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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

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

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm

    Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm by Abdurrahim, Salem Hamed

    Published 2004
    “…The aim of this work is the development of a segmentation technique for efficient and accurate segmentation of MR brain images. The proposed technique based on the watershed algorithm, which is applied to the gradient magnitude of the MRI data. …”
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  7. 7
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The segmentation of brain MRI images is a challenging and complex task, due to noise and inhomogeneity. …”
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  8. 8
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  9. 9
    Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network

    Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network by Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

    Published 2015
    “…The complex values form the input data of the Complex Back-Propagation (CBP) algorithm. …”
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  10. 10
    Brain source localization using reduced EEG sensors

    Brain source localization using reduced EEG sensors by Jatoi, M.A., Kamel, N.

    Published 2018
    “…The results are shown valid for synthetic EEG data at low SNR level, i.e., 5 dB and real-time EEG data, respectively. …”
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  11. 11
    Brain source localization using reduced EEG sensors

    Brain source localization using reduced EEG sensors by Jatoi, M.A., Kamel, N.

    Published 2018
    “…The results are shown valid for synthetic EEG data at low SNR level, i.e., 5 dB and real-time EEG data, respectively. …”
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  12. 12
    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
    “…In the drug development for the Central Nervous System (CNS), the discovery of the compounds that can pass through the brain across the Blood-Brain Barrier (BBB) is the most challenging assessment. …”
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  13. 13
    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
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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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
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  15. 15
    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function

    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

    Published 2018
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  16. 16
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  17. 17
    Deep learning for EEG data analysis

    Deep learning for EEG data analysis by Cheah, Kit Hwa

    Published 2018
    “…Deep learning (or deep neural network) which enables higher hierarchical representation of complex data has been strongly suggested by a wide range of recent research that these deep architectures of artificial neural network generally outperform the classical EEG feature extraction algorithms or classical EEG classifiers. …”
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  18. 18
    An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa

    An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa by Muhd Suberi, Anis Azwani

    Published 2020
    “…Until today, manual delineation of ischemic stroke in PF on NECT demands dealing with a large amount of data, which leads to late prognosis. As the amount of image data generated by NECT is massive, Deep Learning (DL) solutions are among the effective ways to deal with complex and large amount of cross-sectional data. …”
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  19. 19
    P300 detection of brain signals using a combination of wavelet transform techniques

    P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

    Published 2012
    “…Brain signals known as electroencephalogram (EEG) carry the huge amount of information which is related to nerves activity sending the orders through the brain. …”
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  20. 20
    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective

    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

    Published 2019
    “…The human brain is considered as a complex system having different mental states such as resting, active or cognitive states. …”
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