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  1. 1

    Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

    Published 2025
    “…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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    Article
  2. 2

    An improved public key cryptography based on the elliptic curve by Al-Daoud, Essam Faleh

    Published 2002
    “…To speed up the underlying finite field operations, several new algorithms are introduced namely: selecting random sparse elements algorithm, finding sparse base points, sparse multiplication over polynomial basis, and sparse multiplication over normal basis. …”
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    Thesis
  3. 3

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Moreover, sparse coding has been commonly used in recent years for the purposes of retrieving and identifying images. …”
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    Article
  4. 4

    Evaluation of sparsifying algorithms for speech signals by Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya

    Published 2012
    “…Sparse representations of signals have been used in many areas of signal and image processing. …”
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    Proceeding Paper
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    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…Hence, a new fusion framework namely, Collaborative Framework of Algorithms (CoFA) is proposed, to pursue accurate recovery of the sparse signals from few linear measurements. …”
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    Thesis
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    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
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    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). …”
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    Thesis
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    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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    Thesis
  12. 12

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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    Thesis
  13. 13

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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    Thesis
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    Visual Simultaneous Localization and Mapping Using Direct-Based Method for Unmanned Aerial Vehicle (UAV) by M. H., Badzli, N., Mohamad Yatim, A., Jamaludin, Z., Mohd Noh, M. I., Idris, N. A., Sulaiman, Nur Aqilah, Othman

    Published 2023
    “…The Direct Sparse Odometry (DSO) technique is a new form of visual odometry that makes use of a direct and sparse structure to achieve precision. …”
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    Article
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    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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    Thesis
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    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…In some cases, they are quite distant and sparseness. This uniqueness of Y-STR data has become problematic in partitioning the data using the existing partitional clustering algorithms. …”
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    Thesis