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  1. 1
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…This study emphasizes on the performance evaluation of given algorithms and their pitfalls in predicting accurate pressure drop. …”
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  2. 2
    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm

    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

    Published 2023
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  3. 3
    Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics

    Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics by Saaidah A.M., Jali M.Z., Marhusin M.F., Abdel-Jaber H.

    Published 2024
    Conference Paper
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  4. 4
    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs

    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs by Afshar Ghotli, Reza, Abbasi, Mohammad Reza, Bagheri, AmirHossein, Abdul Raman, Abdul Aziz, Ibrahim, Shaliza, Bostanci, Huseyin

    Published 2019
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  5. 5
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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  6. 6
    Markov-modulated Bernoulli-based Performance Analysis for BLUE Algorithm under Bursty and Correlated Traffics

    Markov-modulated Bernoulli-based Performance Analysis for BLUE Algorithm under Bursty and Correlated Traffics by Saaidah, AM, Jali, MZ, Marhusin, MF, Abdel-Jaber, H

    Published 2024
    “…The MMBP is used to replace the conventional and widely-used Bernoulli process (BP) in evaluating and proposing analytical models based on the BLUE algorithm. …”
    Proceedings Paper
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  7. 7
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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    Thesis
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  8. 8
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…Finally, the rigor of evaluation phase is carried out to evaluate the model utilizing precision, recall, F1 score, and the overall accuracy metrics which ascertained robustness and reliability for the model.…”
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  9. 9
    Benchmark simulator with dynamic environment for job scheduling in grid computing

    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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  10. 10
    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues

    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

    Published 2024
    “…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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  11. 11
    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study

    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…This study aims to develop a universal artificial neural network model for estimating pressure drop at pipelines under multiphase flow conditions. …”
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  12. 12
    Development of MyCGPA for early predicting students’ academic performance

    Development of MyCGPA for early predicting students’ academic performance by Abdul Mutalib, Muhammad Yazid, Zainol, Zuraini, Nohuddin, Puteri Nor Ellyza, Abdul Rauf, Ummul Fahri

    Published 2025
    “…One of the primary concerns in higher education is the early identification of underperforming students. …”
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  13. 13
    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. …”
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  14. 14
    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
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  15. 15
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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  16. 16
    Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques

    Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques by Muhammad Afnan, Mohammad Nasir

    Published 2022
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    Undergraduates Project Papers
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  17. 17
    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning

    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

    Published 2023
    “…Early identification of high-risk patients enables timely intervention and implementation of preventive measures, potentially reducing the burden of stroke-related complications. …”
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  18. 18
    A VOICE PRIORITY QUEUE (VPQ) SCHEDULER FOR VOIP OVER WLANs

    A VOICE PRIORITY QUEUE (VPQ) SCHEDULER FOR VOIP OVER WLANs by NISAR, KASHIF

    Published 2011
    “…We proposed a new Voice Priority Queue (VPQ) scheduling system model and algorithms to solve scheduling issues. …”
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  19. 19
    Development of IoT-based heatstroke early symptoms monitoring system for students in Malaysia

    Development of IoT-based heatstroke early symptoms monitoring system for students in Malaysia by A Rahim, Nabilah, Othman, Nurmiza

    Published 2024
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  20. 20
    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
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