Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network

Zhang, Xinmin; Huang, Baoxiang; Chen, Ge; Ge, Linyao; Radenkovic, Milena; Hou, Guojia

doi:10.1109/tgrs.2024.3388040

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.

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.

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.

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.

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.

Implementing responsible innovation: the role of the meso-level(s) between project and organisation (2024)
Journal Article
Stahl, B. C., Portillo, V., Wagner, H., Craigon, P. J., Darzentas, D., De Ossorno Garcia, S., Dowthwaite, L., Greenhalgh, C., Middleton, S. E., Nichele, E., Wagner, C., & Webb, H. (2024). Implementing responsible innovation: the role of the meso-level(s) between project and organisation. Journal of Responsible Innovation, 11(1), Article 2370934. https://doi.org/10.1080/23299460.2024.2370934

Much of academic discussion of responsible innovation (RI) has focused on RI integration into research projects. In addition, significant attention has also been paid to RI structures and policies at the research policy and institutional level. This... Read More about Implementing responsible innovation: the role of the meso-level(s) between project and organisation.

Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra (2024)
Journal Article
Kok, Y. E., Crisford, A., Parkes, A., Venkateswaran, S., Oreffo, R., Mahajan, S., & Pound, M. (2024). Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra. Scientific Reports, 14(1), Article 15902. https://doi.org/10.1038/s41598-024-66857-6

Raman spectroscopy is a rapid method for analysing the molecular composition of biological material. However, noise contamination in the spectral data necessitates careful pre-processing prior to analysis. Here we propose an end-to-end Convolutional... Read More about Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.

From Corporate Digital Responsibility to Responsible Digital Ecosystems (2024)
Journal Article
Stahl, B. C. (2024). From Corporate Digital Responsibility to Responsible Digital Ecosystems. Sustainability, 16(12), Article 4972. https://doi.org/10.3390/su16124972

The significant and rapidly growing impact that digital technologies has on all aspects of our lives has raised awareness of benefits but also concerns and worries linked to the development and use of these technologies. The concept of responsibility... Read More about From Corporate Digital Responsibility to Responsible Digital Ecosystems.

CUDA-based parallel local search for the set-union knapsack problem (2024)
Journal Article
Sonuç, E., & Özcan, E. (2024). CUDA-based parallel local search for the set-union knapsack problem. Knowledge-Based Systems, 299, Article 112095. https://doi.org/10.1016/j.knosys.2024.112095

The Set-Union Knapsack Problem (SUKP) is a complex combinatorial optimisation problem with applications in resource allocation, portfolio selection, and logistics. This paper presents a parallel local search algorithm for solving SU... Read More about CUDA-based parallel local search for the set-union knapsack problem.

Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context (2024)
Journal Article
Taher, R., Bhanushali, P., Allan, S., Alvarez-Jimenez, M., Bolton, H., Dennison, L., …Yiend, J. (2024). Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context. BJPsych Open, 10(4), Article e126. https://doi.org/10.1192/bjo.2024.713

Background
Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed fo... Read More about Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context.

Africa, ChatGPT, and Generative AI Systems: Ethical Benefits, Concerns, and the Need for Governance (2024)
Journal Article
Wakunuma, K., & Eke, D. (2024). Africa, ChatGPT, and Generative AI Systems: Ethical Benefits, Concerns, and the Need for Governance. Philosophies, 9(3), Article 80. https://doi.org/10.3390/philosophies9030080

This paper examines the impact and implications of ChatGPT and other generative AI technologies within the African context while looking at the ethical benefits and concerns that are particularly pertinent to the continent. Through a robust analysis... Read More about Africa, ChatGPT, and Generative AI Systems: Ethical Benefits, Concerns, and the Need for Governance.

“The ChatGPT bot is causing panic now – but it’ll soon be as mundane a tool as Excel”: analysing topics, sentiment and emotions relating to ChatGPT on Twitter (2024)
Journal Article
Heaton, D., Clos, J., Nichele, E., & Fischer, J. E. (2024). “The ChatGPT bot is causing panic now – but it’ll soon be as mundane a tool as Excel”: analysing topics, sentiment and emotions relating to ChatGPT on Twitter. Personal and Ubiquitous Computing, https://doi.org/10.1007/s00779-024-01811-x

ChatGPT, a sophisticated chatbot system by OpenAI, gained significant attention and adoption in 2022 and 2023. By generating human-like conversations, it attracted over 100 million monthly users; however, there are concerns about the social impact of... Read More about “The ChatGPT bot is causing panic now – but it’ll soon be as mundane a tool as Excel”: analysing topics, sentiment and emotions relating to ChatGPT on Twitter.

Perceptions on the Ethical and Legal Principles that Influence Global Brain Data Governance (2024)
Journal Article
Ochang, P., Eke, D., & Stahl, B. C. (2024). Perceptions on the Ethical and Legal Principles that Influence Global Brain Data Governance. Neuroethics, 17(2), Article 23. https://doi.org/10.1007/s12152-024-09558-1

Advances in neuroscience and other disciplines are producing large-scale brain data consisting of datasets from multiple organisms, disciplines, and jurisdictions in different formats. However, due to the lack of an international data governance fram... Read More about Perceptions on the Ethical and Legal Principles that Influence Global Brain Data Governance.

How Personal Value Orientations Influence Behaviors in Digital Citizen Science (2024)
Journal Article
Jeong, E., Jackson, C., Dowthwaite, L., Johnson, C., & Trouille, L. (2024). How Personal Value Orientations Influence Behaviors in Digital Citizen Science. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1), 1-25. https://doi.org/10.1145/3637341

While much research has examined motivations for contributing to citizen science projects, few studies have considered the role of personal values in directing citizen scientists' interactions and contribution patterns. We investigated whether person... Read More about How Personal Value Orientations Influence Behaviors in Digital Citizen Science.

Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple experts (2024)
Journal Article
Tyasnurita, R., Özcan, E., Drake, J. H., & Asta, S. (2024). Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple experts. Knowledge-Based Systems, 295, Article 111731. https://doi.org/10.1016/j.knosys.2024.111731

Hyper-heuristics are general purpose search methods for solving computationally difficult problems. A selection hyper-heuristic is composed of two key components: a heuristic selection method and move acceptance criterion. Under an iterative single-p... Read More about Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple experts.

Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network (2024)
Journal Article
Zhang, X., Huang, B., Chen, G., Ge, L., Radenkovic, M., & Hou, G. (2024). Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 4205214. https://doi.org/10.1109/tgrs.2024.3388040

Efficient eddy trajectory prediction driven by multiinformation fusion can facilitate the scientific research of oceanography, while the complicated dynamics mechanism makes this issue challenging. Benefiting from ocean observing technology, the eddy... Read More about Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network.

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