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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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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Undergraduates Project Papers -
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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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A study on advanced statistical analysis for network anomaly detection
Published 2005“…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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Monograph -
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Classification and detection of intelligent house resident activities using multiagent
Published 2013“…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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Conference or Workshop Item -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The first stage is to apply reverse engineering method to obtain the specific patterns of individual jammers. …”
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Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection
Published 2015“…The pattern recognition results showed that the AR algorithm is more effective in defect identification. …”
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Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
Published 2019“…Viola-Jones algorithm can be categorized as one of an established and effective method (feature-based approach) for detecting face. …”
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Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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Academic Exercise -
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column
Published 2003“…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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Analytical method for forensic investigation of social networking applications on smartphones
Published 2016“…The identified patterns are then used to design an algorithm for detecting social networking data remnants automatically. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO
Published 2016“…This method used a collaborative Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) based on people detection algorithm to detect headshoulder region. …”
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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi
Published 2022“…This problem occurs due to lacking of existing system in detecting children image in a car. Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. …”
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