Search Results - (( parallel distribution some algorithm ) OR ( parallel distribution mining algorithm ))

Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

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The AGEB Algorithm for Solving Heat Equation in Two Space Dimensions and Its Parallelization on a Distributed Memory Machine by Alias, Norma, Sahimi, Mohamed Salleh, Abdullah, Abdul Rahman

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The AGEB algorithm for solving the heat equation in two space dimensions and its parallelization on a distributed memory machine by Alias N., Sahimi M.S., Abdullah A.R.

High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

“…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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A critical analysis of simulators in grid by Dakkak, Omar, Che Mohamed Arif, Ahmad Suki, Awang Nor, Shahrudin

“…In parallel and distributed computing environment such as "The Grid", anticipating the behavior of the resources and tasks based on certain scheduling algorithm is a great challenging.Thus, studying and improving these types of environments becomes very difficult. …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

“…Key features of this paper are the use of the domain decomposition and encapsulated message passing to enable execution in parallel. A parallel version of a CFD code, FLUENT, has been applied to model some multiphase systems on a number of different platforms. …”
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Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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Regenerative braking strategy for electric vehicles using improved adaptive genetic algorithm by Taleghani, Hussein

“…One uses Standard Genetic Algorithm (SGA), the second strategy uses Improved Adaptive Genetic Algorithm (IAGA). …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul by Tom´As, Maul

“…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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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

“…The fruit flies or Drosophila Melanogaster movement strategy offers some advantages such as strategic 'search-aggregation' cycle, distribution of moving patterns with Levy Random, information sharing in real-time, and reduction of controller parameters during movements. …”
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Automatic generic process migration system in linux by Zarrabi, Amirreza

“…A fexible interface to the underlying checkpoint/ restart subsystem is designed which permits users to specify the migration mechanism according to process constraints. A migration algorithm is designed which attempts to exploit the unique features of the basic migration algorithms to form a generic algorithm. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Parallelizing web scraping to improve performance and scalability by Na, Yi Chun

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Communication and computation rate-cheating problems in divisible load scheduling: revisited by Ghanbari, Shamsollah, Othman, Mohamed, Sembiyev, Ordabay, Umarova, Zhanat

“…It is a paradigm in the area of parallel and distributed computing. Based on the DLS the computation and communication can be divided into some arbitrary independent parts, in which each part can be processed independently by a processor. …”
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NUMERICAL DIRECTIONAL OVERCURRENT PROTECTION FOR POWER DISTRIBUTION NETWORK by AHMAD, MUHAMMAD NURULDIN

“…The future work to be done is to do simulation in order toprove that the algorithm proposed is applicable to perform the digital directional overcurrent protection for theparallel-line distribution network.…”
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Extended Kalman Filter (EKF)-based modular-stack Vanadium Redox Flow Battery (V-RFB) prediction model development for reducing electrode contact resistance and parallelization curr... by Mohamed, Mohd Rusllim

“…Extended reduction of power losses by 53% were recorded as parallel flow channels has been applied to the V-RFB. …”
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Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

“…In many data grid applications, data can be decomposed into multiple independent sub datasets and distributed for parallel execution. This property has been successfully employed using Divisible Load Theory (DLT) , which has been proven to be a powerful tool for modeling divisible load problems in large scale data grid. …”
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DC-based PV-powered home energy system by Sabry, Ahmad H.

“…The work initially investigates the feasibility of using the DC distribution system to power the locally available AC appliances, that are analyzed and evaluated individually to match the DC supply either by direct coupling or some modification. …”
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Critical insight for MAPReduce optimization in Hadoop by Khan, Burhan ul Islam, Olanrewaju, Rashidah Funke, Altaf, Hunain, Shah, Asadullah

“…The predominant philosophy behind Hadoop optimization is the optimization of MapReduce, which is a dominant programming platform effective in bringing a=bout many functional enhancements as per scheduling algorithms developed and implemented. MapReduce has emerged as the most significant part of Hadoop system that establishes itself as a framework that can effectively simplify the overall complexity of running parallel data processes across the network of computing nodes. …”
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