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Outputs (88)

On difunctions (2023)
Journal Article
Backhouse, R., & Oliveira, J. N. (2023). On difunctions. Journal of Logical and Algebraic Methods in Programming, 134, Article 100878. https://doi.org/10.1016/j.jlamp.2023.100878

The notion of a difunction was introduced by Jacques Riguet in 1948. Since then it has played a prominent role in database theory, type theory, program specification and process theory. The theory of difunctions is, however, less known in computing t... Read More about On difunctions.

Components and acyclicity of graphs. An exercise in combining precision with concision (2021)
Journal Article
Backhouse, R., Doornbos, H., Glück, R., & van der Woude, J. (2022). Components and acyclicity of graphs. An exercise in combining precision with concision. Journal of Logical and Algebraic Methods in Programming, 124, Article 100730. https://doi.org/10.1016/j.jlamp.2021.100730

Central to algorithmic graph theory are the concepts of acyclicity and strongly connected components of a graph, and the related search algorithms. This article is about combining mathematical precision and concision in the presentation of these conc... Read More about Components and acyclicity of graphs. An exercise in combining precision with concision.

Public health messaging by political leaders: a corpus linguistic analysis of COVID-19 speeches delivered by Boris Johnson (2021)
Report
McClaughlin, E., Nichele, E., Adolphs, S., Barnard, P., Clos, J., Knight, D., …Lang, A. (2021). Public health messaging by political leaders: a corpus linguistic analysis of COVID-19 speeches delivered by Boris Johnson. Nottingham: UKRI/AHRC

This study analyses the language of speeches about COVID-19 delivered by Boris Johnson, the Prime Minister of the United Kingdom between 3rd March 2020 and 5th April 2021. We use transcribed speeches to construct a digitised body of texts called a... Read More about Public health messaging by political leaders: a corpus linguistic analysis of COVID-19 speeches delivered by Boris Johnson.

Defence against the dark artefacts: Smart home cybercrimes and cybersecurity standards (2021)
Journal Article
Piasecki, S., Urquhart, L., & McAuley, D. (2021). Defence against the dark artefacts: Smart home cybercrimes and cybersecurity standards. Computer Law and Security Review, 42, Article 105542. https://doi.org/10.1016/j.clsr.2021.105542

This paper analyses the assumptions underpinning a range of emerging EU and UK smart home cybersecurity standards. We use internet of things (IoT) case studies (such as the Mirai Botnet affair) and the criminological concept of 'routine activity theo... Read More about Defence against the dark artefacts: Smart home cybercrimes and cybersecurity standards.

A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms (2021)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2021). A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms. Machine Vision and Applications, 32(3), Article 75. https://doi.org/10.1007/s00138-021-01196-4

Over recent years, many approaches have been proposed for the denoising or semantic segmentation of X-ray computed tomography (CT) scans. In most cases, high-quality CT reconstructions are used; however, such reconstructions are not always available.... Read More about A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms.

Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning (2021)
Journal Article
Maciel-Guerra, A., Esener, N., Giebel, K., Lea, D., Green, M. J., Bradley, A. J., & Dottorini, T. (2021). Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning. Scientific Reports, 11(1), Article 7736. https://doi.org/10.1038/s41598-021-87300-0

Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate th... Read More about Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

Solving the Rubik’s Cube with Stepwise Deep Learning (2021)
Journal Article
JOHNSON, C. (2021). Solving the Rubik’s Cube with Stepwise Deep Learning. Expert Systems, Article e12665. https://doi.org/10.1111/exsy.12665

This paper explores a novel technique for learning the fitness function for search algorithms such as evolutionary strategies and hillclimbing. The aim of the new technique is to learn a fitness function (called a Learned Guidance Function) from a se... Read More about Solving the Rubik’s Cube with Stepwise Deep Learning.

Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning (2020)
Journal Article
Khan, F. A., Voß, U., Pound, M. P., & French, A. P. (2020). Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning. Frontiers in Plant Science, 11, Article 1275. https://doi.org/10.3389/fpls.2020.01275

© Copyright © 2020 Khan, Voß, Pound and French. Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasing... Read More about Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning.

Choosing Sample Sizes for Statistical Measures on Interval-Valued Data (2020)
Conference Proceeding
McCulloch, J., Ellerby, Z., & Wagner, C. (2020). Choosing Sample Sizes for Statistical Measures on Interval-Valued Data. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/FUZZ48607.2020.9177745

Intervals have frequently been used in the literature to represent uncertainty in data, from eliciting uncertain judgements from experts to representing uncertainty in sensor measurements. This widespread use of intervals has led to research on inter... Read More about Choosing Sample Sizes for Statistical Measures on Interval-Valued Data.

An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities (2020)
Journal Article
Standen, P., Brown, D. J., Taheri, M., Galvez Trigo, M. J., Boulton, H., Burton, A., …Hortal, E. (2020). An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities. British Journal of Educational Technology, 51(5), 1748-1765. https://doi.org/10.1111/bjet.13010

Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a... Read More about An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities.