Search Results - (( bubble detection method algorithm ) OR ( parallel distribution issues algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. …”
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Charge coupled device based on optical tomography system in detecting air bubbles in crystal clear water
Published 2024“…Experiments in detecting moving air bubbles are conducted. The images of captured data are reconstructed based on filtered image of Linear Back Projection with Hybrid algorithms. …”
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The visualization of three dimensional brain tumors' growth on distributed parallel computer systems
Published 2009“…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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Regenerative braking strategy for electric vehicles using improved adaptive genetic algorithm
Published 2017“…One uses Standard Genetic Algorithm (SGA), the second strategy uses Improved Adaptive Genetic Algorithm (IAGA). …”
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Adaptive resource allocation for reliable performance in heterogeneous distributed systems.
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Book Section -
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Charge-coupled device based on optical tomography system in detecting solid and transparent objects in non-flowing crystal clear water
Published 2024“…Experiments in detecting static solid, transparent objects and moving air bubbles are conducted. …”
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Charge-coupled device based on optical tomography system in detecting solid and transparent objects in non-flowing crystal clear water
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…In the implementation phase, Bubble Sort, Euclidean Distance, 10-Fold Cross validation, and K Nearest Neighbor algorithm are developed. …”
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Brewing perfection: real-time monitoring of arabic coffee using iot and machine learning
Published 2026“…The system demonstrated high efficiency and accuracy in performance, mimicking human coffee brewing methods. The results demonstrate the potential of the YOLOv8 algorithm to automate and optimize routine tasks with high accuracy.…”
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Proceeding Paper -
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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An adaptive controller of hydro generators for smart grid application in Malaysia
Published 2010“…The controller has been modeled considering the existing Malaysia' distribution network of mini hydro power plant connected in parallel to the grid. …”
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A study on performance evaluation of conventional cache replacement algorithms: A review
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3d Morphing And Shape Transformation Using Slices
Published 2009“…This thesis addresses the above-mentioned issues by proposing a novel 3D morphing algorithm using slices. …”
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Initial study of invasive approach of electrical capacitance tomography for identifying non-conducting medium in steel pipe application
Published 2021“…In short, the invasive approach for ECT is seen to be possible to apply for oil-gas application in steel pipe. The LBP algorithm with the average MSSIM value around 0.3 was able to detect the oil-gas regime inside the steel pipe.…”
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Critical insight for MAPReduce optimization in Hadoop
Published 2014“…Achieving an optimal approach for higher performance in terms of efficient load balancing, load distribution, optimum resource utilization, minimum overheads and least possible delay has been the vital issue for cloud infrastructure. …”
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Random sampling method of large-scale graph data classification
Published 2024“…After that, we randomly select a subset of data blocks, each being a random sample of the graph dataset, and compute the different graph property distributions. Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. …”
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