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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Published 2013“…We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power
Published 2022“…The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM)
Published 2009“…Expectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Thesis -
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Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm
Published 2017“…This paper presents a preliminary study of a model-free approach based on spiral dynamic algorithm (SDA) for maximizing wind farms power production. …”
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Using a novel algorithm in ultrasound images to detect renal stones
Published 2021“…Expectation–Maximization algorithm is a novel method used by us for the first time for identifying renal stones. …”
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Proceedings -
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…It had been successfully used for optimization of many engineering problems. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production
Published 2022“…The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm
Published 2017“…Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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Article -
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Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm
Published 2020“…To fill in missing data, Nearest Neighbour Method(NNM) and Expectation Maximization(EM) algorithm are the two most widely used methods. …”
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Article -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…However, SURE-Autometrics has not been estimated using maximum likelihood estimation (MLE). Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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