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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Clustering algorithm for market-basket analysis : the underlying concept of data mining technology

    Clustering algorithm for market-basket analysis : the underlying concept of data mining technology by Abdul Kadir, Khairil Annuar

    Published 2003
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  3. 3
    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
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  4. 4
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
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  5. 5
    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
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  6. 6
    Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering

    Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering by Annisa Eka Haryati, ., Sugiyarto, Surono, Tommy Tanu, Wijaya, Goh, Khang Wen, Aris, Thobirin

    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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  7. 7
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  8. 8
    Data mining in network traffic using fuzzy clustering

    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
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  9. 9
    Data mining in network traffic using fuzzy clustering

    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
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  10. 10
    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
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  11. 11
    Efficient genetic partitioning-around-medoid algorithm for clustering

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

    Published 2019
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  12. 12
    A cluster-based hybrid replica control protocol for high availability in data grid

    A cluster-based hybrid replica control protocol for high availability in data grid by Mabni, Zulaile

    Published 2019
    “…Another proposed algorithm is replica placement algorithm which selects and places only one replica in each cluster. …”
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  13. 13
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  14. 14
    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

    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 by Khameneh, Azadeh Zahedi, Ghaznavi, Mehrdad, Kilicman, Adem, Mahad, Zahari, Mardani, Abbas

    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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  15. 15
    Learning analytic framework for students’ academic performance and critical learning pathways

    Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

    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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  16. 16
    Off-the-shelf indoor localization system using radio frequency for wireless local area network

    Off-the-shelf indoor localization system using radio frequency for wireless local area network by Alhammadi, Abdulraqeb Shaif Ahmed

    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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  17. 17
    Feature clustering for pso-based feature construction on high-dimensional data

    Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

    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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  18. 18
    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata

    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

    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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  19. 19
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…In order to have a realistic characteristic of a parallel computing engine, a Rocks based computer cluster was built and used for the test. Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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  20. 20
    Computational study of cobalt oxide: Nanoparticles, surfaces and thin films supported on metal oxide surfaces / Ala’ Omar Hasan Zayed

    Computational study of cobalt oxide: Nanoparticles, surfaces and thin films supported on metal oxide surfaces / Ala’ Omar Hasan Zayed by Ala’ Omar , Hasan Zayed

    Published 2018
    “…Besides using our genetic algorithm code called Universal Genetic Algorithm (UGA) combined with DFT calculations to find the global and local energy minimum structures of (CoO)n (n = 3 − 7) clusters, we have also extended the search space to (CoO)nq (n = 3−10, q = 0, +1) clusters by another code of ours, the Modified Basin-Hopping Monte Carlo Algorithm (MBHMC) program, accompanied by accurate DFT calculations. …”
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