Search Results - (( developing interactive clustering algorithm ) OR ( java application optimization algorithm ))

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    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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    Final Year Project / Dissertation / Thesis
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    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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    Article
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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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    Article
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    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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    Article
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    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering by Abang Mohd Arif Anaqi, Abang Isa

    Published 2021
    “…Research has shown that an automated segmentation from the Magnetic Resonance Image (MRI) is potentially giving more effective and accurate results. This study aims to develop an automatic segmentation by utilizing clustering algorithm for acute ischemic stroke lesion identification. …”
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    Thesis
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    Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization by Hamdi, Mustafa Maad, Audah, Lukman, Rashid, Sami Abduljabbar

    Published 2022
    “…This developed multi-objective optimization was designated as adaptive jumping multi-objective firefly algorithm (AJ-MOFA). …”
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    Article
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    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri by Nik Mohd Asri, Nik Asyraniasna

    Published 2024
    “…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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    Thesis
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    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…Lastly, a dashboard was developed using Microsoft Power BI to visualize the clustering results in meaningful analysis. …”
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    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI by Abang Mohd Arif Anaqi, Abang Isa, Kuryati, Kipli, Ahmad Tirmizi, Jobli, Muhammad Hamdi, Mahmood, Siti Kudnie, Sahari, Aditya Tri, Hernowo, Sinin, Hamdan

    Published 2021
    “…The result shows the potential of automated segmentation to differentiate between the healthy and lesion tissues with 90.08% in accuracy and 0.89 in dice coefficient. The development of an automated segmentation algorithm was successfully achieved by entirely depending on the computer with minimal interaction.…”
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    Article