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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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  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
    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The simulation results for the first and second models are done using the data obtained from Malaysia distribution network (DISCO-Net) and 69 bus test system that were implemented using Java Agent Development Framework package software. …”
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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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

    “…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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  9. 9
    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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  10. 10
    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
    “…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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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
    “…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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  12. 12
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…In this paper, three essential segmentation algorithms, namely Fuzzy C-means, K-means, and Expectation–Maximization algorithms, are proposed for the identification of renal stone in kidney ultrasound images. …”
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  13. 13
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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  14. 14
    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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  15. 15
    Clustering of rainfall data using k-means algorithm

    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

    Published 2019
    “…This study aims to describe regional cluster pattern of rainfall based on maximum daily rainfall in Johor, Malaysia. K-Means algorithm is used to obtain optimal rainfall clusters. …”
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  16. 16
    Adaptive interference canceller using analog algorithm with offset voltage

    Adaptive interference canceller using analog algorithm with offset voltage by Mohammed, Alaa Hadi

    Published 2015
    “…They require the utilization of the adaptive algorithms. Algorithms such as Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms often have poor numerical properties due to the practical implementation complexities. …”
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  17. 17
    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
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  18. 18
    Tracking The Eyes Using Interdependence Mean Shift Tracking Algorithm With Appropriate Information Provided

    Tracking The Eyes Using Interdependence Mean Shift Tracking Algorithm With Appropriate Information Provided by Masrullizam, Mat Ibrahim, Syafeeza, Ahmad Radzi, Soraghan, John

    Published 2016
    “…Most of the developed eyes tracking algorithm are not considered the condition of the eyes that would provide the appropriate information to be used in the processes of the facial analysis algorithm. …”
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  19. 19
    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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  20. 20
    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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