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Intelligent Predictive Maintenance Model for Rolling Components of a Machine based on Speed and Vibration (2021)
Presentation / Conference Contribution
Ahmad, B., Mishra, B. K., Ghufran, M., Pervez, Z., & Ramzan, N. (2021). Intelligent Predictive Maintenance Model for Rolling Components of a Machine based on Speed and Vibration. In 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (459-464). https://doi.org/10.1109/ICAIIC51459.2021.9415249

Machines have come a long way, from the industrial revolution to a modern-day industry 4.0. In this massive transition, one thing that has never changed within a machine is the moving part. Most industries use rotating machine with different load cap... Read More about Intelligent Predictive Maintenance Model for Rolling Components of a Machine based on Speed and Vibration.

INtergenerational Stories of Erosion and Coastal community Understanding of REsilience ‘INSECURE’ (2021)
Presentation / Conference Contribution
Parsons, K., Jones, L., & Halstead, F. (2021, April). INtergenerational Stories of Erosion and Coastal community Understanding of REsilience ‘INSECURE’. Presented at EGU General Assembly 2021 (European Geosciences Union), vEGU21: Gather Online

The Holderness has some of the most rapidly eroding coastline in the world, with sections of cliff retreating >10m per year. These rates are due, in large part, to the soft composition of the boulder clay cliffs, but rates are accelerating rapidly in... Read More about INtergenerational Stories of Erosion and Coastal community Understanding of REsilience ‘INSECURE’.

Comparison of performance of alternative post combustion carbon capture processes for a biogas fueled micro gas turbine (2021)
Presentation / Conference Contribution
Font-Palma, C., Lychnos, G., Somehsaraei, H. N., Willson, P., & Assadi, M. (2020, September). Comparison of performance of alternative post combustion carbon capture processes for a biogas fueled micro gas turbine. Presented at ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition

Copyright © 2020 ASME The urgent need to decrease greenhouse gases (GHG) has prompted countries such as the UK and Norway to commit to net zero emissions by 2050 and 2030, respectively. One of the sectors contributing to GHG emissions is agriculture,... Read More about Comparison of performance of alternative post combustion carbon capture processes for a biogas fueled micro gas turbine.

The Virtual Dissection Room: Live-streamed Demonstrations to Complement Recorded Lectures (2021)
Presentation / Conference Contribution
Shaw, V., & Winder, I. C. (2021, January). The Virtual Dissection Room: Live-streamed Demonstrations to Complement Recorded Lectures. Presented at Anatomical Society Virtual Winter Meeting: Vision and Visualisation, Newcastle

Complying with the constraints on class size created by social distancing meant that in Bangor, it was not possible to have in-person cadaveric teaching this year. This had the biggest impact on the second-year Medical Sciences students, and the firs... Read More about The Virtual Dissection Room: Live-streamed Demonstrations to Complement Recorded Lectures.

Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines (2020)
Presentation / Conference Contribution
Chatterjee, J. (2020). Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines. In J. M. Alonso, & U. Cortés (Eds.), Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI2020-proceedings) (53-54)

As global efforts in transitioning to sustainable energy sources rise, wind energy has become a leading renewable energy resource. However, turbines are complex engineering systems and rely on effective operations & maintenance (O&M) to prevent catas... Read More about Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines.

Refining the Teaching of Programming (2020)
Presentation / Conference Contribution
Gordon, N., Cargill, M., Grey, S., & Brayshaw, M. (2020, July). Refining the Teaching of Programming. Presented at INSPIRE XXV: e-Learning as a Solution during Unprecedented Times in the 21st Century, Online

This paper considers issues around the teaching of programming, a critical yet challenging part of the computing education at all levels. This paper begins by outlining some of the key concerns around computing education-from secondary school, throug... Read More about Refining the Teaching of Programming.

Identifying Gaps in Cybersecurity Teaching and Learning (2020)
Presentation / Conference Contribution
Brayshaw, M., Gordon, N., & Karatazgianni, A. (2020, July). Identifying Gaps in Cybersecurity Teaching and Learning. Presented at INSPIRE XXV : e-Learning as a solution during unprecedented times in the 21st Century

This paper explores perceptions and expectations of privacy when using computer-mediated communication and social media. In this paper we present the results of an empirical survey into this topic and explore the pedagogic implications for the teachi... Read More about Identifying Gaps in Cybersecurity Teaching and Learning.

A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease (2020)
Presentation / Conference Contribution
Rana, S. S., Ma, X., Pang, W., & Wolverson, E. (2020, December). A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease. Presented at 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Leicester, United Kingdom

Mild cognitive impairment (MCI) has been described as the intermediary stage before Alzheimer's Disease - many people however remain stable or even demonstrate improvement in cognition. Early detection of progressive MCI (pMCI) therefore can be utili... Read More about A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease.

A Model-based RCM Analysis Method (2020)
Presentation / Conference Contribution
Mian, Z., Jia, S., Shi, X., Tang, C., Chen, J., & Gao, Y. (2020). A Model-based RCM Analysis Method. In IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C) (301-307). https://doi.org/10.1109/QRS-C51114.2020.00059

The reliability-centered maintenance (RCM) is one of the most advanced maintenance plan generating technologies for equipments. At present, the key technologies such as FMEA and FMECA supporting the RCM analysis remains in the manual stage in some en... Read More about A Model-based RCM Analysis Method.

An age-associated reduction in Nav1.5 protein expression correlates with an increase in Nav1.8 protein expression in the right atrial appendage of the human heart. (2020)
Presentation / Conference Contribution
Isaac, E., Cooper, S., Lancaster, M., Loubani, M., & Jones, S. An age-associated reduction in Nav1.5 protein expression correlates with an increase in Nav1.8 protein expression in the right atrial appendage of the human heart. Presented at Basic Cardiovascular Sciences Scientific Sessions 2020, Online

Background: Nav1.5 is the predominantly expressed voltage-gated sodium channel (VGSC) isoform in the heart, responsible for phase 0 of the action potential. Our rodent studies have shown expression of neuronal isoform Nav1.8 protein in the adult hear... Read More about An age-associated reduction in Nav1.5 protein expression correlates with an increase in Nav1.8 protein expression in the right atrial appendage of the human heart..

Deep reinforcement learning for maintenance planning of offshore vessel transfer (2020)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. (2020). Deep reinforcement learning for maintenance planning of offshore vessel transfer. In C. Guedes Soares (Ed.), Developments in Renewable Energies Offshore Proceedings of the 4th International Conference on Renewable Energies Offshore (RENEW 2020, 12 - 15 October 2020, Lisbon, Portugal) (435-443)

Offshore wind farm operators need to make short-term decisions on planning vessel transfers to turbines for preventive or corrective maintenance. These decisions can play a pivotal role in ensuring maintenance actions are carried out in a timely and... Read More about Deep reinforcement learning for maintenance planning of offshore vessel transfer.

Comparative review of pipelines monitoring and leakage detection techniques (2020)
Presentation / Conference Contribution
Aljuaid, K. G., Albuoderman, M. A., Alahmadi, E. A., & Iqbal, J. (2020). Comparative review of pipelines monitoring and leakage detection techniques. In 2nd International Conference on Computer and Information Sciences (ICCIS). https://doi.org/10.1109/ICCIS49240.2020.9257602

The oil and gas industry owns expensive and widely-spread assets. Any fault in this complex transportation network may result in accidents and/or huge losses thereby triggering various environmental and economic issues. Thus, real-time monitoring and... Read More about Comparative review of pipelines monitoring and leakage detection techniques.

In-situ measurement and prediction of traffic noise transmission loss across a residential flat unit façade installed with two plenum windows (2020)
Presentation / Conference Contribution
Tang, S. K., & Li, X. (2020). In-situ measurement and prediction of traffic noise transmission loss across a residential flat unit façade installed with two plenum windows. In INTER-NOISE and NOISE-CON Congress and Conference Proceedings 2020 (1368-1375)

In the present study, the traffic noise transmission loss across a residential flat unit façade installed with two plenum windows are measured in-situ in a 30-storey high-rise building located in an opened environment next to a very busy and noisy ma... Read More about In-situ measurement and prediction of traffic noise transmission loss across a residential flat unit façade installed with two plenum windows.

Taboo Or Not Taboo: (In)visibilities Of Death, Dying And Bereavement (2020)
Presentation / Conference Contribution
Hård Af Segerstad, Y., Bell, J., Giaxoglou, K., Pitsillides, S., & Yeshua-Katz, D. Taboo Or Not Taboo: (In)visibilities Of Death, Dying And Bereavement. Presented at Annual Conference of the Association of Internet Researchers., 2020

The notion that ‘death is a taboo’ pervades private, public and academic discourses around death, dying and bereavement in contemporary Western societies. The rise of digital media within the last decades further complicates the appreciation of the s... Read More about Taboo Or Not Taboo: (In)visibilities Of Death, Dying And Bereavement.

Soundscape assessment: Towards a validated translation of perceptual attributes in different languages (2020)
Presentation / Conference Contribution
Aletta, F., Oberman, T., Axelsson, Ö., Xie, H., Zhang, Y., Lau, S. K., …Kang, J. (2020). Soundscape assessment: Towards a validated translation of perceptual attributes in different languages. In INTER-NOISE and NOISE-CON Congress and Conference Proceedings 2020 ( 3137-3146)

The recently published ISO/TS 12913-2:2018 standard aims to provide researchers and practitioners around the world with a reliable questionnaire for soundscape characterization. The ISO Technical Specifications report protocols and attributes grounde... Read More about Soundscape assessment: Towards a validated translation of perceptual attributes in different languages.

A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines (2020)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. (2020, July). A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK

© 2020 IEEE. Wind energy is one of the fastest-growing sustainable energy sources in the world but relies crucially on efficient and effective operations and maintenance to generate sufficient amounts of energy and reduce downtime of wind turbines an... Read More about A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines.

Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI (2020)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI. Presented at The Science of Making Torque from Wind (TORQUE 2020), Online, Netherlands

© 2020 Published under licence by IOP Publishing Ltd. Machine learning techniques have been widely used for condition-based monitoring of wind turbines using Supervisory Control & Acquisition (SCADA) data. However, many machine learning models, inclu... Read More about Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI.

Advance care planning: exploration of the public’s understanding. In Abstracts from the 11th EAPC World Research Congress Online, 7th – 9th October 2020 (2020)
Presentation / Conference Contribution
Mcllfatrick, S., Hasson, F., Slater, P., Beck, E., McCloskey, S., Carr, K., Muldrew, D., Bamidele, O., & Hanna-Trainor, L. Advance care planning: exploration of the public’s understanding. In Abstracts from the 11th EAPC World Research Congress Online, 7th – 9th October 2020. Presented at 11th EAPC World Research Congress, Online

Background/aims: Advance care planning, a voluntary process whereby an individual outline their preferences and beliefs, to aid in planning for end of life care, is widely considered an essential step for achieving a `good death”. Raising awareness o... Read More about Advance care planning: exploration of the public’s understanding. In Abstracts from the 11th EAPC World Research Congress Online, 7th – 9th October 2020.

SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures (2020)
Presentation / Conference Contribution
Aslansefat, K., Sorokos, I., Whiting, D., Tavakoli Kolagari, R., & Papadopoulos, Y. SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures. Presented at IMBSA: International Symposium on Model-Based Safety and Assessment, Lisbon

Ensuring safety and explainability of machine learning (ML) is a topic of increasing relevance as data-driven applications venture into safety-critical application domains, traditionally committed to high safety standards that are not satisfied with... Read More about SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures.