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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  2. 2
    Context Independent Expectation Maximization Algorithm for Segmentation of Brain MR Images

    Context Independent Expectation Maximization Algorithm for Segmentation of Brain MR Images by Jasni, Mohamad Zain, Ahmed, M. Masroor, Rana, M.T.A

    Published 2012
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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
    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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  5. 5
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…The use of sensors known as Brain-Computer Interface (BCI) tool can monitor the physical processes and mental states that occur in the human brain. …”
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  6. 6
    EEG signal classification for real-time brain-computer interface applications: a review

    EEG signal classification for real-time brain-computer interface applications: a review by Khorshidtalab, A., Salami, Momoh Jimoh Emiyoka

    Published 2011
    “…Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. …”
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  7. 7
    Brain computer interface design and applications: challenges and future

    Brain computer interface design and applications: challenges and future by Alwasiti, Haider Hussein, Aris, Ishak, Jantan, Adznan

    Published 2010
    “…However, it is only in the last ten years that these systems have been shown to be feasible in laboratories. Successful Brain Computer Interface (BCI) systems have many potential applications, especially for patients who are paralyzed. …”
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  8. 8
    Investigation Of Edge Detection Techniques Based On Brain Tumor Images

    Investigation Of Edge Detection Techniques Based On Brain Tumor Images by Rosnan, Murni Nur Athirah

    Published 2018
    “…However, from visual perspective, Sobel operator produced better edge maps of the brain tumor compared to the Modified Canny algorithm.…”
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  9. 9
    Brain tumor image segmentation using deep learning approach

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

    Published 2022
    “…In neurosurgical, Magnetic Resonance Images (MRI) scans are used to detect cancerous cell grow thin brain called brain tumor. Application that can aid in providing automatic brain tumor segmentation is crucial as segmentation of the exact size and spatial location of these tumors are a time-consuming task. …”
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  10. 10
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  11. 11
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  12. 12
    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device

    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

    Published 2021
    “…One of the proposals that could help solve this problem is the use of brain-computer interface (BCI)s. Brain-Computer Interface (BCI) can be used as a direct communication path between the brain and an external device. …”
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  13. 13
    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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  14. 14
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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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
    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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  17. 17
    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
    “…Future improvements on the present U-Net is necessary so that the accuracy can be increased further, computationally economic, and to produce a near accurate semantic segmentation of brain lesion.…”
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  18. 18
    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen

    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

    Published 2006
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  19. 19
    Electroencephalogram signal interpretation system for mobile robot

    Electroencephalogram signal interpretation system for mobile robot by Hasan, Intan Helina

    Published 2013
    “…The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. Currently, the BCI application is to acquire signals from 32 to 64 electrodes’ recordings and translate them to a movement using various computing algorithm which can be used in wheelchair navigation, or control robot movements. …”
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  20. 20
    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering

    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering by Abang Mohd Arif Anaqi, Abang Isa

    Published 2021
    “…The development of an automatic segmentation algorithm was successfully achieved by entirely depending on the computer without human interaction. …”
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