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  1. 1
    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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  2. 2
    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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  3. 3
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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  4. 4
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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  5. 5
    Diagnosis security problems in cloud computing for business cloud

    Diagnosis security problems in cloud computing for business cloud by Shakir M., Abubakar A.B., Yousoff Y.B., Sagher A.M., Alkayali H.

    Published 2023
    “…Secondly , they prefer to develop the multi-key cipher algorithm in order to manage the encryption based on the level of security. � 2005 - 2016 JATIT & LLS. …”
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  6. 6
    Mapping of oil palm land cover using integration of cloud computing, machine learning and big data

    Mapping of oil palm land cover using integration of cloud computing, machine learning and big data by Shaharum, Nur Shafira Nisa

    Published 2019
    “…However, the expansion of oil palm plantation has been recognised as a threat to the wildlife species and had caused massive amount of deforestations. A tropical country with humid weather, Malaysia has been listed as one of the top three countries with the highest rate of deforestation in the world. …”
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  7. 7
    Establishment of perez du-mortier calibration algorithm as a sunphotometers calibration protocol at a altitude above sea level

    Establishment of perez du-mortier calibration algorithm as a sunphotometers calibration protocol at a altitude above sea level by Nur Hasinah Najiah Maizan

    Published 2017
    “…However, it is impenetrable to find cloud free condition at near sea level altitude especially tropical country due to cloud loading and rainfall throughout the year. …”
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  8. 8
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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  9. 9
    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…In FFB and PO models, the data used 15 variables, namely: percentage of mature area and percentage of immature area, rainfall, rainy days, humidity, radiation, temperature, surface wind speed, evaporation and cloud cover, O3, CO, NO2, SO2, and PM10. The study used input energy data from 8 variables for developing energy models. …”
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