All Outputs (261)

Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees (2024)
Journal Article
Pimbblet, K. A., & Morrell, L. J. (2025). Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees. European Journal of Physics, 46(1), Article 015702. https://doi.org/10.1088/1361-6404/ad9874

The emergence of conversational natural language processing models presents a significant challenge for Higher Education. In this work, we use the entirety of a UK Physics undergraduate (BSc with Honours) degree including all examinations and coursew... Read More about Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees.

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

A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample (2024)
Journal Article
Eden, S. L., Sadler, E. M., Pimbblet, K. A., Mahony, E. K., & Yoon, H. (2025). A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample. Monthly notices of the Royal Astronomical Society, 536(1), 387-407. https://doi.org/10.1093/mnras/stae2581

We present and discuss two catalogues of UV-selected (NUV < 22.8 mag) galaxies that lie within a 200 deg 2 area of sky covered by the ASKAP FLASH survey and have an impact parameter of less than 20 arcsec to a FLASH radio continuum source. These cata... Read More about A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample.

Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction (2024)
Journal Article
Mishra, B. K., Preniqi, V., Thakker, D., & Feigl, E. (2024). Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction. Discover Internet of Things, 4(1), Article 24. https://doi.org/10.1007/s43926-024-00075-4

Electricity price prediction has an imperative role in the UK energy market among energy trading organisations. The price prediction directly impacts organisational policy for profitable electricity trading, better bidding plans, and the optimisation... Read More about Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction.

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.

Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment (2024)
Journal Article
House, L. R., Gebhardt, K., Finkelstein, K., Mentuch Cooper, E., Davis, D., Farrow, D., & Schneider, D. P. (2024). Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment. The Astrophysical journal, 975(2), Article 172. https://doi.org/10.3847/1538-4357/ad782c

We are merging a large participatory science effort with machine learning to enhance the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources... Read More about Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment.

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.

A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features (2024)
Presentation / Conference Contribution
Khan, G., Pimbblet, K., Wertheim, K., & Ahmed, W. (2024, August). A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, United Kingdom

Considering the face as a vital and most informative portion of the human body, it reflects different high-level information about an individual. This high-level information includes Age, Gender, and Emotion. Facial muscles' shape and movement can be... Read More about A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features.

Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach (2024)
Journal Article
Ren, X., Lai, C. S., Guo, Z., & Taylor, G. (2024). Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/TCE.2024.3482101

Consumer electronics such as advanced GPS,vehicular sensors,inertial measurement units (IMUs),and wireless modules integrate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) within internet of thing (IoT),enabling connected autonomous ele... Read More about Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach.

Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI (2024)
Presentation / Conference Contribution
Kadel, R., Mishra, B. K., Shailendra, S., Abid, S., Rani, M., & Mahato, S. P. (2024, July). Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI. Presented at 2024 International Symposium on Educational Technology, ISET 2024, Macau

In recent years, no other technology has revolutionised our life as Generative Artificial Intelligence (GenAI). GenAI has gained the attention of a myriad of users in almost every profession. Its advancement has had an intense impact on education, si... Read More about Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI.

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.

DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture (2024)
Presentation / Conference Contribution
Babaferi, E. V., Fagbola, T. M., & Thakur, C. S. (2024, August). DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture. Presented at 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, Mauritius

Brain tumors are abnormal cell growths within the brain tissues, necessitating their early detection towards effective treatment. To achieve this, high-quality brain images via medical imaging techniques, such as Magnetic Resonance Imaging (MRI), are... Read More about DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture.

Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis (2024)
Presentation / Conference Contribution
Fagbola, T. M., Aderemi, E. T., & Thakur, C. S. (2024, August). Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis. Presented at 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD), Mauritius

The use of Deep Learning (DL)-based methods for Colorectal Cancer (CRC) classification and segmentation has gained significant attention in recent times. This study employs a bibliometric analysis to investigate the state-of-The-art research on DL-ba... Read More about Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis.

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.

Constraining SN Ia Progenitors from the Observed Fe-peak Elemental Abundances in the Milky Way Dwarf Galaxy Satellites (2024)
Preprint / Working Paper
Alexander, R., & Vincenzo, F. Constraining SN Ia Progenitors from the Observed Fe-peak Elemental Abundances in the Milky Way Dwarf Galaxy Satellites

Chemical abundances of iron-peak elements in the red giants of ultra-faint dwarf galaxies (UFD) and dwarf spheroidal galaxies (dSph) are among the best diagnostics in the cosmos to probe the origin of Type Ia Supernovae (SNe Ia). We incorporate metal... Read More about Constraining SN Ia Progenitors from the Observed Fe-peak Elemental Abundances in the Milky Way Dwarf Galaxy Satellites.

The evolution of democratic peace in animal societies (2024)
Journal Article
Hunt, K. L., Patel, M., Croft, D. P., Franks, D. W., Green, P. A., Thompson, F. J., Johnstone, R. A., Cant, M. A., & Sankey, D. W. (2024). The evolution of democratic peace in animal societies. Nature communications, 15(1), Article 6583. https://doi.org/10.1038/s41467-024-50621-5

A major goal in evolutionary biology is to elucidate common principles that drive human and other animal societies to adopt either a warlike or peaceful nature. One proposed explanation for the variation in aggression between human societies is the d... Read More about The evolution of democratic peace in animal societies.

A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study (2024)
Journal Article
Azam, M. M. B., Anwaar, F., Khan, A. M., Anwar, M., Ghani, H. B. A., Eisa, T. A. E., & Abdelmaboud, A. (2024). A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study. Egyptian Informatics Journal, 27, Article 100508. https://doi.org/10.1016/j.eij.2024.100508

Infectious disease is a particular type of disorder triggered by organisms and transmitted directly or indirectly from an infected one like COVID-19. The global economy and public health are immensely affected by COVID-19, a recently emerging infecti... Read More about A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study.

Constraining the duration of ram pressure stripping features in the optical from the direction of jellyfish galaxy tails (2024)
Journal Article
Salinas, V., Jaffé, Y. L., Smith, R., Shinn, J. H., Crossett, J. P., Gullieuszik, M., González-Torà, G., Piraino-Cerda, F., Poggianti, B., Vulcani, B., Biviano, A., Lourenço, A. C. C., Bilton, L. E., Kelkar, K., & Calderón-Castillo, P. (2024). Constraining the duration of ram pressure stripping features in the optical from the direction of jellyfish galaxy tails. Monthly notices of the Royal Astronomical Society, 533(1), 341-359. https://doi.org/10.1093/mnras/stae1784

Ram pressure stripping is perhaps the most efficient mechanism for removing gas and quenching galaxies in dense environments, as they move through the intergalactic medium. Extreme examples of on-going ram pressure stripping are known as jellyfish ga... Read More about Constraining the duration of ram pressure stripping features in the optical from the direction of jellyfish galaxy tails.

Tests of subgrid models for star formation using simulations of isolated disc galaxies (2024)
Journal Article
Nobels, F. S. J., Schaye, J., Schaller, M., Ploeckinger, S., Chaikin, E., & Richings, A. J. (2024). Tests of subgrid models for star formation using simulations of isolated disc galaxies. Monthly notices of the Royal Astronomical Society, 532(3), 3299-3321. https://doi.org/10.1093/mnras/stae1390

We use smoothed particle hydrodynamics simulations of isolated Milky Way-mass disc galaxies that include cold, interstellar gas to test subgrid prescriptions for star formation (SF). Our fiducial model combines a Schmidt law with a gravitational inst... Read More about Tests of subgrid models for star formation using simulations of isolated disc galaxies.

Estimating the household secondary attack rate and serial interval of COVID-19 using social media (2024)
Journal Article
Dhiman, A., Yom-Tov, E., Pellis, L., Edelstein, M., Pebody, R., Hayward, A., House, T., Finnie, T., Guzman, D., Lampos, V., Virus Watch Consortium, & Cox, I. J. (2024). Estimating the household secondary attack rate and serial interval of COVID-19 using social media. npj Digital Medicine, 7(1), Article 194. https://doi.org/10.1038/s41746-024-01160-2

We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive,... Read More about Estimating the household secondary attack rate and serial interval of COVID-19 using social media.