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    IJCSA
    2007
    104views more  IJCSA 2007»
    Solving the Satisfiability Problem Using Finite Learning Automata
    13 years 11 months ago
    Solving the Satisfiability Problem Using Finite Learning Automata
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    A large number of problems that occur in knowledge-representation, learning, VLSI-design, and other areas of artificial intelligence, are essentially satisfiability problems. The ...
    Ole-Christoffer Granmo, Noureddine Bouhmala
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    IJCSA
    2007
    100views more  IJCSA 2007»
    Using Artificial Neural networks for the modelling of a distillation column
    13 years 11 months ago
    Using Artificial Neural networks for the modelling of a distillation column
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    The main aim of this paper is to establish a reliable model both for the steady-state and unsteady-state regimes of a nonlinear process. The use of this model should reflect the t...
    Yahya Chetouani
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    IJCSA
    2007
    86views more  IJCSA 2007»
    OSPF Performance and Optimization of Open Source Routing Software
    13 years 11 months ago
    OSPF Performance and Optimization of Open Source Routing Software
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    Vincenzo Eramo, Marco Listanti, Antonio Cianfrani
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    IJCSA
    2007
    89views more  IJCSA 2007»
    Selection of Indexing Structures in Grid Data Warehouses with Software Agents
    13 years 11 months ago
    Selection of Indexing Structures in Grid Data Warehouses with Software Agents
    Download  www.tmrfindia.org
    Data warehouse systems service larger and larger sets of data. Effective data indexing is not sufficient, because one system node is unable to store such amount ofquickly flowing ...
    Marcin Gorawski, Michal Gorawski, Slawomir Bankows...
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    IJCSA
    2007
    101views more  IJCSA 2007»
    Concurrent Error Detection in S-boxes
    13 years 11 months ago
    Concurrent Error Detection in S-boxes
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    In this paper we present low -cost, concurrent checking methods for multiple error detection in S-boxes of symmetric block ciphers. These are redundancy-based fault detection sche...
    Ewa Idzikowska, Krzysztof Bucholc
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    IJCSA
    2007
    213views more  IJCSA 2007»
    Adaptive Depth Control for Autonomous Underwater Vehicles Based on Feedforward Neural Networks
    13 years 11 months ago
    Adaptive Depth Control for Autonomous Underwater Vehicles Based on Feedforward Neural Networks
    Download  www.tmrfindia.org
    This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...
    Yang Shi, Weiqi Qian, Weisheng Yan, Jun Li
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    IJCSA
    2007
    99views more  IJCSA 2007»
    Wing Pattern-Based Classification of the Rhagoletis pomonella Species Complex Using Genetic Neural Networks
    13 years 11 months ago
    Wing Pattern-Based Classification of the Rhagoletis pomonella Species Complex Using Genetic Neural Networks
    Download  www.tmrfindia.org
    The Rhagoletis pomonella species complex consists of at least four sibling species. They are highly host specific as larvae, and display great fidelity as adults. The only certain...
    Chengpeng Bi, Michael C. Saunders, Bruce A. McPher...
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    IJCSA
    2007
    98views more  IJCSA 2007»
    Extracted Knowledge Interpretation in mining biological data: a survey
    13 years 11 months ago
    Extracted Knowledge Interpretation in mining biological data: a survey
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    This paper discusses different approaches for integrating biological knowledge in gene expression analysis. Indeed we are interested in the fifth step of microarray analysis pro...
    Martine Collard, Ricardo Martínez
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    IJCSA
    2007
    84views more  IJCSA 2007»
    Real Time Model Checking Using Timed Concurrent State Machines
    13 years 11 months ago
    Real Time Model Checking Using Timed Concurrent State Machines
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    Timed Concurrent State Machines are an application of Alur’s Timed Automata concept to coincidence-based (rather than interleaving) CSM modeling technique. TCSM support the idea...
    Wiktor B. Daszczuk
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    IJCSA
    2007
    88views more  IJCSA 2007»
    A New Quantitative Trust Model for Negotiating Agents using Argumentation
    13 years 11 months ago
    A New Quantitative Trust Model for Negotiating Agents using Argumentation
    Download  users.encs.concordia.ca
    In this paper, we propose a new quantitative trust model for argumentation-based negotiating agents. The purpose of such a model is to provide a secure environment for agent negot...
    Jamal Bentahar, John-Jules Ch. Meyer
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