Search Results - data distribution ((computer algorithm) OR (((window algorithm) OR (means algorithm))))
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…The data distributed in these systems sometimes come in inconsistent formats. …”
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A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things
Published 2018“…Grid computing is a powerful distributed and scalable computing infrastructure that deals with massive data-intensive applications. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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Web based applications for energy management system incorporated network reconfiguration using genetic algorithm / Wan Adnan Wan
Published 2006“…The development on Web Application system uses An ActiveX technology approach. The Genetic Algorithm Based Network Reconfiguration Technique for loss minimization in the UiTM Distribution System is also proposed based on general combinatorial optimization algorithm. …”
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Analysis and decentralised optimal flow control of heterogeneous computer communication network models
Published 1993“…A new method of general model reduction using the Norton' s theorem for general queueing networks in conjunction with the universal maximum entropy algorithm is proposed for the analysis of xix large general closed queueing networks. …”
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An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon
Published 1990“…The intended meaning of broadcasting there is the mannereach datum is distributed among the processors in a computer system. …”
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Dynamic replication aware load blanced scheduling in distributed environment / Said Bakhshad
Published 2018“…Grid computing is an effective distributed and adaptable processing network that manages a huge number of data applications. …”
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Final exam question paper data encryption and decryption using advance encryption standard / Khairul Nashran Nazari
Published 2017“…AES is a data encryption technique that exist in the world with as currently the most secured algorithms. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Replica Creation Algorithm for Data Grids
Published 2012“…This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. …”
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Traffic management algorithms for LEO satellite networks
Published 2016“…The performances of the proposed algorithms are then compared with the previously developed algorithms. …”
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Fuzzy Soft Set Clustering for Categorical Data
Published 2024“…Conventional clustering, such as k-means, cannot be openly used to categorical data. …”
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Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks
Published 2021“…The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
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Survey on job scheduling mechanisms in grid environment
Published 2015“…Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.…”
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