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  1. 1
    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems

    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems by Alias, Norma, Masseri, Mohd. Ikhwan Safa, Islam, Md. Rajibul, Khalid, Siti Nurhidayah

    Published 2009
    “…The discretization of the three-dimensional parabolic equations for the brain tumor’s growth mathematical model using a numerical finite-difference method will be implemented from the previous study of two dimensional model and thus a parallelization of algorithm simulation to computational resources based on high-performance computing systems will be used to generate the growth of the brain tumor in three dimensional. …”
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  2. 2
    High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems

    High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems by Pheng, H. S., Alias, Norma, Mohd. Said, Norfarizan

    Published 2007
    “…The implementation of parallel algorithm based on parallel computing system is used to capture the growth of brain tumour. …”
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  3. 3
    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms

    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms by Feng, Tan wei, Raihana Zahirah, Edros, Ngahzaifa, Ab Ghani, Siti Umairah, Mokhtar, Dong, Ruihai

    Published 2024
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  4. 4
    High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system

    High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system by Pheng H. S., Norma Alias, Norfarizan Mohd Said

    Published 2007
    “…The implementation of parallel algorithm based on parallel computing system is used to capture the growth of brain tumour. …”
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  5. 5
    Brain tumor image segmentation using deep learning approach

    Brain tumor image segmentation using deep learning approach by Darshan, Suresh

    Published 2022
    “…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces

    EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces by Paulraj, Murugesapandian, Hema, Chengalvarayan Radhakrishnamurthy, Ramachandran, Nagarajan, Sazali, Yaacob, Abdul Hamid, Adom

    Published 2009
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  7. 7
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  8. 8
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  9. 9
    Brain tumor quantification equation: modeled on complete step response algorithm

    Brain tumor quantification equation: modeled on complete step response algorithm by Aboaba, Abdulfattah A., Hameed, Shihab A., Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Harun, Rahmat, Zain, Norzaini Rose Mohd

    Published 2012
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    Proceeding Paper
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  10. 10
    Brain Topographic Mapping of Emotions using Computational Cerebellum

    Brain Topographic Mapping of Emotions using Computational Cerebellum by Yaacob, Hamwira Sakti, Kamaruddin, Norhaslinda, Abdul Rahman, Abdul Wahab

    Published 2013
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    Proceeding Paper
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  11. 11
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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  12. 12
    Numerical investigation of treated brain glioma model using a two-stage successive over-relaxation method

    Numerical investigation of treated brain glioma model using a two-stage successive over-relaxation method by Hussain, A., Muthuvalu, M.S., Faye, I., Zafar, M., Inc, M., Afzal, F., Iqbal, M.S.

    Published 2023
    “…This study presents the formulation the two-stage successive over-relaxation (TSSOR) algorithm based on the finite difference approximation for solving the treated brain glioma model to predict glioma cells in treating the brain tumor. …”
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  13. 13
    Biologically-Inspired Modeling of Filtering Noise in Signal Sound

    Biologically-Inspired Modeling of Filtering Noise in Signal Sound by Hammuzamer , Irwan, Azween, Abdullah

    Published 2009
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  14. 14
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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  15. 15
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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  16. 16
    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling

    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

    Published 2025
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  17. 17
    High performance visualization of human tumor growth software

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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  18. 18
    Biologically Inspired Signal Noise Elimination Using Human Ear Model with Concurrent Algorithm

    Biologically Inspired Signal Noise Elimination Using Human Ear Model with Concurrent Algorithm by Hammuzamer Irwan, Hamzah, Azween, Abdullah

    Published 2008
    “…All these processes are concurrently executed to optimize the time and space factors in computing. Therefore, for the moment, a high level conceptual model is introduced to solve this research problem.…”
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  19. 19
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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    Book
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  20. 20
    Biologically-Inspired Abstraction Model to Analyze Sound Signal

    Biologically-Inspired Abstraction Model to Analyze Sound Signal by Hammuzamer Irwan , Hamzah, Azween, Abdullah

    Published 2008
    “…This research maps the biologicallyinspired ability to computational process then develops a conceptual model and a system model. …”
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