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Outputs (302)

Digital twins in industry 4.0 cyber security (2024)
Conference Proceeding
Lo, C., Win, T. Y., Rezaeifar, Z., Khan, Z., & Legg, P. (2024). Digital twins in industry 4.0 cyber security. In Proceedings of the IEEE Smart World Congress 2023. https://doi.org/10.1109/swc57546.2023.10449147

The increased adoption of sophisticated Cyber Physical Systems (CPS) in critical infrastructure and various aspects of Industry 4.0 has exposed vulnerabilities stemming from legacy CPS and Industrial Internet of Things (IIoT) devices. The interconnec... Read More about Digital twins in industry 4.0 cyber security.

Towards digital-twin solutions for the 15 minute city (2023)
Conference Proceeding
Ludlow, D., Khan, Z., Chrysoulakis, N., & Mitraka, Z. (2023). Towards digital-twin solutions for the 15 minute city. In 2023 Joint Urban Remote Sensing Event (JURSE). https://doi.org/10.1109/jurse57346.2023.10144161

The Covid-19 pandemic and the climate emergency have re-emphasised the need to re-evaluate urban governance and planning process in cities. The "new-normal"and digital transformations offer catalysts to drive and deliver climate mitigation in cities.... Read More about Towards digital-twin solutions for the 15 minute city.

Hear here: Sonification as a design strategy for robot teleoperation using virtual reality (2023)
Conference Proceeding
Simmons, J., Bown, A., Bremner, P., McIntosh, V., & Mitchell, T. J. (2023). Hear here: Sonification as a design strategy for robot teleoperation using virtual reality.

This paper introduces a novel methodology for the sonification of data, and shares the results of a usability study, putting the method- ology into practice within an industrial use case. Working with partners at Sellafield nuclear facility, we explo... Read More about Hear here: Sonification as a design strategy for robot teleoperation using virtual reality.

Participatory conceptual design of accessible digital musical instruments using generative AI (2023)
Conference Proceeding
Aynsley, H., Mitchell, T. J., & Meckin, D. (in press). Participatory conceptual design of accessible digital musical instruments using generative AI.

This paper explores the potential of AI text-to-image diffusion models (e.g. DALLE-2 and Midjourney) to support the early phase design of new digital musical instruments in collaboration with Disabled musicians. The paper presents initial findings fr... Read More about Participatory conceptual design of accessible digital musical instruments using generative AI.

Integrity auditing for secure cloud storage on sensitive data protection (2023)
Conference Proceeding
Sivakumar, J., Malik, M., & Rajasekaran, A. S. (2023). Integrity auditing for secure cloud storage on sensitive data protection. In 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC). https://doi.org/10.1109/ICMNWC56175.2022.10031918

Users can interchange data with others and remotely store their data on the cloud using cloud storage services. The integrity of data saved in the cloud should be ensured through remote data integrity audits. An electronic health record system is one... Read More about Integrity auditing for secure cloud storage on sensitive data protection.

Chatbot in E-learning (2023)
Conference Proceeding
Hussain, S., Al-Hashmi, S. H., Malik, M. H., & Ali Kazmi, S. I. (2023). Chatbot in E-learning. In SHS Web of Conferences: International Conference on Teaching and Learning – Digital Transformation of Education and Employability (ICTL 2022). https://doi.org/10.1051/shsconf/202315601002

In many modern apps, especially those that provide the user intelligence help, the usage of chatbots is quite common. In reality, these systems frequently have chatbots that can read user inquiries and give the appropriate replies quickly and accurat... Read More about Chatbot in E-learning.

Learning embeddings from free-text triage notes using pretrained transformer models (2022)
Conference Proceeding
Arnaud, É., Elbattah, M., Gignon, M., & Dequen, G. (2022). Learning embeddings from free-text triage notes using pretrained transformer models. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (835-841). https://doi.org/10.5220/0011012800003123

The advent of transformer models has allowed for tremendous progress in the Natural Language Processing (NLP) domain. Pretrained transformers could successfully deliver the state-of-the-art performance in a myriad of NLP tasks. This study presents an... Read More about Learning embeddings from free-text triage notes using pretrained transformer models.

Vision-based approach for autism diagnosis using transfer learning and eye-tracking (2022)
Conference Proceeding
Elbattah, M., Guérin, J., Carette, R., Cilia, F., & Dequen, G. (2022). Vision-based approach for autism diagnosis using transfer learning and eye-tracking. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF (256-263). https://doi.org/10.5220/0010975500003123

The potentials of Transfer Learning (TL) have been well-researched in areas such as Computer Vision and Natural Language Processing. This study aims to explore a novel application of TL to detect Autism Spectrum Disorder. We seek to develop an approa... Read More about Vision-based approach for autism diagnosis using transfer learning and eye-tracking.

Eye-tracking dataset to support the research on autism spectrum disorder (2022)
Conference Proceeding
Cilia, F., Carette, R., Elbattah, M., Guérin, J., & Dequen, G. (2022). Eye-tracking dataset to support the research on autism spectrum disorder. In Proceedings of the 1st Workshop on Scarce Data in Artificial Intelligence for Healthcare (59-64). https://doi.org/10.5220/0011540900003523

The availability of data is a key enabler for researchers across different disciplines. However, domains, such as healthcare, are still fundamentally challenged by the paucity and imbalance of datasets. Health data could be inaccessible due to a vari... Read More about Eye-tracking dataset to support the research on autism spectrum disorder.