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All Outputs (45)

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.

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.

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.

Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks (2020)
Journal Article
Soltaninejad, M., Sturrock, C. J., Griffiths, M., Pridmore, T. P., & Pound, M. P. (2020). Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks. IEEE Transactions on Image Processing, 29, 6667-6679. https://doi.org/10.1109/TIP.2020.2992893

© 1992-2012 IEEE. We address the complex problem of reliably segmenting root structure from soil in X-ray Computed Tomography (CT) images. We utilise a deep learning approach, and propose a state-of-the-art multi-resolution architecture based on enco... Read More about Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks.

Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo (2020)
Journal Article
Rostam, H. M., Fisher, L. E., Hook, A. L., Burroughs, L., Luckett, J. C., Figueredo, G. P., …Ghaemmaghami, A. M. (2020). Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo. Matter, 2(6), 1564-1581. https://doi.org/10.1016/j.matt.2020.03.018

© 2020 The Author(s) Implantation of medical devices can result in inflammation. A large library of polymers is screened, and a selection found to promote macrophage differentiation towards pro- or anti-inflammatory phenotypes. The bioinstructive pro... Read More about Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo.

Multigranulation Super-Trust Model for Attribute Reduction (2020)
Journal Article
Ding, W., Pedrycz, W., Triguero, I., Cao, Z., & Lin, C. (2020). Multigranulation Super-Trust Model for Attribute Reduction. IEEE Transactions on Fuzzy Systems, 29(6), 1395-1408. https://doi.org/10.1109/tfuzz.2020.2975152

As big data often contains a significant amount of uncertain, unstructured, and imprecise data that are structurally complex and incomplete, traditional attribute reduction methods are less effective when applied to large-scale incomplete information... Read More about Multigranulation Super-Trust Model for Attribute Reduction.

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum] (2020)
Journal Article
Shukla, A. K., Kumar Bansal, S., Seth, T., Basu, A., John, R., & Muhuri, P. K. (2020). A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]. IEEE Computational Intelligence Magazine, 15(1), 89-98. https://doi.org/10.1109/MCI.2019.2954669

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situa... Read More about A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum].

A hybrid approach for stain normalisation in digital histopathological images (2019)
Journal Article
Bukenya, F. (2020). A hybrid approach for stain normalisation in digital histopathological images. Multimedia Tools and Applications, 79(3-4), 2339-2362. https://doi.org/10.1007/s11042-019-08262-0

Stain in-homogeneity adversely affects segmentation and quantifi-cation of tissues in histology images. Stain normalisation techniques have been used to standardise the appearance of images. However, most the available stain normalisation techniques... Read More about A hybrid approach for stain normalisation in digital histopathological images.

A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic (2019)
Journal Article
Venkatesan, S., Nguyen-Van-Tam, J., & Siebers, P. (2019). A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic. PLoS ONE, 14(10), https://doi.org/10.1371/journal.pone.0223946

© 2019 Venkatesan et al. The importance of accounting for social and behavioural processes when studying public health emergencies has been well-recognised. For infectious disease outbreaks in particular, several methods of incorporating individual b... Read More about A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic.

Probing IoT-based consumer services: 'insights' from the connected shower (2019)
Journal Article
Crabtree, A., Hyland, L., Colley, J., Flintham, M., Fischer, J. E., & Kwon, H. (2020). Probing IoT-based consumer services: 'insights' from the connected shower. Personal and Ubiquitous Computing, 24, 595–611. https://doi.org/10.1007/s00779-019-01303-3

This paper presents findings from the deployment of a technology probe-the connected shower-and implications for the development of 'living services' or autonomous context-aware consumer-oriented IoT services that exploit sensing to gain consumer 'in... Read More about Probing IoT-based consumer services: 'insights' from the connected shower.