All Outputs (10)

Refining the Teaching of Programming (2020)
Conference Proceeding
Gordon, N., Cargill, M., Grey, S., & Brayshaw, M. (2020). Refining the Teaching of Programming. In INSPIRE XXV : e-Learning as a solution during unprecedented times in the 21st Century (97-107)

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)
Conference Proceeding
Brayshaw, M., Gordon, N., & Karatazgianni, A. (2020). Identifying Gaps in Cybersecurity Teaching and Learning. In INSPIRE XXV : e-Learning as a solution during unprecedented times in the 21st Century (165-178)

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.

Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines (2020)
Conference Proceeding
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.

A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease (2020)
Conference Proceeding
Rana, S. S., Ma, X., Pang, W., & Wolverson, E. (2020). A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease. In 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) (9-18). https://doi.org/10.1109/BDCAT50828.2020.00013

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)
Conference Proceeding
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.

Comparative review of pipelines monitoring and leakage detection techniques (2020)
Conference Proceeding
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.

Deep reinforcement learning for maintenance planning of offshore vessel transfer (2020)
Conference Proceeding
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.

A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines (2020)
Conference Proceeding
Chatterjee, J., & Dethlefs, N. (2020). A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.9206839

© 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.

Semantic Mapping for Model Transformation between AADL2 and HiP-HOPS (2020)
Conference Proceeding
Mian, Z., Gao, Y., Shi, X., & Tang, C. (2020). Semantic Mapping for Model Transformation between AADL2 and HiP-HOPS. In 4th International Conference on System Reliability and Safety (ICSRS) (539-543). https://doi.org/10.1109/ICSRS48664.2019.8987619

Currently, AADL has gradually become as one of the standards for the architecture design of complex embedded system. It is widely used in aerospace, automotive electronics and other fields for the design and analysis of high dependability-critical sy... Read More about Semantic Mapping for Model Transformation between AADL2 and HiP-HOPS.

A Cost Modeling Method Based on AADL2 (2020)
Conference Proceeding
Mian, Z., Tang, C., Gao, Y., Jia, S., Shi, X., & Chen, J. (2020). A Cost Modeling Method Based on AADL2. In 4th International Conference on System Reliability and Safety (ICSRS) (549-553). https://doi.org/10.1109/ICSRS48664.2019.8987612

The Architecture Analysis and Design Language (AADL) is widely used in the modeling, analysis and verification of the dependability-critical system. Previously, we have implemented the multi-objective (based on dependability and cost) architecture op... Read More about A Cost Modeling Method Based on AADL2.