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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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4
Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…This automated generator will facilitate NPSF analysis as manual fault analysis is no longer practical due to increasing memory size. The algorithms used in this generator are based on March algorithm. …”
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5
Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Conference or Workshop Item -
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Randomness Tests On Nine Data Categories Of RECTANGLE Using NIST Statistical Test Suite
Published 2024Article -
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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8
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Text searching algorithm using boyer moore horspool (BMH) algorithm
Published 2015“…We study about the selected technique which is Boyer Moore Horspool algorithm that used for searching the occurrences of a pattern (keyword) in a random text in medical database. …”
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Undergraduates Project Papers -
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Hybrid of firefly algorithm and pattern search for solving optimization problems
Published 2018“…In the final stage, the optimized values obtained from the FA during its maximum number of iteration are given as inputs to the pattern search algorithm. The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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Random Undersampling on Imbalance Time Series Data for Anomaly Detection
Published 2023Conference Paper -
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Monograph -
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm
Published 2023“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
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Final Year Project Report / IMRAD -
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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…The traditional marble game is a stochastic game which is has random probability of distribution or pattern that may be analysed statistically but not be predicted precisely. …”
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18
Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier
Published 2013“…FP-Growth (frequent pattern growth) algorithm was employed as a feature extraction technique. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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The analysis of road traffic fatality pattern for Selangor, Malaysia case study
Published 2021“…The analysed algorithms among others are neural network, random forest, decision tree, logistic regression, naïve Bayes, and support vector machine. …”
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