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Outputs (610)

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.

PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms (2024)
Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Al-Dubai, A., Jaroucheh, Z., Pitropakis, N., & Buchanan, W. J. (2023, November). PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

Traditional permutation schemes mostly focus on random scrambling of pixels, often neglecting the intrinsic image information that could enhance diffusion in image encryption algorithms. This paper introduces PermutEx, a feature-extractionbased permu... Read More about PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms.

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. (2024). 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, 238(7), 1231 - 1241. 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. (2024). Application of Randomness for Security and Privacy in Multi-Party Computation. IEEE Transactions on Dependable and Secure Computing, 21(6), 5694-5705. 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.