Maghsoud Morshedi Chinibolagh

• Morshedi, Maghsoud & Noll, Josef (2021). Estimating PQoS of Video Conferencing on Wi-Fi Networks Using Machine Learning . Future Internet. ISSN 1999-5903. 13(3). doi: 10.3390/fi13030063. Full text in Research Archive
• Morshedi, Maghsoud & Noll, Josef (2021). Estimating PQoS of Video Streaming on Wi-Fi Networks Using Machine Learning. Sensors. ISSN 1424-8220. 21(2). doi: 10.3390/s21020621. Full text in Research Archive
• Morshedi Chinibolagh, Maghsoud & Noll, Josef Alfons (2020). A Survey on Prediction of PQoS Using Machine Learning on Wi-Fi Networks. Proceedings (International Conference on Advanced Technologies for Communications). ISSN 2162-1020. p. 5–11. doi: 10.1109/ATC50776.2020.9255457.
• Morshedi, Maghsoud (2020). Preparing Wi-Fi Networks for Novel Services in Smart Infrastructure, International Conference on Fog and Mobile Edge Computing (FMEC). IEEE conference proceedings. ISSN 978-1-7281-7216-3. p. 312–318. doi: 10.1109/FMEC49853.2020.9144819. Full text in Research Archive
• Morshedi, Maghsoud & Noll, Josef (2019). Deploying Energy Efficient Wi-Fi Networks, 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). IEEE conference proceedings. ISSN 978-1-7281-3316-4. p. 33–39. doi: 10.1109/WiMOB.2019.8923399. Full text in Research Archive
• Morshedi, Maghsoud; Noll, Josef & Kari, Raheleh (2018). Building Trustable Remote Monitoring and Management Systems. In IEEE, . (Eds.), IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-0359-4. p. 213–219. doi: 10.1109/UCC-Companion.2018.00059. Full text in Research Archive
• Kari, Raheleh; Gaspar, Henrique Murilo; Gausdal, Anne Haugen & Morshedi, Maghsoud (2018). Human Interactions Framework for Remote Ship Operations. In Antsaklis, Panos (Eds.), The 26th Mediterranean Conference on Control and Automation. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781538674994. p. 581–589. doi: 10.1109/MED.2018.8442624. Show summary

  The concept of unmanned ships capable of being controlled remotely is now beyond the idea and will start a revolution in maritime industry. In this context, remote ship operations refer to processes of controlling the vessels from distance such that operators obtain information from sensors. Thus, assessment and improvement of human interactions can enhance the overall performance of remote ship operations. However, there are unknown (i) human-human and (ii) human-machine relationships in remote ship operations, which increase the complexity of ship operations and therefore affect the overall system performance. This paper introduces a human interaction framework in remote ship operations domain in order to maximize system performance by minimizing conflicting operations. Hence, the proposed framework identifies the human interactions in remote control centers as well as the main differences between remote and non-remote ship operations. The current paper employed human system integration (HSI) approach in order to consider human as a sub-system. In this respect, literature review and human factor engineering technique (HFE) named similar system analysis were utilized to collect data and accordingly coding process was performed to analyze collected data. The proposed framework updated the earlier models of human-automated interactions and tailored to fit in the context of remote control centers. Besides, differences between remote and non-remote operations provide insight into human interactions in remote ship operations and consequently facilitates performance improvement actions. As a result, the proposed framework provides a solid understanding of human as a critical sub-system in remote ship domain so that gained knowledge could be used by designers and engineers.

• Morshedi, Maghsoud; Haugerud, Hårek & Begnum, Kyrre (2017). Making the Case for Highly Efficient Multicore Enabled Unikernels With IncludeOS. In NN, NN (Eds.), The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization. International Academy, Research and Industry Association (IARIA). ISSN 978-1-61208-529-6. p. 10–15.

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