Search Results - (( java implementation rsa algorithm ) OR ( program data clustering algorithm ))
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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Thesis -
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe
Published 2017“…Java programming language is used to implement the algorithm. …”
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Secure Image Steganography Using Encryption Algorithm
Published 2016“…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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Conference or Workshop Item -
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Digitally signed electronic certificate for workshop / Azinuddin Baharum
Published 2017“…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
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Data mining in network traffic using fuzzy clustering
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Data mining in network traffic using fuzzy clustering
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Efficient genetic partitioning-around-medoid algorithm for clustering
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A cluster-based hybrid replica control protocol for high availability in data grid
Published 2019“…Another proposed algorithm is replica placement algorithm which selects and places only one replica in each cluster. …”
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A maximal-clique-based clustering approach for multi-observer multi-view data by using k-nearest neighbor with S-pseudo-ultrametric induced by a fuzzy similarity
Published 2024“…The proposed clustering algorithm is programmed and tested on synthetic and four real-world datasets using the R software. …”
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Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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Off-the-shelf indoor localization system using radio frequency for wireless local area network
Published 2018“…The proposed system is enhanced further by using offline clustering (OC) algorithm to reduce the data size of radio map and improve the system’s accuracy. …”
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Feature clustering for pso-based feature construction on high-dimensional data
Published 2019“…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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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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