All Outputs (10944)

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.

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.

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.

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.

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.

The collaborative use of career information by young people and career advisers: A thematic content analysis of career counselling records (2024)
Journal Article
Milosheva, M., Robertson, P., Cruickshank, P., & Hall, H. (2024). The collaborative use of career information by young people and career advisers: A thematic content analysis of career counselling records. Australian Journal of Career Development, 33(1), 72-81. https://doi.org/10.1177/10384162241232267

This study explores the career information-seeking behaviours of young people and career advisers. These are examined through the interrogation of a secondary data set held by Scotland's national skills agency, Skills Development Scotland. Descriptiv... Read More about The collaborative use of career information by young people and career advisers: A thematic content analysis of career counselling records.

Guest Editorial: Special Issue on Physics-Informed Machine Learning (2024)
Journal Article
Piccialli, F., Raissi, M., Viana, F. A. C., Fortino, G., Lu, H., & Hussain, A. (2024). Guest Editorial: Special Issue on Physics-Informed Machine Learning. IEEE Transactions on Artificial Intelligence, 5(3), 964-966. https://doi.org/10.1109/tai.2023.3342563

Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts (2024)
Journal Article
Sarvari, H., Asaadsamani, P., Olawumi, T. O., Chan, D. W., Rashidi, A., & Beer, M. (2024). Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts. Architectural Engineering and Design Management, 20(3), 673-693. https://doi.org/10.1080/17452007.2024.2329687

Building information modeling (BIM) is a disruptive information technology tool in the construction sector. Although this technology had a significant impact on the manufacturing industries, it, like any other technology, encountered several challeng... Read More about Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts.

Can we predict QPP? An approach based on multivariate outliers (2024)
Presentation / Conference Contribution
Chifu, A., Déjean, S., Garouani, M., Mothe, J., Ortiz, D., & Ullah, M. Z. (2024, March). Can we predict QPP? An approach based on multivariate outliers. Presented at 46th European Conference on Information Retrieval, ECIR 2024, Glasgow

Query performance prediction (QPP) aims to predict the success and failure of a search engine on a collection of queries and documents. State of the art predictors can enable this prediction with a degree of accuracy; however, it is far from being pe... Read More about Can we predict QPP? An approach based on multivariate outliers.

Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments (2024)
Presentation / Conference Contribution
Casas, L., Mitchell, K., Tamariz, M., Hannah, S., Sinclair, D., Koniaris, B., & Kennedy, J. (2024, May). Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments. Presented at CHI24 - Generative AI in User-Generated Content, Honolulu, Hawaii

We consider practical and social considerations of collaborating verbally with colleagues and friends, not confined by physical distance, but through seamless networked telepres-ence to interactively create shared virtual dance environments. In respo... Read More about Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments.

Wireless Power Transfer Technologies, Applications, and Future Trends: A Review (2024)
Journal Article
Alabsi, A., Hawbani, A., Wang, X., Dubai, A. A., Hu, J., Aziz, S. A., Kumar, S., Zhao, L., Shvetsov, A. V., & Alsamhi, S. H. (online). Wireless Power Transfer Technologies, Applications, and Future Trends: A Review. IEEE Transactions on Sustainable Computing, https://doi.org/10.1109/TSUSC.2024.3380607

Wireless Power Transfer (WPT) is a disruptive technology that allows wireless energy provisioning for energy- limited IoT devices, thus decreasing the over-reliance on batteries and wires. WPT could replace conventional energy provisioning (e.g., ene... Read More about Wireless Power Transfer Technologies, Applications, and Future Trends: A Review.

Towards Building a Smart Water Management System (SWAMS) in Nigeria (2024)
Presentation / Conference Contribution
Bamgboye, O., Chrysoulas, C., Liu, X., Watt, T., Sodiya, A., Oyeleye, M., & Kalutharage, S. (2024, June). Towards Building a Smart Water Management System (SWAMS) in Nigeria. Presented at The 22nd IEEE Mediterranean Electrotechnical Conference, Porto, Portugal

The water management landscape in Nigeria struggles with formidable obstacles characterized by a lack of adequate infrastructure, an uneven distribution of resources, and insufficient access to clean water, particularly in rural areas. These challeng... Read More about Towards Building a Smart Water Management System (SWAMS) in Nigeria.

A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection (2024)
Journal Article
Alshehri, M. S., Saidani, O., Alrayes, F. S., Abbasi, S. F., & Ahmad, J. (2024). A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection. IEEE Access, 12, 45762-45772. https://doi.org/10.1109/access.2024.3380816

The Industrial Internet of Things (IIoT) comprises a variety of systems, smart devices, and an extensive range of communication protocols. Hence, these systems face susceptibility to privacy and security challenges, making them prime targets for mali... Read More about A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection.

A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control (2024)
Presentation / Conference Contribution
Montague, K., Hart, E., & Paechter, B. (2024, April). A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. Presented at EvoStar 2024, Aberystwyth

Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an algorithmic perspective, an additional advantage is that extra modules can e... Read More about A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control.

Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records (2024)
Presentation / Conference Contribution
Noyon, M. S. I., Moradpoor, N., Maglaras, L., & Ahmad, J. (in press). Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records.

On the Utility of Probing Trajectories for Algorithm-Selection (2024)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2024, April). On the Utility of Probing Trajectories for Algorithm-Selection. Presented at EvoStar 2024, Aberystwyth, UK

Machine-learning approaches to algorithm-selection typically take data describing an instance as input. Input data can take the form of features derived from the instance description or fitness landscape , or can be a direct representation of the ins... Read More about On the Utility of Probing Trajectories for Algorithm-Selection.

Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario (2024)
Presentation / Conference Contribution
Adesanya, O. M., Moradpoor, N., Maglaras, L., Lim, I. S., & Ferrag, M. A. (in press). Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario.

DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments (2024)
Journal Article
Chen, B., Zhang, H., Zhang, F., Jiang, Y., Miao, Z., Yu, H., & Wang, Y. (online). DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2024.3379166

Aiming at the area search task of a multi-robot system in an unknown complex obstacle environment, we propose a cooperative area search algorithm based on a dual improved bio-inspired neural network (DIBNN). First, we improve the BNN model to reduce... Read More about DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments.

Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language (2024)
Presentation / Conference Contribution
Urquhart, N., & Hunter, K. (2024, April). Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language. Presented at 27th European Conference, EvoApplications 2024, Aberystwyth, UK

When using a meta-heuristic based optimiser in some industrial scenarios, there may be a need to amend the objective function as time progresses to encompass constraints that did not exist during the development phase of the software. We propose a me... Read More about Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language.