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SDN-Based VANET Routing: A Comprehensive Survey on Architectures, Protocols, Analysis, and Future Challenges by Hussein N.H., Koh S.P., Yaw C.T., Tiong S.K., Benedict F., Yusaf T., Kadirgama K., Hong T.C.

“…Then, the potential of SDN-based VANET is explored from the aspect of routing and the design requirements of routing protocols in SDVNs. SDVN routing algorithms are uniquely classified according to various criteria. …”

SDN-based VANET routing: A comprehensive survey on architectures, protocols, analysis, and future challenges by Hussein, Nehad Hameed, Koh, Siaw Paw, Yaw, Chong Tak, Tiong, Sieh Kiong, Benedict, F., Yusaf, Talal, K., Kadirgama, Tan, Chung Hong

“…Then, the potential of SDN-based VANET is explored from the aspect of routing and the design requirements of routing protocols in SDVNs. SDVN routing algorithms are uniquely classified according to various criteria. …”
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Blockchain for Healthcare Medical Records Management System with Sharing Control by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Zabidi, Suriza Ahmad

“…This is achieved using trained algorithms that provide an intelligent decision strategy based on Convolutional Neural Networks (CNN) to automatically extract high-level semantic information from electronic medical records and then perform automatic diagnosis. …”
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Trust‑based lightweight security protocol for device to device multihop cellular communication (TLwS) by Adnan Shahid, Khan, Yasir, Javed, Johari, Abdullah, Kartinah, Zen

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Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence by Rezk, H., Nassef, A.M., Inayat, A., Sayed, E.T., Shahbaz, M., Olabi, A.G.

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Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

“…Software agent-based middleware can be an effective solution due to the nature of agents as being both intelligent and autonomous.…”
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Decision Support Tools: Machine Learning Application in Smart Planner by Baharom, M.A.A., Rahman, M.S.A., Sabudin, A.R., Nor, M.F.M.

“…Immaculate Project Planning and Execution (PPE) is capital to edge over competitors, decrease costs and honour delivery dates.Project Management Information System (PMIS) is necessary towards an improved and efficient quality of any project.Machine Learning (ML) Algorithms enabled learned the date of experience to develop insights into various associations between data and outcomes.A defined set of rules prescribed by the analysts makes the probability of the fault possible.In this paper, Regression Model compute across all viable sectors expending the tool for Downstream Business and other Facilities Upstream, including Resource Estimation Schedule Generation.Extending structured information into a reliable database allows super users to define the data structures and completely configurable the settingâ��s dynamics.The model used to decrease the approximation error and measure the closest possible outcome.This subset of artificial intelligence has tremendous potential in improving schedule generation configuration to develop Project Planning timely and financially smartly.This paper aims to share standard protocols and methods applied in ML-aided as a tool in PPE decision making.Additionally, the abundant used data resources devoted to implementing ML are outlined.Finally, ML success as a Decision Support tool in project management by having a Smart Planner in supporting project recommendation accelerates the decision process, increases stakeholder confidence, and minimizes uncertainty; results are reviewed and analyzed where gaps and potential improvement for future projects are being noted and highlighted. …”
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