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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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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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Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost
Published 2023“…In this paper, we propose a sparse equity portfolio optimization model that aims at minimizing transaction cost by avoiding small investments while promoting diversification to help mitigate the volatility in the portfolio. …”
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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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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field
Published 2018“…Blind Source Separation (BSS) refers to the statistical technique of separating a mixture of underlying source signals.BSS denotes as a phenomena and separation on mixed heart-lung sound is one of its example.The challenge of this research is to separate the separate lung sound and heart sound from mixed heart-lung sound.A clear lung sound for diagnosis purpose able to be obtained after separating the mixed heart-lung sound.In biomedical field,lung information is precious due to it has been provided for respiratory diagnosis.However,the interference of heart sound towards lung sound will generate ambiguity and it will lead to drop down the accuracy of diagnosis.Thus,a clean lung sound is needed to increases the accuracy of diagnosis.One of the ways for non-invasive respiratory diagnosis for obtaining lung information is through extracting lung sound from mixed heart-lung sound by using Two-Dimensional Nonnegative Matrix Factorization (NMF2D) algorithm.This method is based on cocktail party effect in which it refers to human brain able to selectively listen to target among a cacophony of conversations and background noise and this considered as a difficult task to machine.Therefore, duplication on cocktail party effect into machine is used to separate the mixed heart-lung sound.This research presents a novel approach NMF2D algorithm in which a suitable model for signal mixture that accommodated the reverberations and nonlinearity of the signals.The objectives of this research are focusing on investigating the useful signal analysis algorithms,defining a new technique of signal separability,designing and developing novel methods for BSS. …”
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Thesis -
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Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm
Published 2024“…Subsequently, we applied RAMPA-TCF to identify the parameters of one numerical example and a twin-rotor system (TRS) under various sparse measurement data cases. …”
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Article -
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Thesis -
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Image denoising using combined higher order non-convex total variation with overlapping group sparsity
Published 2019“…In this paper, we address this problem by proposing a combined non-convex higher order total variation with overlapping group sparse regularizer. …”
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Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks
Published 2019“…The first step of the proposed protocol involves the development of an energy efficient clustering algorithm which is appropriate for WSN with a sparse density topology. …”
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Thesis -
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. …”
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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…As opposed to a point cloud generated from high-end LiDAR sensors where many algorithms have been developed for object detection, sparse LiDAR point clouds still possess large room for improvement. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Speech compression using compressive sensing on a multicore system
Published 2011“…In this paper, a novel algorithm for speech coding utilizing CS principle is developed. …”
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Proceeding Paper -
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Thesis -
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Thus far, a few efficient interactive mining algorithms have been proposed. …”
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Counting roots of the Polynomial systems by using mixed volume of the Newton polytopes / Nur Suhailah Norazhar, Nur Ain Sofiya Zainuri and Nor Suhada Mohd Rosdi
Published 2024“…Since the study dealing with the sparse polynomial systems with two variables, to derive the sparse matrices, the developed Maple program, “multires.mpl” is used. …”
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