Search Results - (( program solution clustering algorithm ) OR ( java application modified algorithm ))

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

“…For this kind of problem, researchers believe that it will be better to find an approximate solution that can be delivered by a stochastic algorithm than waiting for an exact solution from the deterministic algorithm. …”
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An integrated model of automated elementary programming feedback using assisted and recommendation approach by Safei, Suhailan

“…Meanwhile, similar difficulty groups of the computer programs were generated using a K-Means clustering algorithm that was enhanced with ranking consideration. …”
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Linear programming approach for scheduling sports league problems in Malaysia by Ahmad Rosdi, Muhammad Ifwat

“…In order to solve the formulated LP model, we proposed several solution methods such as simplex and genetics algorithm. …”
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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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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications by Far Chen, Jong

“…To address these challenges, a novel Geographical Information System-based fuzzy Technique for Order Preference by Similarity to Ideal Solution coupled with filtration algorithms was proposed. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…The algorithm is implemented as a plugin. It does not interfere with the web application original code. …”
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Bottleneck-based heuristic for permutation flowshop scheduling by Isa, Noor Amira

“…There are four potential dominant machines (M1, M2, M3, M4) clustered as bottleneck machines. A total 1000 set random processing time for each job sizes was tested using Excel simple programming with built in Visual Basic for Application (VBA). …”
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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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4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer by Ahmed, R., Mahadzir, S., Mota-Babiloni, A., Al-Amin, M., Usmani, A.Y., Ashraf Rana, Z., Yassin, H., Shaik, S., Hussain, F.

“…Finally, the K-means clustering technique is applied for Pareto characterization. …”
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Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

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