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An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles
Published 2022“…An important differentiation of this work is that the proposed algorithm can coordinate with all phasor measurement units to accurately determine the faulty line using the index of unwrapped dynamic phase angles. …”
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Detection And Classification Of Impact-Induced Delamination In Fiberglass Pre-Impregnated Laminated Composites From Ultrasonic A-Scan Signal Using Artificial Intelligence
Published 2018“…Besides affected the material strength and structural reliability, this failure mode normally present minor damage on the surface but the internal damage may extensive. Existing detection method using static and dynamic load response have limitations that are considered static based monitoring and require the sensor to be attached to the test specimen surface. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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5
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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Distribution network fault section estimation using analytical database approach
Published 2004“…The method proposed in this thesis is by data compression and reconstruction using wavelet transform.…”
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Delamination in fiberglass pre-impregnated laminated composites from ultrasonic a-scan signal using artificial intelligence
Published 2018“…Besides affected the material strength and structural reliability, this failure mode normally present minor damage on the surface but the internal damage may extensive. Existing detection method using static and dynamic load response have limitations that are considered static based monitoring and require the sensor to be attached to the test specimen surface. …”
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8
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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Distinguishing Micro-Scale Voltage Disturbances Using Wavelet Decomposition Techniques
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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Final Year Project -
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
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Feature extraction of power disturbance signal using time frequency analysis
Published 2006“…Those signals are transformed into time frequency plane using Bdistribution algorithm. Then the important feature vectors or components are extracted using Singular Value Decomposition (SVD) and Principle Component Analysis (PCA). …”
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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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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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Edge Detection Algorithm For Image Processing Of Search And Rescue Robot
Published 2016“…This paper highlights the various edge detection algorithms working method and comparison is made based on the advantages and disadvantages of the algorithms for the identification of an optimum edge detection algorithm. …”
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Final Year Project -
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Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…One of the embedded systems that received great attention is road detection system, that operates using road markings detection algorithm. …”
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Thesis -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Amplitude independent muscle activity detection algorithm of soft robotic glove system for hemiparesis stroke patients using single sEMG channel
Published 2020“…The algorithm employs the First Lag Autocorrelation and the Modified Sample Entropy methods to detect and classify weak hand closing and opening muscle activities by using signal obtained from the Flexor Carpi Ulnaris forearm muscle. …”
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