All Outputs (121)

Creating a Digital Mirror of Creative Practice (2021)
Presentation / Conference Contribution
Johnson, C. (2021, April). Creating a Digital Mirror of Creative Practice. Presented at 10th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2021), Online

This paper describes an ongoing project to create a “digital mirror” to my practice as a composer of contemporary classical music; that is, a system that takes descriptions (in code) of aspects of that practice, and reflects them back as computer-gen... Read More about Creating a Digital Mirror of Creative Practice.

Adaptive Covariance Pattern Search (2021)
Book Chapter
Neri, F. (2021). Adaptive Covariance Pattern Search. In P. A. Castillo, & J. L. Jiménez Laredo (Eds.), Applications of Evolutionary Computation – 24th International Conference, EvoApplications 2021 (178-193). Springer. https://doi.org/10.1007/978-3-030-72699-7_12

Pattern search is a family of single solution deterministic optimisation algorithms for numerical optimisation. Pattern search algorithms generate a new candidate solution by means of an archive of potential moves, named pattern. This pattern is gen... Read More about Adaptive Covariance Pattern Search.

Generalised Pattern Search Based on Covariance Matrix Diagonalisation (2021)
Journal Article
Neri, F., & Rostami, S. (2021). Generalised Pattern Search Based on Covariance Matrix Diagonalisation. SN Computer Science, 2, Article 171. https://doi.org/10.1007/s42979-021-00513-y

Pattern Search is a family of gradient-free direct search methods for numerical optimisation problems. The characterising feature of pattern search methods is the use of multiple directions spanning the problem domain to sample new candidate solution... Read More about Generalised Pattern Search Based on Covariance Matrix Diagonalisation.

Constructing a universe for the setoid model (2021)
Presentation / Conference Contribution
Altenkirch, T., Boulier, S., Kaposi, A., Sattler, C., & Sestini, F. (2021, March). Constructing a universe for the setoid model. Presented at 24th International Conference on Foundations of Software Science and Computation Structures (FOSSACS 2021), Online

The setoid model is a model of intensional type theory that validates certain extensionality principles, like function extensionality and propositional extensionality, the latter being a limited form of univalence that equates logically equivalent pr... Read More about Constructing a universe for the setoid model.

Text Data Augmentations: Permutation, Antonyms and Negation (2021)
Journal Article
Haralabopoulos, G., Torres, M. T., Anagnostopoulos, I., & McAuley, D. (2021). Text Data Augmentations: Permutation, Antonyms and Negation. Expert Systems with Applications, 177, Article 114769. https://doi.org/10.1016/j.eswa.2021.114769

Text has traditionally been used to train automated classifiers for a multitude of purposes, such as: classification, topic modelling and sentiment analysis. State-of-the-art LSTM classifier require a large number of training examples to avoid biases... Read More about Text Data Augmentations: Permutation, Antonyms and Negation.

Teaching Mathematics to Computer Scientists: Reflections and a Case Study (2021)
Journal Article
Neri, F. (2021). Teaching Mathematics to Computer Scientists: Reflections and a Case Study. SN Computer Science, 2(2), Article 75. https://doi.org/10.1007/s42979-021-00461-7

Mathematics, despite being the foundation of computer science, is nowadays often considered a totally separate subject. The fact that many jobs in computer science do not explicitly require any specific mathematical knowledge posed questions about th... Read More about Teaching Mathematics to Computer Scientists: Reflections and a Case Study.

Exploring touch-based behavioral authentication on smartphone email applications in IoT-enabled smart cities (2021)
Journal Article
Li, W., Meng, W., & Furnell, S. (2021). Exploring touch-based behavioral authentication on smartphone email applications in IoT-enabled smart cities. Pattern Recognition Letters, 144, 35-41. https://doi.org/10.1016/j.patrec.2021.01.019

© 2021 Elsevier B.V. The Internet of Things (IoT) allows various embedded devices and smart sensors to be connected with each other, which provides a basis for building smart cities. The IoT-enabled smart city can greatly benefit people's daily lives... Read More about Exploring touch-based behavioral authentication on smartphone email applications in IoT-enabled smart cities.

The impact of algorithmic decision-making processes on young people’s well-being (2021)
Journal Article
Perez Vallejos, E., Dowthwaite, L., Creswick, H., Portillo, V., Koene, A., Jirotka, M., McCarthy, A., & McAuley, D. (2021). The impact of algorithmic decision-making processes on young people’s well-being. Health Informatics Journal, 27(1), 1-21. https://doi.org/10.1177/1460458220972750

This study aims to capture the online experiences of young people when interacting with algorithm mediated systems and their impact on their well-being. We draw on qualitative (focus groups) and quantitative (survey) data from a total of 260 young pe... Read More about The impact of algorithmic decision-making processes on young people’s well-being.

A framework for differentiation in composed digital-physical products (2020)
Journal Article
Baumers, M., Ashcroft, I., Benford, S., Flintham, M., Koleva, B., Tóth, Z., & Winklhofer, H. (2020). A framework for differentiation in composed digital-physical products. International Journal of Mechatronics and Manufacturing Systems, 13(4), 286-298. https://doi.org/10.1504/IJMMS.2020.112351

Product-service systems (PSS) composed of physical products and digital services are emerging as an important new product category. In this paper we suggest that the established metaphor of 'layering' is insufficient to capture the diverse ways in wh... Read More about A framework for differentiation in composed digital-physical products.

Pulling Back the Curtain on the Wizards of Oz (2020)
Journal Article
Porcheron, M., Fischer, J. E., & Reeves, S. (2020). Pulling Back the Curtain on the Wizards of Oz. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), Article 243. https://doi.org/10.1145/3432942

The Wizard of Oz method is an increasingly common practice in HCI and CSCW studies as part of iterative design processes for interactive systems. Instead of designing a fully-fledged system, the 'technical work' of key system components is completed... Read More about Pulling Back the Curtain on the Wizards of Oz.

Posture, movement, and aircraft passengers: An investigation into factors influencing in-flight discomfort (2020)
Journal Article
Sharafkhani, M., Argyle, E., Cobb, S., & Tennent, P. (2021). Posture, movement, and aircraft passengers: An investigation into factors influencing in-flight discomfort. WORK: A Journal of Prevention, Assessment & Rehabilitation, 68(s1), S183-S195. https://doi.org/10.3233/wor-208016

BACKGROUND: Aircraft passengers’ physical activity levels are often limited during flight for extended periods of time, which can have serious impact on health, comfort, and passenger experience. However, several factors, such as limited personal spa... Read More about Posture, movement, and aircraft passengers: An investigation into factors influencing in-flight discomfort.

Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis (2020)
Journal Article
Chernbumroong, S., Johnson, J., Gupta, N., Miller, S., Mccormack, F. X., Garibaldi, J. M., & Johnson, S. R. (2021). Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis. European Respiratory Journal, 57(6), Article 2003036. https://doi.org/10.1183/13993003.03036-2020

Background: Lymphangioleiomyomatosis (LAM) is a rare multisystem disease with variable clinical manifestations and differing rates of progression that make management decisions and giving prognostic advice difficult. We used machine learning to ident... Read More about Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.

Software Fault Localisation via Probabilistic Modelling (2020)
Presentation / Conference Contribution
Johnson, C. (2020, December). Software Fault Localisation via Probabilistic Modelling. Presented at 40th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI 2020), Online

Software development is a complex activity requiring intelligent action. This paper explores the use of an AI technique for one step in software development, viz. detecting the location of a fault in a program. A measure of program progress is propos... Read More about Software Fault Localisation via Probabilistic Modelling.

Further Exploration of Necrotic Control of Evolved Art (2020)
Presentation / Conference Contribution
Ashlock, D., & Greensmith, J. (2020, December). Further Exploration of Necrotic Control of Evolved Art. Presented at 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, ACT, Australia

This study is the second in investigating the use of necrosis based filtration as a method of steering evolutionary algorithms to create evolved art. We use a technique inspired by the danger theory of immune system activation - a method employed in... Read More about Further Exploration of Necrotic Control of Evolved Art.

Contesting control: journeys through surrender, self-awareness and looseness of control in embodied interaction (2020)
Journal Article
Benford, S., Ramchurn, R., Marshall, J., Wilson, M. L., Pike, M., Martindale, S., Hazzard, A., Greenhalgh, C., Kallionpää, M., Tennent, P., & Walker, B. (2021). Contesting control: journeys through surrender, self-awareness and looseness of control in embodied interaction. Human-Computer Interaction, 36(5-6), 361-389. https://doi.org/10.1080/07370024.2020.1754214

As Human-Computer Interaction (HCI) engages with technologies that sense and actuate the body, there is a need to reconsider the human bodily experience. We present three case studies that each involve different forms of bodily experience: a breath-c... Read More about Contesting control: journeys through surrender, self-awareness and looseness of control in embodied interaction.

Big Step Normalisation for Type Theory (2020)
Presentation / Conference Contribution
Altenkirch, T., & Geniet, C. Big Step Normalisation for Type Theory. Presented at 25th International Conference on Types for Proofs and Programs (TYPES 2019), Oslo, Norway

Big step normalisation is a normalisation method for typed lambda-calculi which relies on a purely syntactic recursive evaluator. Termination of that evaluator is proven using a predicate called strong computability, similar to the techniques used to... Read More about Big Step Normalisation for Type Theory.

An Adaptive Optimization Spiking Neural P System for Binary Problems (2020)
Journal Article
Zhu, M., Yang, Q., Dong, J., Zhang, G., Gou, X., Rong, H., Paul, P., & Neri, F. (2021). An Adaptive Optimization Spiking Neural P System for Binary Problems. International Journal of Neural Systems, 31(1), Article 2050054. https://doi.org/10.1142/S0129065720500549

© 2020 World Scientific Publishing Company. Optimization Spiking Neural P System (OSNPS) is the first membrane computing model to directly derive an approximate solution of combinatorial problems with a specific reference to the 0/1 knapsack problem.... Read More about An Adaptive Optimization Spiking Neural P System for Binary Problems.

Decomposition-Fusion for Label Distribution Learning (2020)
Journal Article
González, M., González-Almagro, G., Triguero, I., Cano, J.-R., & García, S. (2021). Decomposition-Fusion for Label Distribution Learning. Information Fusion, 66, 64-75. https://doi.org/10.1016/j.inffus.2020.08.024

Label Distribution Learning (LDL) is a general learning framework that assigns an instance to a distribution over a set of labels rather than to a single label or multiple labels. Current LDL methods have proven their effectiveness in many real-life... Read More about Decomposition-Fusion for Label Distribution Learning.

Designing Hybrid Gifts (2020)
Journal Article
Koleva, B., Spence, J., Benford, S., Kwon, H., Schnädelbach, H., Thorn, E., Preston, W., Hazzard, A., Greenhalgh, C., Adams, M., Row Farr, J., Tandavanitj, N., Angus, A., & Lane, G. (2020). Designing Hybrid Gifts. ACM Transactions on Computer-Human Interaction, 27(5), 1–33. https://doi.org/10.1145/3398193

Hybrid gifting combines physical artefacts and experiences with digital interactivity to generate new kinds of gifts. Our review details how gifting is a complex social phenomenon and how digital gifting is less engaging than physical gifting for bot... Read More about Designing Hybrid Gifts.

Response to Call for Evidence – Joint Select Committee on Human Rights: The Government’s response to COVID-19: human rights implications (2020)
Other
McAuley, D., Koene, A., & Chen, J. (2020). Response to Call for Evidence – Joint Select Committee on Human Rights: The Government’s response to COVID-19: human rights implications

This submission addresses the three questions formulated in the Joint Select Committee’s call with a particular focus on both the digital rights implications of the Government’s measures against COVID-19 and the wider human rights implications of the... Read More about Response to Call for Evidence – Joint Select Committee on Human Rights: The Government’s response to COVID-19: human rights implications.