Cobot in LambdaMOO: An Adaptive Social Statistics Agent

We describe our development of Cobot, a novel software agent who lives in LambdaMOO, a popular virtual world frequented by hundreds of users. Cobot’s goal was to become an actual part of that community. Here, we present a detailed discussion of the functionality that made him one of the objects most frequently interacted with in LambdaMOO, human or artificial. Cobot’s fundamental power is that he has the ability to collect social statistics summarizing the quantity and quality of interpersonal interactions. Initially, Cobot acted as little more than a reporter of this information; however, as he collected more and more data, he was able to use these statistics as models that allowed him to modify his own behavior. In particular, cobot is able to use this data to “self-program,” learning the proper way to respond to the actions of individual users, by observing how others interact with one another. Further, Cobot uses reinforcement learning to proactively take action in this complex social environment, and adapts his behavior based on multiple sources of human reward. Cobot represents a unique experiment in building adaptive agents who must live in and navigate social spaces.     

Editorial

At the time of writing this editorial, subscribers will have just received their copies of the triple issue honouring the work of Rod Burstall. Coordinating this collection was a substantial undertaking; and thanks go to all concerned, particularly to David Rydeheard and Don Sannella and the behind the scenes production staff. We (the journal editors) hope you agree that it was well worth waiting for the fascinating collection. The production and scheduling of that set of papers, and other incidental but cumulative factors, have contributed to recent issues being late. We hope soon to be back close to our planned, evenly timed, publication timetable; however it also seems timely to mention, and to reiterate, some changes which are afoot. As of this issue (14.1) we shall revert to our initial publication frequency of 4 issues per year, but these will be larger than in earlier volumes and will retain the large page format adopted in Volume 12. [A reminder for authors who use LaTeX to use the new class files.] We are now receiving, and publishing, long papers (but still with the option of including supplementary material on the web) and, except in special issues, strive to achieve a reasonable coverage of topics within the given constraints. Although normally skipped over, readers of the journal front matter might notice periodic changes to the editorial board. These usually go unmentioned; our editors (who are working editors, not merely ‘names’) seek no reward or praise. Readers will also notice the recently modernised BCS-FACS logo and a declaration that the journal (although truly international in scope) was founded by (BCS-)FACS, some even to this day refer to it as ‘the FACS journal’, and we are very happy for this to continue. Bringing these two threads together gets me to the point of this digression. Dan Simpson founded the BCS specialist group on Formal Aspects of Computing Science some 25 years ago. Without his radical suggestion that the BCS had a specialist group that actually addressed Computer Science, there would have been no FACS and no FACS journal. Dan has recently finished his spell as Dean in the Faculty of IT at Brighton University and he has also resigned as a member of our editorial board. As you can see, he was active to the very end being responsible for progressing 2 of the 3 papers in this issue. I gather he now intends to concern himself with other matters; I would counsel a less stressful life and more Bob Dylan music. He has been a friend and colleague of many of those associated with the FACS group and its journal; on their behalf may I offer a big ‘thank you’ for all that you have done for us and offer our best wishes for whatever endeavours you are about to embark upon. Very many years ago, at a conference, I heard someone respond in debate “I didn't see who said that but it sounded like Mr Simpson from Teesside … .” – well it's no longer ‘Mr’ nor ‘Teesside’ but I can't believe that we really have seen or heard the last of this Yorkshire lad. Thanks, goodbye and good luck. It is with deep regret that we have to report the death of Ole-Johan Dahl. Professor Dahl was a leader of thought in many fields; his contributions on Object-Oriented languages and methods were recently recognised in his (joint) awards of the IEEE von Neumann prize and the ACM Turing Award. He was also a major contributor to Formal Methods and a future edition of this journal will attempt to mark his contribution. We have lost an editor; our thoughts are with his family who have lost so much more.au     

Family of models for describing one class of metallographic images

Models for images syntax are developed, tried, and tested in describing the syntax of microstructural metallographic images of wrought aluminum alloys. Gennadii Mikhailovich Tsibul’skii was born in 1947 and graduated from Krasnoyarsk Polytechnic Institute in 1973. Since 1975, he has been involved in the analysis of digital images. In 1978, he completed his postgraduate course at the Lenin Leningrad Electronic Technical Institute. He received his candidate’s degree in 1987 and a doctoral degree in engineering in 2006. He was appointed a professor in 2007. In 1996, he founded the Artificial Intelligence Systems Department and has worked there as a chairman since then. His scientific interests include the multiagent approach to images analysis, and he is the author of more than 70 publications (including one book published by the Siberian Branch of the Russian Academy of Sciences). At present, Gennadii Tsibul’skii is the director of the Space and Information Technologies Institute at Krasnoyarsk Siberian Federal University. Yurii Anatol’evich Maglinest was born 1965 and graduated from Krasnoyarsk Polytechnic Institute in 1973; he then pursued postgraduate studies there. He received his candidate’s degree in engineering in 1996 in the analysis of metallographic images. He is an associate professor at the State Commission for Academic Degrees and Titles of the Russian Federation. At present, he is a chair of the Scientific University Laboratory of Flexible Software Systems at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University. His scientific interests include aerospace information storage, processing and analysis, and flexible software systems. Dmitrii Al’bertovich Perfil’ev was born in 1968 and graduated from Krasnoyarsk Polytechnic Institute in 1992. Since 2000, he has been specializing in problems in digital images analysis and, in particular, in describing microstructural pictures of aluminum alloys. He received his candidate’s degree in engineering in 2007 and is the author of 8 publications related to the problem in question. At present, he is a researcher and a lecturer at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University.     

Mathematics for/from Society: The Role of the Module in Modernizing Japanese Architectural Production

This paper presents an examination of the process of the development of module in the works and theories of Japanese architect Ikebe Kiyoshi (1920-79). Ikebe based his idea of module on the belief that “Beauty is Mathematics.” He applied his ideas of module in various ways from the 1940s to the 1970s. Analyzing his ideas and works against their historical background, the social and creative meanings of the idea of module and of mathematics in architecture will be re-examined. This allows us to see how Ikebe developed his ideas of module from a characteristic mathematical approach, and how he developed his idea of mathematical logic into his creative theories based on the flexible nature of people’s lifestyles and social conditions. Going beyond the cultural and social differences and the limitations of Le Corbusier’s Modulor, the idea of module as the method for organizing human space in a harmonious manner was reframed in Ikebe’s works, and was developed in a more flexible mathematical way.     

The Body, the Temple and the Newtonian Man Conundrum

From his early days at the University of Cambridge until his death, Isaac Newton had a long running interest in the Temple of Solomon, a topic which appeared in his works on prophecy, chronology and metrology. At the same time that Newton was working on the Principia, he reconstructed the Temple and commented on the reconstructions of others. An important part of his investigations concerned the measurements of the Temple, which were harmonic and were built “exactly as the proportion of architecture demands.” Newton considered these proportions to be in accordance with Book III and IV of De Architectura. However, while insisting on exact architectural proportions, Newton moved away from the traditional proportions of the Vitruvian man; he derived a Newtonian man. This poses an interesting conundrum: Newton accepted the Temple’s architectural proportions as outlined in Vitruvius’s Book III, yet he rejected the human model Vitruvius used as the foundation of these proportions. At the same time Newton accepted the human frame as the basis of all ancient measurements and attempted to estimate the length of the sacred cubit based on the lengths of the parts for the body and the measurements set out by the ancient writers such a Vitruvius.     

Anisotropic Curvature Motion for Structure Enhancing Smoothing of 3D MR Angiography Data

We propose a novel concept of shape prior for the processing of tubular structures in 3D images. It is based on the notion of an anisotropic area energy and the corresponding geometric gradient flow. The anisotropic area functional incorporates a locally adapted template as a shape prior for tubular vessel structures consisting of elongated, ellipsoidal shape models. The gradient flow for this functional leads to an anisotropic curvature motion model, where the evolution is driven locally in direction of the considered template. The problem is formulated in a level set framework, and a stable and robust method for the identification of the local prior is presented. The resulting algorithm is able to smooth the vessels, pushing solution toward elongated cylinders with round cross sections, while bridging gaps in the underlying raw data. The implementation includes a finite-element scheme for numerical accuracy and a narrow band strategy for computational efficiency. Oliver Nemitz received his Diploma in mathematics from the university of Duisburg, Germany in 2003. Then he started to work on his Ph.D. thesis in Duisburg. Since 2005 he is continuing the work on his Ph.D. project at the Institute for Numerical Simulation at Bonn University. His Ph.D. subject is fast algorithms for image manipulation in 3d, using PDE’s, variational methods, and level set methods. Martin Rumpf received his Ph.D. in mathematics from Bonn University in 1992. He held a postdoctoral research position at Freiburg University. Between 1996 and 2001, he was an associate professor at Bonn University and from 2001 until 2004 full professor at Duisburg University. Since 2004 he is now full professor for numerical mathematics and scientific computing at Bonn University. His research interests are in numerical methods for nonlinear partial differential equations, geometric evolution problems, calculus of variations, adaptive finite element methods, image and surface processing. Tolga Tasdizen received his B.S. degree in Electrical Engineering from Bogazici University, Istanbul in 1995. He received the M.S. and Ph.D. degrees in Engineering from Brown University in 1997 and 2001. From 2001 to 2004 he was a postdoctoral research associate with the Scientific Computing and Imaging Institute at the University of Utah. Since 2004 he has been with the School of Computing at the University of Utah as a research assistant professor. He also holds an adjunct assistant professor position with the Department of Neurology and the Center for Alzheimer’s Care, Imaging and Research, and a research scientist position with the Scientific Computing and Imaging Institute at the University of Utah. Ross Whitaker received his B.S. degree in Electrical Engineering and Computer Science from Princeton University in 1986, earning Summa Cum Laude. From 1986 to 1988 he worked for the Boston Consulting Group, entering the University of North Carolina at Chapel Hill in 1989. At UNC he received the Alumni Scholarship Award, and completed his Ph.D. in Computer Science in 1994. From 1994–1996 he worked at the European Computer-Industry Research Centre in Munich Germany as a research scientist in the User Interaction and Visualization Group. From 1996–2000 he was an Assistant Professor in the Department of Electrical Engineering at the University of Tennessee. He is now an Associate Professor at the University of Utah in the College of Computing and the Scientific Computing and Imaging Institute.     

ScaleSpaceViz: α-Scale spaces in practice

Kernels of the so-called α-scale space have the undesirable property of having no closed-form representation in the spatial domain, despite their simple closed-form expression in the Fourier domain. This obstructs spatial convolution or recursive implementation. For this reason an approximation of the 2D α-kernel in the spatial domain is presented using the well-known Gaussian kernel and the Poisson kernel. Experiments show good results, with maximum relative errors of less than 2.4%. The approximation has been successfully implemented in a program for visualizing α-scale spaces. Some examples of practical applications with scale space feature points using the proposed approximation are given. The text was submitted by the authors in English. Frans Kanters received his MSc degree in Electrical Engineering in 2002 from the Eindhoven University of Technology in the Netherlands. Currently he is working on his PhD at the Biomedical Imaging and Informatics group at the Eindhoven University of Technology. His PhD work is part of the “Deep Structure, Singularities, and Computer Vision (DSSCV)” project sponsored by the European Union. His research interests include scale space theory, image reconstruction, image processing algorithms, and hardware implementations thereof. Luc Florack received his MSc degree in theoretical physics in 1989 and his PhD degree cum laude in 1993 with a thesis on image structure, both from Utrecht University, the Netherlands. During the period from 1994 to 1995, he was an ERCIM/HCM research fellow at INRIA Sophia-Antipolis, France, and IN-ESC Aveiro, Portugal. In 1996 he was an assistant research professor at DIKU, Copenhagen, Denmark, on a grant from the Danish Research Council. From 1997 to June 2001, he was an assistant research professor at Utrecht University in the Department of Mathematics and Computer Science. Since June 1, 2001, he has been working as an assistant professor and, then, as an associate professor at Eindhoven University of Technology, Department of Biomedical Engineering. His interest includes all multiscale structural aspects of signals, images, and movies and their applications to imaging and vision. Remco Duits received his MSc degree (cum laude) in Mathematics in 2001 from the Eindhoven University of Technology, the Netherlands. Today he is a PhD student at the Department of Biomedical Engineering at the Eindhoven University of Technology on the subject of multiscale perceptual organization. His interest subtends functional analysis, group theory, partial differential equations, multiscale representations and their applications to biomedical imaging and vision, perceptual grouping. Currently, he is finishing his thesis “Perceptual Organization in Image Analysis (A Mathematical Approach Based on Scale, Orientation and Curvature).” During his PhD work, several of his submissions at conferences were chosen as selected or best papers—in particular, at the PRIA 2004 conference on pattern recognition and image analysis in St. Petersburg, where he received a best paper award (second place) for his work on invertible orientation scores. Bram Platel received his Masters Degree cum laude in biomedical engineering from the Eindhoven University of Technology in 2002. His research interests include image matching, scale space theory, catastrophe theory, and image-describing graph constructions. Currently he is working on his PhD in the Biomedical Imaging and Informatics group at the Eindhoven University of Technology. Bart M. ter Haar Romany is full professor in Biomedical Image Analysis at the Department of Biomedical Engineering at Eindhoven University of Technology. He has been in this position since 2001. He received a MSc in Applied Physics from Delft University of Technology in 1978, and a PhD on neuromuscular nonlinearities from Utrecht University in 1983. After being the principal physicist of the Utrecht University Hospital Radiology Department, in 1989 he joined the department of Medical Imaging at Utrecht University as an associate professor. His interests are mathematical aspects of visual perception, in particular linear and non-linear scale-space theory, computer vision applications, and all aspects of medical imaging. He is author of numerous papers and book chapters on these issues; he edited a book on non-linear diffusion theory and is author of an interactive tutorial book on scale-space theory in computer vision. He has initiated a number of international collaborations on these subjects. He is an active teacher in international courses, a senior member of IEEE, and IEEE Chapter Tutorial Speaker. He is chairman of the Dutch Biophysical Society.     

Determination of user interfaces in adaptive systems using a rough classification-based method

This paper presents a novel method for user classification in adaptive systems based on rough classification. Adaptive systems could be used in many areas, for example in a user interface construction or e-Learning environments for learning strategy selection. In this paper the adaptation of web-based system user interface is presented. The goal of rough user classification is to select the most essential attributes and their values that group together users who are very much alike concerning the system logic. In order to group users we exploit their usage data taken from the user model of the adaptive web-based system user interface. We presented three basic problems for attribute selection that generates the following partitions: that is included, that includes and that is the closest to the given partition. Ngoc Thanh Nguyen, Ph.D., D.Sc.: He currently works as an associate professor at the Faculty of Computer Science and Management, Wroclaw University of Technology in Poland. He received his diplomas of M.Sc, Ph.D. and D.Sc. in Computer Science in 1986, 1989 and 2002, respectively. Actually, he is working on intelligent technologies for conflict resolution and inconsistent knowledge processing and e-learning methods. His teaching interests consist of database systems and distributed systems. He is a co-editor of 4 special issues in international journals, author of 3 monographs, editor of one book and about 110 other publications (book chapters, journal and refereed conference papers). He is an associate editor of the following journals: “International Journal of Computer Science & Application”; “Journal of Information Knowledge System Management”; and “International Journal of Knowledge-Based & Intelligent Engineering Systems”. He is a member of societies: ACM, IFIP WG 7.2, ISAI, KES International, and WIC. Janusz Sobecki, Ph.D.: He is an Assistant Professor in Institute of Applied Informatics (IAI) at Wroclaw University of Technology (WUT). He received his M. Sc. in Computer Science from Faculty of Computer Science and Management at WUT in 1986 and Ph.D. in Computer Science from Faculty of Electronics at WUT in 1994. For 1986–1996 he was an Assistant at the Department of Information Systems (DIS) at WUT. For 1988–1996 he was also a head of the laboratory at DIS. For 1996–2004 he was an Assistant Professor in DIS and since fall of 2004 at IAI, both at WUT. His research interests include information retrieval, multimedia information systems, system usability and recommender systems. He is on the editorial board of New Generation Computing and was a co-editor of two journal special issues. He is a member of American Association of Machinery.     

An American Vision of Harmony

Thomas Jefferson dedicated his later years to establishing the University of Virginia, believing that the availability of a public liberal education was essential to national prosperity and individual happiness. His design for the University stands as one of his greatest accomplishments and has been called “the proudest achievement of American architecture.” Taking Jefferson’s design drawings as a basis for study, this paper explores the possibility that he incorporated incommensurable geometric proportions in his designs for the Rotunda. Without actual drawings to illustrate specific geometric constructions, it cannot be said definitively that Jefferson utilized such proportions. But a comparative analysis between Jefferson’s plans and Palladio’s renderings of the Pantheon (Jefferson’s primary design source) suggests that both designs developed from similar geometric techniques.     

Evolution of fuzzy logic: from intelligent systems and computation to human mind

Inspired by human’s remarkable capability to perform a wide variety of physical and mental tasks without any measurements and computations and dissatisfied with classical logic as a tool for modeling human reasoning in an imprecise environment, Lotfi A. Zadeh developed the theory and foundation of fuzzy logic with his 1965 paper “Fuzzy sets” (Zadeh in Inf Control 8:378–53, 1965) and extended his work with his 2005 paper “Toward a generalized theory of uncertainty (GTU)—an outline” (Zadeh in Inf Control, 2005). Fuzzy logic has at least two main sources over the past century. The first of these sources was initiated by Peirce in the form what he called a logic of vagueness in 1900s, and the second source is Lotfi’s A. Zadeh work, fuzzy sets and fuzzy Logic in the 1960s and 1970s.     

Temporal disjunctive logic programming

In this paper we introduce the logic programming languageDisjunctive Chronolog which combines the programming paradigms of temporal and disjunctive logic programming. Disjunctive Chronolog is capable of expressing dynamic behaviour as well as uncertainty, two notions that are very common in a variety of real systems. We present the minimal temporal model semantics and the fixpoint semantics for the new programming language and demonstrate their equivalence. We also show how proof procedures developed for disjunctive logic programs can be easily extended to apply to Disjunctive Chronolog programs. Manolis Gergatsoulis, Ph.D.: He received his B.Sc. in Physics in 1983, the M.Sc. and the Ph.D. degrees in Computer Science in 1986 and 1995 respectively all from the University of Athens, Greece. Since 1996 he is a Research Associate in the Institute of Informatics and Telecommunications, NCSR ‘Demokritos’, Athens. His research interests include logic and temporal programming, program transformations and synthesis, as well as theory of programming languages. Panagiotis Rondogiannis, Ph.D.: He received his B.Sc. from the Department of Computer Engineering and Informatics, University of Patras, Greece, in 1989, and his M.Sc. and Ph.D. from the Department of Computer Science, University of Victoria, Canada, in 1991 and 1994 respectively. From 1995 to 1996 he served in the Greek army. From 1996 to 1997 he was a visiting professor in the Department of Computer Science, University of Ioannina, Greece, and since 1997 he is a Lecturer in the same Department. In January 2000 he was elected Assistant Professor in the Department of Informatics at the University of Athens. His research interests include functional, logic and temporal programming, as well as theory of programming languages. Themis Panayiotopoulos, Ph.D.: He received his Diploma on Electrical Engineering from the Department of Electrical Engineering, National Technical Univesity of Athens, in 1984, and his Ph.D. on Artificial Intelligence from the above mentioned department in 1989. From 1991 to 1994 he was a visiting professor at the Department of Mathematics, University of the Aegean, Samos, Greece and a Research Associate at the Institute of Informatics and Telecommunications of “Democritos” National Research Center. Since 1995 he is an Assistant Prof. at the Department of Computer Science, University of Piraeus. His research interests include temporal programming, logic programming, expert systems and intelligent agent architectures.     

Dennett’s Overlooked Originality

 No philosopher has worked harder than Dan Dennett to set the possibility of machine mentality on firm philosophical footing. Dennett’s defense of this possibility has both a positive and a negative thrust. On the positive side, he has developed an account of mental activity that is tailor-made for the attribution of intentional states to purely mechanical contrivances, while on the negative side, he pillories as mystery mongering and skyhook grasping any attempts to erect barriers to the conception of machine mentality by excavating gulfs to keep us “bona fide” thinkers apart from the rest of creation. While I think he’s “won” the rhetorical tilts with his philosophical adversaries, I worry that Dennett’s negative side sometimes gets the better of him, and that this obscures advances that can be made on the positive side of his program. In this paper, I show that Dennett is much too dismissive of original intentionality in particular, and that this notion can be put to good theoretical use after all. Though deployed to distinguish different grades of mentality, it can (and should) be incorporated into a philosophical account of the mind that is recognizably Dennettian in spirit.     

Fully automated segmentation of multiple sclerosis lesions in multispectral MRI

This paper addresses segmentation of multiple sclerosis lesions in multispectral 3-D brain MRI data. For this purpose, we propose a novel fully automated segmentation framework based on probabilistic boosting trees, which is a recently introduced strategy for supervised learning. By using the context of a voxel to be classified and its transformation to an overcomplete set of Haar-like features, it is possible to capture class specific characteristics despite the well-known drawbacks of MR imaging. By successively selecting and combining the most discriminative features during ensemble boosting within a tree structure, the overall procedure is able to learn a discriminative model for voxel classification in terms of posterior probabilities. The final segmentation is obtained after refining the preliminary result by stochastic relaxation and a standard level set approach. A quantitative evaluation within a leave-one-out validation shows the applicability of the proposed method. The text was submitted by the authors in English. Michael Wels was born in 1979 and graduated with a degree in computer science from the University of Wuerzburg in 2006. Currently, he is a member of the research staff at the University of Erlangen-Nuremberg’s Institute of Pattern Recognition working towards his Ph.D. His research interests are medical imaging in general and the application of machine learning techniques to medical image segmentation. Martin Huber studied at the University of Karlsruhe and received his Ph.D. degree in computer science in 1999. Since 1996, he has been with Siemens Corporate Technology and Siemens Medical Solutions. He currently is technical coordinator of the EU funded project Health-e-Child with research interests in medical imaging and semantic data integration. Joachim Hornegger graduated with a degree in computer science (1992) and received his Ph.D. in applied computer science (1996) at the University of Erlangen-Nuremberg (Germany). His Ph.D. thesis was on statistical learning, recognition, and pose estimation of 3-D objects. Joachim was a visiting scholar and lecturer at Stanford University (Stanford, CA, USA) during the 1997–1998 academic year, and, in 2007–2008, he was a visiting professor at Stanford’s Radiological Science Laboratory. In 1998, he joined Siemens Medical Solutions Inc., where he was working on 3D angiography. In parallel with his responsibilities in industry, he was a lecturer at the Universities of Erlangen (1998–1999), Eichstaett-Ingolstadt (2000), and Mannheim (2000–2003). In 2003, Joachim became Professor of Medical Imaging Processing at the University of Erlangen-Nuremberg, and, since 2005, he has been a chaired professor heading the Institute of Pattern Recognition. His main research topics are currently pattern recognition methods in medicine and sports.     

Tracking the activity of participants in a meeting

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

Segmentation of convex cells with partially undefined edges

This paper presents an algorithm for segmentation of convex cells with partially undefined edges based on application of a marker-controlled watershed transform to a combination of a source grayscale image and the result of a “geodesic distance” morphological operation, applied to the result of binarization of a source image. The presented approach is used in computer image processing systems for analysis of several industrial materials. The text was submitted by the authors in English. Ilia V. Safonov received his MS degree in automatic and electronic engineering from Moscow Engineering Physics Institute/University (MEPhI), Russia in 1994 and his PhD degree in computer science from MEPhI in 1997. Since 1998 he is an associate professor of faculty of Cybernetics of MEPhI while conducting researches in image segmentation, features extraction and pattern recognition problems. Since 2004, Dr. I. Safonov has joint Image Enhancement Technology Group, Printing Technology Lab, Samsung Research Center, Moscow, Russia where he is engaged in photo, video, and document image enhancement projects. Konstantin A. Kryzhanovsky received the MS degree in cybernetics from Moscow Engineering Physics Institute/University (MEPhI), Russia in 2000. Since 2006 he is an assistant professor of faculty of Cybernetics of MEPhI. He is presently working towards his Ph.D. degree. His current research interests include image processing and pattern recognition. Gennady N. Mavrin received his MS degree in automatic and electronic engineering from Moscow Engineering Physics Institute/University (MEPhI), Russia in 1998. Since 2002 he is an assistant professor of faculty of Cybernetics of MEPhI. He is currently pursuing the PhD degree. His research interests include image segmentation and feature extraction problems.     

Word confidence measure based on frame likelihood score

The automatic recognition of natural or close to natural speech is linked to the problem of detection of “new” or “unknown” words. These are the words or the nonverbal acoustical events that do not belong to the speech recognition system’s vocabulary. In this paper we consider a new method for the estimation of confidence score for words at the output of the recognition system based on a likelihood score of the signal frame. The method and confidence measure could be used, for example, for out-of-vocabulary (OOV) word detection and rejection. The text was submitted by the authors in English. Minh T. Nguyen received the MS degree in computer sciences from Moscow State University in 2004. In 2004 he began postgraduate studies at the Computing Centre, Russian Academy of Sciences. He is working on development and evaluation of confidence measures for speech recognition. Vladimir J. Chuchupal received the MS degree in mathematics from Moscow State Pedagogical Institute in 1976. He received his Candidate of Sciences degree from the Computing Centre, USSR Academy of Sciences, in 1984 completing his dissertation work in noisy speech enhancement methods. Since 1984 he has been with the Speech Recognition subdivision of the Computing Centre, Russian Academy of Sciences, where he works on speech recognition problems. Currently he is the head of the subdivision.     

Variable frame rate control jerkiness-driven

We are introducing a real-time variable frame rate control scheme capable of optimizing both spatial and temporal video qualities. It traces the motion of incoming video frames and automatically tunes the outgoing frame rate according to the level of jerkiness acceptable by the user. The control scheme was conceived within the framework of mobile communications, which require an optimum use of both the available bandwidth and terminal resources. We have designed and implemented a video transcoding architecture which supports our frame rate control. The transcoder has been developed at the Coritel laboratories, Rome, Italy (Coritel is a research consortium managed by Ericsson Lab, Italy, and the University of Rome La Sapienza), while the visual tests were carried out at the ISCOM laboratory, Italian Communication Ministry, Rome, Italy. The proposed transcoding architecture is compatible with the constraints of real-time communications and it has been extensively tested under a wide range of conditions. We then present a subjective assessment of our solution carried out in a fully equipped professional laboratory. Within this assessment a number of non-expert viewers were asked to express their preference when watching side by side the same video, coded at a variable frame rate and at a fixed frame rate. Results show that in most cases a variable frame rate control based on a dynamic bit/frame allocation scheme might substantially improve video quality perceived by viewers.

Intuition Pumps

The award of the 2003 Barwise Prize to Daniel Dennett by the American Philosophical Association signifies Dennett’s importance in the developing area of philosophical inquiry into computing and information. One source of Dennett’s intellectual stature is his command of scientific and engineering ideas, which he effectively applies to philosophical debates over machine intelligence, consciousness, and intentionality. Dennett regards the computer as both a model and a tool that will transform the ways that philosophy is pursued in the 21st century. In order to understand Dennett’s conception of how philosophy changes and fares, if his mechanistic and reductionist conception of the life of the mind succeeds, we turn to an examination of a central idea in Dennett’s thought: the intuition pump.