Search Results - parallel reduction clustering algorithm

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  1. 1
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel algorithm. …”
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  2. 2
    An evolutionary-based term reduction approach to bilingual clustering of Malay-English corpora

    An evolutionary-based term reduction approach to bilingual clustering of Malay-English corpora by Rayner Alfred, Leow, Ching Leong, Joe Henry Obit

    Published 2017
    “…Hence, this encourages the study of term reduction technique in clustering bilingual documents. …”
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  3. 3
    A proposed design for noise reduction algorithm in seismograph on high performance computing using F-K filter

    A proposed design for noise reduction algorithm in seismograph on high performance computing using F-K filter by I.A., Aziz, T., Sandran, N.S., Haron, M., Mehat

    Published 2008
    “…This paper proposes a design of noise reduction algorithm for seismic data on a High Performance Computing (HPC) environment. …”
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  4. 4
    Enhancing speed performance of the cryptographic algorithm based on the lucas sequence

    Enhancing speed performance of the cryptographic algorithm based on the lucas sequence by M. Abulkhirat, Esam

    Published 2003
    “…The improved algorithm is applied on the lab-PC for the sequential platform, and cluster-computing machine for the parallel platform, which lead to a substantial time reduction and an enhancement of the algorithm speed in both platforms.…”
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  5. 5
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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