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  1. 1
    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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  2. 2
    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
    thesis::doctoral thesis
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  3. 3
    Enhannced sampling algorithm in bluetooth low energy for indoor localization

    Enhannced sampling algorithm in bluetooth low energy for indoor localization by Mat Daud, Mohd Faiz

    Published 2018
    “…Therefore, this project enhanced the Delta Sampling algorithm in order to mitigate this issues and through the experiments, it is proven that the proposed algorithm able to stabilize the signal while solving the sample size and number of invalid samples issue.…”
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  4. 4
    Evaluation of feature selection algorithm for android malware detection

    Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

    Published 2018
    “…Therefore, the proposed approach modified the TF-IDF algorithm, where the algorithm focused on both sample and feature. …”
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  5. 5
    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)

    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

    Published 2019
    “…It was proven that MTF-IDF is an effective Android malware detection algorithm regardless of different kinds of features or sample sizes used. …”
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  6. 6
    GOS: a Genetic OverSampling Algorithm for classification of Quranic verses

    GOS: a Genetic OverSampling Algorithm for classification of Quranic verses by Arkok, Bassam, Zeki, Akram M.

    Published 2022
    “…In this paper, a new technique called "GOS: a Genetic OverSampling algorithm”, is proposed using a genetic algorithm. …”
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  7. 7
    Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test

    Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test by Chuan, Zun Liang, Noriszura, Ismail, Wan Nur Syahidah, Wan Yusoff, Soo-Fen, Fam, Mohd Akramin, Mohd Romlay

    Published 2018
    “…The Cophenetic Correlation Coefficients (CCC) from ten similarity measures are used as attributes for the TOPSIS algorithm to identify the most suitable AHC algorithm out of seven algorithms considered. …”
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  8. 8
    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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  9. 9
    A novel algorithm to detect a QPSK signal with the minimum number of samples

    A novel algorithm to detect a QPSK signal with the minimum number of samples by Mohammed, Saleh, Hilmi, Sanusi, Abubakar, Adamu, Haruna, Chiroma, Edi, Sutoyo, Mungad, Mu, Tutut, Herawan

    Published 2015
    “…The algorithm was simulated and tested using ANSI C++. …”
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  10. 10
    Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm

    Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm by Goay, Chan Hong

    Published 2019
    “…This work proposes an improvement to the original adaptive sampling algorithm and uses it as the sampling method for eye diagram modeling. …”
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  11. 11
    Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations

    Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations by Cheah, Jun Hwa, Roldan, Jose L., Ciavolino, Enrico, Ting, Hiram, Ramayah, T.

    Published 2020
    “…The results of the WPLS algorithm and the traditional PLS algorithm are then compared using a marketing research model. …”
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  12. 12
    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification

    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…The inference algorithm used in this research work is Gibbs sampling. …”
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  13. 13
    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification

    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…The inference algorithm used in this research work is Gibbs sampling. …”
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  14. 14
    Statistical Based Real-Time Selective Herbicide Weed Classifier

    Statistical Based Real-Time Selective Herbicide Weed Classifier by Ahmed, Irshad, Abdul Muhamin , Naeem, Muhammad, Islam, Azween, Abdullah

    Published 2007
    “…This paper deals with the development of an algorithm for real time specific weed recognition system based on Sample Variance of an image that is used for the weed classification and comparison of its result with the algorithm based on population variance. …”
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  15. 15
    Adaptive interference canceller using analog algorithm with offset voltage

    Adaptive interference canceller using analog algorithm with offset voltage by Mohammed, Alaa Hadi

    Published 2015
    “…The experimental tests of the proposed algorithm have shown that the reduction percentage in the MSE output using the proposed algorithm is 51% compared to the NLMS algorithm and 61% compared to the RLS algorithm. …”
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  16. 16
    Comparison between reverse and traditional screening algorithms for syphilis diagnosis in Hospital Universiti Sains Malaysia

    Comparison between reverse and traditional screening algorithms for syphilis diagnosis in Hospital Universiti Sains Malaysia by Sidek, Nurul Azira

    Published 2021
    “…Results: Out of 206 serum samples, 32 (15.53%) were diagnosed with syphilis using the reverse algorithm, but only 23 (11.17%) were diagnosed with syphilis using the traditional algorithm. …”
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  17. 17
    Algorithm for the legal regulation of internet financial crime

    Algorithm for the legal regulation of internet financial crime by Ambaras Khan, Hanna, Ab. Rahman, Suhaimi, Xinxin, Mao

    Published 2024
    “…Similarly, association rules showed a strong correlation between the test and experimental samples, further validating the predictive capabilities of the algorithms. …”
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  18. 18
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…These algorithms generate paths using random numbers and perform efficiently in guiding the robot in known environments. …”
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  19. 19
    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning

    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning by Md. Ali, Mohd. Adli, Badrud’din, Nu’man, Abdullah, Hafidzul, Kemi, Faiz

    Published 2020
    “…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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  20. 20
    Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

    Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz

    Published 2019
    “…However, when handling imbalanced class data, DBN encounters low performance as other machine learning algorithms. In this paper, the genetic algorithm (GA) and bootstrap sampling are incorporated into DBN to lessen the drawbacks occurs when imbalanced class datasets are used. …”
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