On condensed representations of constrained frequent patterns

Constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns to a smaller, more interesting, subset. Although a lot of work has been done with both these paradigms, there is still confusion around the mining problem obtained by joining closed and constrained frequent patterns in a unique framework. In this paper, we shed light on this problem by providing a formal definition and a thorough characterisation. We also study computational issues and show how to combine the most recent results in both paradigms, providing a very efficient algorithm that exploits the two requirements (satisfying constraints and being closed) together at mining time in order to reduce the computation as much as possible. Francesco Bonchi received his Ph.D. in computer science from the University of Pisa in December 2003, with the thesis “Frequent Pattern Queries: Language and Optimizations”. Currently, he is a postdoc at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council in Pisa, where he is a member of the Knowledge Discovery and Delivery Laboratory. He has been a visiting fellow at the Kanwal Rekhi School of Information Technology, Indian Institute of Technology, Bombay (2000, 2001). His current research interests are data mining query language and Optimization, frequent pattern mining, privacy-preserving data mining, bioinformatics. He is one of the teachers of a course on data mining held at the faculty of Economics at the University of Pisa. He served as a referee at various national and international conferences on databases, data mining, logic programming and artificial intelligence. Claudio Lucchese received the Master Degree in Computer Science summa cum laude from Ca' Foscari University of Venice in October 2003. He is currently a Ph.D. student at the same university and Research Associate at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council in Pisa, where he is a member of the High Performance Computing Laboratory. He is mainly interested in frequent pattern mining, privacy-preserving data mining, and data mining techniques for information retrieval.     

A comparison between the first absolute central moment and the gradient of Gaussian when detecting edges in presence of Gaussian noise

The gray-level absolute central moment of the first order provides ridges at gray-level discontinuities as well as a conventional gradient of Gaussian (GoG). A mass center b of the gray-level variability can also be associated to the first absolute central moment. When given a starting point p, vector b indicates the path which joins p to the nearest gray-level discontinuity as well as the gradient of the GoG magnitude. However, when the right configuration of the operator is chosen, vector b indicates a point which is closer to the discontinuity than p, regardless of the distance between p and the discontinuity. Therefore, when using vector b, gray-level discontinuities can be located with an iterative approach. In this paper, the edge detection properties of the first absolute central moment are compared with those of the GoG. The text was submitted by the authors in English. Marcello Demi was born in Cecina, Italy, in 1956. He graduated in electronic engineering from the University of Florence, Italy, in 1985. He is currently head of the Computer Vision Group at the CNR Institute of Clinical Physiology in Pisa, senior scientist for ESAOTE Spa, and he teaches a course on medical image processing at the Faculty of Applied Physics, University of Pisa. His research interests are cardiovascular image processing systems, contour tracking of moving deformable objects, and filtering schemes inspired by the early stages of biological vision systems. He has 80 scientific publications and his objective is the development of common projects with people who work in the area of biological vision for the purpose of both understanding biological vision and developing image processing systems. Francesco Faita was born on June 28, 1973, in La Spezia (Italy). In 2001, he graduated from Universitá degli Studi di Pisa obtaining the degree of electronic engineer. Since 2001, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in computer vision, in particular, in the field of ultrasound imaging. Elisabetta Bianchini was born in Lucca, Italy, in 1975. She received her degree in electronic engineering from the University of Pisa, Italy, in 2004. Since 2004, she has been a junior researcher at CNR, the Italian National Research Council, at the DSP lab in IFC (Institute of Clinical Physiology). Vincenzo Gemignani was born on October 10, 1969, in Viareggio (Italy). In 1995, he graduated from Universitá degli Studi di Pisa obtaining the degree of electronic engineer. Since 1996, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in digital signal processing, in particular, in field real-time image analysis.     

Contour tracking on ultrasound sequences of vascular images

Simple vascular measurements on sequences of echographic images can be used to quantify important indexes of cardiovascular risk. The measurement of the intima-media thickness and the characterization of the endothelial function are but two examples. Real-time image processing systems would be helpful to automatically track, locate, and discriminate vascular structures through image sequences. Many algorithms have been developed to accomplish this task and they are generally based on the application of a mathematical operator at the points of a starting contour and on an iterative procedure that brings the starting contour to the final contour. In this paper, the performances of a mathematical operator that exploits both temporal and spatial information are compared to those of an operator that only exploits spatial information. The paper shows that, in general, when tracking contours on image sequences and when two or more gray-level discontinuities are present and close to each other, as in the case of arteries, both operators should be used in sequence. The text was submitted by the authors in English. Marcello Demi was born in Cecina, Italy, in 1956. He graduated in Electronic Engineering from the University of Florence, Italy in 1985. He is currently head of the Computer Vision Group at the CNR Institute of Clinical Physiology in Pisa and he teaches a course on Medical Image Processing at the faculty of Applied Physics, University of Pisa. His research interests are image processing systems and filtering schemes inspired by the early stages of biological vision systems. He has 80 scientific publications and his objective is the development of common projects with people who work in the area of biological vision for the purpose of both understanding biological vision and developing image processing systems. Elisabetta Bianchini was born in Lucca, Italy, in 1975. She received the degree in Electronic Engineering from the University of Pisa, Italy, in 2004. Since 2004 she is junior research at CNR, the Italian National Research Council, at the DSP lab in IFC (Institute of Clinical Physiology). Her field of interest is image processing and in particular development of methods for the assessment of indices of cardiovascular risk from ultrasound images. She is author or co-author of 14 scientific publications in international journals and conference proceedings. Francesco Faita was born in 1973 in La Spezia (Italy). In 2001 he graduated from Università degli Studi di Pisa obtaining the degree of Electronic Engineer. Since 2001, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in Computer Vision, in particular in the field of ultrasound image motion estimation. A major focus of his research in the last years has been development of clinically applicable automated techniques for cardiovascular analysis and prediction of disease progression. He is author or co-author of 58 scientific publications in international journals and conference proceedings. Viencenzo Gemignani was born in 1969, in Viareggio (Italy). In 1995, he graduated in Electronic Engineering from the University of Pisa. Since 1996, he has been working at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests are in diagnostic ultrasound, realtime image analysis and non-invasive patient monitoring systems. He teaches a course on DSP processors at the Faculty of Engineering, University of Pisa. He is author or coauthor of 40 scientific publications in international journals and conference proceedings and is co-inventor of 4 patents in the field of ultrasonic image processing.     

Constructive negation and constraint logic programming with sets

The aim of this paper is to extend theConstructive Negation technique to the case ofCLP(SεT), a Constraint Logic Programming (CLP) language based on hereditarily (and hybrid) finite sets. The challenging aspects of the problem originate from the fact that the structure on whichCLP(SεT) is based is notadmissible closed, and this does not allow to reuse the results presented in the literature concerning the relationships betweenCLP and constructive negation. We propose a new constraint satisfaction algorithm, capable of correctly handling constructive negation for large classes ofCLP(SεT) programs; we also provide a syntactic characterization of such classes of programs. The resulting algorithm provides a novel constraint simplification procedure to handle constructive negation, suitable to theories where unification admits multiple most general unifiers. We also show, using a general result, that it is impossible to construct an interpreter forCLP(SεT) with constructive negation which is guaranteed to work for any arbitrary program; we identify classes of programs for which the implementation of the constructive negation technique is feasible. Agostino Dovier, Ph.D.: He is a researcher in the Department of Science and Technology at the University of Verona, Italy. He obtained his master degree in Computer Science from the University of Udine, Italy, in 1991 and his Ph.D. in Computer Science from the University of Pisa, Italy, in 1996. His research interests are in Programming Languages and Constraints over complex domains, such as Sets and Multisets. He has published over 20 research papers in International Journals and Conferences. He is teaching a course entitled “Special Languages and Techniques for Programming” at the University of Verona. Enrico Pontelli, Ph.D.: He is an Assistant Professor in the Department of Computer Science at the New Mexico State University. He obtained his Laurea degree from the University of Udine (Italy) in 1991, his Master degree from the University of Houston in 1992, and his Ph.D. degree from New Mexico State University in 1997. His research interests are in Programming Languages, Parallel Processing, and Constraint Programming. He has published over 50 papers and served on the program committees of different conferences. He is presently the Associate Director of the Laboratory for Logic, Databases, and Advanced Programming. Gianfranco Rossi, Ph.D.: He received his degree in Computer Science from the University of Pisa in 1979. From 1981 to 1983 he was employed at Intecs Co. System House in Pisa. From November 1983 to February 1989 he was a researcher at the Dipartimento di Informatica of the University of Turin. Since March 1989 he is an Associate Professor of Computer Science, currently with the University of Parma. He is the author of several papers dealing mainly with programming languages, in particular logic programming languages and Prolog, and extended unification algorithms. His current research interests are (logic) programming languages with sets and set unification algorithms.     

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.     

Object tracking in video-surveillance

This paper faces the automatic object tracking problem in a video-surveillance task. A previously selected and then identified target has to be retrieved in the scene under investigation because it is lost due to masking, occlusions, or quick and unexpected movements. A two-step procedure is used, firstly motion detection is used to determine a candidate target in the scene, secondly using a semantic categorization and Content Based Image Retrieval techniques, the candidate target is identified whether it is the one that was lost or not. The use of Content Based Image Retrieval serves as support to the search problem and is performed using a reference data base which was populated a priori. The article is published in the original. Davide Moroni (Magenta, 1977), M.Sc. in Mathematics honours degree from the University of Pisa in 2001, dipl. at the Scuola Normale Superiore of Pisa in 2002, Ph.D. in Mathematics at the University of Rome ‘La Sapienza’ in 2006, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. His main interests include geometric modelling, computational topology, image processing and medical imaging. At present he is involved in a number of European research projects working in discrete geometry and scene analysis. Gabriele Pieri (Pescia, 1974), M.Sc. (2000) in Computer Science from the University of Pisa, since 2001 joined the “Signals and Images” Laboratory at ISTI-CNR, Pisa, working in the field of image analysis. His main interests include neural networks, machine learning, industrial diagnostics and medical imaging. He is author of more than twenty papers.     

Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique

Ancient documents are usually degraded by the presence of strong background artifacts. These are often caused by the so-called bleed-through effect, a pattern that interferes with the main text due to seeping of ink from the reverse side. A similar effect, called show-through and due to the nonperfect opacity of the paper, may appear in scans of even modern, well-preserved documents. These degradations must be removed to improve human or automatic readability. For this purpose, when a color scan of the document is available, we have shown that a simplified linear pattern overlapping model allows us to use very fast blind source separation techniques. This approach, however, cannot be applied to grayscale scans. This is a serious limitation, since many collections in our libraries and archives are now only available as grayscale scans or microfilms. We propose here a new model for bleed-through in grayscale document images, based on the availability of the recto and verso pages, and show that blind source separation can be successfully applied in this case too. Some experiments with real-ancient documents arepresented and described. Anna Tonazzini graduated cum laude in Mathematics from the University of Pisa, Italy, in 1981. In 1984 she joined the Istituto di Scienza e Tecnologie dell'Informazione of the Italian National Research Council (CNR) in Pisa, where she is currently a researcher at the Signals and Images Laboratory. She cooperated in special programs for basic and applied research on image processing and computer vision, and is co-author of over 60 scientific papers. Her present interest is on inverse problems theory, image restoration and reconstruction, document analysis and recognition, independent component analysis, neural networks and learning. Emanuele Salerno graduated in Electronic Engineering from the University of Pisa, Italy, in 1985. In September 1987 he joined the Italian National Research Council (CNR) at the Department of Signal and Image Processing, Information Processing Institute (now Institute of Information Science and Technologies, ISTI, Signals and Images Laboratory), Pisa, Italy, where he has been working in applied inverse problems, image reconstruction and restoration, microwave nondestructive evaluation, and blind signal separation. He has been assuming different responsibilities in research programs in nondesctructive testing, robotics, numerical models for image reconstruction and computer vision, neural networks techniques in astrophysical imagery. At present, he is local scientific responsible in the framework of the European Space Agency's “Planck Surveyor Satellite” mission, and takes part in the European CRAFT project “ISyReADeT”, for document image restoration. Luigi Bedini graduated cum laude in Electronic Engineering from the University of Pisa, Italy, in 1968. Since 1970 he has been a Researcher of the Italian National Research Council, Istituto di Scienza e Tecnologie dell'Informazione, Pisa, Italy. His interests have been in modelling, identification, and parameter estimation of biological systems applied to non-invasive diagnostic techniques. At present, his research interest is in the field of digital signal processing, image reconstruction and neural networks applied to image processing. He is co-author of more than 80 scientific papers. From 1971 to 1989, he was Associate Professor of System Theory at the Computer Science Department, University of Pisa, Italy.     

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).     

Relationships between broadcast and shared memory in reliable anonymous distributed systems

We study the power of reliable anonymous distributed systems, where processes do not fail, do not have identifiers, and run identical programmes. We are interested specifically in the relative powers of systems with different communication mechanisms: anonymous broadcast, read-write registers, or read-write registers plus additional shared-memory objects. We show that a system with anonymous broadcast can simulate a system of shared-memory objects if and only if the objects satisfy a property we call idemdicence this result holds regardless of whether either system is synchronous or asynchronous. Conversely, the key to simulating anonymous broadcast in anonymous shared memory is the ability to count: broadcast can be simulated by an asynchronous shared-memory system that uses only counters, but read-write registers by themselves are not enough. We further examine the relative power of different types and sizes of bounded counters and conclude with a non-robustness result. James Aspnes is a Professor of Computer Science at Yale University. He received his Ph.D. from Carnegie-Mellon University in 1992. Faith Ellen Fich is a Professor of Computer Science at the University of Toronto. She received her Ph.D. from the University of California, Berkeley in 1982. Eric Ruppert was educated at the University of Toronto, where he completed his doctorate in 1999. He spent a year as a postdoctoral fellow at Brown University and is an Associate Professor at York University.     

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).     

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.

Automatic computation of left ventricle ejection fraction from dynamic ultrasound images

Left Ventricle (LV) Ejection Fraction (EF) is a fundamental parameter for heart function assessment. Being based on border tracing, however, manual computation of EF is time-consuming and extremely prone to inter-and intraobserver variability. In this paper we present an automatic method for EF computation which provides results in agreement with those provided by expert observers. The segmentation strategy consists of two stages: first, the region of interest is identified by means of mimetic criteria; then, the identified region is used for initialization of an active contour based on a variational formulation of level set methods, which provides accurate segmentation of the LV cavity. Volume calculation is then performed according to the conventional Simpson’s rule and, finally, the EF is computed. The text was submitted by the authors in English. Umberto Barcaro is an Associate Professor at the Computer Science Department of Pisa University and an Associate Researcher at the Signals and Images Laboratory of the Institute of Information Science and Technologies of the National Research Council. He teaches Physics and Computer Science Laboratory at the Faculty of Pharmacy, and Signal Theory at the Faculty of Sciences. His research activity regards the automatic analysis of signals and images of clinical interest. In particular, he has studied spontaneous and evoked electroencephalographic and polygraphic signals, and ultrasound images. Davide Moroni (Magenta, 1977), M.Sc. in Mathematics honours degree from the University of Pisa in 2001, dipl. at the Scuola Normale Superiore of Pisa in 2002, PhD in Mathematics at the University of Rome “La Sapienza” in 2006, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. His main interests include geometric modeling, computational topology, image processing and medical imaging. At present he is involved in a number of European research projects working in discrete geometry and dynamic scene analysis. Ovidio Salvetti, director of research at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is a coauthor of four books and monographs and more than three hundred technical and scientific articles; he also possesses ten patents regarding systems and software tools for image processing. He has been a scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding, member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory.     

Evolving dynamic Bayesian networks with Multi-objective genetic algorithms

A dynamic Bayesian network (DBN) is a probabilistic network that models interdependent entities that change over time. Given example sequences of multivariate data, we use a genetic algorithm to synthesize a network structure that models the causal relationships that explain the sequence. We use a multi-objective evaluation strategy with a genetic algorithm. The multi-objective criteria are a network's probabilistic score and structural complexity score. Our use of Pareto ranking is ideal for this application, because it naturally balances the effect of the likelihood and structural simplicity terms used in the BIC network evaluation heuristic. We use a basic structural scoring formula, which tries to keep the number of links in the network approximately equivalent to the number of variables. We also use a simple representation that favors sparsely connected networks similar in structure to those modeling biological phenomenon. Our experiments show promising results when evolving networks ranging from 10 to 30 variables, using a maximal connectivity of between 3 and 4 parents per node. The results from the multi-objective GA were superior to those obtained with a single objective GA. Brian J. Ross is a professor of computer science at Brock University, where he has worked since 1992. He obtained his BCSc at the University of Manitoba, Canada, in 1984, his M.Sc. at the University of British Columbia, Canada, in 1988, and his Ph.D. at the University of Edinburgh, Scotland, in 1992. His research interests include evolutionary computation, language induction, concurrency, and logic programming. He is also interested in computer applications in the fine arts. Eduardo Zuviria received a BS degree in Computer Science from Brock University in 2004 and a MS degree in Computer Science from Queen's University in 2006 where he held jobs as teacher and research assistant. Currently, he is attending a Ph.D. program at the University of Montreal. He holds a diploma in electronics from a technical college and has worked for eight years in the computer industry as a software developer and systems administrator. He has received several scholarships including the Ontario Graduate Scholarship, Queen's Graduate Scholarship and a NSERC- USRA scholarship.     

On the message complexity of binary byzantine agreement under crash failures

Summary The binary Byzantine Agreement problem requiresn–1 receivers to agree on the binary value broadcast by a sender even when some of thesen processes may be faulty. We investigate the message complexity of protocols that solve this problem in the case of crash failures. In particular, we derive matching upper and lower bounds on the total, worst and average case number of meassages needed in the failure-free executions of such protocols.More specifically, we prove that any protocol that tolerates up tot faulty processes requires a total of at leastn+t–1 messages in its failure-free executions —and, therefore, at least [(n+t–1)/2] messages in the worst case and min (P ₀,P ₁)·(n+t–1) meassages in the average case, whereP _v is the probability that the value of the bit that the sender wants to broadcast isv. We also give protocols that solve the problem using only the minimum number of meassages for these three complexity measures. These protocols can be implemented by using 1-bit messages. Since a lower bound on the number of messages is also a lower bound on the number of meassage bits, this means that the above tight bounds on the number of messages are also tight bounds on the number of meassage bits. Vassos Hadzilacos received a BSE from Princeton University in 1980 and a PhD from Harvard University in 1984, both in Computer Science. In 1984 he joined the Department of Computer Science at the University of Toronto where he is currently an Associate Professor. In 1990–1991 he was visiting Associate Professor in the Department of Computer Science at Cornell University. His research interests are in the theory of distributed systems. Eugene Amdur obtained a B. Math from the University of Waterloo in 1986 and a M.Sc. from the University of Toronto in 1988. He is currently employed by the Vision and Robotics group at the University of Toronto in both technical and research capacities. His current areas of interest are vision, robotics, and networking. Samuel Weber received his B.Sc. in Mathematics and Computer Science and his M.Sc. in Computer Science from the University of Toronto. Currently, he is at Cornell University as a Ph.D. student in Computer Science with a minor in Psychology. His research interests include distributed systems, and the semantics of programming languages.     

Rank order filters and priority queues

Summary A derivation of a parallel algorithm for rank order filtering is presented. Both derivation and result differ from earlier designs: the derivations are less complicated and the result allows a number of different implementations. The same derivation is used to design a collection of priority queues. Both filters and priority queues are highly efficient: they have constant response time and small latency. Anne Kaldewaij received an M.Sc. degree in Mathematics from the University of Utrecht (The Netherlands) and a Ph.D. degree in Computing Science from the Eindhoven University of Technology. Currently, he is associate professor in Computing Science at Eindhoven University. His research includes parallel programming and the design of algorithms and data structures. He enjoys teaching and he has written a number of textbooks on mathematics and programming. Jan Tijmen Udding received an M.Sc. degree in Mathematics in 1980 and a Ph.D. degree in Computing Science in 1984 from Eindhoven University of Technology. Currently, he is associate professor at Groningen University. His main research interests are mathematical aspects of VLSI, program derivation and correctness, and functional programming.     

Measuring the Performance of Schedulability Tests

The high computational complexity required for performing an exact schedulability analysis of fixed priority systems has led the research community to investigate new feasibility tests which are less complex than exact tests, but still provide a reasonable performance in terms of acceptance ratio. The performance of a test is typically evaluated by generating a huge number of synthetic task sets and then computing the fraction of those that pass the test with respect to the total number of feasible ones. The resulting ratio, however, depends on the metrics used for evaluating the performance and on the method for generating random task parameters. In particular, an important factor that affects the overall result of the simulation is the probability density function of the random variables used to generate the task set parameters. In this paper we discuss and compare three different metrics that can be used for evaluating the performance of schedulability tests. Then, we investigate how the random generation procedure can bias the simulation results of some specific scheduling algorithm. Finally, we present an efficient method for generating task sets with uniform distribution in a given space, and show how some intuitive solutions typically used for task set generation can bias the simulation results.This work has been partially supported by the European Union, under contract IST-004527, and by the Italian Ministry of University Research (MIUR), under contract 2003094275.Enrico Bini received the Ph.D. in Computer Engineering from Scuola Superiore SantAnna in Pisa, in October 2004. In 2000 he received the Laurea degree in Computer Engineering from Università di Pisa and, one year later, he obtained the Diploma di Licenza from the Scuola Superiore SantAnna. In 1999 he studied at Technische Universiteit Delft, in the Nederlands, by the Erasmus student exchange program. In 2001 he worked at Ericsson Lab Italy in Roma. In 2003 he was a visiting student at University of North Carolina at Chapel Hill, collaborating with prof. Sanjoy Baruah. His research interests cover scheduling algorithms, real-time operating systems, embedded systems design and linear programming.Giorgio Buttazzo is an Associate Professor of Computer Engineering at the University of Pavia, Italy. He graduated in Electronic Engineering at the University of Pisa in 1985, received a Master in Computer Science at the University of Pennsylvania in 1987, and a Ph.D. in Computer Engineering at the Scuola Superiore S. Anna of Pisa in 1991. During 1987, he worked on active perception and real-time control at the G.R.A.S.P.     

Defect detection in <Emphasis Type="Italic">C</Emphasis>-scan maps

An image processing procedure is proposed aiming at detecting porosity defects in materials used in the aerospace industry by means of the analysis of C-scan images obtained by ultrasound inspection techniques. An image is described through a number of features, which are then analyzed in order to evaluate the similarity of an unknown examined image with respect to a set of reference ones. The procedure is performed by firstly applying a 2D wavelet transform of the input image and then a feature extraction process based on statistics of the detail images produced by the transform itself. A data reduction process is then applied using the principal component analysis technique. Finally, a decision ruler performs the image classification by considering the distance among points in the principal component plane. An application of this procedure is presented for the analysis of single images, giving a localization of defects. Preliminary results, obtained by processing both simulation images and real C-scan maps, showed the efficacy of the proposed method. The text was submitted by the authors in English. Edoardo Bozzi (Pisa, 1943) is a researcher at ISTI-CNR, in Pisa, working in the field of signal processing. His main interests include design of hardware and software instrumentation and development of noninvasive diagnostic techniques for medical and industrial applications. He is author of about a hundred technical papers. Maria Grazia Di Bono (Potenza, 1975), MS (2002) in computer science from the University of Pisa, has been performing since March 2003 her research activity at ISTI-CNR, in Pisa, working in the field of computer vision. Her main interests include neural networks, multimedia processing, and web systems for industrial and medical applications. She is coauthor of more than twelve technical and scientific papers. G. Cavaccini. Born in Naples October 28, 1959. Graduate in physics. From 1986 to 1988, he was at the Naples Section of the National Institute for Nuclear Physics, where he participated in research on gamma spectroscopy. From 1988 to 1999, he was at Aerodynamics Institute U. Nobile of the University of Naples with a scholarship on “Nondestructive Testing of Aeronautical Structures by Means of Thermographics Techniques.” From 1989 to the present date, he has been an Alenia Aeronautica employee. Up to 2001, he worked as an NDI technologist and researcher at the Engineering Materials, Processes, and NDI Dept. He holds ASNT Level III, Italian Aerospace NDT Board, and JAR 145 NDT certifications. He is involved also as coordinator in national and European research programs; since 2001, he has been responsible for nondestructive testing and structural health monitoring, as well as for the exploitation of technology research. Massimo Chimenti (Altopascio, 1946) is a senior scientist at ISTI-CNR, in Pisa, working in the field of signal and image formation, acquisition, and preprocessing. His scientific interests range from hardware design to software systems with specific applications in medical imaging. He is author of more than two hundred technical and scientific papers and he is also owner of more than ten patents regarding hardware and software systems for image acquisition and processing. He is at present leader of a research group in the Signals and Images Lab of ISTI working in the field of microwave and ultrasound imaging. Ovidio Salvetti, Director of Research at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is coauthor of four books and monographs and more than three hundred technical and scientific articles; he is also owner of ten patents regarding systems and software tools for image processing. He has been scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on “Vision and Image Understanding,” member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory.     

Real time object detection and tracking through a robotized system

The task of detection and tracking of a moving object is addressed. Algorithms have been developed which perform this task for monitoring and surveillance purposes. Prediction is also implemented in the algorithm to locate the target in order to keep it stationary in the center of the image, resolve events of occlusion or masking, and increase normal tracking performance. Real-time implementation generates deformation in target appearance, and then a shape database is used to improve these situations when a target is lost. A prototypical system has been developed that makes use of a moving camera located on a robotized system. A case study is presented about animal tracking in infrared live video. The text was submitted by the authors in English. Gabriele Pieri (Pescia, 1974), M. Sci. (2000) in Computer Science from the University of Pisa, since 2001 joined the “Signals and Images” Laboratory at ISTI-CNR, Pisa, working in the field of image analysis. His main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. He is the author of more than 20 papers. Marco Benvenuti, born in 1965. He received a degree in electronic engineering from the University of Florence in 1994. Since 2002 he is director of the Research and Development Department of TD Group Spa. Since 1994 he has been a researcher and consultant of the National Research Council of Italy and he collaborates with various private and public research institutions, charged as scientifically responsible of several national and international research projects. His fields of activity are related to data and image processing and integration for environmental monitoring and analysis, satellite and airborne remote sensing techniques, and GIS applications. He has long experience in international projects management and was reviewer of the EU Commission as an expert on remote sensing and GIS applications. He has been a consultant to certain international organizations, such as the World Meteorological Organisation, F.A.O., and the European Space Agency. In 1996 he was the Italian delegate to the Thematic Cooperation Group on Operational Environment Monitoring of the DG-XII (EC). He has publications and communications at the national and international level. Edoardo Carnier, born in 1962. He received a degree in computer science from the University of Pisa in 1997, developing a thesis on high order perceptron initialization. He has strong experience in image processing and analysis. He participated in the design and development of the SIRIO infrared system for environmental monitoring and, in particular, contributed to the study and implementation of tracking and motion detection algorithms. Since February 1998 he has been on the staff of the research and development group of TD Group Spa as project manager on a research project to realize an integrated system based on infrared technology for video-surveillance applications. Ovidio Salvetti, Director of Research at the Institute of Information Science and Technologies (ISTI) of the Italian National research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling and intelligent processes in computer vision. He is co-author of four books and monographs and more than three hundreds technical and scientific articles; he is also owner of ten patents regarding systems and software tools for image processing. He has been scientific coordinator of several National and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the Editorial Boards of the International Journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR Contact Person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on “Vision and Image Understanding,” Member of IEEE and of the Steering Committee of a number of EU Projects. He is Head of the ISTI “Signals and Images” Laboratory.     

A program specialiser for meta-level compositions of logic programs

Metal-level compositions of object logic programs are naturally implemented by means of meta-programming techniques. Metainterpreters defining program compositions however suffer from a computational overhead that is due partly to the interpretation layer present in all meta-programs, and partly to the specific interpretation layer needed to deal with program compositions. We show that meta-interpreters implementing compositions of object programs can be fruitfully specialised w.r.t. meta-level queries of the form Demo (E, G), where E denotes a program expression and G denotes a (partially instantiated) object level query. More precisely, we describe the design and implementation of declarative program specialiser that suitably transforms such meta-interpreters so as to sensibly reduce — if not to completely remove — the overhead due to the handling of program compositions. In many cases the specialiser succeeds in eliminating also the overhead due to meta-interpretation. Antonio Brogi, Ph.D.: He is currently assistant professor in the Department of Computer Science at the University of Pisa, Italy. He received his Laurea Degree in Computer Science (1987) and his Ph. D. in Computer Science (1993) from the University of Pisa. His research interests include programming language design and semantics, logic programming, deductive databases, and software coordination. Simone Contiero: He is currently a Ph. D. student at the Department of Computer Science, University of Pisa (Italy). He received his Laurea Degree in Computer Science from the University of Pisa in 1994. His research interests are in high-level programming languages, metaprogramming and logic-based coordination of software.