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All Outputs (830)

NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction (2024)
Journal Article
Hong, Q., Yang, C., Chen, J., Li, Z., Wu, Q., Li, Q., & Tian, J. (2024). NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2024.3447088

3D reconstruction from multi-view images is considered as a longstanding problem in computer vision and graphics. In order to achieve high-fidelity geometry and appearance of 3D scenes, this paper proposes a novel geometric object learning method for... Read More about NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction.

Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance (2023)
Presentation / Conference Contribution
Walker, C., Rothon, C., Aslansefat, K., Papadopoulos, Y., & Dethlefs, N. (2024, February). Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance. Presented at Safety Critical Systems Symposium SSS'24, Bristol, UK

It has been forecasted that a quarter of the world's energy usage will be supplied from Offshore Wind (OSW) by 2050 (Smith 2023). Given that up to one third of Levelised Cost of Energy (LCOE) arises from Operations and Maintenance (O&M), the motive f... Read More about Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance.

Addressing Complexity and Intelligence in Systems Dependability Evaluation (2023)
Thesis
Aslansefat, K. Addressing Complexity and Intelligence in Systems Dependability Evaluation. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4500562

Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. T... Read More about Addressing Complexity and Intelligence in Systems Dependability Evaluation.

Safety Analysis Concept and Methodology for EDDI development (Initial Version) (2023)
Report
Aslansefat, K., Gerasimou, S., Michalodimi-trakis, E., Papoutsakis, M., Reich, J., Sorokos, I., Walker, M., & Papadopoulos, Y. (2023). Safety Analysis Concept and Methodology for EDDI development (Initial Version). European Comission

Executive Summary:
This deliverable describes the proposed safety analysis concept and accompanying methodology to be defined in the SESAME project. Three overarching challenges to the development of safe and secure multi-robot systems are identifie... Read More about Safety Analysis Concept and Methodology for EDDI development (Initial Version).

Safety-Security Co-Engineering Framework (2023)
Report
Aslansefat, K., Gerasimou, S., Hamibi, H., Matragkas, N., Michalodimitrakis, E., Papadopoulos, Y., Papoutsakis, M., & Walker, M. (2023). Safety-Security Co-Engineering Framework. European Commission

Executive Summary:
The advantages of a model-based approach for safety have been clear for many years now. However, security analysis is typically less formal and more ad-hoc; it may involve systematic processes but these are not generally tied into... Read More about Safety-Security Co-Engineering Framework.

A literature review of fault diagnosis based on ensemble learning (2023)
Journal Article
Mian, Z., Deng, X., Dong, X., Tian, Y., Cao, T., Chen, K., & Jaber, T. A. (2024). A literature review of fault diagnosis based on ensemble learning. Engineering applications of artificial intelligence, 127, Article 107357. https://doi.org/10.1016/j.engappai.2023.107357

The accuracy of fault diagnosis is an important indicator to ensure the reliability of key equipment systems. Ensemble learning integrates different weak learning methods to obtain stronger learning and has achieved remarkable results in the field of... Read More about A literature review of fault diagnosis based on ensemble learning.

Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring (2023)
Journal Article
Yemson, R., Kabir, S., Thakker, D., & Konur, S. (2023). Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring. Computers, 12(11), Article 238. https://doi.org/10.3390/computers12110238

With the increasing amount of data collected by IoT devices, detecting complex events in real-time has become a challenging task. To overcome this challenge, we propose the utilisation of semantic web technologies to create ontologies that structure... Read More about Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring.

A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi (2023)
Presentation / Conference Contribution
Kambili-Mzembe, F., & Gordon, N. A. A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi. Presented at International Conference on Immersive Learning 2023, San Luis Obispo, USA

This paper discusses and evaluates a self-contained portable multi-user cross-platform Virtual Reality (VR) setup that was devised and configured using off the shelf technologies and devices. This paper exemplifies how some fundamental challenges lik... Read More about A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi.

A Nonlinear Model Predictive Controller for Trajectory Planning of Skid-Steer Mobile Robots in Agricultural Environments (2023)
Presentation / Conference Contribution
Aro, K., Urvina, R., Deniz, N. N., Menendez, O., Iqbal, J., & Prado, A. (2023, September). A Nonlinear Model Predictive Controller for Trajectory Planning of Skid-Steer Mobile Robots in Agricultural Environments. Presented at 2023 IEEE Conference on AgriFood Electronics (CAFE), Torino, Italy

This research presents an integrated trajectory planning strategy with a motion control approach using a Nonlinear Model Predictive Control (NMPC) framework for Skid-Steer Mobile Robots (SSMRs) in agricultural scenarios. In a single architecture, the... Read More about A Nonlinear Model Predictive Controller for Trajectory Planning of Skid-Steer Mobile Robots in Agricultural Environments.

Intelligent digital twin - machine learning system for real-time wind turbine wind speed and power generation forecasting (2023)
Presentation / Conference Contribution
Tuton, E., Ma, X., & Dethlefs, N. (2023, August). Intelligent digital twin - machine learning system for real-time wind turbine wind speed and power generation forecasting. Presented at The 6th International Conference on Renewable Energy and Environment Engineering REEE 2023, Brest , France

Wind power is a key pillar in efforts to decarbonise energy production. However, variability in wind speed and resultant wind turbine power generation poses a challenge for power grid integration. Digital Twin (DT) technology provides intelligent ser... Read More about Intelligent digital twin - machine learning system for real-time wind turbine wind speed and power generation forecasting.

EMG Controlled Modular Prosthetic Hand–Design and Prototyping (2023)
Book Chapter
Suddaby, A., & Iqbal, J. (2023). EMG Controlled Modular Prosthetic Hand–Design and Prototyping. In X.-S. Yang, R. S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of Eighth International Congress on Information and Communication Technology : ICICT 2023 (97-107). Springer. https://doi.org/10.1007/978-981-99-3043-2_8

Prosthetic hands can be essential for those without a biological hand(s) to accomplish everyday tasks but the cost, of up to tens of thousands, keeps them out of reach for many people. This paper reports on the development of a low-cost affordable an... Read More about EMG Controlled Modular Prosthetic Hand–Design and Prototyping.

LViT: Language meets Vision Transformer in Medical Image Segmentation (2023)
Journal Article
Li, Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., Jin, D., Zhang, Y., & Hong, Q. (2024). LViT: Language meets Vision Transformer in Medical Image Segmentation. IEEE Transactions on Medical Imaging, 43(1), 96-107. https://doi.org/10.1109/TMI.2023.3291719

Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the challenge of obtaining sufficient high-quality labeled data due to the... Read More about LViT: Language meets Vision Transformer in Medical Image Segmentation.

Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller (2023)
Journal Article
Saleem, O., Ali, S., & Iqbal, J. (2023). Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller. Energies, 16(13), Article 5039. https://doi.org/10.3390/en16135039

The Photovoltaic (PV) system is an eco-friendly renewable energy system that is integrated with a DC-DC buck-boost converter to generate electrical energy as per the variations in solar irradiance and outdoor temperature. This article proposes a nove... Read More about Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller.

Real-time social media sentiment analysis for rapid impact assessment of floods (2023)
Journal Article
Bryan-Smith, L., Godsall, J., George, F., Egode, K., Dethlefs, N., & Parsons, D. (2023). Real-time social media sentiment analysis for rapid impact assessment of floods. Computers & geosciences, 178, Article 105405. https://doi.org/10.1016/j.cageo.2023.105405

Traditional approaches to flood modelling mostly rely on hydrodynamic physical simulations. While these simulations can be accurate, they are computationally expensive and prohibitively so when thinking about real-time prediction based on dynamic env... Read More about Real-time social media sentiment analysis for rapid impact assessment of floods.

Towards achieving net zero by 2050 in the UK – Stakeholder perspectives in integrated urban planning (2023)
Journal Article
Mazumdar, S., Thakker, D., Hayes, J., Matos, N., & Bate, P. (2023). Towards achieving net zero by 2050 in the UK – Stakeholder perspectives in integrated urban planning. Futures: for the interdisciplinary study of futures, visioning, anticipation and foresight, 152, Article 103197. https://doi.org/10.1016/j.futures.2023.103197

In light of severe risks of extreme conditions arising out of global warming, the push towards sustainable development and management of our resources has been a topic of immense interest globally. The UK's recent promise of reducing all greenhouse g... Read More about Towards achieving net zero by 2050 in the UK – Stakeholder perspectives in integrated urban planning.

Why the Educational Metaverse Is Not All About Virtual Reality Apps (2023)
Presentation / Conference Contribution
Gordon, N., Brayshaw, M., Kambili-Mzembe, F., & Al Jaber, T. Why the Educational Metaverse Is Not All About Virtual Reality Apps. Presented at Learning and Collaboration Technologies : 10th International Conference, LCT 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagan, Denmark

This paper explores how the Metaverse can be used in the context of learning and collaboration. In it we seek to dispel the story that the Metaverse is just another synonym for Virtual Reality and future technology. Instead we will argue that the Met... Read More about Why the Educational Metaverse Is Not All About Virtual Reality Apps.

A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification (2023)
Journal Article
Hong, Q., Lin, L., Li, Z., Li, Q., Yao, J., Wu, Q., Liu, K., & Tian, J. (in press). A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2023.3280646

Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray (CXR) images is one of the most effective ways for disease diagnosis and patient triage. The application of deep neural networks (DNNs) for CXR image classification... Read More about A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification.

Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning (2023)
Journal Article
Chatterjee, J., Alvela Nieto, M. T., Gelbhardt, H., Dethlefs, N., Ohlendorf, J. H., Greulich, A., & Thoben, K. D. (2023). Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning. Environmental Data Science, 2, 1-15. https://doi.org/10.1017/eds.2023.9

Wind energy's ability to liberate the world from conventional sources of energy relies on lowering the significant costs associated with the maintenance of wind turbines. Since icing events on turbine rotor blades are a leading cause of operational f... Read More about Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning.

Learning Fair Representations through Uniformly Distributed Sensitive Attributes (2023)
Presentation / Conference Contribution
Kenfack, P., Rivera, A., Khan, A., & Mazzara, M. (2023, February). Learning Fair Representations through Uniformly Distributed Sensitive Attributes. Presented at 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), Raleigh, NC, USA

Machine Learning (ML) models trained on biased data can reproduce and even amplify these biases. Since such models are deployed to make decisions that can affect people's lives, ensuring their fairness is critical. One approach to mitigate possi... Read More about Learning Fair Representations through Uniformly Distributed Sensitive Attributes.