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    » A Graph Based Process Representation for Process Modeling
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    SDM
    2009
    SIAM
    223views Data Mining» more  SDM 2009»
    Context Aware Trace Clustering: Towards Improving Process Mining Results.
    14 years 5 months ago
    Context Aware Trace Clustering: Towards Improving Process Mining Results.
    Download  www.siam.org
    Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
    R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
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    GECCO
    2005
    Springer
    384views Optimization» more  GECCO 2005»
    A case study of process facility optimization using discrete event simulation and genetic algorithm
    14 years 1 months ago
    A case study of process facility optimization using discrete event simulation and genetic algorithm
    Download  www.cs.bham.ac.uk
    Optimization problems such as resource allocation, job-shop scheduling, equipment utilization and process scheduling occur in a broad range of processing industries. This paper pr...
    Keshav P. Dahal, Stuart Galloway, Graeme M. Burt, ...
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    FPGA
    1995
    ACM
    120views FPGA» more  FPGA 1995»
    Synthesis of Signal Processing Structured Datapaths for FPGAs Supporting RAMs and Busses
    13 years 12 months ago
    Synthesis of Signal Processing Structured Datapaths for FPGAs Supporting RAMs and Busses
    Download  www.cecs.uci.edu
    A novel approach is presented for transforming a given scheduled and bound signal processing algorithm for a multiplexer based datapath to a BUS/RAM based FPGA datapath. A datapat...
    Baher Haroun, Behzad Sajjadi
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    SE
    2007
    146views Software Engineering» more  SE 2007»
    Requirements traceability in the model-based testing process
    13 years 9 months ago
    Requirements traceability in the model-based testing process
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    : Automated test case and test driver generation from a precise behaviour UML model is an emerging approach for software functional validation. This innovative approach for validat...
    Eddy Bernard, Bruno Legeard
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    IGARSS
    2009
    195views Remote Sensing» more  IGARSS 2009»
    Spatially Adaptive Classification of Hyperspectral Data with Gaussian Processes
    13 years 6 months ago
    Spatially Adaptive Classification of Hyperspectral Data with Gaussian Processes
    Download  ideal.ece.utexas.edu
    Automated classification of land cover types based on hyperspectral imagery often involves a large geographical area, but class labels are available for only small portions of the...
    Goo Jun, Joydeep Ghosh
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