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  1. 1
    Mental stress classification based on selected EEG channels using Correlation Coefficient of Hjorth Parameters

    Mental stress classification based on selected EEG channels using Correlation Coefficient of Hjorth Parameters by Hag, Ala, Fares, Al-Shargie, Handayani, Dini Oktarina Dwi, Houshyar, Asadi

    Published 2023
    “…To evaluate the effectiveness of CCHP, we conducted experiments using the DEAP public dataset. Comparing our results with other recent algorithms that utilize the full set of EEG channels, CCHP achieved a superior classification accuracy of 81.56% using only eight EEG channels. …”
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  2. 2
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Two publicly activity datasets are used; Wireless Sensor Data Mining (WISDM) and Physical Activity Monitoring for Aging People (PAMAP2). …”
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  3. 3
    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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  4. 4
    Analysis Of Personal Protective Equipment Classification Method Using Deep Learning

    Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

    Published 2022
    “…Face mask has final accuracy of 95.60%, face shield 94.32%, safety goggle 89.79%, safety helmet 98.90% and lastly safety jacket has 88.45% testing accuracy. Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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  5. 5
    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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  6. 6
    Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters

    Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

    Published 2023
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  7. 7
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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  8. 8
    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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    Book Section
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  9. 9
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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  10. 10
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
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    Monograph
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  11. 11
    Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah

    Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah by Airul Sharizli, Abdullah

    Published 2017
    “…To represent the adaptive minimum safe distance which will be used in activation algorithm for CAWS, the new distance-based CAWS model, namely Minimum Safe Distance Gap (MSDG) is introduced. …”
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  12. 12
    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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  13. 13
    Supervised neural network classifier for voice pathology

    Supervised neural network classifier for voice pathology by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

    Published 2011
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  14. 14
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  15. 15
    Signal quality measures for pulse oximetry through waveform morphology analysis

    Signal quality measures for pulse oximetry through waveform morphology analysis by Sukor, J. Abdul, Redmond, S. J., Lovell, N. H.

    Published 2011
    “…The performance of the algorithm was assessed using Cohen’s kappa coefficient (κ), sensitivity, specificity and accuracy measures. …”
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  16. 16
    Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling

    Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

    Published 2018
    “…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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  17. 17
    Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring

    Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz, Anith Khairunnisa Ghazali

    Published 2026
    journal::journal article
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  18. 18
    Quantifying forest disturbance using LiDAR data and time series Landsat images / Syaza Rozali

    Quantifying forest disturbance using LiDAR data and time series Landsat images / Syaza Rozali by Rozali, Syaza

    Published 2021
    “…Two fusion data are tested; 1) SpectralLandsat and 2) SpectralLandsat + HeightALS by Random Forest and Support Vector Machine classification algorithm. The result shows second fusion data having 1 meter Landsat resolution and Airborne LiDAR performed better classification using object-based segmentation and Random Forest classification, about 96% of the overall accuracy with 0.91 kappa index of aggreement. …”
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  19. 19
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The third stage is to classify individual jammers according to the specific pattern and characteristics design as defined in jamming identification and classification parameters. It involves development of Max-Min Rule-Based Classification Algorithm. …”
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  20. 20
    Probe Drilling Based Prediction Of Rock Mass Strength, Natm-4, Pahang-Selangor Raw Water Transfer Tunnel, Hulu Langat, Selangor, Malaysia

    Probe Drilling Based Prediction Of Rock Mass Strength, Natm-4, Pahang-Selangor Raw Water Transfer Tunnel, Hulu Langat, Selangor, Malaysia by Hassan, Nurfarhana

    Published 2018
    “…Japanese Highway (JH) classification method is used to classified the rock class. …”
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