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  1. 1
    Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

    Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation by Abualigah, Laith

    Published 2023
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  2. 2
    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
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  3. 3
    The use of multi-task learning in cybersecurity applications: a systematic literature review

    The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

    Published 2024
    “…Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”
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  4. 4
    Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem

    Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

    Published 2023
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  5. 5
    SPA & MLST typing as epidemiological tools for the study of MRSA & MSSA Isolates in Lebanon. (c2009)

    SPA & MLST typing as epidemiological tools for the study of MRSA & MSSA Isolates in Lebanon. (c2009) by Rizk, Mazen

    Published 2009
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  6. 6
    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security

    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

    Published 2023
    “…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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  7. 7
    CEAP

    CEAP by Abdel Wahab, Omar

    Published 2016
    “…The infrastructureless and decentralized nature of Vehicular Ad Hoc Network (VANET) makes it quite vulnerable to different types of malicious attacks. Detecting such attacks has attracted several contributions in the past few years. …”
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