Search Results - (( developing learning aspect algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Computational Thinking (Algorithms) Through Unplugged Programming Activities: Exploring Upper Primary Students’ Learning Experiences by Bih Loong, Lim, Chwen Jen, Chen

    Published 2021
    “…A total of 31 students from a rural primary school were exposed to the learning about the algorithm concept (an aspect of CT skills) via UPA learning materials. …”
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  2. 2

    Designing algorithm visualization on mobile platform: The proposed guidelines by Supli, Ahmad Affandi, Shiratuddin, Norshuhada

    Published 2017
    “…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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  3. 3

    User interface and interactivity design guidelines of algorithm visualization on mobile platform by Supli, Ahmad Affandi

    Published 2019
    “…It includes the fundamental recommendations for designers, developer, and lecturers to produce AVOMP which are based on two aspects, namely UI design and interactivity aspects. …”
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    Thesis
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    Developing computational thinking competencies through constructivist argumentation learning: a problem-solving perspective by Voon, Xin Pei, Wong, Su Luan, Wong, Lung Hsiang, Md Khambari, Mas Nida, Syed Abdullah, Sharifah Intan Sharina

    Published 2022
    “…To nurture higher order thinking skills and to engage effective problem-solvers, our framework incorporates four Computational Thinking-Argumentation design principles to support instructional innovation in the teaching and learning of science at the secondary school level, viz. 1) developing problem-solving competencies and building capability in solving uncertainties throughout scientific inquiry; 2) developing creative thinking and cooperativity through negotiation and evaluation; 3) developing algorithmic thinking in talking and writing; 4) developing critical thinking in the processes of abstraction and generalization.…”
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  10. 10

    Development of a genetic algorithm controller for cartesian robot by Ong, Joo Hun

    Published 2008
    “…This project involves in developing a machine learning system that is capable of performing independent learning capability for a given tasks. …”
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    DEVELOPMENT OF DRIVER DROWSINESS DETECTION ALGORITHM by YVONNE, PHUA YEE WUN

    Published 2022
    “…The deep learning approaches perform better than the technique that calculates the eye and mouth aspect ratios to detect drowsiness. …”
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    Final Year Project Report / IMRAD
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    Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

    Published 2023
    “…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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  13. 13

    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
    “…In addition, this research also develops price prediction model using Machine Learning Model based on green building datasets covering the District of Kuala Lumpur, Malaysia. …”
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    Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

    Published 2017
    “…Then, the research status and development trend of convolution neural network model based on deep learning in image classification are reviewed, which is mainly introduced from the aspects of typical network structure construction, training method and performance. …”
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  15. 15

    Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

    Published 2016
    “…With irrelevant and redundant features learning algorithm builds detection model with less accuracy rate. …”
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  16. 16

    Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

    Published 2021
    “…Seven deep learning models trained by seven noise datasets with different aspect ratios were selected and implemented in the proposed noise prediction model. …”
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    Final Year Project / Dissertation / Thesis
  17. 17

    Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin by Raja Kamarudin, Raja Muhammad Hafiz

    Published 2012
    “…However, this is a step stone towards developing a biological-inspired Sentiment Mining algorithm…”
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    Automated visual defect detection using deep learning by Loh, Xiao

    Published 2022
    “…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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    Final Year Project / Dissertation / Thesis
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    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

    Published 2023
    “…Nowadays, the advancement of drones is also factored in the development of a world surrounded by technologies. One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. …”
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    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

    Published 2023
    “…Nowadays, the advancement of drones is also factored in the development of a world surrounded by technologies. One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. …”
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