Search Results - (( software evaluation clustering algorithm ) OR ( java application sensor algorithm ))

Software module clustering: An in-depth literature analysis by Qusay I., Sarhan, Ahmed, Bestoun S., Bures, Miroslav, Kamal Z., Zamli

“…The obtained data were then used to answer several research questions regarding state-of-the-art clustering approaches, applications of clustering in software engineering, clustering processes, clustering algorithms, and evaluation methods. …”
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Datasets Size: Effect on Clustering Results by Raheem, Ajiboye Adeleke, Ruzaini, Abdullah Arshah, Hongwu, Qin

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A hybrid Method Of Centroid-Based Clustering And Meta-Heuristic For Personalized Web Search by Bourair Sadik Mohamad Taqi

Web cluster load balancing via genetic-fuzzy based algorithm by Chin, Wen Cheong, Lim, Amy Hui Lan

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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

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Crowdsource requirements engineering: Using online reviews as input to software features clustering by Bakar, Noor Hasrina, M. Kasirun, Zarinah, Salleh, Norsaremah, Halim, Azni H.

“…The clustering results achieved by K-Means were evaluated in terms of cluster compactness and cohesion. …”
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

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The Impact of Exponent Variable on the Performance and Effectiveness of FCM Algorithm for Ontology Construction in Structured Knowledge Management by Mahmood, Khalid, Rahmah, Mokhtar, Fauziah, Zainuddin, Nor Azhar, Ahmad, Noraziah, Ahmad, Norshita, MN

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

“…Thus, there is a need to evaluate this kind of approach against relevant industrial software, with a purpose to show the degree of interaction required to cover the code as well as finding faults. …”
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Crowdsource requirements engineering: Using online reviews as input to software features clustering by Bakar N.H., Kasirun Z.M., Salleh N., Halim A.H.

Empirical robustness evaluation of DNA-based clustering methods by Rohani, Abu Bakar, Watada, Junzo

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Food recommendation based on their nutrition using K-means algorithm / Norqistina Afsha Afzan Apandi by Apandi, Norqistina Afsha Afzan

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A Community-Based Fault Isolation Approach for Effective Simultaneous Localization of Faults by Zakari, Abubakar, Lee, Sai Peck, Targio Hashem, Ibrahim Abaker

“…However, the relationship between faults and failures is not easily identified and depends solely on the accuracy of clustering, such as existing clustering algorithms are not able to isolate failed tests to their causative faults effectively which hinder localization effectiveness. …”
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Analysis of Microscopic Blood Samples for Detecting Malaria by Saw Hui, Ann

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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj by Bryan Raj , Peter Jabaraj

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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

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A framework for automated quality assessment of software requirement specification based on part-of-speech tagging, multi-agent k-means clustering and case-based reasoning by Jubair, Mohammed Ahmed

“…Software Requirement Specification (SRS) is an imperative process in a Software Engineering (SE) cycle, where its role is to document functional and non-functional requirements and to establish the tasks that a particular system is set to accomplish. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…Euclidean Distance, Pearson Correlation and Matching Matrix were used to measure the performance of the feature extraction and clustering methods. Recognition software achieved 87.14%, EPD algorithm achieved 73.57% and HMT algorithm achieved 74.30%) prediction accuracy with OTs. …”
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Application of clustering in managing unstructured textual data in relational database / Wael Mohamed Shaher Yafooz by Yafooz, Wael Mohamed Shaher

“…Three experiments have been conducted on textual Reuters corpus, Classic and WAP dataset. The clustering results have been validated using the F-measure, Entropy and Purity methods of measurement and compared with two common methods, which are information extraction and textual document clustering, for example, K-means, Frequent Item-Set, Hierarchical Clustering Algorithms and Oracle Text. …”
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