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Cyberbullying detection: a machine learning approach
Published 2022“…Machine learning is a hot topic and it is widely implemented in software, web application and more. Those algorithms are used in the classification or regression model to predict an input. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
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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Thesis -
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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Thesis -
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…Information from load profile is useful for electricity suppliers to plan their generation, improving their market strategies and load balancing. …”
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Thesis -
8
Intuitive content management system via manipulation and duplication with if-else rules classification
Published 2018“…As a result, ICMS can transform dynamic websites into static websites with faster load speed using manipulation method mixed with data mining classification prediction and Boyer-Moore Horspool algorithm which can be classified, edited, adjustable and searched more precisely. …”
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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective
Published 2019“…The brain waves were extracted using discrete wavelet transform (DWT) for each segment and fed these segments to proposed model for classification and assessment of cognitive load. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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Review of Plug-Based Load Energy Management Systems (PLEMS) for energy and comfort management of buildings
Published 2016“…The global energy consumption has risen significantly for the last few years that contributed to the large amount of Carbon Dioxide (CO2). Plug-based load equipments has been identified as one crucial component of whole-building energy use. …”
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…Thirdly, for a faulty line classification (FLC), this study develops the current angles differential scheme by introducing unwrapped dynamic phase angles using the modified PMU measurements. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…The current study of the hand posture classification requires a higher number of EMG sensor used to achieve an accurate classification performance that leads the system to be complicated. …”
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria
Published 2010“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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Service based load balance mechanism using software-defined networks / Ahmed Abdelaziz Abdelltif Osman
Published 2017“…The SDN controller is leveraged to provide online flow classification. The proposed mechanism is evaluated using benchmarking experiments and validated using a statisticalmodel. …”
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An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus
Published 2018“…Therefore, data classification by APSO is used to enhance the coefficient of performance (COP). …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The deliverable of this phase is the selection of the best candidate of machine learning algorithm for university campus energy load prediction. …”
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Teleworking monitoring system using NILM and K-NN algorithms: a strategy for sustainable smart cities
Published 2024“…Together with an event classification method known as K-Nearest Neighbor (k-NN) algorithm, the teleworking event and duration can be identified.The results were presented using classification metrics that consist of confusion matrix andaccuracy score. …”
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