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  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Article
  2. 2

    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

    Published 2021
    “…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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    Thesis
  3. 3

    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

    Published 2011
    “…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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    Book Section
  4. 4

    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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    Article
  5. 5

    Deep reinforcement learning with robust deep deterministic policy gradient by Teckchai Tiong, Ismail Saad, Kenneth Tze Kin Teo, Herwansyah Lago

    Published 2020
    “…Recently, Deep Deterministic Policy Gradient (DDPG) is a popular deep reinforcement learning algorithms applied to continuous control problems like autonomous driving and robotics. …”
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    Proceedings
  6. 6

    Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

    Published 2026
    “…The deployed web-based tool enables rapid and individualized estimation of DEP risk in patients with T2DM using routinely available clinical and demographic information. …”
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    Article
  7. 7

    Prediction of breast cancer diagnosis using machine learning in Malaysian women by Mokhtar, Tengku Muhammad Hanis Tengku

    Published 2024
    “…Thus, this thesis aims to explore the use of machine learning (ML) for breast cancer risk estimation and prediction. …”
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    Thesis
  8. 8
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    Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

    Published 2025
    “…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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    Article
  10. 10

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Thesis
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    Bayesian Network of Traffic Accidents in Malaysia by Zamzuri, Zamira Hasanah, Shabadin, Akmalia, Ishak, Siti Zaharah

    Published 2019
    “…By using Hill Climb (HC) and Tabu algorithms, the structure of the data was learnt and their relationship is estimated through the conditional probability based on the Bayes theorem. …”
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    Article
  13. 13

    Hospital readmission risk prediction of COVID-19 patients using machine learning / Loo Wei Kit by Loo , Wei Kit

    Published 2024
    “…Concurrently, six deep learning models were developed and trained after data balancing was executed, namely Multilayer Perceptron, TabNet, Value Imputation and Mask Estimation, TabTransformer, Deep Factorial Machine, and Regularization Learning Model. …”
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    Thesis
  14. 14

    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks by Mahzan, Shahruddin, J. Staszewski, Wieslaw, Worden, Keith

    Published 2010
    “…The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.…”
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    Article
  15. 15

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
    Article
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    Predicting Diseases Using Multi-BackPropagation by Wan Hussain, Wan Ishak

    Published 2002
    “…Multi-network approach does not require any changes in neural network learning algorithm. Instead, the large data is divided into several smaller categories or network. …”
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    Thesis
  18. 18

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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    Thesis
  19. 19

    System setup on jetson nano for smart crowd covid monitoring system by Muhammad Othman, Maliki

    Published 2022
    “…The NVIDIA Jetson Nano was used to prototype a real-world scenario using the Object Detection Algorithm (YOLOv5) and an edge AI application: a smart camera capable of estimating the percentage of people wearing face masks in its field of view. …”
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    Undergraduates Project Papers
  20. 20

    SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

    Published 2021
    “…Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. However, choosing the best machine learning approach is still a challenging task. …”
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    Article