Search Results - (( parallel distribution database algorithm ) OR ( java application force algorithm ))

Managing Fragmented Database Replication for Mygrants Using Binary Vote Assignment on Cloud Quorum by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Wan Maseri, Wan Mohd, Mohd Azhar, Mohd Amer, Herawan, Tutut

“…Replication in distributed database is the process of copying and maintaining database objects in multiple databases that make up a distributed database system. …”
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Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR) by Noraziah, Ahmad, Abdalla, Ahmed N., Beg, Abul Hashem

“…Distributed database replication in the heterogeneous system is a very promising and challenging platform which is the compound of multi environment. …”
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Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach by Othman, Khairulnizam

“…In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…Therefore, replication is a useful technique for distributed systems. It can improve the performance and the reliability of a database application. …”
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Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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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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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider by Omer Fadlelmola Elkhider, Samih

“…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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