All Outputs (1968)

A European Agency for Artificial Intelligence: Protecting fundamental rights and ethical values (2022)
Journal Article
Stahl, B. C., Rodrigues, R., Santiago, N., & Macnish, K. (2022). A European Agency for Artificial Intelligence: Protecting fundamental rights and ethical values. Computer Law and Security Review, 45, Article 105661. https://doi.org/10.1016/j.clsr.2022.105661

Following years of intensive international debate of the ethical and human rights implications of artificial intelligence (AI)-related technologies, there are numerous proposals to legislate and regulate these technologies. One aspect of possible leg... Read More about A European Agency for Artificial Intelligence: Protecting fundamental rights and ethical values.

Learning from Carers to inform the Design of Safe Physically Assistive Robots - Insights from a Focus Group Study (2022)
Conference Proceeding
Camilleri, A., Dogramadzi, S., & Caleb-Solly, P. (2022). Learning from Carers to inform the Design of Safe Physically Assistive Robots - Insights from a Focus Group Study. In 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2022) (703-707). https://doi.org/10.1109/hri53351.2022.9889658

This research investigates how professional carers physically assist frail older adults. Carers were asked to discuss their approach and steps for providing safe physical assistance and highlight hazards that assistive robots would have to deal with... Read More about Learning from Carers to inform the Design of Safe Physically Assistive Robots - Insights from a Focus Group Study.

A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica (2022)
Journal Article
Calderon-Ramirez, S., Murillo-Hernandez, D., Rojas-Salazar, K., Elizondo, D., Yang, S., Moemeni, A., & Molina-Cabello, M. (2022). A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica. Medical and Biological Engineering and Computing, 60(4), 1159-1175. https://doi.org/10.1007/s11517-021-02497-6

The implementation of deep learning-based computer-aided diagnosis systems for the classification of mammogram images can help in improving the accuracy, reliability, and cost of diagnosing patients. However, training a deep learning model requires a... Read More about A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica.

Using Patient and Public Involvement to Elicit Opinion on Cognitive Training Games and Assessment Technologies for Dementia (2022)
Working Paper
Harrington, K., Craven, M. P., Wilson, M. L., & Landowska, A. Using Patient and Public Involvement to Elicit Opinion on Cognitive Training Games and Assessment Technologies for Dementia

Background: Cognitive training and assessment technologies offer the promise of dementia risk reduction and more timely diagnosis of dementia respectively. Cognitive training technologies may help to reduce the lifetime risk of dementia by helping... Read More about Using Patient and Public Involvement to Elicit Opinion on Cognitive Training Games and Assessment Technologies for Dementia.

Data-inspired co-design for museum and gallery visitor experiences (2022)
Journal Article
Darzentas, D., Cameron, H., Wagner, H., Craigon, P., Bodiaj, E., Spence, J., …Benford, S. (2022). Data-inspired co-design for museum and gallery visitor experiences. AI EDAM, 36, Article e3. https://doi.org/10.1017/S0890060421000317

The capture and analysis of diverse data is widely recognized as being vital to the design of new products and services across the digital economy. We focus on its use to inspire the co-design of visitor experiences in museums as a distinctive case t... Read More about Data-inspired co-design for museum and gallery visitor experiences.

Brain simulation as a cloud service: The Virtual Brain on EBRAINS (2022)
Journal Article
Schirner, M., Domide, L., Perdikis, D., Triebkorn, P., Stefanovski, L., Pai, R., …Ritter, P. (2022). Brain simulation as a cloud service: The Virtual Brain on EBRAINS. NeuroImage, 251, Article 118973. https://doi.org/10.1016/j.neuroimage.2022.118973

The Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS (ebrains.eu). It offers software for constructing, simulating and analysing brain network models including the TVB simulator; magnetic resonance i... Read More about Brain simulation as a cloud service: The Virtual Brain on EBRAINS.

Complying with the GDPR when vulnerable people use smart devices (2022)
Journal Article
Piasecki, S., & Chen, J. (2022). Complying with the GDPR when vulnerable people use smart devices. International Data Privacy Law, 12(2), 113-131. https://doi.org/10.1093/idpl/ipac001

The number of smart home devices is increasing. They are used by vulnerable people regardless of whether they are designed specifically for them or for the general population (eg, smart door locks, smart alarms, or voice assistants). This article foc... Read More about Complying with the GDPR when vulnerable people use smart devices.

Examining the influential factors of consumer purchase intentions for blockchain traceable coffee using the theory of planned behaviour (2022)
Journal Article
Dionysis, S., Chesney, T., & McAuley, D. (2022). Examining the influential factors of consumer purchase intentions for blockchain traceable coffee using the theory of planned behaviour. British Food Journal, 124(12), 4304-4322. https://doi.org/10.1108/BFJ-05-2021-0541

Purpose: Given the increasing industry interest in blockchain technologies for supply chain management and product traceability, this paper aims to investigate consumer purchasing intentions for blockchain traceable coffee and their psychosocial ante... Read More about Examining the influential factors of consumer purchase intentions for blockchain traceable coffee using the theory of planned behaviour.

Improving simulated consumption context with virtual Reality: A focus on participant experience (2022)
Journal Article
Yang, Q., Nijman, M., Flintham, M., Tennent, P., Hidrio, C., & Ford, R. (2022). Improving simulated consumption context with virtual Reality: A focus on participant experience. Food Quality and Preference, 98, Article 104531. https://doi.org/10.1016/j.foodqual.2022.104531

Context can have a significant impact on liking, emotional response and product choice, and Virtual Reality (VR) is a promising tool to evoke realistic consumption contexts in a controlled testing environment. This study compared an innovative approa... Read More about Improving simulated consumption context with virtual Reality: A focus on participant experience.

Crossing with care: bogs, streams and assistive mobilities as family praxis in the countryside (2021)
Journal Article
Laurier, E., Dunkley, R., Smith, T. A., & Reeves, S. (2021). Crossing with care: bogs, streams and assistive mobilities as family praxis in the countryside. Gesprächsforschung, 22, 544-568

In this paper, we use ethnomethodology, membership categorisation analysis, and conversation analysis (EMCA) to investigate traversing obstacles in outdoor environments as reflexively constitutive of producing, resisting and adjusting family relation... Read More about Crossing with care: bogs, streams and assistive mobilities as family praxis in the countryside.

A self-adaptive multi-objective feature selection approach for classification problems (2021)
Journal Article
Xue, Y., Zhu, H., & Neri, F. (2022). A self-adaptive multi-objective feature selection approach for classification problems. Integrated Computer-Aided Engineering, 29(1), 3-21. https://doi.org/10.3233/ICA-210664

In classification tasks, feature selection (FS) can reduce the data dimensionality and may also improve classification accuracy, both of which are commonly treated as the two objectives in FS problems. Many meta-heuristic algorithms have been applied... Read More about A self-adaptive multi-objective feature selection approach for classification problems.

Constraint reformulations for set point optimization problems using fuzzy cognitive map models (2021)
Journal Article
Garzón Casado, A., Cano Marchal, P., Wagner, C., Gómez Ortega, J., & Gámez García, J. (2022). Constraint reformulations for set point optimization problems using fuzzy cognitive map models. Optimal Control Applications and Methods, 43(3), 711-721. https://doi.org/10.1002/oca.2846

The selection of optimal set points is an important problem in modern process control. Fuzzy cognitive maps (FCMs) allow to construct models of complex processes using expert knowledge, which is particularly useful in situations where measuring the v... Read More about Constraint reformulations for set point optimization problems using fuzzy cognitive map models.

Generalised Pattern Search with Restarting Fitness Landscape Analysis (2021)
Journal Article
Neri, F. (2022). Generalised Pattern Search with Restarting Fitness Landscape Analysis. SN Computer Science, 3(2), Article 110. https://doi.org/10.1007/s42979-021-00989-8

Fitness landscape analysis for optimisation is a technique that involves analysing black-box optimisation problems to extract pieces of information about the problem, which can beneficially inform the design of the optimiser. Thus, the design of the... Read More about Generalised Pattern Search with Restarting Fitness Landscape Analysis.

A fusion spatial attention approach for few-shot learning (2021)
Journal Article
Song, H., Deng, B., Pound, M., Özcan, E., & Triguero, I. (2022). A fusion spatial attention approach for few-shot learning. Information Fusion, 81, 187-202. https://doi.org/10.1016/j.inffus.2021.11.019

Few-shot learning is a challenging problem in computer vision that aims to learn a new visual concept from very limited data. A core issue is that there is a large amount of uncertainty introduced by the small training set. For example, the few image... Read More about A fusion spatial attention approach for few-shot learning.

International data governance for neuroscience (2021)
Journal Article
Eke, D. O., Bernard, A., Bjaalie, J. G., Chavarriaga, R., Hanakawa, T., Hannan, A. J., …Pestilli, F. (2022). International data governance for neuroscience. Neuron, 110(4), 600-612. https://doi.org/10.1016/j.neuron.2021.11.017

As neuroscience projects increase in scale and cross international borders, different ethical principles, national and international laws, regulations, and policies for data sharing must be considered. These concerns are part of what is collectively... Read More about International data governance for neuroscience.

Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester (2021)
Journal Article
Akintoye, S., Ogoh, G., Krokida, Z., Nnadi, J., & Eke, D. (2021). Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester. Journal of Information, Communication and Ethics in Society, 19(4), 521-536. https://doi.org/10.1108/jices-06-2021-0071

Purpose Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpo... Read More about Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester.

The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review (2021)
Journal Article
Majid, S., Reeves, S., Figueredo, G., Brown, S., Lang, A., Moore, M., & Morriss, R. (2021). The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review. JMIR Mental Health, 8(12), Article e27991. https://doi.org/10.2196/27991

Background: The number of self-monitoring apps for bipolar disorder (BD) is increasing. The involvement of users in human-computer interaction (HCI) research has a long history and is becoming a core concern for designers working in this space. The a... Read More about The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review.

Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis (2021)
Journal Article
Laparidou, D., Curtis, F., Akanuwe, J., Goher, K., Niroshan Siriwardena, A., & Kucukyilmaz, A. (2021). Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis. Journal of NeuroEngineering and Rehabilitation, 18(1), Article 181. https://doi.org/10.1186/s12984-021-00976-3

Background: In recent years, robotic rehabilitation devices have often been used for motor training. However, to date, no systematic reviews of qualitative studies exploring the end-user experiences of robotic devices in motor rehabilitation have bee... Read More about Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis.

EHR STAR: The State-Of-the-Art in Interactive EHR Visualization (2021)
Journal Article
Wang, Q., & Laramee, R. S. (2022). EHR STAR: The State-Of-the-Art in Interactive EHR Visualization. Computer Graphics Forum, 41(1), 69-105. https://doi.org/10.1111/cgf.14424

Since the inception of electronic health records (EHR) and population health records (PopHR), the volume of archived digital health records is growing rapidly. Large volumes of heterogeneous health records require advanced visualization and visual an... Read More about EHR STAR: The State-Of-the-Art in Interactive EHR Visualization.

Domain Adaptation of Synthetic Images for Wheat Head Detection (2021)
Journal Article
Hartley, Z. K., & French, A. P. (2021). Domain Adaptation of Synthetic Images for Wheat Head Detection. Plants, 10(12), Article 2633. https://doi.org/10.3390/plants10122633

Wheat head detection is a core computer vision problem related to plant phenotyping that in recent years has seen increased interest as large-scale datasets have been made available for use in research. In deep learning problems with limited training... Read More about Domain Adaptation of Synthetic Images for Wheat Head Detection.