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  1. 1
    Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR)

    Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR) by Noraziah, Ahmad, Abdalla, Ahmed N., Beg, Abul Hashem

    Published 2013
    “…Proper mechanism is significantly required in order to manage the complex heterogeneous data replication. This paper presents a new algorithm namely the Persistence Layer Synchronous Replication (PLSR) in order to manage the agent handling the replication. …”
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  2. 2
    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
    “…All the replication servers established its connection through interfaces. …”
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  3. 3
    Improving response time, availability and reliability through asynchronous replication technique in cluster architecture of web server cluster

    Improving response time, availability and reliability through asynchronous replication technique in cluster architecture of web server cluster by Aznida Hayati, Zakaria@Mohamad, Ahmad Nazari, Mohd Rose, Zarina, Mohamad, Wan Suryani, Wan Awang

    Published 2010
    “…This paper proposes an algorithm of data replication scheme based on asynchronous replication in order to improve web server cluster system reliability. …”
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  4. 4
    A technique of dispatching algorithms for web-server cluster

    A technique of dispatching algorithms for web-server cluster by Zarina Mohamad

    Published 2011
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  5. 5
    Fault Tolerence on Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique

    Fault Tolerence on Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Fairuzullah, A., Nurzety Aqtar, Ahmad Azuan, Azlina, Zainuddin

    Published 2013
    “…It also increases the degrees of data availability. This is because the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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  6. 6
    Fault Tolerance On Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique

    Fault Tolerance On Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique by Noraziah, Ahmad, Abdulla Fairuzullah, Ahmad Tajuddin, Ainul Azila, Che Fauzi, Nurzety Aqtar, Ahmad Azuan, Azlina, Zainuddin, Herawan, Tutut

    Published 2013
    “…It also increases the degrees of data availability. This is be cause the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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  7. 7
    Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication

    Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Herawan, Tutut, Zailani, Abdullah

    Published 2015
    “…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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  8. 8
    Binary vote assignment on grid quorum replication technique with association rule

    Binary vote assignment on grid quorum replication technique with association rule by Ainul Azila, Che Fauzi

    Published 2018
    “…However, these techniques have its weaknesses in terms of communication costs that is the total replication servers needed to replicate the data. Furthermore, these techniques also do not consider the correlation between data during the fragmentation process. …”
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  9. 9
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  10. 10
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  11. 11
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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  12. 12
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  13. 13
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  14. 14
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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  15. 15
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  16. 16
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  17. 17
    Development of classification algorithms of human gait

    Development of classification algorithms of human gait by Koh, Chee Hong

    Published 2022
    “…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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  18. 18
    Text Extraction Algorithm for Web Text Classification

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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  19. 19
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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  20. 20
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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