Search Results - (( java application customization algorithm ) OR ( knowledge active learning 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

    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

    Published 2001
    “…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. …”
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  3. 3

    Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences by Lim, Bih Loong

    Published 2019
    “…The result shows that there is no significant effect of the learning material in increasing the participants’ algorithm skill. …”
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    Thesis
  4. 4

    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong by Mailah, Musa, Ong, Miaw Yong

    Published 2004
    “…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. …”
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  5. 5
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    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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  7. 7

    Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

    Published 2016
    “…Those activities define learning in its own specific domain and context. …”
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  8. 8

    Adaptive approach in handling human inactivity in computer power management by Candrawati, Ria, Hashim, Nor Laily

    Published 2016
    “…This study introduces Control, Learn and Knowledge model that adapts the Monitor, Analyze, Planning, Execute control loop integrates with Q Learning algorithm to learn human inactivity period to minimize the computer power consumption.An experiment to evaluate this model was conducted using three case studies with same activities. …”
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  9. 9

    Comparison on machine learning algorithm to fast detection of malicious web pages by Wan Nurul Safawati, Wan Manan, Mohd Nizam, Mohmad Kahar, Noorlin, Mohd Ali

    Published 2021
    “…Therefore, implementing the principle of the machine learning, which is training the classification algorithm will be perform to improve the detection accuracy. …”
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  10. 10

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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  11. 11

    Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

    Published 2017
    “…The activities were conducted involving first and fourth year undergraduate students and Master students in Programming 1 (31 students), Data Structure (6 students), Analysis of Algorithm (12 students) and Advanced Algorithm (22 students) courses respectively. …”
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  12. 12

    Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian by Zahedeh, Zamanian

    Published 2019
    “…People who are greatest asset of organization, they may also be the greatest threat due to their access to highly confidential information and their knowledge of the organizational systems. Insider threat activity has huge impact on business. …”
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  13. 13

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  14. 14

    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

    Published 2021
    “…Even though there was no significant difference between the scores of the active learning methods, a comparison between both the approaches from a teaching perspective suggested that game-based learning was more suitable due to its interactivity. …”
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  15. 15

    Clustering Student Performance Data Using k-Means Algorithms by Sultan Alalawi, Sultan Juma, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2023
    “…Clustering, an unsupervised learning technique, is one of the most powerful machine- learning tools for discovering patterns and unseen data. …”
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  16. 16

    Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning by Abdulrazak Yahya, Saleh, Ros Ameera, Rosdi

    Published 2023
    “…The objectives of this study are to pre-process lung nodules data, develop a CNN with transfer learning algorithm, and analyse the effectiveness of CNN with transfer learning compared to standard of other methods. …”
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    Proceeding
  17. 17

    Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

    Published 2012
    “…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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    Conference or Workshop Item
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    Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

    Published 2006
    “…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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  20. 20

    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

    Published 2022
    “…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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