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  1. 1
    Benchmarking Framework for Performance in Load Balancing Single System Image

    Benchmarking Framework for Performance in Load Balancing Single System Image by S. Ahmed, Bestoun

    Published 2009
    “…There is an essential need for a benchmark framework for the Single System Image clusters due to the wide range of implementation and the need for identifying the performance and behaviour of the system. …”
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  2. 2
    Big data clustering using grid computing and ant-based algorithm

    Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

    Published 2013
    “…However, there are many challenges in dealing with big data such as storage, transfer, management and manipulation of big data.Many techniques are required to explore the hidden pattern inside the big data which have limitations in terms of hardware and software implementation. This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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  3. 3
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…The experimental results show that c=5, which is consistent for cost function with the ideal silhouette coefficient of 1, is the optimal number of clusters for this dataset. A comparative study is done to validate the proposed algorithm by implementing the other contemporary algorithms for the same dataset. …”
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  4. 4
    Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach

    Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach by Othman, Khairulnizam

    Published 2022
    “…Segmentation clustering algorithms have setbacks on overlapping clusters, proportion, and multidimensional scaling to map and leverage the data. …”
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  5. 5
    Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb

    Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb by Riyaz Ahamed , Ariyaluran Habeeb

    Published 2019
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  6. 6
    Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine

    Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

    Published 2019
    “…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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  7. 7
    New filtering framework for web personalization search / Anitawati Mohd Lokman and Aishah Ahmad

    New filtering framework for web personalization search / Anitawati Mohd Lokman and Aishah Ahmad by Mohd Lokman, Anitawati, Ahmad, Aishah

    Published 2012
    “…This algorithm can be implemented in both website and search engine.…”
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  8. 8
    Cooperative heterogeneous vehicular clustering for road traffic management / Iftikhar Ahmad

    Cooperative heterogeneous vehicular clustering for road traffic management / Iftikhar Ahmad by Iftikhar , Ahmad

    Published 2019
    “…This implementation increases the level of synchronization of CMs with a cluster head, thereby increasing cluster stability. …”
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  9. 9
    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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  10. 10
    A coverage path planning approach for autonomous radiation mapping with a mobile robot

    A coverage path planning approach for autonomous radiation mapping with a mobile robot by Abd Rahman N.A., Sahari K.S.M., Hamid N.A., Hou Y.C.

    Published 2023
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  11. 11
    An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study

    An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study by Sutanto, Daniel Hartono

    Published 2018
    “…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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  12. 12
    Blockchain based security framework for device authentication and data communication in decentralized IoT network

    Blockchain based security framework for device authentication and data communication in decentralized IoT network by Alahmed, Mahmoud Tayseer

    Published 2023
    “…First, this thesis proposes a clustering algorithm for IoT devices based on the device energy residues, the device location relative to other devices in the network, and the device computational ability. …”
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  13. 13
    Application-Programming Interface (API) for Song Recognition Systems

    Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

    Published 2024
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  14. 14
    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

    Published 2024
    “…Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. …”
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  15. 15
    A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications

    A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications by Far Chen, Jong

    Published 2025
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  16. 16
    Collective interaction filtering with graph-based descriptors for crowd behaviour analysis

    Collective interaction filtering with graph-based descriptors for crowd behaviour analysis by Wong, Pei Voon

    Published 2018
    “…The group detection experiment is implemented using the clustering algorithm. Normalized Mutual Information and Rand Index are used to measure the performance of Collective Interaction Filtering. …”
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  17. 17
    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning

    The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

    Published 2025
    “…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
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  18. 18
    A study on component-based technology for development of complex bioinformatics software

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…From the enriched GO tree, the BTreeBicluster algorithm is applied during the clustering process. …”
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  19. 19
    FSM-Gear weight-based energy-efficient protocol for illegal logging monitoring using firefly synchronization

    FSM-Gear weight-based energy-efficient protocol for illegal logging monitoring using firefly synchronization by Mutiara, Giva Andriana

    Published 2022
    “…The effort of low-power algorithm was conducted in several stages, such as (1) randomly distributed localization technique; (2) randomly applied clustering and cluster head selection; (3) the use of Time Division Multiple Access (TDMA) synchronization; and (4) how to formulate the distance factor to the power emitted by sensor nodes not based on the real environment. …”
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  20. 20
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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