, Italy, in 1988. Since 1989, she has been a Programmer at the Bioengineering Department, the Fondazione Salvatore Maugeri, Rehabilitation Institute of Veruno (NO), Italy. Her research interests include robot-aided neurorehabilitation, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. Carmen Delconte received the Diploma in neurophysiology techniques from the University of Pavia, Pavia, Italy, in 1989. She is currently with the Clinical Neurophysiology Unit, Scientific Institute of Veruno “Salvatore Maugeri” Foundation, Rehabilitation Institute, Veruno, Italy. Her research concerns the quantification of muscle tone, emg-biomechanical studies, and the robotic rehabilitation of upper limb in cerebrovascular diseases. She has been published in the clinical and electrophisiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. Her current research is focused on the evaluation and treatment of upper limbs disorders like spasticity and paresis. Dr. Delconte is a member of the Italian Neurophysiology Technician Society. Fabrizio Pisano received the M.D. degree from the University of Milan, Milan, Italy, in 1981. In 1986, he completed his training as resident in neurology and became Neurologist at the same University He was a teacher in “Electromyography” from 1991 to 1997 at the School of Physical Medicine and Rehabilitation, the University of Turin, Torino, Italy. He has taught several national and international electromyographic courses on hand neuromotor rehabilitation, occupational pathology, rehabilitation therapy, muscle fatigue, posture and movement, clinical neurophysiology, and EMG Culture. He was a Scientific Project co-leader of a telethon program (1994–1996); speech motor control in ALS; a search for an early marker of disease. He was the Project Leader of “Quantitative Analysis of Spastic Hypertonia” by the Istituto Superiore della Sanitá during 1998–1999. He was the Clinical Scientific Leader of the INAIL project “International clinical survey over functional electrical stimulation.” He was the Scientific Project Leader of the Clinical Neurophysiology Unit of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. He is currently a Neurologist and the Head of the Clinical Neurophysiology Unit, ”Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. He has been published in the clinical and electrophysiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. His current research interests are in evaluation and treatment of upper limb disorders like spasticity and paresis. Dr. Pisano is a Member of the Italian Neurological Society and the Italian Clinical Neurophysiology Society. Giuseppe Minuco received the Dr. Eng. degree in mechanical engineering from the Politecnico Milano, Milan, Italy, in 1972, and a postgraduate degree in biomedical engineering from the Faculty of Medicine, Bologna, Italy, in 1975. He is currently Head of the Bioengineering Department, “Salvatore Maugeri” Foundation, IRCCS, Pavia, Italy. He is Chair of the Technical Scientific Committee of “CBIM” (Medical Informatics and Bioengineering Consortium) Pavia, Italy. He is Member of the Editorial Board of The Monaldi Archives for Chest Disease and of Giornale Italiano di Medicina del Lavoro ed Ergonomia. Has taught several courses in healthcare management. His main interests are in the fields of rehabilitation engineering, clinical engineering, medical informatics, and telemedicine. Paolo Dario received the Dr. Eng. degree in mechanical engineering from the University of Pisa, Pisa, Italy, in 1977. He is currently a Professor of Biomedical Robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. He also teaches courses at the School of Engineering of the University of Pisa, and at the Campus Biomedico University, Rome, Italy. He has been a Visiting Professor at Brown University, Providence, RI, at the Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, and at Waseda University, Tokyo, Japan. He was the founder of the Advanced Robotics Technologies and Systems (ARTS) Laboratory and is currently the co-cordinator of the Center for Research in Microengineering (CRIM) Laboratory of the Scuola Superiore Sant'Anna, where he supervises a team of about 70 researchers and Ph.D. students. He is also the Director of the Polo Sant'Anna Valdera and a Vice-Director of the Scuola Superiore Sant'Anna. His main research interests are in the fields of medical robotics, mechatronics, and micro/nanoengineering, and specifically in sensors and actuators for the above applications. He is the coordinator of many national and European projects, the editor of two books on the subject of robotics, and the author of more than 200 scientific papers (75 in ISI journals). He is Editor-in-Chief, Associate Editor, and Member of the Editorial Board of many international journals. Prof. Dario served as President of the IEEE Robotics and Automation Society during 2002–2003, and he is currently Co-Chair of the Technical Committees on Bio-robotics and of Robo-ethics of the same society. He is a Fellow of the European Society on Medical and Biological Engineering, and a recipient of many honors and awards, such as the Joseph Engelberger Award. He is also a Member of the Board of the International Foundation of Robotics Research (IFRR).     

Zikimi: A Case Study in Micro Kernel Design for Multimedia Applications

Due to recent rapid deployment of Internet Appliances and PostPC products, the importance of developing lightweight embedded operating system is being emphasized more. In this article, we like to present the details of design and implementation experience of low cost embedded system, Zikimi, for multimedia data processing. We use the skeleton of existing Linux operating system and develop a micro-kernel to perform a number of specific tasks efficiently and effectively. Internet Appliances and PostPC products usually have very limited amount of hardware resources to execute very specific tasks. We carefully analyze the system requirement of multimedia processing device. Weremove the unnecessary features, e.g. virtual memory, multitasking, a number of different file systems, and etc. The salient features of Zikimi micro kernel are (i) linear memory system and (ii) user level control of I/O device. The result of performance experiment shows that LMS (linear memory system) of Zikimi micro kernel achieves significant performance improvement on memory allocationagainst legacy virtual memory management system of Linux. By exploiting the computational capability of graphics processor and its local memory, we achieve 2.5 times increase in video processing speed. Supported by KOSEF through Statistical Research Center for Complex Systems at Seoul National University. Funded by Faculty Research Institute Program 2001, Sahmyook University, Korea. Sang-Yeob Lee received his B.S. and M.S degree from Hanyang University, seoul, Korea in 1995. He is currently working towards the Ph.D. degree in Devision of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. Since 1998, he has been on the faculty of Information Management System at Sahmyook university, Seoul, Korea. His research interests include robot vision systems, pattern recognition, Multimedia systems. He is a member of IEEE. Youjip Won received the B.S and M.S degree in Computer Science from the Department of Computer Science, Seoul National University, Seoul, Korea in 1990 and 1992, respectively and the Ph.D. in Computer Science from the University of Minnesota, Minneapolis in 1997. After finishing his Ph.D., He worked as Server Performance Analysts at Server Architecture Lab., Intel Corp. Since 1999, he has been on the board of faculty members in Division of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. His current research interests include Multimedia Systems, Internet Technology, Database and Performance Modeling and Analysis. He is a member of ACM and IEEE. Whoi-Yul Kim received his B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea in 1980. He received his M.S. from Pennsylvania State University, University Park, in 1983 and his Ph.D. from Purdue University, West Lafayette, in 1989, both in Electrical Engineering. From 1989 to 1994, he was with the Erick Jonsson School of Engineering and Computer Science at the University of Texas at Dallas. Since 1994, he has been on the faculty of Electronic Engineering at Hanyang University, Seoul, Korea. He has been involved with research development of various range sensors and their use in robot vision systems. Recently, his work has focused on content-based image retrieval system. He is a member of IEEE.     

Inference of abduction theories for handling incompleteness in first-order learning

In real-life domains, learning systems often have to deal with various kinds of imperfections in data such as noise, incompleteness and inexactness. This problem seriously affects the knowledge discovery process, specifically in the case of traditional Machine Learning approaches that exploit simple or constrained knowledge representations and are based on single inference mechanisms. Indeed, this limits their capability of discovering fundamental knowledge in those situations. In order to broaden the investigation and the applicability of machine learning schemes in such particular situations, it is necessary to move on to more expressive representations which require more complex inference mechanisms. However, the applicability of such new and complex inference mechanisms, such as abductive reasoning, strongly relies on a deep background knowledge about the specific application domain. This work aims at automatically discovering the meta-knowledge needed to abduction inference strategy to complete the incoming information in order to handle cases of missing knowledge. Floriana Esposito received the Laurea degree in electronic Physics from the University of Bari, Italy, in 1970. Since 1994 is Full Professor of Computer Science at the University of Bari and Dean of the Faculty of Computer Science from 1997 to 2002. She founded and chairs the Laboratory for Knowledge Acquisition and Machine Learning of the Department of Computer Science. Her research activity started in the field of numerical models and statistical pattern recognition. Then her interests moved to the field of Artificial Intelligence and Machine Learning. The current research concerns the logical and algebraic foundations of numerical and symbolic methods in machine learning with the aim of the integration, the computational models of incremental and multistrategy learning, the revision of logical theories, the knowledge discovery in data bases. Application include document classification and understanding, content based document retrieval, map interpretation and Semantic Web. She is author of more than 270 scientific papers and is in the scientific committees of many international scientific Conferences in the field of Artificial Intelligence and Machine Learning. She co-chaired ICML96, MSL98, ECML-PKDD 2003, IEA-AIE 2005, ISMIS 2006. Stefano Ferilli was born in 1972. After receiving his Laurea degree in Information Science in 1996, he got a Ph.D. in Computer Science at the University of Bari in 2001. Since 2002 he is an Assistant Professor at the Department of Computer Science of the University of Bari. His research interests are centered on Logic and Algebraic Foundations of Machine Learning, Inductive Logic Programming, Theory Revision, Multi-Strategy Learning, Knowledge Representation, Electronic Document Processing and Digital Libraries. He participated in various National and European (ESPRIT and IST) projects concerning these topics, and is a (co-)author of more than 80 papers published on National and International journals, books and conferences/workshops proceedings. Teresa M.A. Basile got the Laurea degree in Computer Science at the University of Bari, Italy (2001). In March 2005 she discussed a Ph.D. thesis in Computer Science at the University of Bari titled “A Multistrategy Framework for First-Order Rules Learning.” Since April 2005, she is a research at the Computer Science Department of the University of Bari working on methods and techniques of machine learning for the Semantic Web. Her research interests concern the investigation of symbolic machine learning techniques, in particular of the cooperation of different inferences strategies in an incremental learning framework, and their application to document classification and understanding based on their semantic. She is author of about 40 papers published on National and International journals and conferences/workshops proceedings and was/is involved in various National and European projects. Nicola Di Mauro got the Laurea degree in Computer Science at the University of Bari, Italy. From 2001 he went on making research on machine learning in the Knowledge Acquisition and Machine Learning Laboratory (LACAM) at the Department of Computer Science, University of Bari. In March 2005 he discussed a Ph.D. thesis in Computer Science at the University of Bari titled “First Order Incremental Theory Refinement” which faces the problem of Incremental Learning in ILP. Since January 2005, he is an assistant professor at the Department of Computer Science, University of Bari. His research activities concern Inductive Logic Programming (ILP), Theory Revision and Incremental Learning, Multistrategy Learning, with application to Automatic Document Processing. On such topics HE is author of about 40 scientific papers accepted for presentation and publication on international and national journals and conference proceedings. He took part to the European projects 6th FP IP-507173 VIKEF (Virtual Information and Knowledge Environment Framework) and IST-1999-20882 COLLATE (Collaboratory for Annotation, Indexing and Retrieval of Digitized Historical Archive Materials), and to various national projects co-funded by the Italian Ministry for the University and Scientific Research.     

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.     

Development of a biomimetic miniature robotic crawler

The paper presents the development of segmented artificial crawlers endowed with passive hook-shaped frictional microstructures. The goal is to find design rules for fabricating biomimetic, adaptable and mobile machines mimicking segmented animals with hydrostatic skeleton, and intended to move effectively along unstructured substrates. The paper describes the mechanical model, the design and the fabrication of a SMA-actuated segmented microrobot, whose locomotion is inspired by the peristaltic motion of Annelids, and in particular of earthworms (Lumbricus Terrestris). Experimental locomotion performance are compared with theoretical performance predicted by a purposely developed friction model -taking into account design parameters such as number of segments, body mass, special friction enhancement appendixes—and with locomotion performance of real earthworms as presented in literature. Experiments indicate that the maximum speed of the crawler prototype is 2.5 mm/s, and that 3-segment crawlers have almost the same velocity as earthworms having the same weight (and about 330% their length), whereas 4-segment crawlers have the same velocity, expressed as body lengths/s, as earthworms with the same mass (and about 270% their length). Arianna Menciassi (MS, 1995; PhD, 1999) joined the CRIM Lab of the Scuola Superiore Sant’Anna (Pisa, Italy) as a Ph.D. student in Bioengineering with a research program on the micromanipulation of mechanical and biological micro-objects. The main results of the activity on micromanipulation were presented at the IEEE International Conference on Robotics & Automation (May 2001, Seoul) in a paper titled “Force Feedback-based Microinstrument for Measuring Tissue Properties and Pulse in Microsurgery”, which won the “ICRA2001 Best Manipulation Paper Award”. In the year 2000, she was offered a position of Assistant Professor in Biomedical Robotics at the Scuola Superiore Sant’Anna and in June 2006 she obtained a promotion to Associate Professor. Her main research interests are in the field of biomedical microrobotics, biomimetics, microfabrication technologies, micromechatronics and microsystem technologies. She is working on several European projects and international projects for the development of minimally invasive instrumentation for medical applications and for the exploitation of micro- and nano-technologies in the medical field. Samuele Gorini received his Laurea Degree in Mechanical Engineering (with honors) from the University of Pisa, Italy, in 2001. In 2005 he obtained the Ph.D. in Microsystem Engineering with a thesis on locomotion methods and systems for miniaturised endoscopic devices. Since 2000, he has been working at the CRIM Lab of the Scuola Superiore Sant’Anna in Pisa, Italy. His research interests are in the field of biomedical robotics with a special focus on actuation technologies. Starting from the year 2004 he has been president of Era Endoscopy S.r.l., a start-up company of Scuola Superiore Sant’Anna developing novel devices for endoscopy. Dino Accoto (MS 1998, PhD 2002) is Assistant Professor of Biomedical Engineering at Scuola Sant’Anna (Pisa, Italy). He received the Laurea degree in Mechanical Engineering from the University of Pisa (cum laude) in 1998, the diploma in Engineering from the Scuola Sant’Anna (cum laude) in 1999 and the PhD degree from the Scuola Sant’Anna in 2002. From October 2001 to September 2002 he has been visiting scholar at the RPL-Lab, Stanford University (Ca, USA). Since 2004 he cooperates with the Biomedical Robotics & EMC Lab at Campus Bio-Medico University in Rome. His main research field is the modelling and development of small electromechanical systems, with a special attention to multi-physics and multi-domain approaches. The research, often inspired by the analysis of natural mechanisms, has been mainly applied to hybridizing microtechnologies, including microfluidics, and robotics. He has co-authored more than 30 papers, appeared in international journals and conference proceedings. Paolo Dario received his Dr. Eng. Degree in Mechanical Engineering from the University of Pisa, Italy, in 1977. He is currently a Professor of Biomedical Robotics at the Scuola Superiore Sant’Anna in Pisa.. He also teaches courses at the School of Engineering of the University of Pisa and at the Campus Biomedico University in Rome. He has been Visiting Professor at Brown University, Providence, RI, USA, at the Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, at Waseda University, Tokyo, Japan, at the College de France, Paris, and at the Ecole Normale Superieure de Cachan, France. He was the founder of the ARTS (Advanced Robotics Technologies and Systems) Laboratory and is currently the Co-ordinator of the CRIM (Center for the Research in Microengineering) Laboratory of the Scuola Superiore Sant’Anna, where he supervises a team of about 70 researchers and Ph.D. students. His main research interests are in the fields of medical robotics, bio-robotics, mechatronics and micro/nanoengineering, and specifically in sensors and actuators for the above applications, and in robotics for rehabilitation. He is the coordinator of many national and European projects, the editor of two books on the subject of robotics, and the author of more than 200 scientific papers (75 on ISI journals). He is Editor-in-Chief, Associate Editor and member of the Editorial Board of many international journals. Prof. Dario has served as President of the IEEE Robotics and Automation Society in the years 2002–2003. He has been the General Chair of the IEEE RAS-EMBS BioRob’06 Conference and he is the General Co-Chair of ICRA 2007 Conference. Prof. Dario is an IEEE Fellow, a Fellow of the European Society on Medical and Biological Engineering, and a recipient of many honors and awards, such as the Joseph Engelberger Award. He is also a member of the Board of the International Foundation of Robotics Research (IFRR).     

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

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

Real-time pinch detection algorithm: Robust to impulsive noise

A robust pinch detection algorithm which can be implemented in a cheap microprocessor is proposed for the development of a safety feature in the automotive power window system. To solve the problems caused by the performance degradation of a Hall sensor or real driving situations, the proposed algorithm makes use of the H _∞ state estimation technique. The motivation of this approach comes from the advantage that the H _∞ filter can minimize or bound the worst-case estimation error energy for all bounded energy disturbances. Herein, the pinch torque rate estimator is derived from applying the steady-state H _∞ filter to the augmented model, which includes the motor dynamics and an additional torque rate state. Then, to redesign an appropriate estimator for real-time implementation, the torque rate estimate can be calculated more efficiently than the previous method [1]. Experimental results verify that, with a small amount of computation, the proposed pinch detection algorithm provides fast pinch detection performance superior to the existing method. Furthermore, it guarantees robustness against the worst-case measurement noises. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Young Il Lee. Jung-Hoon Park received the B.E. degree in Electronic Engineering in 1996, and the M.S. degree in Electrical and Electronic Engineering from Yonsei University, Seoul, Korea, in 2002. He worked with Samsung Electronics as an Engineer from 1996 to 1999. He is currently pursuing his doctoral degree at Yonsei University. His research interests include robust control and filtering theory, robot vision, and its applications. Won-Sang Ra received the B.E., M.S., and Ph.D. degrees in Electrical and Electronics Engineering from Yonsei University, Seoul, Korea, in 1998, 2000, and 2009, respectively. From March 2000 to February 2009, he was with the Guidance and Control Department of Agency for Defense Development, Daejeon, as a Senior Researcher. Since March 2009, he has been with the School of Mechanical and Control Engineering, Handong Global University, where he is currently a Full-Time Instructor. His main research topic includes the robust filtering theory and its applications to autonomous vehicle guidance and control. Tae-Sung Yoon received the B.E., M.S., and Ph.D. degrees, in Electrical Engineering from Yonsei University, Seoul, Korea, in 1978, 1980, and 1988, respectively. He worked with the Department of Electrical Engineering at the 2nd Naval Academy, Jinhae, Korea, as a member of the teaching staff from 1980 to 1983. He worked with the Department of Electrical Engineering at Vanderbilt University, Nashville, as a Visiting Assistant Professor from 1994 to 1995. Since 1989, he has been with the Department of Electrical Engineering, Changwon National University, Changwon, Korea where he is currently a Professor. His research interests include robust filtering, mobile robotics, and time-frequency signal processing in instrumentation. Jin-Bae Park received the B.E. degree in Electrical Engineering from Yonsei University, Seoul, Korea, in 1977, and the M.S. and Ph.D. degrees in Electrical Engineering from Kansas State University, Manhattan, in 1985, and 1990, respectively. Since 1992, he has been with the Department of Electrical and Electronic Engineering, Yonsei University, where he is currently a Professor. His research interests include robust control and filtering, nonlinear control, mobile robotics, fuzzy logic control, neural networks, genetic algorithms, and Hadamard-transform spectroscopy. He has served as the Director for the Transactions of the Korean Institute of Electrical Engineers (1998–2003) and the Institute of Control, Automation, and Systems Engineers (1999–2003). He is currently the Editor-in-Chief for the International Journal of Control, Automation, and Systems.     

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.