Outputs (590)

AI-Driven Design of a Quasi-digitally-coded Wideband Microstrip Patch Antenna Array (2023)
Presentation / Conference Contribution
Akinsolu, M. O., Al-Yasir, Y. I. A., Hua, Q., See, C., & Liu, B. (2024, March). AI-Driven Design of a Quasi-digitally-coded Wideband Microstrip Patch Antenna Array. Presented at EuCAP 2024, Glasgow

Artificial intelligence (AI) is enabling the automated design of contemporary antennas for numerous applications. Specifically, the use of machine learning (ML)-assisted global optimization techniques for the efficient design of modern antennas is no... Read More about AI-Driven Design of a Quasi-digitally-coded Wideband Microstrip Patch Antenna Array.

Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks (2023)
Journal Article
Tmamna, J., Ayed, E. B., Fourati, R., Hussain, A., & Ayed, M. B. (2024). Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks. Expert Systems, 41(4), Article e13522. https://doi.org/10.1

Neural network quantization is a critical method for reducing memory usage and computational complexity in deep learning models, making them more suitable for deployment on resource-constrained devices. In this article, we propose a method called BBP... Read More about Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks.

Investigating Markers and Drivers of Gender Bias in Machine Translations (2023)
Presentation / Conference Contribution
Barclay, P., & Sami, A. (2024, March). Investigating Markers and Drivers of Gender Bias in Machine Translations. Presented at IEEE International Conference on Software Analysis, Evolution and Reengineering, Rovaniemi, Finland

Implicit gender bias in Large Language Models (LLMs) is a well-documented problem, and implications of gender introduced into automatic translations can perpetuate real-world biases. However, some LLMs use heuristics or post-processing to mask such b... Read More about Investigating Markers and Drivers of Gender Bias in Machine Translations.

Characteristic and Allowable Compressive Strengths of Dendrocalamus Sericeus Bamboo Culms with/without Node Using Artificial Neural Networks (2023)
Journal Article
Buachart, C., Hansapinyo, C., Sukontasukkul, P., Zhang, H., Sae-Long, W., Chetchotisak, P., & O'Brien, T. E. (2024). Characteristic and Allowable Compressive Strengths of Dendrocalamus Sericeus Bamboo Culms with/without Node Using Artificial Neural Networ

The strength of construction material is a crucial consideration in the process of structural design and construction. Conventional materials such as concrete or steel have been widely utilized due to their predictable material performance. However,... Read More about Characteristic and Allowable Compressive Strengths of Dendrocalamus Sericeus Bamboo Culms with/without Node Using Artificial Neural Networks.

Models to predict the radial variation of stiffness, strength, and density in planted noble fir, Norway spruce, western hemlock, and western red cedar in Great Britain (2023)
Journal Article
Gil-Moreno, D., MClean, J. P., & Ridley-Ellis, D. (2023). Models to predict the radial variation of stiffness, strength, and density in planted noble fir, Norway spruce, western hemlock, and western red cedar in Great Britain. Annals of Forest Science, 80

Key message: This study compares the measured radial variation in wood stiffness, strength, and density of noble fir, Norway spruce, western hemlock, and western red cedar by developing mixed-effects models for each property using age as the explanat... Read More about Models to predict the radial variation of stiffness, strength, and density in planted noble fir, Norway spruce, western hemlock, and western red cedar in Great Britain.

A hybrid dependency-based approach for Urdu sentiment analysis (2023)
Journal Article
Sehar, U., Kanwal, S., Allheeib, N. I., Almari, S., Khan, F., Dashtipur, K., …Khashan, O. A. (2023). A hybrid dependency-based approach for Urdu sentiment analysis. Scientific Reports, 13, Article 22075. https://doi.org/10.1038/s41598-023-48817-8

In the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse backgrounds, races, cultures, and age groups, spanning a wide range of top... Read More about A hybrid dependency-based approach for Urdu sentiment analysis.

A case study of fairness in generated images of Large Language Models for Software Engineering tasks (2023)
Presentation / Conference Contribution
Sami, M., Sami, A., & Barclay, P. (2023). A case study of fairness in generated images of Large Language Models for Software Engineering tasks. In 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME). https://doi.org/10.1109/i

Bias in Large Language Models (LLMs) has significant implications. Since they have revolutionized content creation on the web, they can lead to more unfair outcomes, lack of inclusivity, reinforcement of stereotypes and ethical and legal concerns. No... Read More about A case study of fairness in generated images of Large Language Models for Software Engineering tasks.

Translated transcription of a focus group with participative councillors, for information literacy research in Brazil (2023)
Data
Ryan, B., & Cruickshank, P. (2023). Translated transcription of a focus group with participative councillors, for information literacy research in Brazil. [Dataset]. https://doi.org/10.17869/enu.2023.3407211

This focus group took place on 24 January 2019, in São Paulo city hall. It was held in English and Portuguese with eight participative councillors, with in situ interpretation. The outcome of the research was a paper presenting an evaluation of the i... Read More about Translated transcription of a focus group with participative councillors, for information literacy research in Brazil.

Effective and Fast-Screening Route to Evaluate Dynamic Elastomer-Filler Network Reversibility for Sustainable Rubber Composite Design (2023)
Journal Article
Xia, T., Wemyss, A. M., Salehiyan, R., Heeley, E. L., Hu, X., Tang, F., …Wan, C. (2023). Effective and Fast-Screening Route to Evaluate Dynamic Elastomer-Filler Network Reversibility for Sustainable Rubber Composite Design. ACS sustainable chemistry & e

The introduction of self-healing and reprocessability into conventional vulcanized rubbers has been recognized as a promising strategy to promote elastomer circularity. However, the reversibility and recovery of cross-linking polymer networks have of... Read More about Effective and Fast-Screening Route to Evaluate Dynamic Elastomer-Filler Network Reversibility for Sustainable Rubber Composite Design.

Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces (2023)
Journal Article
Li, W., Buchanan, E., Goff, L. K. L., Hart, E., Hale, M. F., Wei, B., Carlo, M. D., Angus, M., Woolley, R., Gan, Z., Winfield, A. F., Timmis, J., Eiben, A. E., & Tyrrell, A. M. (online). Evaluation of Frameworks That Combine Evolution and Learning to Desi

Jointly optimising both the body and brain of a robot is known to be a challenging task, especially when attempting to evolve designs in simulation that will subsequently be built in the real world. To address this, it is increasingly common to combi... Read More about Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces.