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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  5. 5
    E4ML: Educational Tool for Machine Learning

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
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  6. 6
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  7. 7
    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Even though, there is a tool for clustering, some of this tool required an expert knowledge in clustering in order to understand the results. …”
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  8. 8
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…But all the clustering tool available are not suitable enough for a normal people that does not have expert knowledge in this field. …”
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  9. 9
    Decision tree as knowledge management tool in image classification

    Decision tree as knowledge management tool in image classification by Kusrini, , Harjoko, Agus

    Published 2008
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  10. 10
    Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming

    Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming by Mansor, Mohd. Asyraf

    Published 2017
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  11. 11
    Comparative study of apriori-variant algorithms

    Comparative study of apriori-variant algorithms by Mutalib, Sofianita, Abdul Subar, Ammar Azri, Abdul Rahman, Shuzlina, Mohamed, Azlinah

    Published 2016
    “…Handling and processing this “big data” demand powerful data mining methods and analysis tools that can turn data into useful knowledge. One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
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  12. 12
    'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Algorithms".

    'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Al... by Eka Wahyu, Aditya, Nur Haryani, Zakaria, Fazli, Azzali, Mohamad Nazim, Jambli

    Published 2024
    “…The Future of Human-Computer Integration: Industry 5.0 Technology, Tools, and Algorithms provides a valuable insight into how Industry 5.0 technologies, tools, and algorithms can revolutionise industries and drive innovation. …”
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  13. 13
    The development of semantic meta-database: an ontology based semantic integration of biological databases

    The development of semantic meta-database: an ontology based semantic integration of biological databases by Samsudin, Ruhaidah, Deris, Safaai, Othman, Muhammad Razib, Md. Illias, Rosli

    Published 2007
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  14. 14
    'Chapter 10: 5G-enabled IoT applications in healthcare: Transforming the Industry 5.0 healthcare landscape' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Algorithms, Edited By Norliza Katuk, Roberto Vergallo, Tito Sugiharto, Copyright 2024".

    'Chapter 10: 5G-enabled IoT applications in healthcare: Transforming the Industry 5.0 healthcare landscape' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 T... by Mohamad Nazim, Jambli, Mohamad Zul Haziq, Mohd Fadzli, Sinarwati, Mohamad Suhaili, Nur Haryani, Zakaria

    Published 2024
    “…The Future of Human-Computer Integration: Industry 5.0 Technology, Tools, and Algorithms provides a valuable insight into how Industry 5.0 technologies, tools, and algorithms can revolutionise industries and drive innovation. …”
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  15. 15
    Disparity between theory & practice beyond the worst-case competitive analysis

    Disparity between theory & practice beyond the worst-case competitive analysis by Iqbal, Javeria, Ahmad, Iftikhar, Shah, Asadullah

    Published 2019
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  16. 16
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…It is also expected that tool with fexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.…”
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  17. 17
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Muhamad Aiman Raziq, Muhamad Aiman Raziq, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…It is also expected that tool with fexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.…”
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  18. 18
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, MuhamadAiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…It is also expected that tool with fexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.…”
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  19. 19
    Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, H. P. Manurung, Yupiter, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon6 & Vladimir S. Kachinskyi, John R. C. Dizon6 & Vladimir S. Kachinskyi

    Published 2023
    “…It is also expected that tool with fexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.…”
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  20. 20
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…It is also expected that tool with fexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.…”
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