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  1. 1

    ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

    Published 2013
    “…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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    Article
  2. 2

    Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

    Published 2013
    “…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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    Article
  3. 3

    Advanced solar tracking system with temperature control and real-time monitoring by Mahmuddin, Shohibul Syahmi, Nordin, Siti Aminah, Azli, Shakira Azeehan, Mohamad, Nurul Nadia

    Published 2025
    “…The system integrates key components such as a humidity sensor, light-dependent resistor (LDR) sensor, servo motor, relay module, and LCD display, working in unison to optimize solar panel performance. …”
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    Book Section
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    Arduino solar tracker with blynk / Muhammad Azim Hafizi Azlan by Azlan, Muhammad Azim Hafizi

    Published 2024
    “…The system maximizes solar energy capture by ensuring correct panel alignment in real-time through the use of servo motors, light sensors, and an intelligent algorithm. …”
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    Student Project
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    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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    Article
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    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…The hybrid algorithm is able to preselect customers to be inspected on-site for abnormalities or potential fraud according to their consumption patterns. …”
    Conference Paper
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    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…The proposed chewing detection classifies the chewing activity with an overall accuracy of 96.4% using a medium Gaussian support vector machine (SVM). In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). …”
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    Article
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    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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    Thesis
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    Fuzzy control algorithm for educational light tracking system by Abdul Kareem, Samir A., Muhida, Rizah, Akmeliawati, Rini

    Published 2010
    “…The fuzzy control algorithm for light tracking system is implemented using a webcamera as a vision sensor, two PC sound cards as output signal controller, and two DC motors as a pan-tilt driver mechanism. …”
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    Proceeding Paper
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    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

    Published 2022
    “…The proposed chewing detection classifies the chewing activity with an overall accuracy of 96.4% using a medium Gaussian support vector machine (SVM). In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). …”
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    Article
  18. 18

    Deep convolutional neural networks for forensic age estimation: A review by Alkaabi S., Yussof S., Al-Khateeb H., Ahmadi-Assalemi G., Epiphaniou G.

    Published 2023
    “…The article also aims to evaluate various databases and algorithms used for age estimation using facial images and dental images. � 2020, Springer Nature Switzerland AG.…”
    Book Chapter
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    Effective source number enumeration approach under small snapshot numbers by Ge, Shengguo

    Published 2024
    “…Experimental results show that the SEMD-based method performs significantly better than the traditional signal source number estimation algorithm in these complex environments, especially under a small number of snapshots, the SEMD method can still maintain a high estimation accuracy. …”
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    Thesis
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    A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation by Kasma Diana, Saharuddin, Mohd Hatta, Mohammed Ariff, Bahiuddin, Irfan, Nurhazimah, Nazmi, Mohd Azizi, Abdul Rahman, Mohd Ibrahim, Shapiai, Fauzan, Ahmad, Sarah Atifah, Saruchi

    Published 2024
    “…Therefore, this paper proposed a carbonyl iron particle (CIP) concentration based MRE prediction model using neural network algorithm. Neural network-based machine learning model is more approachable compared to conventional mathematical modelling approach due to easily identify trends and pattern while handling multi-variety data. …”
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    Article