Analysis of window-constrained execution time systems

Feasibility tests for hard real-time systems provide information about the schedulability of the task set. However, this information is a yes or a no answer, that is, whether the task set achieves the test or not. From the real-time system design point of view, having more information available would be useful. For example, how much the computation time can vary without jeopardising the system feasibility. This work specifically provides methods to determine off-line how much a task can increase its computation time, by maintaining the system feasibility under a dynamic priority scheduling. The extra time can be determined not only in all the task activations, but in n of a window of m invocations. This is what we call a window-constrained execution time system. The results presented in this work can be used in all kinds of real-time systems: fault tolerance management, imprecise computation, overrun handling, control applications, etc. Patricia Balbastre is an assistant professor of Computer Engineering. She graduated in Electronic Engineering at the Technical University of Valencia, Spain, in 1998. And the Ph.D. degree in Computer Science at the same university in 2002. Her main research interests include real-time operating systems, dynamic scheduling algorithms and real-time control. Ismael Ripoll received the B.S. degree from the Polytechnic University of Valencia, Spain, in 1992; the Ph.D. degree in Computer Science at the Polytechnic University of Valencia, Spain, in 1996. Currently he is Professor in the DISCA Department of the same University. His research interests include embedded and real-time operating systems. Alfons Crespo is Professor of the Department of Computer Engineering of the Technical University of Valencia. He received the PhD in Computer Science from the Technical University of Valencia, Spain, in 1984. He held the position of Associate professor in 1986 and full Professor in 1991. He leads the group of Industrial Informatics and has been the responsible of several European and Spanish research projects. His main research interest include different aspects of the real-time systems (scheduling, hardware support, scheduling and control integration, …). He has published more than 60 papers in specialised journals and conferences in the area of real-time systems.     

Multisensor Demining Robot

The paper describes an advanced multisensor demining robot. The robot transport system is based on a simple structure using pneumatic drive elements. The robot has robust design and can carry demining equipment up to 100 kg over rough terrains. Due to the adaptive possibilities of pedipulators to obstacles, the robot can adjust the working position of the demining sensors while searching for mines. The detection block consists of a metal detector, an infrared detector, and a chemical explosive sensor. The robot is controlled by means of an on-board processor and by an operator remote station in an interactive mode. Experimental results of the transport, control, and detection systems of the robot are presented.Michael Yu. Rachkov is Professor of Automation at the Moscow State Industrial University. He graduated in Automatic Control Systems from Moscow Higher Technical School, 1979. He held academic posts at the Institute for Problems in Mechanics, Russian Academy of Sciences. In 1986 he completed his PhD in industrial robotics and received his DSc in mobile robotics in 1997. Professor Rachkov has been leading in several international projects like EUREKA and REMAPHOS. He has published over 170 papers and several books in the field of automation, robotics and optimal control. He is a member of Russian Cosmonautics Academy and International Informatization Academy.Lino Marques is a research engineer at the Institute of Systems and Robotics of the University of Coimbra. He received the Engineering and MsC. degrees in Electrical Engineering from the Faculty of Science and Technology of this University in 1992 and 1997 respectively. He is currently working toward the Ph.D. degree and teaching in the Electrical and Computer Engineering Department. His current research interests include sensors, mechatronics, mobile robotics and industrial automation.Anábal T. De Almeida graduated in Electrical Engineering, University of Porto, 1972, and received a Ph.D. in Electrical Engineering, from Imperial College, University of London, 1977. Currently he is a Professor in the Department of Electrical Engineering, University of Coimbra, and he is the Director of the Institute of Systems and Robotics since 1993. Professor De Almeida is a consultant of the European Commission Framework Programmes. He is the co-author of five books and more than one hundred papers in international journals, meetings and conferences. He has coordinated several European and national research projects.     

Oscillation amplitude-controlled resonant accelerometer design using a reference tracking automatic gain control

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project ST·IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the Korea Foundation for International Cooperation of Science & Technology(KICOS) through a grant provided by the Korean Ministry of Education, Science & Technology(MEST) in 2008 (No. K20601000001). Authors also thank to Dr. B.-L. Lee for the help in structure manufacturing. Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, navigation filter, and intelligent vehicle systems. Chang-Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems. Jungkeun Park is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University. Dr. Park received the Ph.D. in Electrical Engineering and Computer Science from the Seoul National University in 2004. His current research interests include embedded real-time systems design, real-time operating systems, distributed embedded real-time systems and multimedia systems. Joon Goo Park is an Assistant Professor of the Department of Electronic Engineering at Gyung Book National University, Korea. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2001. His research interests include mobile navigation and adaptive control.     

Robust fault detection filter design for uncertain LTI systems based on new bounded real lemma

This paper concerns the problem of robust fault detection filter design for uncertain linear time-invariant (LTI) systems with both model uncertainty and disturbances. Firstly, the fault detection filter design is formulated to H _∞ model-matching problem. Secondly, based on a new bounded real lemma, a sufficient condition for the existence of the robust fault detection filter is constructed in term of linear matrix inequalities (LMIs). Owing on the introduction of the tuning parameter and slack variables in obtained LMI condition, the proposed design method can provide higher fault detection sensitivity performance than the existing one. Finally, an illustrative example is employed to demonstrate the effectiveness of the proposed approach. Recommended by Editorial Board member Bin Jiang under the direction of Editor Jae Weon Choi. This work was supported by Postdoctoral Fundation of Jiangsu Province under grant 0901026c and Key Laboratory of Education Ministry for Image Processing and Intelligent Control under grant 200805. Tao Li received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a postdoctoral researcher with the same university. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Lingyao Wu received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Xinjiang Wei was born in Dongying, China, in 1977. He received the B.S. degrees from Yantai Normal University, China in 1999, M.S. degrees from Bohai University in 2002, and the Ph.D. degree in Department of Information from Northeastern University in 2005. From 2006 to Present, he was with Ludong University as an Associate Professor. From 2006 to 2009, he was a Postdoctoral Fellow at Southeast University. His research interests include robust control, nonlinear control, and fuzzy control.     

Implementation of algebraic controllers for non-conventional sampled-data systems

Nowadays, in industrial control applications, is rather usual to sample and update different variables at different rates, although it is common to consider all these activities equally and regularly spaced on time. These applications are implemented on real-time operating systems by decomposing them into several tasks in such a way that pre-emption and blocking may appear due to task priorities and resource sharing. This could imply the presence of delays, leading to a non-regular periodic behaviour and, as a result, the control performance can be degraded. In order to undertake this problem, a solution based on a modelling methodology for non-conventional sampled-data systems is proposed. This technique permits the consideration of any cyclic sampling pattern. Thus, these delays can be considered in the modelling step, and later on, a non-conventional controller based on this model can be designed. In this way, if the considered non-conventional control system is implemented assuming a real-time operating system (Tornado-VxWorks, in this case), a clear performance improvement can be observed. ángel Cuenca was born in Valencia (Spain) in 1974. He received his M.Sc. degree in Computer Science in 1998 and his Ph.D. in Control Engineering in 2004, from the Polytechnic University of Valencia. He is with the department of Systems Engineering and Control at the Polytechnic University of Valencia. He has been teaching courses on systems theory, programmable logic controllers and multi-rate sampled-data systems. His research interests include non-conventionally sampled-data systems and networked based control systems. He has taken part in several national and European research projects. Julian Salt was born in Valencia, Spain in 1960. He received his M.Sc. degree in industrial engineering in 1986 and his Ph.D. in Control Engineering in 1992, from Valencia Polytechnic University. His current position is as Professor of Automatic Control (2000-), Valencia Polytechnic University (UPV), teaching a wide range of subjects in the area from continuous and discrete simulation to automation and programmable logic controllers applications. His research interests include non-conventionally sampled control systems and networked based control systems. He has taken part in research projects funded by local industries, government and the European Science Foundation. He has also been involved in educational projects and currently is Head of the Systems Engineering and Control Department at UPV. He has been director of 8 PhD thesis and coauthor of about 60 technical papers in journals and technical meetings. Pedro Albertos, full Professor since 1975, currently at the Dept of Systems Engineering and Control at the Polytechnic University of Valencia, Spain. He has been Director from 1979 to 1995 and in 1998. He has been teaching courses on Advanced Control Systems, Intelligent Control Systems and Systems Theory. He is Honorary Profesor at the Northwestern University, Senhyang, China and Doctor Honoris Causa at the Universities of Oulu (Finland) and Polytechnic of Bucarest (Rumania). Invited Professor in more than 20 Universities, all around the world, he has delivered seminars in more than 30 universities and research centres. Authored more than 300 papers, book chapters and congress communications, he is co-editor of 7 books and co-author of Multivariable Control Systems (Springer 2004). He has directed 16 PhD thesis, and he is the coordinator of the PhD Program on Automatica and Industrial Informatics, which has been implemented in Spain, Mexico, Columbia and Venezuela. He has participated in many national and international research projects. Currently is involved in the ARTIST2 Node of Excellence on Embedded Control Systems. He is associated editor of Control Engineering Practice and Automatica and editor in chief of the journal Revista RIAI (Revista Iberoamericana de Automática e Informática Industrial). In the period 1999–2002 he was the IFAC President.     

Relative positioning for team robot navigation

The research presented in this paper approaches the issue of robot team navigation using relative positioning. With this approach each robot is equipped with sensors that allow it to independently estimate the relative direction of an assigned leader. Acoustic sensor systems are used and were seen to work very effectively in environments where datum relative positioning systems (such as GPS or acoustic transponders) are typically ineffective. While acoustic sensors provide distinct advantages, the variability of the acoustic environment presents significant control challenges. To address this challenge, directional control of the robot was accomplished with a feed forward neural network trained using a genetic algorithm, and a new approach to training using recent memories was successfully implemented. The design of this controller is presented and its performance is compared with more traditional classic logic and behavior controllers. Patrick McDowell received his bachelor's degree in Computer Science in 1984 from the University of Idaho. He spent the next 15 years working as a computer scientist for a small defense contractor where he specialized in real time data acquisition, application development, and image processing. In 1999 he received his master's degree in computer science from the University of Southern Mississippi. In 2000 he began work at the Naval Research Lab where he has focused on application of machine learning techniques to autonomous underwater navigation. In 2005 he received his Ph.D. in Computer Science from Louisiana State University. His research interests include legged robotics, machine learning, and artificial intelligence. In Fall of 2006 he joined Southeastern Louisiana University as an assistant professor of Computer Science. Brian S. Bourgeois received his Ph.D. in Electrical Engineering from Tulane University located in New Orleans, LA in 1991. Since then he has worked at the Stennis Space Center, MS detachment of the Naval Research Laboratory. He has worked on research projects spanning an array of technologies including airborne survey sytems, acoustic backscattering, bathymetry and imaging sonar systems, the ORCA unmanned underwater vehicle and the development of an autonomous survey system for hydrographic survey ships. He is presently the head of the Position, Navigation and Timing team at NRL with research interests including underwater positioning and communications and autonomous navigation. Ms. McDowell received her M.S. in Applied Physics in 2002 from the University or New Orleans. She is presently a candidate for a Ph. D. in Engineering and Applied Science. She joined the Naval Research Laboratory in 1991 as a research engineer and has spent most of that time working in experimental and theoretical acoustic modeling. Ms. McDowell's specific research interest lie in the areas of sonar performance analysis. Dr. S. S. Iyengar is the Chairman and Roy Paul Daniels Chaired Professor of Computer Science at Louisiana State University and is also Satish Dhawan Chaired Professor at Indian Institute of Science. He has been involved with research in high-performance algorithms, data structures, sensor fusion, data mining, and intelligent systems since receiving his Ph.D. degree (1974) and his M.S. from the Indian Institute of Science (1970). He has been a consultant to several industrial and government organizations (JPL, NASA etc.). In 1999, Professor Iyengar won the most prestigious research award titled Distinguished Research Award and a university medal for his research contributions in optimal algorithms for sensor fusion/image processing. Dr. Jianhua Chen received her Ph.D. in computer science in 1988 from Jilin University, Chang Chun, China. In August 1988, She joined the Computer Science Department of Louisiana State University, Baton Rouge, USA, where she is currently an associate professor. Dr. Chen's research interests include Machine Learning and Data Mining, Fuzzy Sets and Systems, Knowledge Representation and Reasoning.     

Relaxed stability condition and state feedback H ∞ controller design for T-S fuzzy systems

In this paper, a fuzzy Lyapunov approach is presented for stability analysis and state feedback H _∞ controller design for T-S fuzzy systems. A new stability condition is obtained by relaxing the ones derived in previous papers. Then, a set of LMI-based sufficient conditions which can guarantee the existence of state feedback H _∞ controller for T-S fuzzy systems is proposed. In comparison with the existing literature, the proposed approach not only provides more relaxed stability conditions but also ensures better H _∞ performance. The effectiveness of the proposed approach is shown through two numerical examples. Recommended by Editor Young-Hoon Joo. Xiao-Heng Chang received the B.E. and M.S. degrees from Liaoning Technical University, China, in 1998 and 2004, respectively, and the Ph.D. degree from Northeastern University, China, in 2007. He is currently a Lecturer in the School of Information Science and Engineering, Bohai University, China. His research interests include fuzzy control and robust control as well as their applications. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, nonfragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society.     

Robust H∞ Filter Design for 2D Discrete Systems in Roesser Model

This paper investigates the robust H∞ filtering problem for uncertain two-dimensional (2D) systems described by the Roesser model. The parameter uncertainties considered in this paper are assumed to be of polytopie type. A new structured polynomi-ally parameter-dependent method is utilized, which is based on homogeneous polynomially parameter-dependent matrices of arbitrary degree. The proposed method includes results in the quadratic framework and the linearly parameter-dependent framework as special cases for zeroth degree and first degree, respectively. A numerical example illustrates the feasibility and advantage of the proposed filter design methods.     

Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach. Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Young-Hoon Joo. This work was supported by the National Science foundation of China under Grant no. 60774013 and Key Laboratory of Education Ministry for Image Processing and Intelligent Control under grant no. 200805. Tao Li received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in Department of Information and Communication, Nanjing University of Information Science and Technology. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Lei Guo received the Ph.D. degree in the Research Institute of Automation Southeast University, China. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now He is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. His current research interests include robust control, fault detection and diagnosis. Lingyao Wu received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Changyin Sun received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a Professor in the Research Institute of Automation Southeast University. His current research interests include timedelay systems, neural networks.     

Design and performance analysis of tracking controller for uncertain nonlinear composite system using neural networks

Based on high order dynamic neural network, this paper presents the tracking problem for uncertain nonlinear composite system, which contains external disturbance, whose nonlinearities are assumed to be unknown. A smooth controller is designed to guarantee a uniform ultimate boundedness property for the tracking error and all other signals in the dosed loop. Certain measures are utilized to test its performance. No a priori knowledge of an upper bound on the “optimal” weight and modeling error is required; the weights of neural networks are updated on-line. Numerical simulations performed on a simple example illustrate and clarify the approach.     

Visual wheel sinkage measurement for planetary rover mobility characterization

Wheel sinkage is an important indicator of mobile robot mobility in natural outdoor terrains. This paper presents a vision-based method to measure the sinkage of a rigid robot wheel in rigid or deformable terrain. The method is based on detecting the difference in intensity between the wheel rim and the terrain. The method uses a single grayscale camera and is computationally efficient, making it suitable for systems with limited computational resources such as planetary rovers. Experimental results under various terrain and lighting conditions demonstrate the effectiveness and robustness of the algorithm. Christopher Brooks is a graduate student in the Mechanical Engineering department of the Massachusetts Institute of Technology. He received his B.S. degree with honor in engineering and applied science from the California Institute of Technology in 2000, and his M.S. degree from the Massachusetts Institute of Technology in 2004. He is a student collaborator on the Mars Exploration Rover science mission. His research interests include mobile robot control, terrain sensing, and their application to improving autonomous robot mobility. He is a member of Tau Beta Pi. Karl Iagnemma is a research scientist in the Mechanical Engineering department of the Massachusetts Institute of Technology. He received his B.S. degree summa cum laude in mechanical engineering from the University of Michigan in 1994, and his M.S. and Ph.D. from the Massachusetts Institute of Technology, where he was a National Science Foundation graduate fellow, in 1997 and 2001, respectively. He has been a visiting researcher at the Jet Propulsion Laboratory. His research interests include rough-terrain mobile robot control and motion planning, robot-terrain interaction, and robotic mobility analysis. He is author of the monograph Mobile Robots in Rough Terrain: Estimation, Motion Planning, and Control with Application to Planetary Rovers (Springer, 2004). He is a member of IEEE and Sigma Xi. Steven Dubowsky received his Bachelor's degree from Rensselaer Polytechnic Institute of Troy, New York in 1963, and his M.S. and Sc.D. degrees from Columbia University in 1964 and 1971. He is currently a Professor of Mechanical Engineering at M.I.T and Director of the Mechanical Engineering Field and Space Robotics Laboratory. He has been a Professor of Engineering and Applied Science at the University of California, Los Angeles, a Visiting Professor at Cambridge University, Cambridge, England, and Visiting Professor at the California Institute of Technology. During the period from 1963 to 1971, he was employed by the Perkin-Elmer Corporation, the General Dynamics Corporation, and the American Electric Power Service Corporation. Dr. Dubowsky's research has included the development of modeling techniques for manipulator flexibility and the development of optimal and self-learning adaptive control procedures for rigid and flexible robotic manipulators. He has authored or co-authored nearly 300 papers in the area of the dynamics, control and design of high performance mechanical and electromechanical systems. Professor Dubowsky is a registered Professional Engineer in the State of California and has served as an advisor to the National Science Foundation, the National Academy of Science/Engineering, the Department of Energy, and the US Army. He is a fellow of the ASME and IEEE and is a member of Sigma Xi and Tau Beta Pi.     

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.     

Combination of clock-state and clock-rate correction in fault-tolerant distributed systems

This paper proposes the integration of internal and external clock synchronization by a combination of a fault-tolerant distributed algorithm for clock state correction with a central algorithm for clock rate correction. By means of hardware and simulation experiments it is shown that this combination improves the precision of the global time base in a distributed single cluster system while reducing the need for high-quality oscillators. Simulation results have shown that the rate-correction algorithm contributes not only in the internal clock synchronization of a single cluster system, but it can be used for external clock synchronization of a multi-cluster system with a reference clock. Therefore, deployment of the rate-correction algorithm integrates internal and external clock synchronization in one mechanism. Experimental results show that a failure in the clock rate correction will not hinder the distributed fault-tolerant clock state synchronization algorithm, since the state correction operates independently from the rate correction. The paper introduces new algorithms and presents experimental results on the achieved improvements in the precision measured in a time-triggered system. Results of simulation experiments of the new algorithms in single-cluster and multi-cluster configurations are also presented. Hermann Kopetz (Fellow, IEEE) received the Ph.D. degree in physics ísub auspiciis praesidentis from the University of Vienna, Vienna, Austria, in 1968. He was Manager of the Computer Process Control Department at Voest Alpine, Linz, Austria, and Professor of Computer Process Control, Technical University of Berlin, Berlin, Germany. He is currently Professor of Real-Time Systems, Vienna University of Technology, Vienna, Austria, and a Visiting Professor at the University of California, Irvine, and the University of California, Santa Barbara. In 1993, he was offered a position as Director of the Max Planck Institute, Saarbrcken, Germany. Prof. Kopetz is the key architect of the Time-Triggered Architecture. Astrit Ademaj (IEEE member) received the Dipl-Ing. degree (1995) at the University of Prishtina, Kosova, and a doctoral degree (2003) in computer science from the Technical University of Vienna. He is currently working as Assistant Professor at the Technical University of Vienna and as a Visiting Lecturer at the University of Prishtina. His research interests are design and validation of communication systems for safety-critical and real-time applications. He is a member of the IEEE Computer Society. Alexander Hanzlik received a diploma (1995) and a doctoral degree (2004) in computer science from the Technical University of Vienna. From 1995 to 1998, he was concerned with voice communication system design for air traffic control for the Service de Navigation Aérienne (STNA). Since 1998, his focus is on embedded systems in the fields of telecommunication, automation and process control. Since 2001, Dr. Hanzlik is a member of the Real-Time Systems Group and works as a research assistant at the Technical University of Vienna. His main research activities deal with fault-tolerant clock synchronization in distributed systems and simulation. Currently, he is working on SIDERA, a simulation model for time-triggered, dependable real-time architectures.     

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.     

Automatic transaction of signal via statistical modeling

The statistical information processing can be characterized by the likelihood function defined by giving an explicit form for an approximation to the true distribution. This mathematical representation, which is usually called a model, is built based on not only the current data but also prior knowledge on the object and the objective of the analysis. Akaike^2,3) showed that the log-likelihood can be considered as an estimate of the Kullback-Leibler (K-L) information which measures the similarity between the predictive distribution of the model and the true distribution. Akaike information criterion (AIC) is an estimate of the K-L information and makes it possible to evaluate and compare the goodness of many models objectively. In consequence, the minimum AIC procedure allows us to develop automatic modeling and signal extraction procedures. In this article, we give a simple explanation of statistical modeling based on the AIC and demonstrate four examples of applying the minimum AIC procedure to an automatic transaction of signals observed in the earth sciences. Genshiro, Kitagawa, Ph.D.: He is a Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He is currently Deputy Director of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University for Advanced Study. He obtained his Ph.D. from the Kyushu University in 1983. His primary research interests are in time series analysis, non-Gaussian nonlinear filtering, and statistical modeling. He has published over 50 research papers. He was awarded the 2nd Japan Statistical Society Prize in 1997. Tomoyuki Higuchi, Ph.D.: He is an Associate Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He is currently an Associate Professor of Statistical Science at the Graduate University for Advanced Study. He obtained his Ph.D. from the University of Tokyo in 1989. His research interests are in statistical modeling of space-time data, stochastic optimization techniques, and data mining. He has published over 30 research papers.     

A grid-oriented genetic algorithm framework for bioinformatics

In this paper, we propose a framework for enabling for researchers of genetic algorithms (GAs) to easily develop GAs running on the Grid, named “Grid-Oriented Genetic algorithms (GOGAs)”, and actually “Gridify” a GA for estimating genetic networks, which is being developed by our group, in order to examine the usability of the proposed GOGA framework. We also evaluate the scalability of the “Gridified” GA by applying it to a five-gene genetic network estimation problem on a grid testbed constructed in our laboratory. Hiroaki Imade: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2001. He received the M.S. degree in information systems from the Graduate School of Engineering, The University of Tokushima in 2003. He is now in Doctoral Course of Graduate School of Engineering, The University of Tokushima. His research interests include evolutionary computation. He currently researches a framework to easily develop the GOGA models which efficiently work on the grid. Ryohei Morishita: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2002. He is now in Master Course of Graduate School of Engineering, The University of Tokushima, Tokushima. His research interest is evolutionary computation. He currently researches GA for estimating genetic networks. Isao Ono, Ph.D.: He received his B.S. degree from the Department of Control Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 1994. He received Ph.D. of Engineering at Tokyo Institute of Technology, Yokohama, in 1997. He worked as a Research Fellow from 1997 to 1998 at Tokyo Institute of Technology, and at University of Tokushima, Tokushima, Japan, in 1998. He worked as a Lecturer from 1998 to 2001 at University of Tokushima. He is now Associate Professor at University of Tokushima. His research interests include evolutionary computation, scheduling, function optimization, optical design and bioinformatics. He is a member of JSAI, SCI, IPSJ and OSJ. Norihiko Ono, Ph.D.: He received his B.S. M.S. and Ph.D. of Engineering in 1979, 1981 and 1986, respectively, from Tokyo Institute of Technology. From 1986 to 1989, he was Research Associate at Faculty of Engineering, Hiroshima University. From 1989 to 1997, he was an associate professor at Faculty of Engineering, University of Tokushima. He was promoted to Professor in the Department of Information Science and Intelligent Systems in 1997. His current research interests include learning in multi-agent systems, autonomous agents, reinforcement learning and evolutionary algorithms. Masahiro Okamoto, Ph.D.: He is currently Professor of Graduate School of Systems Life Sciences, Kyushu University, Japan. He received his Ph.D. degree in Biochemistry from Kyushu University in 1981. His major research field is nonlinear numerical optimization and systems biology. His current research interests cover system identification of nonlinear complex systems by using evolutional computer algorithm of optimization, development of integrated simulator for analyzing nonlinear dynamics and design of fault-tolerant routing network by mimicking metabolic control system. He has more than 90 peer reviewed publications.     

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

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

Test minimization for human-computer interaction

This paper introduces a model-based approach for minimization of test sets to validate the interaction of human-computer systems. The novelty of the approach is twofold: (i) Test cases generated and selected holistically cover both the behavioral model and the complementary, fault model of the system under test (SUT). (ii) Methods known from state-based conformance testing and graph theory are extended to construct efficient, heuristic search-based algorithms for minimizing the test sets that are constructed in step (i), considering also structural features. Experience shows that the approach can help to considerably save test costs, up to 60% Fevzi Belli received the M.S., Ph.D., and Habilitation degrees in electrical engineering and computer science from the Berlin Technical University. He is presently a Professor of Software Engineering in the Faculty of Computer Science, Electrical Engineering and Mathematics, University of Paderborn, Paderborn, Germany. Prior to this, he headed several projects at a software house in Munich, was a Professor of Computing Science at the Hochschule Bremerhaven and a faculty member of the University of Maryland, European Division. He chaired several international conferences, e.g., ISSRE 1998 and is author and co-author of more than 100 papers published in scientific journals and conference proceedings. His research interests are in testing/fault tolerance/reliability of software and programming techniques. Christof J. Budnik received the MS degree in electrical engineering and computer science in 2001 from the University of Paderborn. In 2002, he joined the Department of Computer Science, Electrical Engineering and Mathematics at the same University where he is currently a faculty member. His research interests are in the areas of software quality, testing of interactive systems and safety-critical user interfaces.