Skip to main content

Research Repository

Advanced Search

All Outputs (456)

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 Cont

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.

International consensus is needed on a core outcome set to advance the evidence of best practice in cancer prehabilitation services and research (2024)
Journal Article
Myers, A. M., Barlow, R. C., Baldini, G., Campbell, A. M., Carli, F., Carr, E. J., Collyer, T., Danjoux, G., Davis, J. F., Denehy, L., Durrand, J., Gillis, C., Greenfield, D. M., Griffiths, S. P., Grocott, M., Humphreys, L., Jack, S., Keen, C., Levett, D.

Prehabilitation aims to optimise patients’ physical and psychological status before treatment. The types of outcomes measured to assess the impact of prehabilitation interventions vary across clinical research and service evaluation, limiting the abi... Read More about International consensus is needed on a core outcome set to advance the evidence of best practice in cancer prehabilitation services and research.

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.

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, Por

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.

Correction: Elsherbeny et al. 2-(3-Bromophenyl)-8-fluoroquinazoline-4-carboxylic Acid as a Novel and Selective Aurora A Kinase Inhibitory Lead with Apoptosis Properties: Design, Synthesis, In Vitro and In Silico Biological Evaluation. Life 2022, 12, 876 (2024)
Journal Article
Elsherbeny, M. H., Ammar, U. M., Abdellattif, M. H., Abourehab, M. A. S., Abdeen, A., Ibrahim, S. F., …Elkamhawy, A. (2024). Correction: Elsherbeny et al. 2-(3-Bromophenyl)-8-fluoroquinazoline-4-carboxylic Acid as a Novel and Selective Aurora A Kinase I

In the original publication [1], reference number 26 [2] was added by mistake. Thus, it was removed. With this correction, the order of some references has been adjusted accordingly. The authors state that the scientific conclusions are unaffected... Read More about Correction: Elsherbeny et al. 2-(3-Bromophenyl)-8-fluoroquinazoline-4-carboxylic Acid as a Novel and Selective Aurora A Kinase Inhibitory Lead with Apoptosis Properties: Design, Synthesis, In Vitro and In Silico Biological Evaluation. Life 2022, 12, 876.

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.

Abstract 4472: Discovery of potential RAF-selective back pocket as a promising biological target for BRAF inhibitors in the treatment of resistant melanoma: Design, synthesis, biological evaluation and in silico studies (2024)
Presentation / Conference Contribution
Ammar, U., Gamal, M., Abdel-Maksoud, M., Ali, E., Mahmoud, Z., Deug, K., …Oh, C. (2024). Abstract 4472: Discovery of potential RAF-selective back pocket as a promising biological target for BRAF inhibitors in the treatment of resistant melanoma: Design,

The mutated BRAF kinase (V600E) is considered the key component in the MAPK signaling pathway that was reported to be significantly contributed to melanoma disease. Vemurafenib and dabrafenib are examples of drugs that were approved by FDA to treat m... Read More about Abstract 4472: Discovery of potential RAF-selective back pocket as a promising biological target for BRAF inhibitors in the treatment of resistant melanoma: Design, synthesis, biological evaluation and in silico studies.

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., …Alsamhi, S. H. (in press). Wireless Power Transfer Technologies, Applications, and Future Trends: A Review. IEEE Transactions on Sustainable Computing, https://doi.org/10.1109/TSUSC.

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.

A review of seagrass cover, status and trends in Africa (2024)
Journal Article
Mwikamba, E., Githaiga, M., Briers, R. A., & Huxham, M. (2024). A review of seagrass cover, status and trends in Africa. Estuaries and Coasts, 47(4), 917–934. https://doi.org/10.1007/s12237-024-01348-5

The recognition of the benefits that seagrasses contribute has enhanced the research interest in these marine ecosystems. Seagrasses provide critical goods and services and support the livelihoods of millions of people. Despite this, they are declini... Read More about A review of seagrass cover, status and trends in Africa.

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.

Understanding fitness landscapes in morpho-evolution via local optima networks (2024)
Presentation / Conference Contribution
Thomson, S. L., Le Goff, L., Hart, E., & Buchanan, E. (2024, July). Understanding fitness landscapes in morpho-evolution via local optima networks. Presented at Genetic and Evolutionary Computation Conference (GECCO 2024), Melbourne, Australia

Morpho-Evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and control. Pre... Read More about Understanding fitness landscapes in morpho-evolution via local optima networks.

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 C

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.

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 Interne

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.

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 MEL

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. (in press). DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments. IEEE Transactions on Automation Science and Engineerin

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.