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    SENSYS
    2005
    ACM
    147views Sensor Networks» more  SENSYS 2005»
    Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea
    15 years 9 months ago
    Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea
    Download  www.eecs.harvard.edu
    Sensing technology is a cornerstone for many industrial applications. Manufacturing plants and engineering facilities, such as shipboard engine rooms, require sensors to ensure pr...
    Lakshman Krishnamurthy, Robert Adler, Philip Buona...
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    124
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    WSC
    2000
    177views Modeling And Simulation» more  WSC 2000»
    Model abstraction for discrete event systems using neural networks and sensitivity information
    15 years 5 months ago
    Model abstraction for discrete event systems using neural networks and sensitivity information
    Download  www.informs-sim.org
    STRACTION FOR DISCRETE EVENT SYSTEMS USING NEURAL NETWORKS AND SENSITIVITY INFORMATION Christos G. Panayiotou Christos G. Cassandras Department of Manufacturing Engineering Boston ...
    Christos G. Panayiotou, Christos G. Cassandras, We...
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    155
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    IROS
    2009
    IEEE
    142views Robotics» more  IROS 2009»
    Phoneme acquisition model based on vowel imitation using Recurrent Neural Network
    15 years 10 months ago
    Phoneme acquisition model based on vowel imitation using Recurrent Neural Network
    Download  winnie.kuis.kyoto-u.ac.jp
    - A phoneme-acquisition system was developed using a computational model that explains the developmental process of human infants in the early period of acquiring language. There a...
    Hisashi Kanda, Tetsuya Ogata, Toru Takahashi, Kazu...
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    179
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    TNN
    2010
    234views Management» more  TNN 2010»
    Novel maximum-margin training algorithms for supervised neural networks
    14 years 10 months ago
    Novel maximum-margin training algorithms for supervised neural networks
    Download  webmail.isr.uc.pt
    This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
    Oswaldo Ludwig, Urbano Nunes
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    279
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    BMCBI
    2011
    252views Artificial Intelligence» more  BMCBI 2011»
    A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
    14 years 7 months ago
    A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
    Download  www.biomedcentral.com
    Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
    Raphael Mourad, Christine Sinoquet, Philippe Leray
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