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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
doctoralThesis -
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Published 2023“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The objective is to minimize different cost types while satisfying constraints such as resources availability, customer service level, and tasks dependency relation. The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
Published 2024Get full text
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masterThesis -
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
Published 2011Get full text
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masterThesis -
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Parallel implementation of clique partitioning using artificial neural networks. (c2000)
Published 2000Get full text
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masterThesis -
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Its purpose was to estimate shear and residual stress levels. Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”
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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications
Published 2019“…<div><p>Fast and accurate arctangent approximations are used in several contemporary applications, including embedded systems, signal processing, radar, and power systems. Three main approximation techniques are well-established in the literature, varying in their accuracy and resource utilization levels. …”
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A Survey of Data Clustering Techniques
Published 2023“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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A Graph Heuristic Approach for the Data Path Allocation Problem
Published 2022“…More speci cally, this automation process known as high-level synthesis (HLS), targets the datapath allocation problem in VLSI design. …”
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masterThesis -
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Severity-Based Prioritized Processing of Packets with Application in VANETs
Published 2019“…In this study, we propose a generic prioritization and resource management algorithm that can be used to prioritize processing of received packets in vehicular networks. …”
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Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection
Published 2019“…In particular, by separating all the subcarriers or some subcarrier groups from each other and by optimizing the selection and beamforming vector(s) using OMP algorithm, a higher level of frequency diversity can be achieved. …”
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Scheduling and allocation in high-level synthesis using stochastic techniques
Published 2020“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
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