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INFOCOM 2006: 25th Ieee International Conference on computer Communications

作者： Callegati, F. Aracil, J. Wosinska, L. Andriolli, N. Careglio, D. Giorgetti, A. Fdez-Palacios, J. Gauger, C. Klinkowski, M. Gonzáles De Dios, O. Hu, G. Karasan, e. Matera, F. Overby, H. Raffaelli, C. Rea, L. Sengezer, N. Tornatore, M. Vlachos, K. D.E.I.S. Unversity of Bologna Viale Risorgimento 2 40123 Bologna Italy Escuela Politecnica Superior Universidad Autonoma de Madrid Campus de Cantoblanco 28049 Madrid Spain Isafjordsgatan 24 164 40 Kista Sweden Scuola Superiore sant'Anna Via Moruzzi 1 56124 Pisa Italy Univeristat Politcnica de Catalunya Jordi Girona 1-3 08034 Barcelona Spain Telefónica Investigación y Desarrollo C/ Emilio Vargas N 6 28043 Madrid Spain University of Stuttgart IKR Pfaffenwaldring 47 70569 Stuttgart Germany Bilkent Universitesi Elektrik Elektronik Muhendisligi PK:06800 Ankara Turkey Fondazione Ugo Bordoni via B. Castiglione 59 00142 Roma Italy Norwegian University of Science and Technology O. S. Bragstadsplass 2B Norway Dipartimento di Elettronica e Informazione Politecnico di Milano Via Ponzio 34/5 20133 Milano Italy Computer Engineering and Informatics Dept. University of Patras GR26500 Rio Greece

This papers reports the advances in Optical Core networks research coordinated in the framework of the e-Photon/ONe and e-Photon/ONe+ networks of excellence.

ISBN: (纸本)1424402212

This papers reports the advances in Optical Core networks research coordinated in the framework of the e-Photon/ONe and e-Photon/ONe+ networks of excellence.

关键词： Optical communication

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Power b.eakdown analysis for a heterogeneous NoC platform running a video application

Power breakdown analysis for a heterogeneous NoC platform ru...

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Ieee 16th International Conference on Application-Specific Systems, Architectures, and Processors, ASAP 2005

作者： Lamb.echts, Andy Raghavan, Praveen Leroy, Anthony Talavera, Guillermo Aa, Tom Vander Jayapala, Murali Catthoor, Francky Verkest, Diederik Deconinck, Geert Corporaal, Henk Robert, Frédéric Carrabina, Jordi IMEC vzw Belgium Dept of Electrical Engineering K.U.L. Belgium Dept of Electrical Engineering V.U.B. Belgium MiEL U.L.B. Belgium Dept of Computer Science U.A.B. Spain Dept of Electrical Engineering TU/e Netherlands

ISBN: (纸本)0769524079

Users expectifuture handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on performance and power consumption and forces designers to optimize all parts of their platform. evaluating the overall platform power b.eakdown is therefore critical to determine where to spend the efforts on power optimization. Surprisingly, few studies exist on that topic and decisions generally rely on common belief. We have realized a complete power b.eakdown for a realistic platform to identify the major power bottlenecks. This paper presents this power assessment of a realistic heterogeneous network on chip platform including processors, network and data/instruction memory hierarchy, running a video processing chain from camera to display. Our power b.eakdown identifies the main bottle-necks in the memory hierarchy and the foreground memory, and shows that global interconnect is not that critical for a well-optimizediapplication mapping. © 2005 Ieee.

关键词： Hand held computers

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Reinforcement learning in swarms that learn

Reinforcement learning in swarms that learn

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2005 Ieee/WIC/ACM International Conference on Intelligent Agent Technology

作者： Peters, James F. Henry, Christopher Ramanna, Sheela University of Manitoba Department of Electrical and Computer Engineering 15 Gillson St. Winnipeg Man. R3T 5V6 Canada Department of Applied Computer Science University of Winnipeg Winnipeg Man. R3B 2E9 Canada

ISBN: (纸本)0769524168

This paper introduces an approach to reinforcement learning by cooperating agents using a variation of the. actor critic method. This is made possib.e by considering behavior patterns of swarms in the context of approximation spaces. Rough set theory introduced by Zdzislaw Pawlak in 1982 provides a ground for deriving pattern-based rewards within approximation spaces. The framework provided by an approximation space makes it possib.e to derive pattern-based reference rewards used to estimate action preferences. Approximation spaces are used to derive action-based reference rewards at the swarm intelligence level. Two different forms of the actor critic reinforcement learning method are considered as a part of a study of learning in real-time by a swarm. The contribution of this article is the presentation of a new actor critic method defined in the context of approximation spaces. An ecosystem designed to facilitate study of reinforcement learning by swarms is briefly described. In addition, the results of ecosystem experiments for two forms of the actor critic method are given. © 2005 Ieee.

关键词： Learning systems

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Reinforcement learning with pattern-based rewards

Reinforcement learning with pattern-based rewards

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IASTeD International Conference on Computational Intelligence

作者： Peters, James F. Henry, Christopher Ramanna, Sheela Department of Electrical and Computer Engineering University of Manitoba 15 Gillson Street ENGR 504 Winnipeg Man. R3T 5V6 Canada Department of Applied Computer Science University of Winnipeg Winnipeg Man. R3B 2E9 Canada

ISBN: (纸本)0889864810

This paper introduces an approach to deriving pattern-based rewards during reinforcement learning by cooperating agents. Rough set theory introduced by Zdzislaw Pawlak in 1982 provides a ground for deriving pattern-based rewards in the context of approximation spaces. The framework provided by an approximation space makes it possib.e to derive pattern-based reference rewards used to compute action rewards as well as action preferences. Approximation spaces are used to derive action-based reference rewards at the swarm intelligence level. Two different forms of reinforcement comparison are considered as a part of a study of learning in real-time by a swarm. In addition, this article introduces an artificial ecosystem testbed that makes it possib.e to study learning by collections of biologically-inspired bots. The contribution of this article is the introduction of an approach to rewarding swarm behavior in the context of approximation spaces.

关键词： Learning systems

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Monte Carlo off-policy reinforcement learning: A rough set approach

Monte Carlo off-policy reinforcement learning: A rough set a...

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HIS 2005: Fifth International Conference on Hybrid Intelligent Systems

作者： Peters, James F. Lockery, Daniel Ramanna, Sheela University of Manitoba Department of Electrical and Computer Engineering 15 Gillson St. Winnipeg Man. R3T 5V6 Canada Department of Applied Computer Science University of Winnipeg Winnipeg Man. R3B 2E9 Canada

ISBN: (纸本)0769524575

This paper introduces a rough set approach to reinforcement learning by cooperating agents using a variation of the Monte Carlo off-policy control method. The prob.em considered in this article is how to measure the value of a state relative to the collections of similar behaviors and select an optimal policy. The solution to this prob.em is made possib.e by considering behavior patterns of swarms in the context of approximation spaces, which provide a framework for computing rough inclusion values for weights in estimating the value of a swarm state. Two different forms of the Monte Carlo off-policy reinforcement learning method are considered as a part of a study of learning in real-time by a swarm. The contribution of this article is the presentation of a new Monte Carlo off-policy control method defined in the context of approximation spaces. The ecosystem provided by swarms of zebra danio fish (brachydanio Rerio) has b.en selected to facilitate study of reinforcement learning. This ecosystem is briefly described. In addition, the results of experiments using reinforcement learning techniques to simulate swarm behavior of the zebra danio ecosystem for two forms of the Monte Carlo off-policy control method are given. © 2005 Ieee.

关键词： Learning algorithms

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Power b.eakdown analysis for a heterogeneous NoC platform running a video application

Power breakdown analysis for a heterogeneous NoC platform ru...

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International Conference on Application Specific Systems (ASAP), Architectures and Processors

作者： A. Lamb.echts P. Raghavan A. Leroy G. Talavera T.V. Aa M. Jayapala F. Catthoor D. Verkest G. Deconinck H. Corporaal F. Robert J. Carrabina Department of Electrical Engineering K.U. Leuven Belgium Dept of Electrical Engineering K.U.L Belgium IMEC vzw Belgium MiEL U.L.B Belgium Dept of Computer Science U.A.B Spain Dept of Electrical Engineering V.U.B Belgium Dept of Electrical Engineering TU/e The Netherlands

Users expect future handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on performance and power consumption and forces designers to optimize all parts of their platform. evaluating the overall platform power b.eakdown is therefore critical to determine where to spend the efforts on power optimization. Surprisingly, few studies exist on that topic and decisions generally rely on common belief. We have realized a complete power b.eakdown for a realistic platform to identify the major power bottlenecks. This paper presents this power assessment of a realistic heterogeneous network on chip platform including processors, network and data/instruction memory hierarchy, running a video processing chain from camera to display. Our power b.eakdown identifies the main bottlenecks in the memory hierarchy and the foreground memory, and shows that global interconnect is not that critical for a well-optimized application mapping.

关键词： electric b.eakdown Network-on-a-chip computer architecture energy consumption Cameras Application software Design optimization Displays Tiles computer science

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The Healthgrid White Paper 3

The Healthgrid White Paper

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3rd Annual Conference of the Healthgrid Association, Healthgrid 2005

作者： b.eton, Vincent Dean, Kevin Solomonides, Tony Aloisio, Giovanni benkner, Siegfried bilofsky, Howard blanquer, Ignacio brady, Michael Cannataro, Mario Chouvarda, Ioanna Claerhout, b.echt De Moor, Georges De Neve, Wilfried De Wagter, Carlos Fiore, Sandro Hassan, Kinda Heeren, Germaine Hernández, Vicente Herveg, Jean A.M. Hofmann, Martin Jones, Chris Koutkias, Vassilios Lloyd, Sharon Lonsdale, Guy Alonso, Victoria L. Maglaveras, Nicos Maigne, Lydia Malousi, Andigoni Martín-Sánchez, Fernando McClatchey, Richard Medico, enzo Miguet, Serge Mirto, Maria Montagnat, Johan Nørager1, Sofie Nozaki, Kazunori Oliveira, Ilídio Castro Pennec, Xavier Poullet, Yves Merino, Juan Pedro Sánchez Strizh, Irina G. Taillet, Michel Tristram, Clive Tverdokhlebov, Nikolay Veltri, Pierangelo Ziegler, René CNRS-IN2P3 LPC Campus des Cézeaux AubiereCedex63177 France Internet Business Solutions Group Cisco Systems 9 New Square Bedfont Lakes Middlesex FelthamTW14 8HA United Kingdom University of the West of England Bristol CEMS Coldharbour Lane BristolBS6 6TH United Kingdom Center for Advanced Computational Technologies ISUFI Dept. of Innovation Engineering University of Lecce Via per Monteroni Lecce73100 Italy Institute of Scientific Computing University of Vienna Nordbergstrasse 15 ViennaA-1090 Austria University of Pennsylvania School of Engineering and Applied Science Computer and Information Science Center for Bioinformatics 1416 Blockley Hall 423 Guardian Drive PhiladelphiaPA19104-6021 United States Universidad Politecnica de Valencia Camino de Vera/n Valencia46022 Spain FRS FREng Dept. of Engineering Science Oxford University Parks Road OxfordOX1 3PJ United Kingdom Magna Graecia University of Catanzaro School of Bioinformatics and Biomedical Engineering Campus di Germaneto Viale Europa Germaneto Catanzaro88100 Italy Aristotle University The Medical School Lab of Medical Informatics Box 323 Thessaloniki54124 Greece Custodix NV Verlorenbroodstraat 120 Bus 14 MerelbekeB-9820 Belgium Research in Advanced Medical Informatics and Telematics UZ Gent 5K3 De Pintelaan 185 GentB9000 Belgium Department of Radiotherapy Ghent University Hospital Building P7 De Pintelaan 185 GentB-9000 Belgium Laboratoire LIRIS Université Lumière Lyon 2 Campus Porte des Alpes 5 avenue Pierre Mendès France Bron69676 France av. E.Mounierlaan 83 Brussels1200 Belgium Faculté de Droit de Namur - FUNDP Centre de Recherches Informatiques & Droit 5 rempart de la Vierge Namur5000 Belgium Schloss Birlinghoven Sankt Augustin53754 Germany CERN Geneva 231211 Switzerland Oxford University Computing Laboratory Wolfson Building OxfordOX1 3QD United Kingdom C&C Research Laboratories NEC Europe Ltd. Rathausallee 10 Sankt AugustinD-53757 Germany Medic

ISBN: (纸本)158603510X

Over the last four years, a community of researchers working on Grid and High Performance Computing technologies started discussing the barriers and opportunities that grid technologies must face and exploit for the development of health-related applications. This interest lead to the first Healthgrid conference, held in Lyon, France, on January 16th–17th, 2003, with the focus of creating increased awareness about the possibilities and advantages linked to the deployment of grid technologies in health, ultimately targeting the creation of a european/international grid infrastructure for health. The topics of this conference converged with the position of the eHealth division of the european Commission, whose mandate from the Lisbon Meeting was "To develop an intelligent environment that enab.es ubiquitous management of citizens’ health status, and to assist health professionals in coping with some major challenges, risk management and the integration into clinical practice of advances in health knowledge." In this context "Health" involves not only clinical procedures but covers the whole range of information from molecular level (genetic and proteomic information) over cells and tissues, to the individual and finally the population level (social healthcare). Grid technology offers the opportunity to create a common working backbone for all different members of this large "health family" and will hopefully lead to an increased awareness and interoperability among disciplines. The first HealthGrid conference led to the creation of the Healthgrid association, a non-profit research association legally incorporated in France but formed from the broad community of european researchers and institutions sharing expertise in health grids. After the second Healthgrid conference, held in Clermont-Ferrand on January 29th–30th, 2004, the need for a "white paper" on the current status and prospective of health grids was raised. Over fifty experts from different areas of grid tec

关键词： Health risks

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Measuring acceptance of intelligent system models

Measuring acceptance of intelligent system models

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8th International Conference on Knowledge-based Intelligent Information and engineering Systems, KeS 2004

作者： Peters, James F. Ramanna, Sheela Department of Electrical and Computer Engineering University of Manitoba WinnipegMBR3T 5V6 Canada Department of Applied Computer Science University of Winnipeg WinnipegMBR3B 2E9 Canada

ISBN: (纸本)9783540301325

This article introduces an approach to measuring the degree to which, intelligent system models conform to a design standard. A fundamental prob.em in system design is that feature values extracted from experimental design models tend not to match exactly patterns associated with standard design models. It is not generally known how to measure the extent that a particular intelligent system design conforms to a standard design pattern. The rough set approach introduced by Zdzislaw Pawlak provides a basis for concluding and more specifically measuring to what degree a particular model for an intelligent system design is a part of a set of models representing a standard. Measurements are carried out within satisfaction-based approximation spaces defined in the context of rough sets. The neuron and sensor behavioral models are briefly considered by way of illustration of the approach to measuring acceptance of an intelligent system design model. © Springer-Verlag berlin Heidelberg 2004.

关键词： Intelligent systems

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Study on An Absolute Non-Collision Hash and Jumping Tab.e IP Classification Algorithms

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Wuhan University Journal of Natural sciences 2004年第5期9卷 835-838页

作者： SHANG Feng-jun 1,2 ,PAN Ying-jun 1 1. Key Laboratory of Opto-electronic Technology and System of Ministry of education/College of Opto-electronic engineering,Chongqing University, Chongqing 400044,China 2. College of computer science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065,China Chongqing University Key Laboratory of Opto-Electronic Technology and System of Ministry of Education/College of Opto-Electronic Engineering Chongqing China (GRID:grid.190737.b) (ISNI:***) Chongqing University of Posts and Telecommunications College of Computer Science and Technology Chongqing China (GRID:grid.411587.e) (ISNI:***) Chongqing University Key Laboratory of Opto-Electronic Technology and System of Ministry of Education/College of Opto-Electronic Engineering Chongqing China (GRID:grid.190737.b) (ISNI:***)

In order to classify packet, we propose a novel IP classification based the non-collision hash and jumping tab.e trie-tree (NHJTTT) algorithm, which is based on noncollision hash Trie-tree and Lakshman and Stiliadis proposing a 2-dimensional classification algorithm (LS algorithm). The core of algorithm consists of two parts: structure the non-collision hash function, which is constructed mainly based on destination/source port and protocol type field so that the hash function can avoid space explosion prob.em; introduce jumping tab.e Trie-tree based LS algorithm in order to reduce time complexity. The test results show that the classification rate of NHJTTT algorithm is up to 1 million packets per second and the maximum memory consumed is 9 Mb for 10 000 rules. Key words IP classification - lookup algorithm - trie-tree - non-collision hash - jumping tab.e CLC number TN 393.06 Foundation item: Supported by the Chongqing of Posts and Telecommunications Younger Teacher Fundation (A2003-03). biography: SHANG Feng-jun (1972-), male, Ph.D. candidate, lecture, research direction: the smart instrument and network.

关键词： IP classification lookup algorithm trie-tree non-collision hash jumping tab.e

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Comparing exact and approximate spatial auto-regression model solutions for spatial data analysis

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3rd International Conference on Geographic Information science, GIscience 2004

作者： Kazar, baris M. Shekhar, Shashi Lilja, David J. Vatsavai, Ranga R. Pace, R. Kelley Electrical and Computer Engineering Department University of Minnesota Twin-CitiesMN55455 United States Computer Science and Engineering Department University of Minnesota Twin-CitiesMN55455 United States LREC Endowed Chair of Real Estate Department of Finance E.J. Ourso College of Business Louisiana State University 2164B CEBA Baton RougeLA70803-6308 United States

ISBN: (纸本)9783540235583

The spatial auto-regression (SAR) model is a popular spatial data analysis technique, which has b.en used in many applications with geo-spatial datasets. However, exact solutions for estimating SAR parameters are computationally expensive due to the need to compute all the eigenvalues of a very large matrix. Recently we developed a dense-exact parallel formulation of the SAR parameter estimation procedure using data parallelism and a hybrid programming technique. Though this parallel implementation showed scalability up to eight processors, the exact solution still suffers from high computational complexity and memory requirements. These limitations have led us to investigate approximate solutions for SAR model parameter estimation with the main ob.ective of scaling the SAR model for large spatial data analysis prob.ems. In this paper we present two candidate approximate-semi-sparse solutions of the SAR model based on Taylor series expansion and Chebyshev polynomials. Our initial experiments showed that these new techniques scale well for very large data sets, such as remote sensing images having millions of pixels. The results also show that the differences between exact and approximate SAR parameter estimates are within 0.7% and 8.2% for Chebyshev polynomials and Taylor series expansion, respectively, and have no significant effect on the prediction accuracy. © Springer-Verlag berlin Heidelberg 2004.

关键词： Chebyshev polynomials

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