Search Results - (( evolution detection method algorithm ) OR ( parallel equalization based algorithm ))

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  1. 1

    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach by Puriwat, Lertkrai

    Published 2012
    “…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. …”
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    Thesis
  2. 2

    The division free parallel algorithm for finding determinant by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda

    Published 2013
    “…A cross multiplication method for determinant was generalized for any size of square matrices using a new permutation strategy.The permutation is generated based on starter sets.However, via permutation, the time execution of sequential algorithm became longer.Thus, in order to reduce the computation time, a parallel strategy was developed which is suited for master and slave paradigm of the high performance computer.A parallel algorithm is integrated with message passing interface.The numerical results showed that the parallel methods computed the determinants faster than the sequential counterparts particularly when the tasks were equally allocated.…”
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    Article
  3. 3

    Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

    Published 2013
    “…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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    Article
  4. 4

    Text steganalysis using evolution algorithm approach by Din, Roshidi, Tuan Muda, Tuan Zalizam, Lertkrai, Puriwat, Omar, Mohd Nizam, Amphawan, Angela, Aziz, Fakhrul Anuar

    Published 2012
    “…This study presents a new alternative of steganalysis method in order to detect hidden messages in text steganalysis called Evolution Detection Steganalysis System (EDSS) based on the evolution algorithm approach under Java Genetic Algorithms Package (JGAP). …”
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    Conference or Workshop Item
  5. 5

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Non detection zone decreases to around zero and the proposed method has the ability to detect islanding up to 0.1% power mismatch. …”
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    Thesis
  6. 6

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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    Article
  7. 7

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…MEMPHA, a hypergraphs-based model, aims to aspire to the challenge by providing topology modelling of the target parallel machine and application modelling of the parallel application, which is hypergraph-based model, to abstract the details of HPAs. …”
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    Thesis
  8. 8
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    Differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan, Raja Abdullah, Raja Syamsul Azmir, Al-Dabbagh, Rawaa Dawoud Hassan, Hashim, Fazirulhisyam

    Published 2013
    “…These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. …”
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    Conference or Workshop Item
  10. 10
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    New Sequential and Parallel Division Free Methods for Determinant of Matrices by Sharmila, Karim

    Published 2013
    “…Numerical results showed that the parallel methods were able to compute determinants faster than the sequential counterparts, particularly when the tasks were equally allocated. …”
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    Thesis
  12. 12
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    Parallel Diagonally Implicit Runge-Kutta Methods For Solving Ordinary Differential Equations by Din, Ummul Khair Salma

    Published 2009
    “…All algorithms are written in C language and the parallel code is implemented on Sun Fire V1280 distributed memory system. …”
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    Thesis
  15. 15

    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

    Published 2013
    “…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
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    Thesis
  16. 16

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…An improvement to the conventional DE algorithm has been made to change it from its classical form to be possibly applied for ambiguous targets range detection for radar system. …”
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    Thesis
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    Islanding detection method using ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud, Hizam, Hashim, Othman, Mohammad Lutfi, Mohd Radzi, Mohd Amran

    Published 2019
    “…A modified differential evolution (MDF) algorithm with a new mutation phase, crossover process, and selection mechanism is proposed to train the RPNN. …”
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    Article
  20. 20

    Segmentation of Retinal Vasculature using Active Contour Models (Snakes) by Pang, Kee Y ong

    Published 2009
    “…The results shows that the algorithm outperforms many other published methods and achieved an accuracy (ability to detect both vessel and non-vessel pixels) range of 0.92-0.94, a sensitivity (ability to detect vessel pixels) range of 0.91-0.95 and a specificity (ability to detect non-vessel pixels) range of0.78-0.85. …”
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    Final Year Project