Search Results - (( java implementation modified algorithm ) OR ( using clustering using algorithm ))

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

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

“…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

“…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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An enhanced cluster head selection algorithm for routing in mobile AD-HOC network by Abdulsaheb, Ghaida Muttasher

“…This thesis proposes a cluster based routing protocol, the Enhanced Cluster Routing Protocol (ECRP), which uses a modified cluster formation algorithm to build the cluster structure and select one of the nodes to be the cluster head. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Tutut, Herawan, K., F.Rabbi

“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

“…Some clustering algorithms, especially those that are partitioned-based, clusters any data presented to them even if similar features do not present. …”
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Extensions to the K-AMH algorithm for numerical clustering by Seman, Ali, Mohd Sapawi, Azizian

“…It can also be used to cluster numerical values with minimum modification to the original algorithm. …”
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Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz by Aziz, Azwani

“…There are many techniques of clustering the image. The most widely used of clustering technique is Fuzzy C-Means algorithm (FCM). …”
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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

“…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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