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Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery (2023)
Conference Proceeding
Wang, G., Leonce, A., Hacid, H., & Edirisinghe, E. (2023). Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery. In 2023 International Symposium on Networks, Computers and Communications (ISNCC). https://doi.org/10.1109/isncc58260.2023.10323960

The United Arab Emirates (UAE) values its relationship with the desert, considering it a crucial part of its heritage and culture. However, the desert faces environmental challenges due to the improper disposal of garbage by visitors and the dumping... Read More about Deep Neural Network Based Automatic Litter Detection in Desert Areas Using Unmanned Aerial Vehicle Imagery.

Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery (2023)
Conference Proceeding
Chen, C., Edirisinghe, E., Leonce, A., Simkins, G., Khafaga, T., Sher Shah, M., & Yahya, U. (2023). Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery. In 2023 International Symposium on Networks, Computers and Communications (ISNCC). https://doi.org/10.1109/isncc58260.2023.10323685

There is a growing interest among the research community in the search for possible technology-driven strategies for the conservation of the much-needed, historically rich and culturally important, desert life. In this work, we investigate the use of... Read More about Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery.

A novel (2+1)-dimensional nonlinear evolution equation for weakly stratified free-surface boundary layers (2023)
Journal Article
Oloo, J. O., & Shrira, V. I. (2023). A novel (2+1)-dimensional nonlinear evolution equation for weakly stratified free-surface boundary layers. Journal of Fluid Mechanics, 973, Article A40. https://doi.org/10.1017/jfm.2023.773

To get an insight into the dynamics of the oceanic surface boundary layer we develop an asymptotic model of the nonlinear dynamics of linearly decaying three-dimensional long-wave perturbations in weakly stratified boundary-layer flows. Although in n... Read More about A novel (2+1)-dimensional nonlinear evolution equation for weakly stratified free-surface boundary layers.

Skew Bracoids (2023)
Journal Article
Truman, P., & Martin-Lyons, I. (2024). Skew Bracoids. Journal of Algebra, 638, 751-787. https://doi.org/10.1016/j.jalgebra.2023.10.005

Skew braces are intensively studied owing to their wide ranging connections and applications. We generalize the definition of a skew brace to give a new algebraic object, which we term a \textit{skew bracoid}. Our construction involves two groups int... Read More about Skew Bracoids.

Expedient, Affective, and Sustained Solidarities? Mediated Contestations of Islamophobia in the Case of Brexit, the Christchurch Terror Attack, and the COVID-19 Pandemic (2023)
Journal Article
Poole, E., Giraud, E. H., Richardson, J. E., & de Quincey, E. (2023). Expedient, Affective, and Sustained Solidarities? Mediated Contestations of Islamophobia in the Case of Brexit, the Christchurch Terror Attack, and the COVID-19 Pandemic. Social Media + Society, 9(3), 1-16. https://doi.org/10.1177/20563051231199452

This article advances research on mediated solidarity, by analyzing the contestation of Islamophobia on the social media platform Twitter, in the context of Brexit, the Christchurch terror attack, and the COVID-19 pandemic. Drawing on a unique longit... Read More about Expedient, Affective, and Sustained Solidarities? Mediated Contestations of Islamophobia in the Case of Brexit, the Christchurch Terror Attack, and the COVID-19 Pandemic.

Discovering asymptotic expansions for problems in mechanics using symbolic regression (2023)
Journal Article
Abdusalamov, R., Kaplunov, J., & Itskov, M. (in press). Discovering asymptotic expansions for problems in mechanics using symbolic regression. Mechanics Research Communications, 133, Article 104197. https://doi.org/10.1016/j.mechrescom.2023.104197

Recently, symbolic regression (SR) has demonstrated its efficiency for discovering basic governing relations in physical systems. A major impact can be potentially achieved by coupling symbolic regression with asymptotic methodolog... Read More about Discovering asymptotic expansions for problems in mechanics using symbolic regression.

Degenerated Boundary Layers and Long-Wave Low-Frequency Motion in High-Contrast Elastic Laminates (2023)
Journal Article
Aghalovyan, L. A., Ghulghazaryan, L. G., Kaplunov, J., & Prikazchikov, D. (in press). Degenerated Boundary Layers and Long-Wave Low-Frequency Motion in High-Contrast Elastic Laminates. Mathematics, 11(18), Article 3905. https://doi.org/10.3390/math11183905

The effect of high contrast on the multiscale behaviour of elastic laminates is studied. Mathematical modelling in this area is of significant interest for a variety of modern applications, including but not limited to advanced sandwich structures an... Read More about Degenerated Boundary Layers and Long-Wave Low-Frequency Motion in High-Contrast Elastic Laminates.

A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic (2023)
Journal Article
Hasan, M. M., Jahan, M., & Kabir, S. (2023). A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic. IEEE Transactions on Intelligent Transportation Systems, 1-14. https://doi.org/10.1109/tits.2023.3305342

Trust establishment among vehicles is essential for vehicular ad hoc networks (VANETs) as it directly impacts the security and privacy of vehicular communication. Many trust estimation approaches have been introduced, however, they often suffer from... Read More about A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic.

Uniform approximations and effective boundary conditions for a high-contrast elastic interface (2023)
Journal Article
Chapman, C. J., & Mogilevskaya, S. G. (2023). Uniform approximations and effective boundary conditions for a high-contrast elastic interface. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 479(2277), 1 - 22. https://doi.org/10.1098/rspa.2023.0140

A difficulty in the theory of a thin elastic interface is that series expansions in its thickness become disordered in the high-contrast limit, i.e. when the interface is much softer or much stiffer than the media on either side. We provide a mathema... Read More about Uniform approximations and effective boundary conditions for a high-contrast elastic interface.

Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey (2023)
Conference Proceeding
Rhodes, R., & Woolley, S. (2023). Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey. . https://doi.org/10.14236/ewic/BCSHCI2023.8

This paper surveys twenty years of published works and implementations of virtual reality (VR), augmented reality (AR) and 3D repositories relevant to ancient Mesopotamia. Results are sorted according to type, relevance to cuneiform, evaluation, an... Read More about Virtual and Augmented Reality Interfaces for 3D Mesopotamian Environments and Artefacts – A Survey.

Computations and Measurements of the Magnetic Polarizability Tensor Characterisation of Highly Conducting and Magnetic Objects (2023)
Journal Article
Elgy, J., Ledger, P. D., Davidson, J. L., Özdeger, T., & Peyton, A. J. (2023). Computations and Measurements of the Magnetic Polarizability Tensor Characterisation of Highly Conducting and Magnetic Objects. Engineering Computations, 40(7/8), 1778-1806. https://doi.org/10.1108/EC-11-2022-0688

Purpose The ability to characterise highly conducting objects, that may also be highly magnetic, by the complex symmetric rank–2 magnetic polarizability tensor (MPT) is important for metal detection applications including discriminating between thre... Read More about Computations and Measurements of the Magnetic Polarizability Tensor Characterisation of Highly Conducting and Magnetic Objects.

Quantifying Device Usefulness - How Useful is an Obsolete Device? (2023)
Conference Proceeding
Goodwin, C., Woolley, S., de Quincey, E., & Collins, T. (2023). Quantifying Device Usefulness - How Useful is an Obsolete Device?. In Human-Computer Interaction – INTERACT 2023 (90-99). https://doi.org/10.1007/978-3-031-42293-5_8

Obsolete devices add to the rising levels of electronic waste, a major environmental concern, and a contributing factor to climate change. In recent years, device manufacturers have established environmental commitments and launched initiatives such... Read More about Quantifying Device Usefulness - How Useful is an Obsolete Device?.

Visual Attention Assisted Games (2023)
Conference Proceeding
Mandal, B., Puhan, N. B., & Homi Anil, V. (2023). Visual Attention Assisted Games. In 2023 IEEE Conference on Games (CoG). https://doi.org/10.1109/cog57401.2023.10333186

In this work, we propose a committee of attention models developed for improving the deep reinforcement learning frequently used for games. The game environment is manifested with spatial and temporal attention mechanisms so as to focus on important... Read More about Visual Attention Assisted Games.

Reduced order modelling using neural networks for predictive modelling of 3d-magneto-mechanical problems with application to magnetic resonance imaging scanners (2023)
Journal Article
Miah, S., Sooriyakanthan, Y., Ledger, P. D., Gil, A. J., & Mallett, M. (2023). Reduced order modelling using neural networks for predictive modelling of 3d-magneto-mechanical problems with application to magnetic resonance imaging scanners. Engineering with Computers, 39(6), 4103-4127. https://doi.org/10.1007/s00366-023-01870-3

The design of magnets for magnetic resonance imaging (MRI) scanners requires the numerical simulation of a coupled magneto-mechanical system where the effects that different material parameters and in-service loading conditions have on both imaging a... Read More about Reduced order modelling using neural networks for predictive modelling of 3d-magneto-mechanical problems with application to magnetic resonance imaging scanners.

Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction (2023)
Conference Proceeding
Goparaju, S. U., Biju, R., M, P., MC, B., Gangadharan, D., Mandal, B., & C, P. (2023). Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction. . https://doi.org/10.1109/vtc2023-spring57618.2023.10200600

Traffic flow prediction has been regarded as a critical problem in intelligent transportation systems. An accurate prediction can help mitigate congestion and other societal problems while facilitating safer, cost and time-efficient travel. However,... Read More about Optimization and Performance Evaluation of Hybrid Deep Learning Models for Traffic Flow Prediction.