Outputs (126)

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 2024: Proceedings of the 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).

A Call to Action: Designing a more transparent online world for children and young people (2024)
Journal Article
Portillo, V., Dowthwaite, L., Creswick, H., Vallejos, E. P., Ten Holter, C., Koene, A., Jirotka, M., & Zhao, J. (2024). A Call to Action: Designing a more transparent online world for children and young people. Journal of Responsible Technology, 19, Article 100093. https://doi.org/10.1016/j.jrt.2024.100093

This paper reports on a qualitative research study that explored the practical and emotional experiences of young people aged 13–17 using algorithmically-mediated online platforms. It demonstrates an RI-based methodology for responsible two-way dialo... Read More about A Call to Action: Designing a more transparent online world for children and young people.

Time-Memory Trade-Offs Sound the Death Knell for GPRS and GSM (2024)
Presentation / Conference Contribution
Avoine, G., Carpent, X., Claverie, T., Devine, C., & Leblanc-Albarel, D. (2024, August). Time-Memory Trade-Offs Sound the Death Knell for GPRS and GSM. Presented at Advances in Cryptology – CRYPTO 2024, Santa Barbara, USA

This paper introduces a practical TMTO-based attack against GSM (A5/3) and GPRS (GEA-3), which are both technologies used in 2G mobile networks. Although designed in the 80 s, these networks are still quite active today, especially for embedded syste... Read More about Time-Memory Trade-Offs Sound the Death Knell for GPRS and GSM.

Beyond Trees: Calculating Graph-Based Compilers (Functional Pearl) (2024)
Journal Article
Bahr, P., & Hutton, G. (2024). Beyond Trees: Calculating Graph-Based Compilers (Functional Pearl). Proceedings of the ACM on Programming Languages, 8(ICFP), 370-394. https://doi.org/10.1145/3674638

Bahr and Hutton recently developed an approach to compiler calculation that allows a wide range of compilers to be derived from specifications of their correctness. However, a limitation of the approach is that it results in compilers that produce tr... Read More about Beyond Trees: Calculating Graph-Based Compilers (Functional Pearl).

Gase: graph attention sampling with edges fusion for solving vehicle routing problems (2024)
Journal Article
Wang, Z., Bai, R., Khan, F., Özcan, E., & Zhang, T. (2024). Gase: graph attention sampling with edges fusion for solving vehicle routing problems. Memetic Computing, 16(3), 337–353. https://doi.org/10.1007/s12293-024-00428-0

Learning-based methods have become increasingly popular for solving vehicle routing problems (VRP) due to their near-optimal performance and fast inference speed. Among them, the combination of deep reinforcement learning and graph representation all... Read More about Gase: graph attention sampling with edges fusion for solving vehicle routing problems.

Insights from explainable AI in oesophageal cancer team decisions (2024)
Journal Article
Thavanesan, N., Farahi, A., Parfitt, C., Belkhatir, Z., Azim, T., Vallejos, E. P., Walters, Z., Ramchurn, S., Underwood, T. J., & Vigneswaran, G. (2024). Insights from explainable AI in oesophageal cancer team decisions. Computers in Biology and Medicine, 180, Article 108978. https://doi.org/10.1016/j.compbiomed.2024.108978

Background: Clinician-led quality control into oncological decision-making is crucial for optimising patient care. Explainable artificial intelligence (XAI) techniques provide data-driven approaches to unravel how clinical variables influence this de... Read More about Insights from explainable AI in oesophageal cancer team decisions.

Decoding AI in Contemporary Art: A Five-Trope Classification for Understanding and Categorisation (2024)
Journal Article
Salimbeni, G., Benford, S., Reeves, S., & Martindale, S. (2024). Decoding AI in Contemporary Art: A Five-Trope Classification for Understanding and Categorisation. Leonardo, 57(4), 415–421. https://doi.org/10.1162/leon_a_02546

The article presents a historical overview of the classification of contemporary artworks that either have utilized artificial intelligence as a tool in their creation or focus on AI as their central theme or subject matter. The authors analyze artwo... Read More about Decoding AI in Contemporary Art: A Five-Trope Classification for Understanding and Categorisation.

AI and the iterable epistopics of risk (2024)
Journal Article
Crabtree, A., McGarry, G., & Urquhart, L. (2024). AI and the iterable epistopics of risk. AI & Society, https://doi.org/10.1007/s00146-024-02021-y

The risks AI presents to society are broadly understood to be manageable through ‘general calculus’, i.e., general frameworks designed to enable those involved in the development of AI to apprehend and manage risk, such as AI impact assessments, ethi... Read More about AI and the iterable epistopics of risk.