Search Results - (( developing event detection algorithm ) OR ( java data visualization algorithm ))
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1
Real time power quality event detection using continuous wavelet transform
Published 2023“…The proposed algorithm is also capable to perform voltage sag and voltage transient classification for event count upon event detection. …”
Conference paper -
2
An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents
Published 2022“…Event Detection (ED) works on identifying events from various types of data. …”
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Thesis -
3
Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
Published 2019“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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4
Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…The result of this project is all algorithm for visualizing data is functioning and the output produced from the system is correct and effective. …”
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5
Fatigue Features Extraction of Road Load Time Data Using the S-Transform
Published 2013“…Three types of road load fatigue data were used for simulation purpose, pave track, highway and country road. In this study, an algorithm was developed, to detect the damaging events in the original fatigue signal. …”
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6
Leveraging Web Scraping in Predictive Modelling of Supply Risk Detection
Published 2022“…For these purposes, a web scraping program is developed to identify the supply risks caused by these temporary events. …”
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Final Year Project Report / IMRAD -
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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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8
Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Computer A will be sent the data to computer B through the internet/LAN using JAVA program. …”
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Monograph -
10
Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications
Published 2017“…The optimization of peak detection algorithms for electroencephalogram (EEG) signal analysis is an ongoing project; previously existing algorithms have been used with different models to detect EEG peaks in various applications. …”
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11
Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: A comprehensive review
Published 2020“…This paper reviews the existing conventional and intelligent models developed for early detection and prediction of lost circulation events. …”
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12
Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: a comprehensive review
Published 2020“…This paper reviews the existing conventional and intelligent models developed for early detection and prediction of lost circulation events. …”
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13
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Proceeding Paper -
14
Walking gait event detection based on electromyography signals using artificial neural network
Published 2019“…In many gait applications, the focal events are the stance and swing phases. Although detecting gait events using electromyography signals will help the development of assistive devices such as exoskeleton, orthoses, and prostheses, stance and swing phases have yet to be observed using electromyography signals. …”
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15
Methods of intrusion detection in information security incident detection: a comparative study
Published 2018“…These algorithms and methods provide fast and high rate of detection. …”
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16
Development of a wearable human fall detection system
Published 2022“…The accuracy of the fall detection algorithm was determined to be at 98.41%. …”
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Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals
Published 2014“…This project aims at developing an automated epileptic seizure event detection algorithm. …”
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Final Year Project -
18
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…The third contribution aims to provide an integrated solution to detect multiple events in different regions-of-interest of a given scene. …”
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Thesis -
20
Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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