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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

    Published 2013
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  3. 3
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

    Published 2013
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  4. 4
    Wearable based-sensor fall detection system using machine learning algorithm

    Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

    Published 2021
    “…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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    Proceeding Paper
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  5. 5
    Application of reinforcement learning to wireless sensor networks: models and algorithms

    Application of reinforcement learning to wireless sensor networks: models and algorithms by Yau, Alvin Kok-Lim *, Goh, Hock Guan *, Chieng, David, Kwong, Kae Hsiang

    Published 2015
    “…Reinforcement learning (RL) has been applied in a wide range of schemes in WSNs, such as cooperative communication, routing and rate control, so that the sensors and sink nodes are able to observe and carry out optimal actions on their respective operating environment for network and application performance enhancements. …”
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  6. 6
    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
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  7. 7
    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective

    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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  8. 8
    Machine learning in botda fibre sensor for distributed temperature measurement

    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
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  9. 9
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
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  10. 10
    IOT-based fertigation system / Mohamad Amir Furqan Darus

    IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

    Published 2024
    “…Advanced algorithms and machine learning processes this data to determine the ideal irrigation and fertilization needs. …”
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    Student Project
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  11. 11
    A wheelchair sitting posture detection system using pressure sensors

    A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

    Published 2024
    “…Three classification algorithms based on the supervised learning of machine learning, such as support vector machine (SVM), random forest (RF),and decision tree (DT) were used to classify the postures which produced an accuracy of 95.44%, 98.72%,and 98.80%, respectively. …”
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  12. 12
    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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  13. 13
    Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.]

    Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.] by Mohamad Zamri, Nurul Farhana, Md Tahir, Nooritawati, Megat Ali, Megat Syahirul Amin, Khirul Ashar, Nur Dalila

    Published 2022
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  14. 14
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Thesis
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  15. 15
    Intelligent Energy Management in Residential Building

    Intelligent Energy Management in Residential Building by Zubair, Nur Faizah

    Published 2014
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    Final Year Project
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  16. 16
    A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective

    A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
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  17. 17
    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation

    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

    Published 2023
    Conference Paper
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  18. 18
    Feature extraction and supervised learning for volatile organic compounds gas recognition

    Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

    Published 2023
    “…This research project aims to investigate effective feature extraction techniques that can be employed as discriminative features for machine learning algorithms. A preliminary dataset was used to predict VOC classification through the application of five supervised machine learning algorithms: k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Machines (SVM), Logistic Regression (LR), and Artificial Neural Networks (ANN). …”
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  19. 19
    Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring

    Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring by Nordin N.D., Abdullah F., Zan M.S.D., Bakar A.A.A., Krivosheev A.I., Barkov F.L., Konstantinov Y.A.

    Published 2023
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  20. 20
    Water quality monitoring using machine learning and IoT: a review

    Water quality monitoring using machine learning and IoT: a review by Hasan, Tahsin Fuad, Kabbashi, Nassereldeen Ahmed, Saleh, Tanveer, Alam, Md. Zahangir, Abd Wahab, Mohd Firdaus, Nour, Abdurahman Hamid

    Published 2024
    “…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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