All Outputs (2039)

Designing Prosocial More-Than-Human Rhetoric within Experiential Futures (2024)
Presentation / Conference Contribution
Coulton, P., Stead, M., Pilling, M., Crabtree, A., Chamberlain, A., & Sailaja, N. (2024, October). Designing Prosocial More-Than-Human Rhetoric within Experiential Futures. Presented at Mindtrek 2024, Tampere, Finland

While prosocial behaviour is often described as behaviour intended to help and benefit others, it is primarily considered through an anthropocentric lens in that the others in question are principally humans. In this research, we consider designed sy... Read More about Designing Prosocial More-Than-Human Rhetoric within Experiential Futures.

Local cryptic diversity in salinity adaptation mechanisms in the wild outcrossing Brassica fruticulosa (2024)
Journal Article
Busoms, S., da Silva, A. C., Escolà, G., Abdilzadeh, R., Curran, E., Bollmann-Giolai, A., Bray, S., Wilson, M., Poschenrieder, C., & Yant, L. (2024). Local cryptic diversity in salinity adaptation mechanisms in the wild outcrossing Brassica fruticulosa. Proceedings of the National Academy of Sciences, 121(40), Article e2407821121. https://doi.org/10.1073/pnas.2407821121

It is normally supposed that populations of the same species should evolve shared mechanisms of adaptation to common stressors due to evolutionary constraint. Here, we describe a system of within-species local adaptation to coastal habitats, Brassica... Read More about Local cryptic diversity in salinity adaptation mechanisms in the wild outcrossing Brassica fruticulosa.

Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets (2024)
Journal Article
Gao, H., Huang, B., Chen, G., Xia, L., & Radenkovic, M. (2024). Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets. Remote Sensing of Environment, 315, Article 114425. https://doi.org/10.1016/j.rse.2024.114425

The world’s first scientific satellite for sustainable development goals (SDGSAT-1) provides valuable data about offshore small-scale ocean phenomena, including the Kármán vortex street phenomenon. Although the simulation of the oce... Read More about Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets.

FiDRL: Flexible Invocation-Based Deep Reinforcement Learning for DVFS Scheduling in Embedded Systems (2024)
Journal Article
Li, J., Jiang, W., He, Y., Yang, Q., Gao, A., Ha, Y., Özcan, E., Bai, R., Cui, T., & Yu, H. (2024). FiDRL: Flexible Invocation-Based Deep Reinforcement Learning for DVFS Scheduling in Embedded Systems. IEEE Transactions on Computers, https://doi.org/10.1109/TC.2024.3465933

Deep Reinforcement Learning (DRL)-based Dynamic Voltage Frequency Scaling (DVFS) has shown great promise for energy conservation in embedded systems. While many works were devoted to validating its efficacy or improving its performance, few discuss t... Read More about FiDRL: Flexible Invocation-Based Deep Reinforcement Learning for DVFS Scheduling in Embedded Systems.

Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima (2024)
Journal Article
Yu, Y., Huang, B., Radenkovic, M., Wang, T., & Chen, G. (2024). Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima. IEEE Transactions on Geoscience and Remote Sensing, 1-1. https://doi.org/10.1109/tgrs.2024.3464850

Subsurface chlorophyll maximum (SCM) is a crucial ecological indicator for marine ecosystems. Previous studies have indicated that this phenomenon is globally widespread. Although the biogeochemical argo assimilation results have yielded positive res... Read More about Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima.

Responsibility and Regulation: Exploring Social Measures of Trust in Medical AI (2024)
Presentation / Conference Contribution
McGarry, G., Crabtree, A., Chamberlain, A., & Urquhart, L. D. (2024, September). Responsibility and Regulation: Exploring Social Measures of Trust in Medical AI. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS ’24), Austin, Texas, USA

This paper explores expert accounts of autonomous systems (AS) development in the medical device domain (MD) involving applications of artificial intelligence (AI), machine learning (ML), and other algorithmic and mathematical modelling techniques. W... Read More about Responsibility and Regulation: Exploring Social Measures of Trust in Medical AI.

Investigating the Impact of Generative AI on Students and Educators: Evidence and Insights from the Literature (2024)
Presentation / Conference Contribution
Clos, J., & Chen, Y. Y. (2024, September). Investigating the Impact of Generative AI on Students and Educators: Evidence and Insights from the Literature. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS ’24), Austin, Texas

Generative artificial intelligence (AI) has become one of the main concerns of knowledge workers due to its ability to mimic realistic human reasoning and creativity. However, this integration raises critical concerns about trust and ethics, which ar... Read More about Investigating the Impact of Generative AI on Students and Educators: Evidence and Insights from the Literature.

A Multimethod Analysis of US Perspectives towards Trustworthy Autonomous Systems (2024)
Presentation / Conference Contribution
Barnard, P., Boudouraki, A., & Clos, J. (2024, September). A Multimethod Analysis of US Perspectives towards Trustworthy Autonomous Systems. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS '24), Austin, Texas

The Trustworthy Autonomous Systems (TAS) Hub is a collabora-tive platform that aims to guide the development of autonomous systems that are safe, reliable, and ultimately trusted by society. Its mission is to address the challenges surrounding the gr... Read More about A Multimethod Analysis of US Perspectives towards Trustworthy Autonomous Systems.

Examining the Feasibility of AI-Generated Questions in Educational Settings (2024)
Presentation / Conference Contribution
Zeghouani, O., Ali, Z., Simson Van Dijkhuizen, W., Wei Hong, J., & Clos, J. (2024, September). Examining the Feasibility of AI-Generated Questions in Educational Settings. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS '24), Austin, Texas, USA

Educators face ever-growing time constraints, leading to poor work-life balance and a negative impact on work quality. Through their language generation capabilities, large language models offer an interesting avenue to ease this academic workload, a... Read More about Examining the Feasibility of AI-Generated Questions in Educational Settings.

LOOM: a Privacy-Preserving Linguistic Observatory of Online Misinformation (2024)
Presentation / Conference Contribution
Clos, J., McClaughlin, E., Barnard, P., Tom, T., & Yajaman, S. (2024, September). LOOM: a Privacy-Preserving Linguistic Observatory of Online Misinformation. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS ’24), Austin, Texas, USA

Online misinformation is an ever-growing challenge that can have a negative impact on individuals, societies, and democracies. We report on LOOM, a project that aims to build and validate a browser-based tool to detect and respond to misinformation i... Read More about LOOM: a Privacy-Preserving Linguistic Observatory of Online Misinformation.

The Earth, Brain, Health Commission: how to preserve mental health in a changing environment (2024)
Journal Article
Schumann, G., Barciela, R., Benegal, V., Bernard, A., Desrivieres, S., Feng, J., Gong, P., Heinz, A., Hunt, X., Jin, L., Luterbacher, J., Marquand, A., Meyer-Lindenberg, A., Salomon, J., Schwalber, A., Shetty, S., Stahl, B., & Thompson, P. (in press). The Earth, Brain, Health Commission: how to preserve mental health in a changing environment. nature mental health, https://doi.org/10.1038/s44220-024-00314-1

Responsible AI in policing (2024)
Presentation / Conference Contribution
Webb, H., Fitzroy-Dale, N., Aqeel, S., Piskopani, A.-M., Stafford-Fraser, Q., Dowthwaite, L., McAuley, D., & Hargreaves, C. (2024, September). Responsible AI in policing. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS '24), Austin, Texas, USA

The deployment of AI-driven technologies in policing is often welcomed as an opportunity to enhance efficiency in dealing with crime. At the same time, however, these technologies pose risks around data bias, data protection, accuracy and privacy. In... Read More about Responsible AI in policing.

Measurable Trust: The Key to Unlocking User Confidence in Black-Box AI (2024)
Presentation / Conference Contribution
Palazzolo, P., Stahl, B., & Webb, H. (2024, September). Measurable Trust: The Key to Unlocking User Confidence in Black-Box AI. Presented at Second International Symposium on Trustworthy Autonomous Systems, Austin, Texas, USA

Given the pervasive integration of artificial intelligence (AI) into our daily lives, establishing public trust is paramount for maximizing AI's benefits and ensuring its responsible use. This research proposes an investigation into the feasibility o... Read More about Measurable Trust: The Key to Unlocking User Confidence in Black-Box AI.

Design and Evaluation of a Tool to assist Small-Medium Organisations (SMOs) to implement Automated Decision-Making (ADM). (2024)
Presentation / Conference Contribution
Baguley, K., Fischer, J., & Hyde, R. (2024, September). Design and Evaluation of a Tool to assist Small-Medium Organisations (SMOs) to implement Automated Decision-Making (ADM). Presented at Second International Symposium on Trustworthy Autonomous Systems, Austin, Texas

We present a new prototype tool intended to enable SMOs without specialist expertise in the area to implement Automated Decision-Making (ADM) with confidence. We report on the design and (briefly) evaluation of the tool, demonstrating the potential u... Read More about Design and Evaluation of a Tool to assist Small-Medium Organisations (SMOs) to implement Automated Decision-Making (ADM)..

Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: a case study and academic’s guide (2024)
Journal Article
Taher, R., Hall, C. L., Gomez Bergin, A. D., Gupta, N., Heaysman, C., Jacobsen, P., Kabir, T., Kalnad, N., Keppens, J., Hsu, C.-W., McGuire, P., Peters, E., Shergill, S., Stahl, D., Wensley Stock, B., & Yiend, J. (2024). Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: a case study and academic’s guide. Trials, 25, Article 604. https://doi.org/10.1186/s13063-024-08421-1

Background: The field of digital mental health has followed an exponential growth trajectory in recent years. While the evidence base has increased significantly, its adoption within health and care services has been slowed by several challenges, inc... Read More about Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: a case study and academic’s guide.

The sound heritage of Kotagede: the evolving soundscape of a living museum (2024)
Journal Article
Mediastika, C. E., Sudarsono, A. S., Utami, S. S., Setiawan, T., Mansell, J. G., Santosa, R. B., Wiratama, A., Yanti, R. J., & Cliffe, L. (2024). The sound heritage of Kotagede: the evolving soundscape of a living museum. Built Heritage, 8(1), Article 38. https://doi.org/10.1186/s43238-024-00145-0

Kotagede, the capital of the ancient Mataram Kingdom and currently an area in the Yogyakarta Province of Indonesia, is known as a ‘real living museum’. It was previously a residential area with many vital premises and heritage buildings that became a... Read More about The sound heritage of Kotagede: the evolving soundscape of a living museum.

Predicting Acute Pain Levels Implicitly from Vocal Features (2024)
Presentation / Conference Contribution
Williams, J., Schneiders, E., Card, H., Seabrooke, T., Pakenham-Walsh, B., Azim, T., Valls-Reed, L., Vigneswaran, G., Bautista, J. R., Chandra, R., & Farahi, A. (2024, September). Predicting Acute Pain Levels Implicitly from Vocal Features. Poster presented at Interspeech 2024, Kos Island, Greece

Evaluating pain in speech represents a critical challenge in high-stakes clinical scenarios, from analgesia delivery to emergency triage. Clinicians have predominantly relied on direct verbal communication of pain which is difficult for patients with... Read More about Predicting Acute Pain Levels Implicitly from Vocal Features.

Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments (2024)
Journal Article
Chen, X., Qu, R., Dong, J., Dong, H., & Bai, R. (2024). Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments. Applied Soft Computing, 166, Article 112190. https://doi.org/10.1016/j.asoc.2024.112190

Efficient truck dispatching strategies are paramount in container terminal operations. The quality of these strategies heavily relies on accurate and expedient simulations, which provide a crucial platform for training and evaluating dispatching algo... Read More about Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments.

Ethics and Governance of Neurotechnology in Africa: Lessons From AI (2024)
Journal Article
Eke, D. (2024). Ethics and Governance of Neurotechnology in Africa: Lessons From AI. JMIR Neurotechnology, 3, Article e56665. https://doi.org/10.2196/56665

As a novel technology frontier, neurotechnology is revolutionizing our perceptions of the brain and nervous system. With growing private and public investments, a thriving ecosystem of direct-to-consumer neurotechnologies has also emerged. These tech... Read More about Ethics and Governance of Neurotechnology in Africa: Lessons From AI.

Calculating Compilers Effectively (Functional Pearl) (2024)
Presentation / Conference Contribution
Garby, Z., Hutton, G., & Bahr, P. (2024, September). Calculating Compilers Effectively (Functional Pearl). Presented at Haskell '24: 17th ACM SIGPLAN International Haskell Symposium, Milan, Italy

Much work in the area of compiler calculation has focused on pure languages. While this simplifies the reasoning, it reduces the applicability. In this article, we show how an existing compiler calculation methodology can be naturally extended to lan... Read More about Calculating Compilers Effectively (Functional Pearl).