Search Results - (( loading classification based algorithm ) OR ( pattern detection using algorithm ))
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1
High impedance fault detection and identification based on pattern recognition of phase displacement computation
Published 2018“…Subsequently, an automatic HIF classification algorithm based on predefined indices is proposed to perform event identification and HIF detection. …”
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Article -
2
Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…In this research, an EMG controlled 3D printed robot hand prototype with improved features and advance hand posture classification method based on EMG signal pattern were proposed. …”
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Thesis -
3
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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4
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Subsequently,the filtered signal containing useful information was extracted by three methods root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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5
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 -
6
Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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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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9
Moiré Method Based Tilt Sensing System For Landslides Monitoring Using Raspberry PI
Published 2019“…An algorithm to detect the centroid of the moiré fringe pattern was developed. …”
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Monograph -
10
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. The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment. …”
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Conference or Workshop Item -
11
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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Thesis -
12
Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…Moreover, most of the memory test algorithm does not have the capability to detect and diagnose NPSF. …”
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13
Review of Plug-Based Load Energy Management Systems (PLEMS) for energy and comfort management of buildings
Published 2016“…The reviews indicate that it is essential to improve plug-based load equipments efficiency standards. Classification of these electrical devices according to their consumption patterns would facilitate energy wastage analysis and predictions of future consumption patterns. …”
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Conference or Workshop Item -
14
Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
Published 2019“…In the empirical experiment by using this algorithm, some region in the image which is supposed to be non-face region is detected as face due to the similarity of human face features. …”
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Article -
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Animal voice recognition for identification (ID) detection system
Published 2011“…While the voice pattern classification will be done by using DTW algorithm. …”
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Conference or Workshop Item -
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Dog voice identification (ID) for detection system
Published 2012“…While the voice pattern classification will be done by using DTW algorithm. …”
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Evaluation of fall detection classification approaches
Published 2012“…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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Conference or Workshop Item -
18
Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. Secondly, the study proposes an index for faulty node classification (FNC) based on the positive sequence voltage (PSV) measurements of the pre-fault and post-fault conditions. …”
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Thesis -
19
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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Conference or Workshop Item -
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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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