All Outputs (3)

Virtual exchange (COIL): shaping the tourism workforce of the future. (2024)
Presentation / Conference Contribution
HARBERT, S. and ROITERSHTEIN, A. 2024. Virtual exchange (COIL): shaping the tourism workforce of the future. Presented at the 32nd Nordic symposium on tourism and hospitality research, 18-20 September 2024, Stavanger, Norway.

Significant and rapid changes in the world's climate, technology and geopolitics has created a new environment for the tourism industry, and for those that rely on it for their livelihoods. These changes create a demand for globally competent, cultur... Read More about Virtual exchange (COIL): shaping the tourism workforce of the future..

An enterprising approach to postgraduate engineering courses for sustainable futures. (2024)
Presentation / Conference Contribution
IYALLA, I., MOULE, C., CHARLES, S. and MAHON, R. 2024. An enterprising approach to postgraduate engineering courses for sustainable futures. Presented at the 2024 Advance HE teaching and learning conference: future-focused education: innovation, inclusion and impact, 2-4 July 2024, Nottingham, UK.

This interactive session is for HE educators seeking to align their teaching to Advance HE's strategic objectives of incorporating "experiential learning, working in multidisciplinary teams on real-world challenges pivotal in cultivating essential co... Read More about An enterprising approach to postgraduate engineering courses for sustainable futures..

Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. (2023)
Presentation / Conference Contribution
FOUGH, F., JANJUA, G., ZHAO, Y. and DON, A.W. 2023. Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea (MetroSea 2023); learning to measure sea health parameters, 4-6 October 2023, La Valletta, Malta. Piscataway: IEEE [online], pages 121-126. Available from: https://doi.org/10.1109/MetroSea58055.2023.10317294

Antimicrobial resistance (AMR) is an increasingly critical public health issue necessitating precise and efficient methodologies to achieve prompt results. The accurate and early detection of AMR is crucial, as its absence can pose life-threatening r... Read More about Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms..