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  1. 1
    Direct approach for mining association rules from structured XML data

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

    Published 2012
    “…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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    Thesis
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  2. 2
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    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.

    Published 2023
    “…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. …”
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  3. 3
    Prevention And Detection Mechanism For Security In Passive Rfid System

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

    Published 2013
    “…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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  4. 4
    Automatic generation of content security policy to mitigate cross site scripting

    Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

    Published 2016
    “…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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  5. 5
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  6. 6
    Extensions to the K-AMH algorithm for numerical clustering

    Extensions to the K-AMH algorithm for numerical clustering by Seman, Ali, Mohd Sapawi, Azizian

    Published 2018
    “…The experimental results prove that the k-AMH Numeric I and k-AMH Numeric II algorithms can be effectively used for numerical clustering. …”
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  7. 7
    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system

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

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Thesis
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  8. 8
    Improved clustering using robust and classical principal component

    Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

    Published 2017
    “…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
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    Thesis
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  9. 9
    Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster

    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

    “…In this paper has been proposed a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. …”
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  10. 10
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  11. 11
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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    Citation Index Journal
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  12. 12
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
    “…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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    Citation Index Journal
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  13. 13
    Autonomous and deterministic supervised fuzzy clustering

    Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

    Published 2010
    “…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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  14. 14
    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy

    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

    Published 2014
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  15. 15
    MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters

    MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar

    Published 2012
    “…In this paper, we propose a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. …”
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  16. 16
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm has been around for over a century. …”
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    Final Year Project / Dissertation / Thesis
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  17. 17
    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour

    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
    “…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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    Proceeding Paper
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  18. 18
    Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles

    Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

    Published 2021
    “…If we use the appropriate features, then the k-NN will be a reliable algorithm. …”
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  19. 19
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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  20. 20
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. Moreover, K-Nearest Neighbour (K-NN) classifier is one of the widely use classifier due to its simplicity. …”
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    Monograph
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