All Outputs (697)

Using outlier elimination to assess learning-based correspondence matching methods (2024)
Journal Article
Ding, X., Luo, Y., Jie, B., Li, Q., & Cheng, Y. (2024). Using outlier elimination to assess learning-based correspondence matching methods. Information Sciences, 659, Article 120056. https://doi.org/10.1016/j.ins.2023.120056

Recently, deep learning (DL) technology has been widely used in correspondence matching. The learning-based models are usually trained on benign image pairs with partial overlaps. Since DL model is usually data-dependent, non-overlapping images may b... Read More about Using outlier elimination to assess learning-based correspondence matching methods.

NEAT Activity Detection using Smartwatch (2024)
Journal Article
Dewan, A., Gunturi, V., & Naik, V. (2024). NEAT Activity Detection using Smartwatch. International Journal of Ad Hoc and Ubiquitous Computing, 45(1), 36-51. https://doi.org/10.1504/IJAHUC.2024.136141

This paper presents a system for distinguishing non-exercise activity thermogenesis (NEAT) and non-NEAT activities at home. NEAT includes energy expended on activities apart from sleep, eating, or traditional exercise. Our study focuses on specific N... Read More about NEAT Activity Detection using Smartwatch.

Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV (2024)
Journal Article
Abbas, N., Liu, X., & Iqbal, J. (2024). Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV. Journal of mechanical science and technology, 38(3), https://doi.org/10.1007/s12206-024-0234-6

The novelty of the proposed work lies in the control technique, referred to as the robust generalized dynamic inversion based adaptive recursive sliding mode control (RGDI-ARSMC), for addressing various challenges to control a highly coupled and pert... Read More about Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV.

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. (2023). 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-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.

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).

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.

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.

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., …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.

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. (2023). Why the Educational Metaverse Is Not All About Virtual Reality Apps. Lecture notes in computer science, 14041 LNCS, 22-32. https://doi.org/10.1007/978-3-031-34550-0_2

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.

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.

Design and Adaptive Compliance Control of a Wearable Walk Assist Device (2023)
Presentation / Conference Contribution
Shah, S. H., Alam, M. S., Arsalan, M., Ul Haq, I., Khan, S. G., & Iqbal, J. (2023, March). Design and Adaptive Compliance Control of a Wearable Walk Assist Device. Presented at 2023 International Conference on Robotics and Automation in Industry (ICRAI), Peshawar, Pakistan

The ability to walk independently is a predominant feature that human beings are bestowed with by nature. People with moving disabilities face many challenges in day-to-day activities and they have to rely on others to perform their day-to-day activi... Read More about Design and Adaptive Compliance Control of a Wearable Walk Assist Device.

Motivating Students to Learn How to Write Code Using a Gamified Programming Tutor (2023)
Journal Article
Gordon, N. A., & Grey, S. (2023). Motivating Students to Learn How to Write Code Using a Gamified Programming Tutor. Education Sciences, 13(3), Article 230. https://doi.org/10.3390/educsci13030230

Engagement and retention are widely acknowledged problems in computer science and more general higher education. The need to develop programming skills is increasingly ubiquitous, but especially so in computer science where it is one of the core comp... Read More about Motivating Students to Learn How to Write Code Using a Gamified Programming Tutor.

Sustainable Language Training for Engineering Students: Integrating Resource-Efficiency into the Course Content through the Educational Process (2023)
Journal Article
Gordon, N., Kemerova, N., Bolsunovskaya, L., & Osipov, S. (2023). Sustainable Language Training for Engineering Students: Integrating Resource-Efficiency into the Course Content through the Educational Process. Education Sciences, 13(2), Article 176. https://doi.org/10.3390/educsci13020176

The sustainable use of the Earth’s resources is recognized as increasingly important on a global scale, especially in relation to natural resource management, and is effectively addressed under the auspices of resource efficiency within engineering e... Read More about Sustainable Language Training for Engineering Students: Integrating Resource-Efficiency into the Course Content through the Educational Process.

Model predictive control of consensus-based energy management system for DC microgrid (2023)
Journal Article
Ali, S. U., Waqar, A., Aamir, M., Qaisar, S. M., & Iqbal, J. (2023). Model predictive control of consensus-based energy management system for DC microgrid. PLoS ONE, 18(1), Article e0278110. https://doi.org/10.1371/journal.pone.0278110

The increasing deployment and exploitation of distributed renewable energy source (DRES) units and battery energy storage systems (BESS) in DC microgrids lead to a promising research field currently. Individual DRES and BESS controllers can operate a... Read More about Model predictive control of consensus-based energy management system for DC microgrid.

A review on micromechanical modelling of progressive failure in unidirectional fibre-reinforced composites (2023)
Journal Article
Wan, L., Ismail, Y., Sheng, Y., Ye, J., & Yang, D. (2023). A review on micromechanical modelling of progressive failure in unidirectional fibre-reinforced composites. Composites Part C: Open Access, 10, Article 100348. https://doi.org/10.1016/j.jcomc.2023.100348

The recent decades have seen various attempts at the numerical modelling of fibre-reinforced polymer (FRP) composites in the aerospace, auto and marine sectors due to their excellent mechanical properties. However, it is still challenging to accurate... Read More about A review on micromechanical modelling of progressive failure in unidirectional fibre-reinforced composites.

A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds (2023)
Journal Article
Riaz, S., Qi, R., Tutsoy, O., & Iqbal, J. (2023). A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds. PLoS ONE, 18(1), Article e0279253. https://doi.org/10.1371/journal.pone.0279253

High precision demands in a large number of emerging robotic applications strengthened the role of the modern control laws in the position control of the Permanent Magnet Synchronous Motor (PMSM) servo system. This paper proposes a learning-based ada... Read More about A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds.