Search Results - (( intelligence system thinking algorithm ) OR ( intelligence model thinking algorithm ))*

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  1. 1
    An empirical study of TensorFlow lite performances in Raspberry Pi / Mohamad Harith Mohd Zahid

    An empirical study of TensorFlow lite performances in Raspberry Pi / Mohamad Harith Mohd Zahid by Mohd Zahid, Mohamad Harith

    Published 2020
    “…Artificial intelligence today is essentially a machine that can do typically any specific task before mimicry to human intelligence. …”
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  2. 2
    Agent architectures (building chatterbot) / Umi Aimah Abu Bakar

    Agent architectures (building chatterbot) / Umi Aimah Abu Bakar by Umi Aimah , Abu Bakar

    Published 2003
    “…The methodology for the system development is also discussed, which is the Waterfall Model with Prototyping. …”
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  3. 3
    A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era

    A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era by Saiid, Muhammad, Bah, Ahmadou Pathe, Ahmad Dahlan, Abdul Rahman

    Published 2022
    “…This paper develops and proposes through the adoption of the design thinking methodology an alternate conceptual business model for a Malaysian private healthcare University-of-the-Future (UotF) using the renowned Business Model Canvas (BMC) and Strategy Canvas (SC) frameworks. …”
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  4. 4
    Artificial Neural Network Flood Prediction for Sungai Isap Residence

    Artificial Neural Network Flood Prediction for Sungai Isap Residence by Khoo, Chun Keong, Mahfuzah, Mustafa, Ahmad Johari, Mohamad, M. H., Sulaiman, Nor Rul Hasma, Abdullah

    Published 2016
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    Conference or Workshop Item
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  5. 5
    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)

    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud M.A., Ahmad M.S., Ahmad A., Mustapha A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
    Short Survey
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  6. 6
    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…It is important to know how this process is exercised. There is a model that studies the social behavior of humans called genetic algorithms (GA). …”
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  7. 7
    Music Recommender System Using Machine Learning Content-Based Filtering Technique

    Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

    Published 2022
    “…Machine Learning is a form of Artificial Intelligence that will make systems to think like human being. …”
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    Undergraduates Project Papers
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  8. 8
    Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction

    Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction by Muna Elsadig, Ashraf Osman Ibrahim Elsayed, Shakila Basheer, Manal Abdullah Alohali, Sara Alshunaifi, Haya Alqahtani, Nihal Alharbi, Wamda Nagmeldin

    Published 2022
    “…Researchers in cyberspace are motivated to create intelligent models and offer secure services on the web as phishing grows more intelligent and malicious every day. …”
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  9. 9
    Predicting Diseases Using Multi-BackPropagation

    Predicting Diseases Using Multi-BackPropagation by Wan Hussain, Wan Ishak

    Published 2002
    “…The computer becomes more important with the introduction of the intelligent system. The intelligent medical system increases the ability of medical practitioners in providing diagnosis and prognosis. …”
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  10. 10
    Humanizing AI in Higher Education: Rethinking HR, Ethics, and Skill Development for University Employees in the SDG Era

    Humanizing AI in Higher Education: Rethinking HR, Ethics, and Skill Development for University Employees in the SDG Era by Shreeja, Nair, Kritika, Banka, Ankur, Pandya

    Published 2025
    “…The results identified three predominant themes: (1) unbalanced ethical frameworks and low transparency in AI-driven hiring and performance appraisal; (2) faculty and staff apprehension due to algorithmic biases, data privacy issues, and a lack of institutional oversight; and (3) an urgent need to develop emotional intelligence, interdisciplinary thinking, and digital sensitivity among employees. …”
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