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  1. 1
    Improvement and performance analysis on statistical selection algorithms

    Improvement and performance analysis on statistical selection algorithms by Kweh, Yeah Lun, Othman, Mohamed

    Published 2006
    “…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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  2. 2
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  3. 3
    Statistical selection algorithm for peer-to-peer system

    Statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
    “…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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  4. 4
    Revisit of statistical selection algorithm for peer-to-peer system

    Revisit of statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
    “…Over the years, the distributed computing environment has been developed so fast that there’s a need to develop an effective selection algorithm for it. …”
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  5. 5
    Statistical fixed range multiple selection algorithm for peer-to-peer system

    Statistical fixed range multiple selection algorithm for peer-to-peer system by Kweh, Yeah Lun, Othman, Mohamed, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2010
    “…In this research, a new multiple selection algorithm, which is known as "statistical fixed range multiple selection algorithm" is proposed. …”
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  6. 6
    Static range multiple selection algorithm for peer-to-peer system

    Static range multiple selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2011
    “…In this research, a new multiple selection algorithm, which is known as "static range statistical multiple selection algorithm" is proposed. …”
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  7. 7
    Multi selection control algorithm in examination invigilation management system (ExIMS) for exchanging invigilation duties among invigilators at UiTM Pulau Pinang branch / Jamal Othman …[et al.]

    Multi selection control algorithm in examination invigilation management system (ExIMS) for exchanging invigilation duties among invigilators at UiTM Pulau Pinang branch / Jamal Ot... by Othman, Jamal, Syed Abdullah, Sharifah Sarimah, Samsudin, Norshuhada, Wan Mohd Rosly, Wan Nur Shaziayani

    Published 2021
    “…This system has been developed to control and cross check the request of invigilation duties exchanged using the algorithm named multi selection control. …”
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  8. 8
    Multi selection control algorithm in examination invigilation management system (ExIMS) for exchanging invigilation duties among invigilators at UiTM Pulau Pinang branch / Jamal Othman ... [et al.]

    Multi selection control algorithm in examination invigilation management system (ExIMS) for exchanging invigilation duties among invigilators at UiTM Pulau Pinang branch / Jamal Ot... by Othman, Jamal, Syed Abdullah, Sharifah Sarimah, Samsudin, Norshuhada, Wan Mohd Rosly, Wan Nur Shaziayani

    Published 2021
    “…This system has been developed to control and cross check the request of invigilation duties exchanged using the algorithm named multi selection control. …”
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  9. 9
    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
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  10. 10
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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  11. 11
    Intership supervisor selection using genetic algorithms

    Intership supervisor selection using genetic algorithms by Karim, Junaida

    Published 2015
    “…By using genetic algorithm approach, the priority factors for the assigning faculty supervisor to internship student has been identified and also development model of selection has been done to fulfill the criteria for the selection specified by the FTMK. …”
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  12. 12
    Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur

    Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur by Abdi Nur, Nur Linda

    Published 2007
    “…In sorting algorithm, we focused on quick sort, heap sort, merge sort, bubble sort, insertion sort and selection sort while in searching algorithm we focused on binary search and sequential search. …”
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  13. 13
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  14. 14
    Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study

    Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

    Published 2020
    “…Proposed cfsw-SVM algorithms are then developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. …”
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  15. 15
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…Swarm intelligence algorithms, are among popular metaheuristic methods, developed and inspired by the collective behaviour of swarms that have attracted significant attention of researchers. …”
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  16. 16
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  17. 17
    Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm

    Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm by Nikfal, Shima

    Published 2007
    “…To achieve such goal, this research modifies and improves the Reduction with Selective Redundancy (RSR) algorithm. In the modify algorithm, test cases would be selected according to the branch coverage if they covered different branch combination. …”
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  18. 18
    Supplier selection for contractors using Fuzzy TOPSIS Algorithm / Mohamed Shafiq Mohamed Yusof

    Supplier selection for contractors using Fuzzy TOPSIS Algorithm / Mohamed Shafiq Mohamed Yusof by Mohamed Yusof, Mohamed Shafiq

    Published 2020
    “…The main objective of this study is to develop a system which is supplier selection by using Fuzzy Technique of Order Preference Similarity to the Ideal Solution (Fuzzy TOPSIS). …”
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  19. 19
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
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  20. 20
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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