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A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems (2021)
Journal Article
Khodayee, S. M., Chiacchio, F., & Papadopoulos, Y. (2021). A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems. IEEE Access, 9, 51029-51049. https://doi.org/10.1109/ACCESS.2021.3069807

Flaring has always been an inseparable part of oil production and exploration. Previously, waste gas collected from different parts of facilities was released for safety or operational reasons and combusted on top of a flare stack since there was not... Read More about A novel approach based on stochastic hybrid fault tree to compare alternative flare gas recovery systems.

A Semantic Knowledge-Based Framework for Information Extraction and Exploration (2021)
Journal Article
Aljamel, A., Osman, T., & Thakker, D. (2021). A Semantic Knowledge-Based Framework for Information Extraction and Exploration. International Journal of Decision Support System Technology, 13(2), 85--109. https://doi.org/10.4018/IJDSST.2021040105

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-ba... Read More about A Semantic Knowledge-Based Framework for Information Extraction and Exploration.

Learning technologies for learning in health and well-being (2020)
Book Chapter
Gordon, N. (2020). Learning technologies for learning in health and well-being. In P. Gökcin Özuyar, W. Leal Filho, T. Wall, A. Marisa Azul, & L. Brandli (Eds.), Good Health and Well-Being. Springer. https://doi.org/10.1007/978-3-319-95681-7

The United Nations (U.N.) Sustainable Goal 3, for healthy lives and promoting well-being, notes that 45% of all countries have less than one physician per 1000 people, that figure rising to 90% for less developed countries (United Nations, 2018). Giv... Read More about Learning technologies for learning in health and well-being.

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.

Technologies for analysing and improving healthcare processes (2020)
Book Chapter
Gordon, N. (2020). Technologies for analysing and improving healthcare processes. In W. Leal Filho, T. Wall, A. Azul, L. Brandli, & P. Özuyar (Eds.), Good Health and Well-Being. Springer. https://doi.org/10.1007/978-3-319-95681-7

The right to a healthy life is a natural expectation and recognised as a human right (WHO, 2017) – and is further recognised as such in the United Nations Sustainable Development Goals, where Goal 3 focusses on “good health and well-being” (United Na... Read More about Technologies for analysing and improving healthcare processes.

Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines (2020)
Presentation / Conference Contribution
Chatterjee, J. (2020, August). Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines. Presented at 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI 2020), Online

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)
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, December). A Model-based RCM Analysis Method. Presented at 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), Macau, China

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.

Computational Intelligence for Safety Assurance of Cooperative Systems of Systems (2020)
Journal Article
Kabir, S., & Papadopoulos, Y. (2020). Computational Intelligence for Safety Assurance of Cooperative Systems of Systems. Computer, 53(12), 24-34. https://doi.org/10.1109/MC.2020.3014604

Cooperative systems of systems (CSoSs) form a new technological frontier for their enormous economic and societal potentials in various domains. This article presents a novel framework for dynamic safety assurance of CSoSs that integrates design time... Read More about Computational Intelligence for Safety Assurance of Cooperative Systems of Systems.

Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050 (2020)
Journal Article
Golizadeh Akhlaghi, Y., Aslansefat, K., Zhao, X., Sadati, S., Badiei, A., Xiao, X., Shittu, S., Fan, Y., & Ma, X. (2021). Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050. Applied energy, 281, Article 116062. https://doi.org/10.1016/j.apenergy.2020.116062

The empirical success of the Artificial Intelligence (AI), has enhanced importance of the transparency in black box Machine Learning (ML) models. This study pioneers in developing an explainable and interpretable Deep Neural Network (DNN) model for a... Read More about Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050.

Effect of IDT position parameters on SAW yarn tension sensor sensitivity (2020)
Journal Article
Lei, B., Lu, W., Mian, Z., & Bao, W. (2020). Effect of IDT position parameters on SAW yarn tension sensor sensitivity. Measurement and Control, 53(9-10), 2055-2062. https://doi.org/10.1177/0020294020965620

In this paper, the effect of the interdigital transducer (IDT) position parameters on the surface acoustic wave (SAW) yarn tension sensor sensitivity is investigated. The stress–strain characteristic of substrate was studied by the combination of fin... Read More about Effect of IDT position parameters on SAW yarn tension sensor sensitivity.

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, October). Comparative review of pipelines monitoring and leakage detection techniques. Presented at 2nd International Conference on Computer and Information Sciences (ICCIS), Sakaka, Saudi Arabia

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)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. (2020, October). Deep reinforcement learning for maintenance planning of offshore vessel transfer. Presented at 4th International Conference on Renewable Energies Offshore (RENEW 2020), Lisbon, Portugal

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)
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.

GANS-based data augmentation for citrus disease severity detection using deep learning (2020)
Journal Article
Zeng, Q., Ma, X., Cheng, B., Zhou, E., & Pang, W. (2020). GANS-based data augmentation for citrus disease severity detection using deep learning. IEEE Access, 8, 172882-172891. https://doi.org/10.1109/ACCESS.2020.3025196

Recently, many Deep Learning models have been employed to classify different kinds of plant diseases, but very little work has been done for disease severity detection. However, it is more important to master the severities of plant diseases accurate... Read More about GANS-based data augmentation for citrus disease severity detection using deep learning.

Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle (2020)
Journal Article
Ahmad, E., Iqbal, J., Khan, M. A., Liang, W., & Youn, I. (2020). Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle. Electronics, 9(9), Article 1463. https://doi.org/10.3390/electronics9091463

This work presents a predictive control strategy for a four degrees of freedom (DOF) half-car model in the presence of active aerodynamic surfaces. The proposed control strategy consists of two parts: the feedback control deals with the tracking erro... Read More about Predictive control using active aerodynamic surfaces to improve ride quality of a vehicle.

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.