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Evaluating the DSMIO cache-coherence algorithm in cluster-based parallel ODBMS 8th

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8th International Conference on Object-Oriented Information systems, OOIS 2002

作者： Osthoff, Carla Bentes, Cristiana Ariosto, Daniel Mattoso, Marta Amorim, Claudio L. Computer Science Department LNCC Spain Systems Engineering Department UERJ Spain Computer Science Department COPPE/UFRJ Spain

ISBN: (纸本)3540440879

In this paper, we assess the performance of DSMIO cachecoherence algorithm implemented in a parallel object-based database management system (ODBMS). The distinguishing feature of DSMIO is its use of the lazy release memory consistency model and multiplewriter protocol to reduce both the number and size of coherence messages required to keep coherent a distributed ODBMS across a cluster of PC servers. Using a large distributed database and several application workloads we evaluate DSMIO performance and also compare it against that of the well-known Call-Back Locking (CBL) algorithm. Our results showt hat both algorithms perform very well for read operations whereas DSMIO outperforms significantly CBL for write operations with DSMIO speed-ups attaining as much as 5.4 while CBL speed-ups reach at most 1.4 for an 8-node cluster. Overall, these results suggest that designers of cluster-based ODBMS should consider D. © Springer-Verlag Berlin Heidelberg 2002

关键词： Locks (fasteners)

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Validating an unsupervised weightless perceptron

Validating an unsupervised weightless perceptron

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International Conference on Neural Information Processing

作者： I. Wickert F.M.G. Franca Computer Systems Engineering Program COPPE-UFRJ Rio de Janeiro Brazil

The paper presents a comparison between two unsupervised neural network models: (i) the well-known fuzzy ART, and (ii) AUTOWISARD, a new unsupervised version of the classic WISARD weightless neural network model. It is shown that AUTOWISARD is simple, fast and stable, whilst keeping compatibility with the original WISARD architecture. Experimental test results over binary patterns benchmarks have shown that, although both unsupervised learning models are remarkably simple, AUTOWISARD consistently exhibits better classification skills than fuzzy ART. It is also shown that such superiority happens thanks to AU-TOWISARD's richer internal representation of the trained patterns and the training methods employed by the algorithm, such as the learning window and partial training strategies.

关键词： Subspace constraints Neurons Fuzzy control Pattern recognition Fuzzy sets Resonance Testing Fuzzy neural networks Neural networks Stability

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Fuzzy Markov predictor in electric load forecasting

Fuzzy Markov predictor in electric load forecasting

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International Joint Conference on Neural Networks (IJCNN)

作者： M.A. Teixeira G. Zaverucha Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Brazil Systems Engineering and Computer Science Program E28093 Graduate Programs in Engineering (COPPE) Federal University of Rio de Janeiro Brazil

We present the fuzzy Markov predictor (FMP), a hybrid system that is applied to the task of monthly electric load forecasting. The FMP is a modification we introduce in the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor (FBP) that was modified from the naive Bayes classifier. For verifying the efficiency of the FMP's prediction, we compare it with the FBP, one fuzzy system and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.

关键词： Load forecasting Fuzzy systems Hidden Markov models Power engineering and energy Smoothing methods Niobium compounds systems engineering and theory computer science Predictive models Electric variables measurement

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Fuzzy Markov predictor with first and second-order dependences

Fuzzy Markov predictor with first and second-order dependenc...

引用

Brazilian Symposium on Neural Networks

作者： M.A. Teixeira G. Zaverucha Systems Engineering and Computer Science-COPPE Federal University of Rio de Janeiro Brazil

We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor. These hybrid systems are applied to the task of monthly electric load forecasting and successfully compared with one fuzzy system, and two traditional forecasting methods: Box-Jenkins and Winters exponential smoothing.

关键词： Fuzzy systems Hidden Markov models Load forecasting Niobium compounds Smoothing methods Shape Fuzzy neural networks Power engineering and energy systems engineering and theory computer science

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Adaptation of current signals with floating-gate circuits

Adaptation of current signals with floating-gate circuits

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作者： Pesavento, Alberto Horiuchi, Timothy Diorio, Chris Koch, Christof Department of Electrical Engineering California Institute of Technology Pasadena CA 91125 United States Department of Electrical and Computer Engineering University of Maryland College Park MD 20742 United States Department of Computer Science and Engineering University of Washington Seattle WA 98195-2350 United States Computation and Neural Systems Program California Institute of Technology Pasadena CA 91125 United States

In this paper we present a new, adaptive spatial-derivative circuit for CMOS image sensors. The circuit removes its offset as a natural part of its operation using a combination of electron tunneling and hot-electron injection to add or remove charge on a floating-gate of an auto-zeroing amplifier. We designed, fabricated and successfully tested a chip with the circuit. Test results show that the circuit reduces the offsets by more than an order of magnitude.

关键词： Image sensors

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Potential benefits of implementing load control

Potential benefits of implementing load control

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IEEE Winter Meeting Power engineering Society

作者： M. Ilic J.W. Black J.L. Watz Department of Electrical Engineering and Computer Science MIT Cambridge MA USA Engineering Systems Division in the Technology Management and Policy Program MIT Cambridge MA USA Engineering Systems Division in the Technology and Policy Program MIT Cambridge MA USA

ISBN: (纸本)0780373227

The design of wholesale electricity markets through deregulation has focused almost exclusively on the development of competitive supply (generation). The demand side of the market has been virtually ignored. Mostly, this is due to the assumption that electricity demand is almost completely inelastic. As a result, deregulated wholesale markets universally fail to pass price signals down to the end-users. This paper challenges the assumption of inelastic demand by exploring the potential benefits of implementing a simple load control scheme. This load control scheme allows consumers to shift demand from high priced hours to low priced hours during the day. The benefits to the individual consumer are explored through an example applied to residential air conditioning using price and demand data from California. This example shows that "smart" use of air conditioning can lead to great savings for residential consumers, without sacrificing comfort. The potential for multiple consumers implementing load control to reduce wholesale prices is also examined.

关键词： Load flow control Aggregates Electricity supply industry Power generation Electricity supply industry deregulation Air conditioning Energy management Energy consumption Power engineering and energy systems engineering and theory

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A soft expert system for the creative exploration of first principles of crystal-laser design

A soft expert system for the creative exploration of first p...

引用

2002 IEEE International Conference on systems, Man and Cybernetics

作者： Rubin, Stuart H. Rush, Robert J. Smith, Michael H. Jayaram Murthy, S.N. Trajkovic, Ljiljana Spawars Systems Center 53560 Hull Street San Diego CA United States BISC Program University of California Berkeley CA United States Department of Computer Science Central Michigan University Mt. Pleasant MI United States School of Engineering Science Simon Fraser University Burnaby BC Canada

A soft expert system is defined to be one that is qualitatively fuzzy. In this paper, we present such a system known as "KASER" which stands for 'Knowledge Amplification by Structural Expert Randomization". KASER facilitates reasoning using domain specific expert and commonsense knowledge. It accomplishes this through object-classed predicates and an associated novel inference engine. It addresses the high cost associated with the knowledge acquisition bottleneck. It also enables the entry of a basis of rules and provides for the automatic extension of that basis through domain symmetries. We demonstrate an application for KASER in the design of an intelligent tutoring system that teaches the basic science of crystal-laser design. It enables the student to experiment with various design concepts and receive feedback on the functionality of the proposed design. This is possible without a need to preprogram all possible scenarios.

关键词： Knowledge engineering

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Proposed framework for applying adaptive critics in real-time realm

Proposed framework for applying adaptive critics in real-tim...

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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Lendaris R.A. Santiago M.S. Carroll Systems Science and of Electrical & Computer Engineering Northwest Computational Intelligence Laboratory Portland State University Portland OR USA Systems Science Program Northwest Computational Intelligence Laboratory Portland State University Portland OR USA

Adaptive critics have shown much promise for designing optimal nonlinear controllers in an off-line context. Still, their greatest potential exists in the context Of reconfigurable control, that is, real time controller redesign in response to (substantial) changes in plant dynamics. To accomplish this, a framework is proposed for the application of adaptive critics in real-time control (for those critic methods requiring a model of the plant). The framework is presented in the context of work being done in reconfigurable flight control by the NW Computational Intelligence Lab (NWCIL) at Portland State University. The proposal incorporates recent work (by others) in fast and efficient on-line plant identification, considerations for bounding the computational costs of converging neural networks, and a novel approach (by us) toward the task of assuring system stability during the adaptation process. The potential and limitations of the proposed framework are discussed. It is suggested that with the recent rapid reduction in computational barriers, only certain theoretical issues remain as the central barriers to successful on-line application of the methods.

关键词： programmable control Adaptive control Optimal control Neural networks Computational intelligence Control systems Stability State-space methods Design methodology Piecewise linear approximation

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Knowledge Acquisition for Adversary Course of Action Prediction Models

Knowledge Acquisition for Adversary Course of Action Predict...

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2002 AAAI Fall Symposium

作者： Brown, Scott M. Santos, Eugene Bell, Benjamin Electronic Systems Center Information Operations Program Office 240 Hall Blvd Suite 105 San AntonioTX78243-7058 United States University of Connecticut Dept of Computer Science & Engineering UTEB 191 Auditorium Rd. U-155 StorrsCT06269-3155 United States CHI Systems Inc. 1035 Virginia Drive Suite 300 Ft. WashingtonPA19034-3107 United States

Intelligence Preparation of the Battlespace (IPB) is a predominantly "gray matter-based" fusion and information synthesis process conducted to predict possible future adversary courses of action. The purpose is to understand where the enemy is in the battlespace, and to infer what we believe he will do next. From that understanding, military commanders plan their own course of action. As the state of the art improves, we are in a position to begin applying technologies to move the labor-intensive parts of IPB to the computer, allowing the planner to perform those tasks that are more suited to human capabilities. This is a primary focus of our research effort. This paper presents the approaches that we are adopting to acquire the knowledge necessary to build models to assist decision makers determine adversary intent. We discuss how the IPB process can assist with knowledge acquisition and we present a detailed discussion of our AII system and the techniques we have developed to collect and process the data necessary to map observations of the adversary into evidence to support reasoning about the adversary’s intent. Copyright © 2002, AAAI (***). All rights reserved.

关键词： Knowledge acquisition

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An efficient heuristic for routing and wavelength assignment in optical WDM networks

An efficient heuristic for routing and wavelength assignment...

引用

IEEE International Conference on Communications (ICC)

作者： Yongbing Zhang K. Taira H. Takagi S.K. Das Institute of Policy and Planning Sciences University of Tsukuba Tsukuba Ibaraki Japan Doctoral Program in Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Department of Computer Science and Engineering University of Texas Arlington TX USA

ISBN: (纸本)0780374002

We propose an efficient heuristic algorithm that sets up and releases lightpaths for connection requests dynamically. We partition the routing and wavelength assignment (commonly known as RWA) problem into two subproblems and solves both of them using a well-known shortest path routing algorithm. For solving the routing subproblem, an auxiliary graph is created whereby the nodes and links in the original network are transformed to the edges and vertices, respectively, and the availability of each wavelength on the input and output links of a node as well as the number of available wavelength converters are taken into account in determining the weights of edges. Furthermore, for solving the wavelength assignment subproblem, an auxiliary graph is also utilized and the cost for wavelength conversion is taken into consideration in the edge weight function. A distinguished feature of our algorithm is that it employs more accurate network information on the availability of both the wavelengths and the wavelength converters than the existing algorithms in deciding the routing and the wavelength assignment. Simulation results show that our algorithm performs much better than previously proposed algorithms with comparable computation time, especially when the number of wavelengths is large while the number of converters at each node is limited.

关键词： Wavelength routing Wavelength assignment Optical fiber networks WDM networks Optical wavelength conversion Partitioning algorithms Heuristic algorithms Cost function Availability Computational modeling

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