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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Prevention And Detection Mechanism For Security In Passive Rfid System

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…A GUI is created in a form of JAVA application to display data detected from tag. …”
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  3. 3
    Academic leadership bio-inspired classification model using negative selection algorithm

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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  4. 4
    Automatic generation of content security policy to mitigate cross site scripting

    Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

    Published 2016
    “…The algorithm is implemented as a plugin. It does not interfere with the web application original code. …”
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  5. 5
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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  6. 6
    Competing risks for reliability analysis using Cox’s model

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. …”
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  7. 7
    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm

    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm by Yifan, Bai, Kamarudin, Khairul Manami, Alli, Hassan

    Published 2024
    “…This research explores the Pareto-primarily based Genetic Algorithm (PGA) inside this framework, with the goal of fostering innovation in product layout and the generation of novel ideas. …”
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  8. 8
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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  9. 9
    Statistical process control for failure crushing time data using competing risks model

    Statistical process control for failure crushing time data using competing risks model by Elfaki, Faiz Ahmed Mohamed, Daoud, Jamal Ibrahim, Azram, Mohammad, Daud, Isa, Ibrahim, N.A., Usman, Mustofa

    Published 2011
    “…EM algorithm method is used to estimate the parameter of the model. …”
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  10. 10
    Statistical process control for failure crushing time data using competing risks model.

    Statistical process control for failure crushing time data using competing risks model. by Elfaki, F.A.M., Daud, Isa, Ibrahim, Noor Akma, Daud, J., Azram, M., Usman, M.

    Published 2011
    “…EM algorithm method is used to estimate the parameter of the model. …”
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  11. 11
    Determination of the best single imputation algorithm for missing rainfall data treatment

    Determination of the best single imputation algorithm for missing rainfall data treatment by Gamil Abdulraqeb Abdullah Saeed, Chuan, Zun Liang, Roslinazairimah Zakaria, Wan Nur Syahidah Wan Yusoff, Mohd Zuki Salleh

    Published 2016
    “…The presence of missing rainfall data is inevitable due to error of recording, meteorological extremes and malfunction of instruments. Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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  12. 12
    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment

    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment by Saeed, Gamil Abdulraqeb Abdullah, Chuan, Zun Liang, Roslinazairimah, Zakaria, Wan Nur Syahidah, Wan Yusoff

    Published 2016
    “…The presence of missing rainfall data is inevitable due to error of recording, meteorological extremes and malfunction of instruments. Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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  13. 13
    Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation

    Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation by Nasser, Abdullah B., Abdul-Qawy, Antar S. H., Abdullah, Nibras, Hujainah, Fadhl, Kamal Z., Zamli, Ghanem, Waheed A. H. M.

    Published 2020
    “…Jaya Algorithm (JA) is a new metaheuristic algorithm, has been used for solving different problems. …”
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  14. 14
    A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links’ weight to increase network stability

    A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links’ weight to increase network stability by Karimi, Abbas, Afsharfarnia, Abbas, Zarafshan, Faraneh, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2014
    “…In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. …”
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  15. 15
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  16. 16
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…It is also discovered that the hybrid-discrete MOPSO (HD-MOPSO) algorithm manages to obtain higher values in the performance metrics consisting of non-dominance ratio and hypervolume compared to the competing algorithms. …”
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  17. 17
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  18. 18
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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  19. 19
    Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization

    Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization by Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.

    Published 2023
    “…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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  20. 20
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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