All Outputs (639)

System architecture of a proactive intelligent system to monitor health of older adults living alone (2021)
Journal Article
Al-Mejibli, I., Al-Majeed, S., Karam, J., Iqbal, J., Adolfo, C. M., & Yalung, C. (2021). System architecture of a proactive intelligent system to monitor health of older adults living alone. International Journal of Computing and Digital Systems, 10(1), 509-517. https://doi.org/10.12785/IJCDS/100149

Worldwide improvements in the quality of life highlight immense need to have a remote health monitoring system that can provide critical biomedical data. This paper presents a low-cost health monitoring system, forming part of the Internet of Things... Read More about System architecture of a proactive intelligent system to monitor health of older adults living alone.

Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems (2021)
Journal Article
Aslansefat, K., Kabir, S., Abdullatif, A., Vasudevan Nair, V., & Papadopoulos, Y. (in press). Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems. Computer,

The application of artificial intelligence (AI) and data-driven decision-making systems in autonomous vehicles is growing rapidly. As autonomous vehicles operate in dynamic environments, the risk that they can face an unknown observation is relativel... Read More about Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems.

SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning (2021)
Journal Article
Tan, J., Yang, Z., Cheng, Y., Ye, J., Wang, B., & Dai, Q. (2021). SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning. Pattern Recognition, 117, Article 107987. https://doi.org/10.1016/j.patcog.2021.107987

Sparse representation and cooperative learning are two representative technologies in the field of multi-view spectral clustering. The former can effectively extract features of multiple views by the removal of redundant information contained in each... Read More about SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning.

Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. (2021). Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future. Renewable & sustainable energy reviews, 144, Article 111051. https://doi.org/10.1016/j.rser.2021.111051

Wind energy has emerged as a highly promising source of renewable energy in recent times. However, wind turbines regularly suffer from operational inconsistencies, leading to significant costs and challenges in operations and maintenance (O&M). Condi... Read More about Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future.

A new perspective on teaching the natural exponential to engineering students (2021)
Journal Article
Ullah, M., Aman, M. N., Wolkenhauer, O., & Iqbal, J. (2021). A new perspective on teaching the natural exponential to engineering students. International Journal of Mathematical Education in Science and Technology, https://doi.org/10.1080/0020739X.2021.1896812

The natural exponential and logarithm are typically introduced to undergraduate engineering students in a calculus course using the notion of limits. We here present an approach to introduce the natural exponential/logarithm through a novel interpret... Read More about A new perspective on teaching the natural exponential to engineering students.

XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines. https://doi.org/10.48550/arXiv.2012.10489. Manuscript submitted for publication

Condition-based monitoring (CBM) has been widely utilised in the wind industry for monitoring operational inconsistencies and failures in turbines, with techniques ranging from signal processing and vibration analysis to artificial intelligence (AI)... Read More about XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines.

Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes (2021)
Journal Article
Schoene, A. M., Turner, A. P., De Mel, G., & Dethlefs, N. (in press). Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes. IEEE Transactions on Affective Computing, https://doi.org/10.1109/TAFFC.2021.3057105

Recent statistics in suicide prevention show that people are increasingly posting their last words online and with the unprecedented availability of textual data from social media platforms researchers have the opportunity to analyse such data. Furth... Read More about Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes.

A divide-and-conquer approach to neural natural language generation from structured data (2021)
Journal Article
Dethlefs, N., Schoene, A., & Cuayáhuitl, H. (2021). A divide-and-conquer approach to neural natural language generation from structured data. Neurocomputing, 433, 300-309. https://doi.org/10.1016/j.neucom.2020.12.083

Current approaches that generate text from linked data for complex real-world domains can face problems including rich and sparse vocabularies as well as learning from examples of long varied sequences. In this article, we propose a novel divide-and-... Read More about A divide-and-conquer approach to neural natural language generation from structured data.

Nonlinear adaptive backstepping control of permanent magnet synchronous motor (2021)
Journal Article
Ali, N., Alam, W., Pervaiz, M., & Iqbal, J. (2021). Nonlinear adaptive backstepping control of permanent magnet synchronous motor. Revue Roumaine des Sciences Techniques : Série Électrotechnique et Énergétique, 66(1), 9-14

This paper addresses the speed tracking problem of a permanent magnet synchronous motor (PMSM) under the influence of parametric uncertainties and external load torque disturbances. The nonlinear dynamics associated with both PMSM and load is conside... Read More about Nonlinear adaptive backstepping control of permanent magnet synchronous motor.

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.

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.

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.

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.

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.

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., …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.

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.