All Outputs (184)

Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real-Time Threat Detection (2025)
Presentation / Conference Contribution
Patel, T., Jhaveri, R. H., Thakker, D., Verma, S., & Ingle, P. (2025, March). Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real-Time Threat Detection. Presented at SAC '25: 40th ACM/SIGAPP Symposium on Applied Computing, Catania, Sicily, Italy

The proliferation of IoV technologies has revolutionized the use of transport systems to a great level of improvement in safety and efficiency, and convenience to users. On the other hand, increased connectivity has also brought new vulnerabilities,... Read More about Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real-Time Threat Detection.

Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management (2024)
Presentation / Conference Contribution
Abid, S., Mishra, B. K., Younis, U., Thakker, D., & Mishra, N. (2024, December). Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management. Presented at 2024 International Conference on Frontiers of Information Technology, FIT 2024, Islamabad, Pakistan

For disaster management, the accurate and timely availability of factual information is crucial for effective decision-making and response. Traditional communication channels are either costly or do not provide real-time data. Here comes the role of... Read More about Social Media Data: Challenges, Mitigation Strategies, and Opportunities for Disaster Management.

Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool (2024)
Presentation / Conference Contribution
Ravindhran, B., Prosser, J., Lim, A., Mishra, B., Lathan, R., Hitchman, L., Smith, G., Carradice, D., Thakker, D., Pymer, S., & Chetter, I. (2024, June). Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool. Presented at The European Society for Vascular Surgery Translational Spring Meeting 2024, Stockholm, Sweden

Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing (2024)
Presentation / Conference Contribution
Wuraola, I., Dethlefs, N., & Marciniak, D. (2024, November). Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing. Presented at EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, Miami, FLorida, USA

In the realm of social media discourse, the integration of slang enriches communication, reflecting the sociocultural identities of users. This study investigates the capability of large language models (LLMs) to paraphrase slang within climate-relat... Read More about Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing.

LLM Based Cross Modality Retrieval to Improve Recommendation Performance (2024)
Presentation / Conference Contribution
Anwaar, F., Khan, A. M., & Khalid, M. (2024, August). LLM Based Cross Modality Retrieval to Improve Recommendation Performance. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, UK

The metadata of items and users play an important role in improving the decision-making process in the Recom-mender System. In recent times, web scraping-based techniques have been widely utilized to extract explicit user and item meta-data from diff... Read More about LLM Based Cross Modality Retrieval to Improve Recommendation Performance.

Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance (2024)
Presentation / Conference Contribution
Kureshi, R. R., Mazumdar, S., Mishra, B. K., Li, X., & Thakker, D. (2023, December). Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance. Presented at 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023), Dubai, UAE

The detrimental effects of air pollutants on human health have prompted increasing concerns regarding indoor air quality (IAQ). The emergence of digital health interventions and citizen science initiatives has provided new avenues for raising awarene... Read More about Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance.

Devising a Responsible Framework for Air Quality Sensor Placement (2024)
Presentation / Conference Contribution
Westcarr, J., Gunturi, V. M. V., Cabaneros, S. M., Raja, R., Thakker, D., & Porter, A. (2024, July). Devising a Responsible Framework for Air Quality Sensor Placement. Presented at 2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS), London, United Kingdom

A major challenge faced when developing smart, sustainable urban environments is the reduction of air pollutants that adversely impact citizens' health. The UK has implemented strategies such as clean air zones (CAZs) coupled with the use of sensor t... Read More about Devising a Responsible Framework for Air Quality Sensor Placement.

Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework (2024)
Presentation / Conference Contribution
Walker, A., Diaz, K. R. V., McKie, D., & Iqbal, J. (2024, February). Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework. Presented at Ninth International Congress on Information and Communication Technology (ICICT 2024), London

Hardware-inspired enquiry-based learning (EBL) is an emerging pedagogy to develop transferable engineering skills in students. This paper is aimed at unleashing the potential of this pedagogy via the multidisciplinary domain of robotics to learn the... Read More about Enquiry-based learning pedagogy – Design, development and delivery of a reproducible robotics framework.

Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE (2024)
Presentation / Conference Contribution
Raza, M., Khattak, A., Abbas, W., & Khan, A. (2024, June). Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE. Presented at 37th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Guadalajara, Mexico

Obesity, a global public health concern, is escalating rapidly, especially in the Middle East, with the United Arab Emirates (UAE) witnessing one of the highest prevalence rates among adults and children. This multifactorial health issue is influence... Read More about Global Knowledge, Local Impact: Domain Adaptation and Classification for Obesity in the UAE.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps (2024)
Presentation / Conference Contribution
Palaev, A., Khan, A., & Kazmi, A. (2024, November). LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps. Paper presented at The 35th British Machine Vision Conference, Glasgow

The advancement of text-to-image synthesis has introduced powerful generative models capable of creating realistic images from textual prompts. However, precise control over image attributes remains challenging, especially at the instance level. Whil... Read More about LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps.

Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels (2024)
Presentation / Conference Contribution
Rezoug, A., Bouderbala, F.-Z., Baizid, K., & Iqbal, J. (2022, December). Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels. Presented at 1st International Conference on Advanced Renewable Energy Systems (ICARES 2022), Tipaza, Algeria

In this paper, inspection of solar energy system is addressed using a quadrotor unmanned aerial vehicle (UAV) system. The accurate positioning of the system on the solar panel requires a robust controller to precisely address the fault while ensuring... Read More about Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels.

AI-Based Hand Gesture Recognition Through Camera on Robot (2024)
Presentation / Conference Contribution
Csonka, G., Khalid, M., Rafiq, H., & Ali, Y. (2023, December). AI-Based Hand Gesture Recognition Through Camera on Robot. Presented at 2023 International Conference on Frontiers of Information Technology (FIT), Islamabad

This paper presents an innovative approach to real-time hand gesture recognition for robot control using Artificial Intelligence (AI). The core of this project is a machine learning model trained on a custom data set of hand gestures, which was metic... Read More about AI-Based Hand Gesture Recognition Through Camera on Robot.

Evaluating Asthma Symptoms in Relation to Indoor Air Quality: Insights from IoT-enabled Monitoring (2024)
Presentation / Conference Contribution
Mishra, B. K., Thakker, D., John, R., Kureshi, R. R., Ahmad, B., Jones, W., & Li, X. (2023, December). Evaluating Asthma Symptoms in Relation to Indoor Air Quality: Insights from IoT-enabled Monitoring. Presented at 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023), Dubai, UAE

Air pollution appears in the form of outdoor air quality and indoor air quality (IAQ). Particulate Matters (PM2.5 and PM10) and CO2, among many air pollutants, are responsible for worsening IAQ. IAQ has been linked to lung illnesses such as asthma, c... Read More about Evaluating Asthma Symptoms in Relation to Indoor Air Quality: Insights from IoT-enabled Monitoring.

Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data (2024)
Presentation / Conference Contribution
Mohamad Mohsin, M. F., Umana, M. K., Hassan, M. G., Sharif, K. I. M., Ismail, M. A., Salleh, K., Zahari, S. M., Sarmani, M. A., & Gordon, N. Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data. Presented at International Conference on Computing and Informatics 2023, Kuala Lumpur, Malaysia

Rice production is critical to food security, and accurate yield predictions are required for planning and decision-making. However, precisely predicting rice yields using machine learning models can be difficult due to the complicated interactions o... Read More about Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data.

Redefining Digital Twins - A Wind Energy Operations and Maintenance Perspective (2024)
Presentation / Conference Contribution
Tuton, E., Ma, X., & Dethlefs, N. (2024, May). Redefining Digital Twins - A Wind Energy Operations and Maintenance Perspective. Presented at The Science of Making Torque from Wind (TORQUE 2024), Florence, Italy

Digital Twin (DT) technology has seen an explosion in popularity, with wind energy no exception. This is particularly true for Operations & Maintenance (O&M) applications. However, this expanded use has been accompanied by loose, conflicting, definit... Read More about Redefining Digital Twins - A Wind Energy Operations and Maintenance Perspective.

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.

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.

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.