Search Results - (( (variable OR variables) evaluation from algorithm ) OR ( java application using algorithm ))
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1
Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The experiment contains two phases; first phase was conducted against java applications that do not use any protection to determine the ability of reversing tools to read the compiled code. …”
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Thesis -
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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4
RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
5
A hybrid heuristic of variable neighbourhood descent and great deluge algorithm for efficient task scheduling in grid computing
Published 2019“…In addition, the performance of the proposed algorithm has been evaluated and compared with some other recent meta-heuristics in the literature. …”
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Provider independent cryptographic tools
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Monograph -
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Mixed variable ant colony optimization technique for feature subset selection and model selection
Published 2013“…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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Conference or Workshop Item -
9
Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…Logistic regression model has long been known and it is commonly used in analysing a binary outcome or dependent variable and connects the binary dependent variable to several independent variables. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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Article -
12
Diagonal R-point variable step variable order block method for solving second order ordinary differential equations
Published 2016“…Further implementation of the 2DBBDF and 3DBBDF methods in variable step variable order scheme displays comparable results with other variable step variable order methods. …”
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Thesis -
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Characterization of digital intra-oral dental radiographs based on image enhancement algorithms (IEAs) / Siti Arpah Ahmad
Published 2017“…Results show SCLAHE is able to champion in reducing the variability of subjective evaluation. Supervised twin-view approach produced consistent evaluation. …”
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Thesis -
14
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…Third, a stenosis detection algorithm from two images is proposed in this thesis. …”
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Thesis -
15
The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…The AUC value increased from 0.88 to 0.92. Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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Single and Multiple variables control using Tree Physiology Optimization
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Influence of respiration on variability of peak systolic blood flow velocity in common carotid artery: preliminary study
Published 2009“…There were significant correlation between peak systolic velocities and its RR intervals that evaluated from synchronized measurement of electrocardiogram (ECG) and Doppler blood velocity. …”
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Proceeding Paper -
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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