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  1. 1
    Parallel visualization approach of a 3D heart model

    Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

    Published 2008
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  2. 2
    Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems

    Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems by Talebpour, Faraz

    Published 2016
    “…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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  3. 3
    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score

    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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  4. 4
    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network

    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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  5. 5
    A case study on quality of sleep and health using Bayesian networks

    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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  6. 6
    Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi

    Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi by Hosseiny Fatemi, Mohammad Reza

    Published 2012
    “…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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  7. 7
    Early detection of breast cancer using wave elliptic equation with high performance computing

    Early detection of breast cancer using wave elliptic equation with high performance computing by Alias, Norma, Rosly, Nur Syazana, Satam, Noriza, A. Ghaffar, Zarith Safiza, Islam, Md. Rajibul

    Published 2008
    “…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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  8. 8
    Deep reinforcement learning with robust deep deterministic policy gradient

    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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  9. 9
    Extreme air pollutant data analysis using classical and Bayesian approaches

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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  10. 10
    Prediction of breast cancer diagnosis using machine learning in Malaysian women

    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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  11. 11
    Image reconstruction using iterative transpose algorithm for optical tomography

    Image reconstruction using iterative transpose algorithm for optical tomography by Md. Yunos, Yusri, Abd. Rahim, Ruzairi, Green, R. G., Fazalul Rahiman, Mohd. Hafiz

    Published 2007
    “…This paper describes a transpose algorithm for use with an optical tomography system. …”
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  12. 12
    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms

    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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  13. 13
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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  14. 14
    Iterative methods for solving split common fixed point problems in Hilbert spaces

    Iterative methods for solving split common fixed point problems in Hilbert spaces by Mohammed, Lawan Bulama

    Published 2016
    “…In other words, we construct parallel and cyclic algorithms for solving the split common fixed point problems for strictly pseudocontractive mappings and prove the convergence results of these algorithms. …”
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  15. 15
    Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

    Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery by Buswig, Yonis.M.Yonis, Al-Khalid, Bin Hj Othman, Norhuzaimin, Bin Julai

    Published 2019
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  16. 16
    Crytojacking Classification based on Machine Learning Algorithm

    Crytojacking Classification based on Machine Learning Algorithm by Mansor W.N.A.B.W., Ahmad A., Zainudin W.S., Kama M.N., Madihah Mohd Saudi

    Published 2024
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  17. 17
    Bayesian Network of Traffic Accidents in Malaysia

    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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  18. 18
    Two-Point Block Variable Order Step Size Multistep Method for Solving Higher Order Ordinary Differential Equations Directly

    Two-Point Block Variable Order Step Size Multistep Method for Solving Higher Order Ordinary Differential Equations Directly by Ahmad Fadly Nurullah Rasedee, Mohammad Hasan Abdul Sathar, Siti Raihana Hamzah, Norizarina Ishak, Tze Jin Wong, Lee Feng Koo, Siti Nur Iqmal Ibrahim

    Published 2024
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  19. 19
    Hospital readmission risk prediction of COVID-19 patients using machine learning / Loo Wei Kit

    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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  20. 20
    New CFAR algorithm and circuit development for radar receiver

    New CFAR algorithm and circuit development for radar receiver by Kamal, Mustafa Subhi

    Published 2020
    “…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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