Outputs (2134)

Reimagining the Design of Mobile Robotic Telepresence: Reflections from a Hybrid Design Workshop (2024)
Presentation / Conference Contribution
Reyes-Cruz, G., Martinez Avila, J., Schneiders, E., & Boudouraki, A. (2024, September). Reimagining the Design of Mobile Robotic Telepresence: Reflections from a Hybrid Design Workshop. Presented at TAS '24: Second International Symposium on Trustworthy Autonomous Systems, Austin, Texas, USA

Mobile robotic telepresence systems have been around for more than a decade, promising to improve on traditional video conferencing by enabling remote movement, and more recently, providing autonomous features for navigation, yet their use in the rea... Read More about Reimagining the Design of Mobile Robotic Telepresence: Reflections from a Hybrid Design Workshop.

A Taxonomy of Domestic Robot Failure Outcomes: Understanding the impact of failure on trustworthiness of domestic robots (2024)
Presentation / Conference Contribution
Cameron, H. R., Castle-Green, S., Chughtai, M., Dowthwaite, L., Kucukyilmaz, A., A. Maior, H. A., Ngo, V., Schneiders, E., & C. Stahl, B. (2024, September). A Taxonomy of Domestic Robot Failure Outcomes: Understanding the impact of failure on trustworthiness of domestic robots. Presented at Trustworthy Autonomous Systems International Symposium '24, Austin, Texas, USA

Domestic robots are fast becoming an integrated part of daily life. In anticipation of increased uptake of robotic assistants in the home, researchers and designers must investigate what makes domestic robotic interventions trustworthy or untrustwort... Read More about A Taxonomy of Domestic Robot Failure Outcomes: Understanding the impact of failure on trustworthiness of domestic robots.

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.

Trustworthy Airspaces of the Future: Hopes and concerns of experts regarding Uncrewed Traffic Management systems (2024)
Presentation / Conference Contribution
R. Cameron, H., McBride, N., Ochang, P., & C. Stahl, B. (2024, September). Trustworthy Airspaces of the Future: Hopes and concerns of experts regarding Uncrewed Traffic Management systems. Presented at Trustworthy Autonomous Systems International Symposium '24, Austin, Texas, USA

Uncrewed aerial systems (UAS) such as drones are an increasingly mundane part of our skies, and are expected as an industry to undergo exponential growth in the coming decade. In order to monitor and manage the airspace, Uncrewed Traffic Management (... Read More about Trustworthy Airspaces of the Future: Hopes and concerns of experts regarding Uncrewed Traffic Management systems.

Explain the world – Using causality to facilitate better rules for fuzzy systems (2024)
Journal Article
Zhang, T., Wagner, C., & Garibaldi, J. M. (2024). Explain the world – Using causality to facilitate better rules for fuzzy systems. IEEE Transactions on Fuzzy Systems, 1-14. https://doi.org/10.1109/TFUZZ.2024.3457962

The rules of a rule-based system provide explanations for its behaviour by revealing the relationships between the variables captured. However, ideally, we have AI systems which go beyond explainable AI (XAI), that is, systems which not only explain... Read More about Explain the world – Using causality to facilitate better rules for fuzzy systems.

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.

Into the Here and Now: Explorations within a New Acoustic Virtual Reality (2024)
Journal Article
Cliffe, L. (in press). Into the Here and Now: Explorations within a New Acoustic Virtual Reality. Leonardo,

The author reflects upon listeners’ experiences and the practice of developing a number of audio augmented reality sound installations deployed between 2019 and 2020. The installations realized audio augmented objects: physical real-world objects aug... Read More about Into the Here and Now: Explorations within a New Acoustic Virtual Reality.