Outputs (609)

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.-G., 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.

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.

Wireless Power Transfer Technologies, Applications, and Future Trends: A Review (2024)
Journal Article
Alabsi, A., Hawbani, A., Wang, X., Al-Dubai, A., Hu, J., Aziz, S. A., Kumar, S., Zhao, L., Shvetsov, A. V., & Alsamhi, S. H. (2025). Wireless Power Transfer Technologies, Applications, and Future Trends: A Review. IEEE Transactions on Sustainable Computing, 10(1), 1-17. 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.

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. (2025). DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments. IEEE Transactions on Automation Science and Engineering, 22, 2361 - 2374. 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.

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.

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.

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.

Digital- Twin Enabled Dairy Farming for Greenhouse Gas Emission Tracking (2024)
Presentation / Conference Contribution
Ak, E., Huseynov, K., Canberk, B., Fahim, M., Dobre, O. A., & Duong, T. Q. (2023, December). Digital- Twin Enabled Dairy Farming for Greenhouse Gas Emission Tracking. Presented at 2023 31st Irish Conference on Artificial Intelligence and Cognitive Science (AICS), Letterkenny, Ireland

The dairy farming industry plays a pivotal role in the agricultural sector. However, its environmental footprint, especially methane and nitrous oxide emissions, has raised concerns. Historically, the industry has relied on conventional methods to fo... Read More about Digital- Twin Enabled Dairy Farming for Greenhouse Gas Emission Tracking.

Generalized Early Stopping in Evolutionary Direct Policy Search (2024)
Journal Article
Arza, E., Le Goff, L. K., & Hart, E. (2024). Generalized Early Stopping in Evolutionary Direct Policy Search. ACM Transactions on Evolutionary Learning and Optimization, 4(3), Article 14. https://doi.org/10.1145/3653024

Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g. in robotics applications. Often when evaluating solution over a fixe... Read More about Generalized Early Stopping in Evolutionary Direct Policy Search.