Search Results - (( case detection using algorithm ) OR ( java application learning algorithm ))
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…The results show the algorithm used in this research can reduce the test suite size as well as significantly improve the fault detection effectiveness. …”
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Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm
Published 2022“…This study aims to detect the spatio-temporal clustering or hotspot regions of dengue cases for the districts of Selangor, Malaysia using a nonparametric algorithm (Multi-EigenSpot) to detect dengue clusters. …”
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Improving test efficiency through multiple criteria coverage based test case prioritization using modified heuristic algorithm
Published 2016“…The fault detection capability of a prioritized test suite is improved up to 15 using Modified PSO which forms the base algorithms for prioritization. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm
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Thalassaemia detection using CBR Algorithm via mobile device
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Undergraduates Project Papers -
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Hybrid anti-islanding algorithm for utility interconnection of distributed generation
Published 2009“…Passive detection algorithm uses several types of loads such as resistive, capacitive and inductive connected in parallel and compares the performance of the algorithm in each case.…”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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DEVELOPMENT OF OE-BASED BROWN-FORSYTHE TEST ALGORITHM FOR CONTROL VALVE STICTION DETECTION
Published 2018“…Therefore, the main objective of the project is to develop an OE-based Brown-Forsythe test algorithm to effectively detect the presence of control valve stiction.In this study, the proposed OE model is developed using System Identification in MATLAB, where it is used to simulate the process output (PV). …”
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Final Year Project Report / IMRAD -
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…Some researchers addressed the issue of test case prioritization using Genetic Algorithm, but the authors do not select modification-revealing before prioritization and used the same fault severity. …”
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Comparison between reverse and traditional screening algorithms for syphilis diagnosis in Hospital Universiti Sains Malaysia
Published 2021“…Results: Out of 206 serum samples, 32 (15.53%) were diagnosed with syphilis using the reverse algorithm, but only 23 (11.17%) were diagnosed with syphilis using the traditional algorithm. …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…The availability of nowadays clinical data of Dengue disease can be used to train machine learning algorithm in order to automaticaly detect the present of Dengue disease of the patients. …”
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Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji
Published 2018“…Then the new rotation angle is used to detect bleeding in the patient and evaluate the performance of the new algorithm. …”
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Early detection and mitigation of DDoS attacks in software defined networks
Published 2018“…This algorithm was minimal in line code to make it lightweight and made use of the controller's functionality without adding extra computational burden on the controller.…”
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…The implementation of the K-Means Clustering algorithm for detecting the level of spread of COVID-19 data in Indonesia by using the parameter k=3 is quite good with areas in Indonesia that have a high the spread of COVID-19 and the results of the cluster validity test get silhouette values on O = (Total Case, Total Death) and P = (Total Case, Total Death, Total Recovered) have the same cluster value, which is 0.93 which means the cluster quality is very good.…”
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Book Section -
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Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency
Published 2018“…Furthermore, they did not consider incorporating evolution process such as applying genetic algorithms to their technique. In this work, we proposed an evolutionary cost-cognizant regression testing approach that prioritizes test case according to the rate of severity detection of test cases connected with dependent faults using genetic algorithms. …”
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