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  1. 1
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
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  2. 2
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

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

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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  3. 3
    Visdom: Smart guide robot for visually impaired people

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

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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    Final Year Project / Dissertation / Thesis
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  4. 4
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…Most existing methods deal with the detection of an action after its completion. …”
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  5. 5
    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

    Published 2009
    “…These values are used to define the objective function’s parameters. …”
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  6. 6
    Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings

    Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

    Published 2023
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  7. 7
    Deep Reinforcement Learning For Control

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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    Monograph
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  8. 8
    STUDIES ON COMPARISON OF PROPORTIONAL ON ERROR WITH PROPORTIONAL ON MEASURED VALUE IN PID CONTROLLERS

    STUDIES ON COMPARISON OF PROPORTIONAL ON ERROR WITH PROPORTIONAL ON MEASURED VALUE IN PID CONTROLLERS by WAN MOHD RUSHIDI, WAN AMIR HAKIMI

    Published 2019
    “… PID Controllers have different algorithms or methods in which the controller action is based on Error or Process Variable (PV). …”
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    Final Year Project
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  9. 9
    Obstacle avoidance robot using sonar sensor (OARuS)

    Obstacle avoidance robot using sonar sensor (OARuS) by Mohamad Sabri Abdullah

    Published 2008
    “…An embedded controller function as total guard actions that made by robot, it will receive, processing, and define data (input), and decide what that should do by robot to further action. …”
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    Learning Object
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  10. 10
    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization

    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization by Mizher, Manar Abduljabbar Ahmad, Ang, Mei Choo, Sheikh Abdullah, Siti Norul Huda, Kok, Weng Ng

    Published 2019
    “…We then evaluated the Improved AKF algorithm with the-state-of-the-art algorithms in terms of compression ratio using Paul videos and Shih-Tang dataset. …”
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  11. 11
    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar

    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

    Published 2019
    “…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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  12. 12
    Modeling sub-event dynamics in first-person action recognition

    Modeling sub-event dynamics in first-person action recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal S.

    Published 2017
    “…We propose a method to represent the high level dynamics of sub-events in first-person videos by dynamically pooling features of sub-intervals of time series using a temporal feature pooling function. …”
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  13. 13
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  14. 14
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  15. 15
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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  16. 16
    Transformer health index prediction using feedforward neural network according to scoring and ranking method

    Transformer health index prediction using feedforward neural network according to scoring and ranking method by Salim, Nur Ashida, Jasni, Jasronita, Mohamad, Hasmaini, Mat Yasin, Zuhaila

    Published 2021
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  17. 17
    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin

    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

    Published 2021
    “…It is a fully automated black-box testing approach that uses Upper Confidence Bound (UCB) exploration-exploitation strategy to generate actions that visit unexplored states of the app and uses the execution of the app on the generated actions to construct a state-transition model. …”
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  18. 18
    Revolutionizing video analytics: a review of action recognition using 3D

    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…As an interdisciplinary field, the 3D video action recognition model interprets human actions in three-dimensional video data using approaches such as pose-based, volumetric, motionbased, and hybrid methods. 3D video action recognition finds application in surveillance, sports analysis, human-computer interaction, healthcare, robotics, and augmented/virtual reality. …”
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  19. 19
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Meanwhile, pattern recognition is using Probability Density Function (PDF) to determine MUAP according to type of activities. …”
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  20. 20
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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