Search Results - (( parallel distribution databases algorithm ) OR ( java application optimisation algorithm ))
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1
Managing Fragmented Database Replication for Mygrants Using Binary Vote Assignment on Cloud Quorum
Published 2014“…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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2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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3
Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR)
Published 2013“…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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4
Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach
Published 2022“…In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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6
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…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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7
K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…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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