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  1. 1
    An Effective Fast Searching Algorithm for Internet Crawling Usage

    An Effective Fast Searching Algorithm for Internet Crawling Usage by Chia, Zhen Hon, Nor Azhar, Ahmad

    Published 2016
    “…The search algorithm is a crucial part in any internet applications. …”
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  2. 2
    An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa

    An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

    Published 2018
    “…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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  3. 3
    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System

    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

    Published 2019
    “…Overall, robustness of the proposed algorithm is tested under different faults scenarios, taking into account several factors such as fault inception angles, line fault resistance, ground fault resistance, and the size of loads. …”
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  4. 4
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  5. 5
    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition

    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

    Published 2018
    “…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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  6. 6
    Gender Classification: A Convolutional Neural Network Approach

    Gender Classification: A Convolutional Neural Network Approach by Shan, Sung Liew, Mohamed, Khalil-Hani, Syafeeza, Ahmad Radzi, Rabia, Bakhteri

    Published 2016
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  7. 7
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.…”
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  8. 8
    An Implementation Framework Overview of Non-Intrusive Load Monitoring

    An Implementation Framework Overview of Non-Intrusive Load Monitoring by Omar Al-Khadher, Azharudin Mukhtaruddin, Fakroul Ridzuan Hashim, Hussin Mamat, Muhammad Mokhzaini Azizan

    Published 2024
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  9. 9
    Distinguishing Micro-Scale Voltage Disturbances Using Wavelet Decomposition Techniques

    Distinguishing Micro-Scale Voltage Disturbances Using Wavelet Decomposition Techniques by Wan, Chen Yoong

    Published 2014
    “…All the modelling and classification processes are performed in MATLAB where wavelet-1D toolbox and MATLAB algorithm are developed and employed. …”
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  10. 10
    Feature extraction of power disturbance signal using time frequency analysis

    Feature extraction of power disturbance signal using time frequency analysis by Sihab, Norsabrina

    Published 2006
    “…Power Quality has been one of the great concerns recently; it due to the increasing number of loads which sensitive to the power disturbance. One of the main issues in power quality problems includes how to localize each disturbance event and recognize its respective type of disturbance more efficiently. …”
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