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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
    “…It achieves faster time execution and cost minimization than that other replication processes. This algorithm also introduces a multi thread based persistence layer, which supports early binding and parallel connection to the servers. …”
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  2. 2
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  3. 3
    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 new replication process will also be used in e-commerce application to secure user transaction information. …”
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  4. 4
    Named entity recognition using a new fuzzy support vector machine.

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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  5. 5
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
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  6. 6
    Wearable based-sensor fall detection system using machine learning algorithm

    Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

    Published 2021
    “…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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  7. 7
    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  8. 8
    Low altitude multispectral mapping for road defect detection

    Low altitude multispectral mapping for road defect detection by Shahrul Nizan Abd Mukti, Khairul Nizam Tahar

    Published 2021
    “…The potential of multispectral images is its help better in resolution due to its spectral characteristic. …”
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  9. 9
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  10. 10
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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  11. 11
    Relationship based replication algorithm for data grid

    Relationship based replication algorithm for data grid by Yusof, Yuhanis

    Published 2014
    “…The Relationship based Replication algorithm aims to improve the Data Grid performance by reducing the job execution time, bandwidth and storage usage.The RBR was realized using a network simulation (OptorSim) and experiment results revealed that it offers better performance than existing replication algorithms.…”
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    Monograph
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  12. 12
    Enhanced extreme learning machine for general regression and classification tasks

    Enhanced extreme learning machine for general regression and classification tasks by Mahmood, Saif F

    Published 2020
    “…The first challenge is to select the optimal number of hidden nodes for ELM in different application. To address this problem, a new approach referred to SVM-ELM is proposed, which utilizes 1-norm support vector machine (SVM) to the hidden layer matrix of ELM in order to automatically discover the optimal number of hidden nodes. …”
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  13. 13
    Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim

    Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim by Tuan Ibrahim, Tuan Nur Azlina

    Published 2024
    “…Facing challenges with existing methods, the Support Vector Machine (SVM) algorithm is employed for its proficiency in handling textual data. …”
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  14. 14
    GREEDY SINGLE USER AND FAIR MULTIPLE USERS' REPLICA SELECTION DECISION IN DATA GRID

    GREEDY SINGLE USER AND FAIR MULTIPLE USERS' REPLICA SELECTION DECISION IN DATA GRID by SALIM JARADAT, AYMAN KAMEL

    Published 2013
    “…Replicas of datasets are usually distributed to different sites, and the choice of any replica locations has a significant impact. Replica selection algorithms decide the best replica places based on some criteria. …”
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  15. 15
    A new technique for maximum load margin estimation and prediction

    A new technique for maximum load margin estimation and prediction by Aziz N.F.A., Rahman T.K.A., Yasin Z.M., Zakaria Z.

    Published 2023
    “…In addition, FAISVM is another new hybrid technique developed for maximum load margin prediction that integrates the application of FAIS and Support Vector Machine (SVM). …”
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  16. 16
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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  17. 17
    Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction

    Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction by Abdul Muqtasid, Rushdi, Mohammad, Hossin, Norita, Norwawi

    Published 2025
    “…The Support Vector Machine (SVM) is well-regarded for its high classification accuracy, but its computational efficiency is often challenged by large datasets. …”
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  18. 18
    Mixed variable ant colony optimization technique for feature subset selection and model selection

    Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  19. 19
    Support vector machine in precision agriculture: a review

    Support vector machine in precision agriculture: a review by Kok, Zhi Hong, Mohamed Shariff, Abdul Rashid, M. Alfatni, Meftah Salem, Bejo, Siti Khairunniza

    Published 2021
    “…The applications of SVM in precision agriculture (PA) are compared by identifying its interactions with variables, comparing its model performance, highlighting its strengths and weaknesses, as well as suggestions for improvements. …”
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  20. 20
    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine

    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine by Farah Nuralissa Muhammad, Lam, Kuok Choy

    Published 2023
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