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  1. 1
    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
    “…The main motivation of this study is to find out techniques that may improve EEG signal classification. SAX algorithm may bring improvement to classic time series classification, so we investigate it`s impact on EEG signal classification. …”
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  2. 2
    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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  3. 3
    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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  4. 4
    Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications

    Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications by Asrul, Adam, Zuwairie, Ibrahim, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Cumming, Paul, Marizan, Mubin

    Published 2017
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  5. 5
    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs

    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2021
    “…The electroencephalogram (EEG) is a tool that potentially can be used to detect gender differences. …”
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  6. 6
    Reference-free Reduction of Ballistocardiogram Artifact from EEG Data Using EMD-PCA

    Reference-free Reduction of Ballistocardiogram Artifact from EEG Data Using EMD-PCA by Javed, Ehtasham, Faye, Ibrahima, Malik, Aamir Saeed, Abdullah, Jafri Malin

    Published 2014
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  7. 7
    Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data

    Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

    Published 2024
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  8. 8
    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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  9. 9
    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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  10. 10
    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method

    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

    Published 2018
    “…In the current study, clinical dataset of 20 subjects were used to examine sLORETA andWMN fed by raw EEG signals and MEMD features on each patient’s realistic head model. sLORETA in combination with MEMD feature after eye blink removal proved to be a reliable ESL algorithm with 100% accuracy. …”
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  11. 11
    Human hearing disorder recognition model using eeg-aep based signal

    Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

    Published 2022
    “…Then, the extracted feature was classified using machine learning and deep learning algorithms. …”
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  12. 12
    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

    Published 2017
    “…The proposed algorithm takes input data from multichannel EEG timeseries, which is also known as multivariate pattern analysis. …”
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  13. 13
    Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA

    Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

    Published 2014
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  14. 14
    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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  15. 15
    A proposed frame work for real time epileptic seizure prediction using scalp EEG

    A proposed frame work for real time epileptic seizure prediction using scalp EEG by Ahmad, R.F., Malik, A.S., Kamel, N., Reza, F.

    Published 2013
    “…Still there is no epileptic seizure prediction algorithm using EEG available for clinical applications. …”
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  16. 16
    Addressing imbalanced EEG data for improved microsleep detection: An ADASYN, FFT and LDA-based approach

    Addressing imbalanced EEG data for improved microsleep detection: An ADASYN, FFT and LDA-based approach by Hasan, Md Mahmudul, Khandaker, Sayma, Norizam, Sulaiman, Hossain, Mirza Mahfuj, Islam, Ashraful

    Published 2024
    “…The methodology begins with preprocessing raw EEG data to improve quality and balance, utilizing the ADASYN algorithm to address dataset imbalances. …”
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  17. 17
    A Proposed Frame Work for Real Time Epileptic Seizure Prediction using Scalp EEG

    A Proposed Frame Work for Real Time Epileptic Seizure Prediction using Scalp EEG by Ahmad, Rana Fayyaz, Malik, Aamir Saeed, Kamel , Nidal, Reza, Faruque

    Published 2013
    “…Still there is no epileptic seizure prediction algorithm using EEG available for clinical applications. …”
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  18. 18
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  19. 19
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  20. 20
    Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals

    Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

    Published 2021
    “…This work explores the impact of bandpower of alpha/beta and theta/beta ratios when combined with other features to classify two-levels of human stress based on EEG signals using five commonly used machine learning algorithms. …”
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