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Talking about interaction* (2019)
Journal Article
Reeves, S., & Beck, J. (2019). Talking about interaction*. International Journal of Human-Computer Studies, 131, 144-151. https://doi.org/10.1016/j.ijhcs.2019.05.010

© 2019 Elsevier Ltd Recent research has exposed disagreements over the nature and usefulness of what may (or may not) be Human–Computer Interaction's fundamental phenomenon: ‘interaction’. For some, HCI's theorising about interaction has been deficie... Read More about Talking about interaction*.

Who is Responsible for Responsible Innovation? Lessons From an Investigation into Responsible Innovation in Health Comment on "What Health System Challenges Should Responsible Innovation in Health Address? Insights From an International Scoping Review" (2019)
Journal Article
Stahl, B. C. (2019). Who is Responsible for Responsible Innovation? Lessons From an Investigation into Responsible Innovation in Health Comment on "What Health System Challenges Should Responsible Innovation in Health Address? Insights From an International Scoping Review". International Journal of Health Policy and Management, 8(7), 447-449. https://doi.org/10.15171/ijhpm.2019.32

Responsible innovation in health (RIH) takes the ideas of responsible research and innovation (RRI) and applies them to the health sector. This comment takes its point of departure from Lehoux et al which describes a structured literature review to d... Read More about Who is Responsible for Responsible Innovation? Lessons From an Investigation into Responsible Innovation in Health Comment on "What Health System Challenges Should Responsible Innovation in Health Address? Insights From an International Scoping Review".

Responsible domestic robotics: exploring ethical implications of robots in the home (2019)
Journal Article
Urquhart, L., Reedman-Flint, D., & Leesakul, N. (2019). Responsible domestic robotics: exploring ethical implications of robots in the home. Journal of Information, Communication and Ethics in Society, 17(2), 246-272. https://doi.org/10.1108/jices-12-2018-0096

Purpose: The vision of robotics in the home promises increased convenience, comfort, companionship, and greater security for users. The robot industry risks causing harm to users, being rejected by society at large, or being regulated in overly presc... Read More about Responsible domestic robotics: exploring ethical implications of robots in the home.

Exploring user behavioral data for adaptive cybersecurity (2019)
Journal Article
Addae, J. H., Sun, X., Towey, D., & Radenkovic, M. (2019). Exploring user behavioral data for adaptive cybersecurity. User Modeling and User-Adapted Interaction, 29(3), 701-750. https://doi.org/10.1007/s11257-019-09236-5

This paper describes an exploratory investigation into the feasibility of predictive analytics of user behavioral data as a possible aid in developing effective user models for adaptive cybersecurity. Partial least squares structural equation modelin... Read More about Exploring user behavioral data for adaptive cybersecurity.

A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram (2019)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2019). A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram. Journal of Synchrotron Radiation, 26(3), 839-853. https://doi.org/10.1107/s1600577519003448

We designed a convolutional neural network to quickly and accurately upscale the sinograms of x-ray tomograms captured with a low number of projections; effectively increasing the number of projections. This is particularly useful for tomograms that... Read More about A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram.

Virtual porous materials to predict the air void topology and hydraulic conductivity of asphalt roads (2019)
Journal Article
Aboufoul, M., Chiarelli, A., Triguero, I., & Garcia, A. (2019). Virtual porous materials to predict the air void topology and hydraulic conductivity of asphalt roads. Powder Technology, 352, 294-304. https://doi.org/10.1016/j.powtec.2019.04.072

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%–31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its par... Read More about Virtual porous materials to predict the air void topology and hydraulic conductivity of asphalt roads.

Evaluating information security core human error causes (IS-CHEC) technique in public sector and comparison with the private sector (2019)
Journal Article
Evans, M., He, Y., Maglaras, L., Yevseyeva, I., & Janicke, H. (2019). Evaluating information security core human error causes (IS-CHEC) technique in public sector and comparison with the private sector. International Journal of Medical Informatics, 127, 109-119. https://doi.org/10.1016/j.ijmedinf.2019.04.019

Background

The number of reported public sector information security incidents has significantly increased recently including 22% related to the UK health sector. Over two thirds of these incidents pertain to human error, but despite this, there a... Read More about Evaluating information security core human error causes (IS-CHEC) technique in public sector and comparison with the private sector.

A review on the self and dual interactions between machine learning and optimisation (2019)
Journal Article
Song, H., Triguero, I., & Özcan, E. (2019). A review on the self and dual interactions between machine learning and optimisation. Progress in Artificial Intelligence, 8(2), 143–165. https://doi.org/10.1007/s13748-019-00185-z

Machine learning and optimisation are two growing fields of artificial intelligence with an enormous number of computer science applications. The techniques in the former area aim to learn knowledge from data or experience, while the techniques from... Read More about A review on the self and dual interactions between machine learning and optimisation.