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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.

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.

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.

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.

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.

Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples (2024)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2024, July). Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples. Presented at GECCO 2024, Melbourne, USA

The choice of input-data used to train algorithm-selection models is recognised as being a critical part of the model success. Recently, feature-free methods for algorithm-selection that use short trajec-tories obtained from running a solver as input... Read More about Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples.

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.

Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation Expensive Bi-Objective (2024)
Presentation / Conference Contribution
Rodriguez, C. J., Thomson, S. L., Alderliesten, T., & Bosman, P. A. N. (2024, July). Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation Expensive Bi-Objective. Presented at Genetic and Evolutionary Computation Conference (GECCO 2024), Melbourne, Australia

Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes... Read More about Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation Expensive Bi-Objective.

Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution (2024)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2024, July). Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. Presented at ACM GECCO 2024, Melbourne, Australia

The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train machine-learning models for algorithm selection. Quality-Diversity (QD) algorit... Read More about Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution.

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.

PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme (2024)
Presentation / Conference Contribution
Yaqub, Z., Yigit, Y., Maglaras, L., Tan, Z., & Wooderson, P. (2024, April). PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme. Presented at The 20th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2024), Abu Dhabi, UAE

In the rapidly evolving landscape of Intelligent Transportation Systems (ITS), Vehicular Ad-hoc Networks (VANETs) play a critical role in enhancing road safety and traffic flow. However, VANETs face significant security and privacy challenges due to... Read More about PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme.

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.

Wide-Scan/High-Gain Phased Array Antenna for 5G/6G Cellular Networks (2024)
Presentation / Conference Contribution
Basherlou, H. J., Ojaroudi Parchin, N., Alibakhshikenari, M., Kouhalvandi, L., & See, C. H. (2024, June). Wide-Scan/High-Gain Phased Array Antenna for 5G/6G Cellular Networks. Presented at 2024 IEEE 22nd Mediterranean Electrotechnical Conference- IEEE MELECON 2024, Porto, Portugal

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.