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‘Weathervanes of their Communities’ – The Sanderson Review, public libraries and information literacy futures (2024)
Digital Artefact
Feeney, D., & Goldstein, S. (2024). ‘Weathervanes of their Communities’ – The Sanderson Review, public libraries and information literacy futures. [Blog]

Recent independent reviews of public library services in England have argued for a more comprehensive and cohesive strategy to promote the many benefits of these services. However a critical lack of quality data to support these conclusions, particu... Read More about ‘Weathervanes of their Communities’ – The Sanderson Review, public libraries and information literacy futures.

New Horizons in Peer Advice Systems: Developing the Freelance Advisor (2024)
Presentation / Conference Contribution
Patrick-Thomson, H., Lawson, A., & Lapok, P. (2024, April). New Horizons in Peer Advice Systems: Developing the Freelance Advisor. Paper presented at Digital Business and Society Consortium, Royal Holloway, University of London

Work in the creative and cultural industries is often seen as “good” because it offers people a chance to earn money while engaged in their passion (McRobbie, 2018), to have autonomy over when, where and how they work (Smith and McKinlay, 2009), and... Read More about New Horizons in Peer Advice Systems: Developing the Freelance Advisor.

Wood properties and uses of larch in Great Britain (2024)
Report
McLean, P., Ridley-Ellis, D., Price, A., & Macdonald, E. (2024). Wood properties and uses of larch in Great Britain. Surrey: Forest Research

This report collates and synthesises research into the production and use of larch timber in Great Britain, drawing on information from a range of published and unpublished studies. It is written for forest scientists, engineers, wood processors and... Read More about Wood properties and uses of larch in Great Britain.

Frequency Fitness Assignment for Untangling Proteins in 2D (2024)
Presentation / Conference Contribution
Koutstaal, J., Kommandeur, J., Timmer, R., Horn, R., Thomson, S. L., & van den Berg, D. (2024, April). Frequency Fitness Assignment for Untangling Proteins in 2D. Presented at EvoStar 2024, Aberyswyth, UK

At the time of writing, there is no known deterministic-time algorithm to sample valid initial solutions with uniform random distribution for the HP protein folding model, because guaranteed uniform random sampling produces collisions (i.e. constrain... Read More about Frequency Fitness Assignment for Untangling Proteins in 2D.

Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges (2024)
Journal Article
Chamola, V., Chougule, A., Sam, A., Hussain, A., & Yu, F. R. (2024). Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges. IEEE Internet of Things, 11(10), 17911-17933. https://doi.org/10.1109/jiot.2024.3362851

The field of autonomous driving research has made significant strides towards achieving full automation, endowing vehicles with self-awareness and independent decision-making. However, integrating automation into vehicular operations presents formida... Read More about Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges.

Net Zero Emissions Buildings, Shifting the Focus from Energy Efficient to Whole Life Carbon Emission: A Review Study (2024)
Presentation / Conference Contribution
Obead, R., Khaddour, L., & D'Amico, B. (2024, April). Net Zero Emissions Buildings, Shifting the Focus from Energy Efficient to Whole Life Carbon Emission: A Review Study. Presented at Environmental Design, Material Science, and Engineering Technologies conference, Dubai, UAE

Building construction and operation are significant contributors to global world emissions. Therefore, reducing emissions in this sector is an essential step in global efforts toward a zero-emission economy. As a response to this need, many works hav... Read More about Net Zero Emissions Buildings, Shifting the Focus from Energy Efficient to Whole Life Carbon Emission: A Review Study.

Discrete model for discontinuous dynamic recrystallisation applied to grain structure evolution inside adiabatic shear bands (2024)
Journal Article
Borodin, E., Bushuev, O., Bratov, V., & Jivkov, A. P. (2024). Discrete model for discontinuous dynamic recrystallisation applied to grain structure evolution inside adiabatic shear bands. Journal of Materials Research and Technology, 30, 2125-2139. https://doi.org/10.1016/j.jmrt.2024.03.206

Discontinuous dynamic recrystallisation (DDRX) is a well-known phenomenon playing a significant role in the high-temperature processing of metals, including industrial forming and severe plastic deformations. The ongoing discussion on the Zener–Hollo... Read More about Discrete model for discontinuous dynamic recrystallisation applied to grain structure evolution inside adiabatic shear bands.

Hybrid Wi-Fi and PLC network for efficient e-health communication in hospitals: a prototype (2024)
Journal Article
Khan, S. U., Ullah Jan, S., Hwang, T., & Koo, I. (2024). Hybrid Wi-Fi and PLC network for efficient e-health communication in hospitals: a prototype. Bulletin of Electrical Engineering and Informatics, 13(2), 1400-1410. https://doi.org/10.11591/eei.v13i2.5309

E-health is being adapted in modern hospitals as a significant addition to the existing healthcare services. To this end, modern hospitals urgently require a mobile, high-capacity, secure, and cost-effective communication infrastructure. In this pape... Read More about Hybrid Wi-Fi and PLC network for efficient e-health communication in hospitals: a prototype.

Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms? (2024)
Journal Article
Anas, M., Saiyeda, A., Sohail, S. S., Cambria, E., & Hussain, A. (2024). Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?. IEEE Intelligent Systems, 39(2), 5-10. https://doi.org/10.1109/mis.2024.3374582

Recent advances in the context of deep learning have led to the development of generative artificial intelligence (AI) models which have shown remarkable performance in complex language understanding tasks. This study proposes an evaluation of tradit... Read More about Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?.

Finite Element Modeling of Electric Field Distribution in a Defective XLPE Cable Insulation Under Different Magnitudes of Stressing Voltage (2024)
Presentation / Conference Contribution
Sulaiman, S. H., Rohani, M. N. K. H., Abdulkarim, A., Abubakar, A. S., Shehu, G. S., Musa, U., Mas'ud, A. A., Rosle, N., & Muhammad-Sukki, F. (2023, August). Finite Element Modeling of Electric Field Distribution in a Defective XLPE Cable Insulation Under Different Magnitudes of Stressing Voltage. Presented at The 12th International Conference on Robotics, Vision, Signal Processing, and Power Applications, Penang, Malaysia

Air voids in solid dielectrics affect the performance and lifespan of high voltage (HV) equipment. In this research, electric field distribution within a cross-linked polyethylene (XLPE) HV cable is analyzed using a finite element analysis (FEA) soft... Read More about Finite Element Modeling of Electric Field Distribution in a Defective XLPE Cable Insulation Under Different Magnitudes of Stressing Voltage.

Pre-Processing-based Fast Design of Multiple EM Structures with One Deep Neural Network (2024)
Journal Article
Wang, P., Li, Z., Luo, C., Wei, Z., Wu, T., Jiang, W., Hong, T., Parchi, N. O., Pedersen, G. F., & Shen, M. (2024). Pre-Processing-based Fast Design of Multiple EM Structures with One Deep Neural Network. IEEE Transactions on Antennas and Propagation, 72(5), https://doi.org/10.1109/tap.2024.3381376

Deep learning plays a vital role in the design of electromagnetic (EM) structures. However, in current research, a single neural network typically supports only one structure design and requires a complex framework to accommodate multiple structure d... Read More about Pre-Processing-based Fast Design of Multiple EM Structures with One Deep Neural Network.

Building an Embodied Musicking Dataset for co-creative music-making (2024)
Presentation / Conference Contribution
Vear, C., Poltronieri, F., Di Donato, B., Zhang, Y., Benerradi, J., Hutchinson, S., Turowski, P., Shell, J., & Malekmohamadi, H. (2024, April). Building an Embodied Musicking Dataset for co-creative music-making. Presented at Evostar 2024: The Leading European Event on Bio‑Inspired Computation, Aberystwyth, Wales, United Kingdom

In this paper, we present our findings of the design, development and deployment of a proof-of-concept dataset that captures some of the physiological, musicological, and psychological aspects of embodied musicking. After outlining the conceptual ele... Read More about Building an Embodied Musicking Dataset for co-creative music-making.

Convex neural network synthesis for robustness in the 1-norm (2024)
Presentation / Conference Contribution
Drummond, R., Guiver, C., & Turner, M. C. (2024, July). Convex neural network synthesis for robustness in the 1-norm. Presented at 6th Annual Learning for Dynamics & Control Conference, Oxford, England

With neural networks being used to control safety-critical systems, they increasingly have to be both accurate (in the sense of matching inputs to outputs) and robust. However, these two properties are often at odds with each other and a trade-off ha... Read More about Convex neural network synthesis for robustness in the 1-norm.

Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks (2024)
Journal Article
Halimu, Y., Zhao, H., Yu, H., Ding, S., & Qiao, S. (online). Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, https://doi.org/10.1177/09596518241236928

This article investigates a Denial-of-Service (DoS) attack problem for nonlinear unknown discrete-time multiagent systems (MASs) to implement bipartite consensus tracking tasks with fixed and switching topologies. Firstly, an equivalent linearization... Read More about Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks.

PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing (2024)
Journal Article
Zhang, Z., Liu, Q., Liu, X., Zhang, Y., Du, Z., & Cao, X. (2024). PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing. Journal of cloud computing: advances, systems and applications, 13(1), Article 76. https://doi.org/10.1186/s13677-024-00637-5

In the field of remote sensing image interpretation, automatically extracting water body information from high-resolution images is a key task. However, facing the complex multi-scale features in high-resolution remote sensing images, traditional met... Read More about PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing.

Application of Randomness for Security and Privacy in Multi-Party Computation (2024)
Journal Article
Saha, R., Kumar, G., Geetha, G., Conti, M., & Buchanan, W. J. (online). Application of Randomness for Security and Privacy in Multi-Party Computation. IEEE Transactions on Dependable and Secure Computing, https://doi.org/10.1109/tdsc.2024.3381959

A secure Multi-Party Computation (MPC) is one of the distributed computational methods, where it computes a function over the inputs given by more than one party jointly and keeps those inputs private from the parties involved in the process. Randomi... Read More about Application of Randomness for Security and Privacy in Multi-Party Computation.

Effect of pulsating flow on flow-induced vibrations of circular and square cylinders in the laminar regime (2024)
Journal Article
Wang, X., Zhang, Z., Shi, K., Zhu, X., Guo, X., Mei, Y., & Kadapa, C. (2024). Effect of pulsating flow on flow-induced vibrations of circular and square cylinders in the laminar regime. Ocean Engineering, 301, Article 117609. https://doi.org/10.1016/j.oceaneng.2024.117609

Through fluid-structure interaction simulations, this study assesses the dynamic response characteristics of elastically mounted circular and square cylinders subjected to pulsating inflow conditions, providing valuable insights int... Read More about Effect of pulsating flow on flow-induced vibrations of circular and square cylinders in the laminar regime.

Application of machine learning in predicting frailty syndrome in patients with heart failure (2024)
Journal Article
Szczepanowski, R., Uchmanowicz, I., Pasieczna-Dixit, A. H., Sobecki, J., Katarzyniak, R., Kołaczek, G., Lorkiewicz, W., Kędras, M., Dixit, A., Biegus, J., Wleklik, M., Gobbens, R. J., Hill, L., Jaarsma, T., Hussain, A., Barbagallo, M., Veronese, N., Morabito, F. C., & Kahsin, A. (2024). Application of machine learning in predicting frailty syndrome in patients with heart failure. Advances in Clinical and Experimental Medicine, 33(3), 309-315. https://doi.org/10.17219/acem/184040

Prevention and diagnosis of frailty syndrome (FS) in patients with heart failure (HF) require innovative systems to help medical personnel tailor and optimize their treatment and care. Traditional methods of diagnosing FS in patients could be more sa... Read More about Application of machine learning in predicting frailty syndrome in patients with heart failure.

Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach (2024)
Journal Article
Aydin, E. E., Akcasoy, A., Cakir, F., Cansiz, B. S., Secinti, G., & Canberk, B. (2024). Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach. IEEE Access, 12, 45631-45643. https://doi.org/10.1109/access.2024.3381859

Self-organization is a key strategy for improving the performance of an aerial swarm ad hoc network. The proliferation of low-cost VTOL drones has broadened the application domain of aerial swarms, and the need for synchronized communication among ne... Read More about Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach.