Search Results - parallel distributed ((((mobile algorithm) OR (mining algorithm))) OR (modified algorithm))

Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system by Krishnan P.S., Kiong T.S., Koh J., Yap D.

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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

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

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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm by Prajindra S.K., Tiong S.K., Johnny Koh S.P., Yap D.F.W.

“…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”

A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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Parallel Diagonally Implicit Runge-Kutta Methods For Solving Ordinary Differential Equations by Din, Ummul Khair Salma

“…All algorithms are written in C language and the parallel code is implemented on Sun Fire V1280 distributed memory system. …”
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A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems by Ahmad, S.G., Liew, Chee Sun, Munir, E.U., Ang, Tan Fong, Khan, S.U.

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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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Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR) by Noraziah, Ahmad, Abdalla, Ahmed N., Beg, Abul Hashem

“…It achieves faster time execution and cost minimization than that other replication processes. This algorithm also introduces a multi thread based persistence layer, which supports early binding and parallel connection to the servers. …”
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Automatic generic process migration system in linux by Zarrabi, Amirreza

“…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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Bead-sort algorithm for load shuffling in miniload AS/RS with an open-rack structure by Vasili, Mohammadreza, Tang, Sai Hong, Ismail, Napsiah, Sulaiman, Shamsuddin, Wong, Shaw Voon, Vasili, Mehdi

“…This paper presents an open-rack structure with unidirectional-upward mobile loads within the rack, for miniload AS/RS. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks by Chien, Stephen Lim Een, Raja Maamor Shah, Raja Noor Farah Azura, Othman, Mohamed

“…The performance parameters and properties of chordal rings have been researched extensively as models for parallel and distributed interconnection topology models since their founding in 1981. …”
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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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P2P-Based Image Recognition for Component Tracking in a Large Engineering Domain by Amir, Amiza, Muhamad Amin , Anang Hudaya, Khan, Asad I.

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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…Nowadays, in the grid community, distributed and clustering system, a lot of work has been focused on providing efficient and safe replication management services through designing of algorithms and systems. …”
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