Search Results - (( pattern detection path 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. …”
Conference paper -
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
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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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Article -
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Animal voice recognition for identification (ID) detection system
Published 2011“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
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Dog voice identification (ID) for detection system
Published 2012“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
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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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7
Feature extraction: hand shape, hand position and hand trajectory path
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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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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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12
Machine Learning Based Detection for Compromised Accounts on Social Media Networks
Published 2025“…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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Development of high speed booth multiplier with optimized stuck-at fault implementation
Published 2002“…Deterministic technique will be used to detect failure circuit base on test pattern generation. …”
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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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15
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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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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