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Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity (2019)
Journal Article
Wang, D., Muller, T., Zhang, J., & Liu, Y. (2019). Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity. IEEE Transactions on Information Forensics and Security, 15, 816-828. https://doi.org/10.1109/TIFS.2019.2929678

Ratings provided by advisors can help an advisee to make decisions, e.g., which seller to select in e-commerce. Unfair rating attacks – where dishonest ratings are provided to mislead the advisee – impact the accuracy of decision making. Current lite... Read More about Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity.

Research ‘In the Wild’ (2019)
Book Chapter
Chamberlain, A., & Crabtree, A. (2020). Research ‘In the Wild’. In A. Chamberlain, & A. Crabtree (Eds.), Into the Wild: Beyond the Design Research Lab (1-6). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-18020-1_1

Over recent years the term `in the wild' has increasingly appeared in publications within the field of Human Computer Interaction (HCI). The phrase has become synonymous with a range of approaches that focus upon carrying out research-based studies r... Read More about Research ‘In the Wild’.

Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty (2019)
Journal Article
He, F., Chaussalet, T., & Qu, R. (2019). Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty. Operations Research Perspectives, 6, Article 100119. https://doi.org/10.1016/j.orp.2019.100119

Nursing workforce management is a challenging decision-making task in hospitals. The decisions are made across different timescales and levels from strategic long-term staffing budget to mid-term scheduling. These decisions are interconnected and imp... Read More about Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty.

Probability Matching on a Simple Simulated Foraging Task: The Effects of Reward Persistence and Accumulation on Choice Behavior (2019)
Journal Article
Ellerby, Z., & Tunney, R. J. (2019). Probability Matching on a Simple Simulated Foraging Task: The Effects of Reward Persistence and Accumulation on Choice Behavior. Advances in Cognitive Psychology, 15(2), 111-126. https://doi.org/10.5709/acp-0261-2

Over a series of decisions between two or more probabilistically rewarded options, humans have a tendency to diversify their choices, even when this will lead to diminished overall reward. In the extreme case of probability matching, this tendency is... Read More about Probability Matching on a Simple Simulated Foraging Task: The Effects of Reward Persistence and Accumulation on Choice Behavior.

The quantification of subjectivity: The R-fuzzy grey analysis framework (2019)
Journal Article
Khuman, A. S., Yang, Y., & John, R. (2019). The quantification of subjectivity: The R-fuzzy grey analysis framework. Expert Systems with Applications, 136, 201-216. https://doi.org/10.1016/j.eswa.2019.06.043

This paper puts forward a newly derived framework for capturing and inferring from subjective based uncertainty for any given observation. The framework is referred to as the R-fuzzy grey analysis framework (RfGAf), which itself is comprised of 3 dis... Read More about The quantification of subjectivity: The R-fuzzy grey analysis framework.

New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets (2019)
Journal Article
Mohamed, S. S., Abdalla, A., & John, R. I. (2019). New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets. Axioms, 8(2), 1-11. https://doi.org/10.3390/axioms8020073

In this paper we propose a new approach to construct similarity measures using the entropy measure for Interval-Valued Intuitionistic Fuzzy Sets. In addition, we provide several illustrative examples to demonstrate the practicality and effectivenes... Read More about New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets.

Mobile app communication aid for Cypriot deaf people (2019)
Journal Article
Pieri, K., & Cobb, S. V. G. (2019). Mobile app communication aid for Cypriot deaf people. Journal of Enabling Technologies, 13(2), 70-81. https://doi.org/10.1108/JET-12-2018-0058

© 2019, Emerald Publishing Limited. Purpose: People with severe or profound hearing loss face daily communication problems mainly due to the language barrier between themselves and the hearing community. Their hearing deficiency, as well as their use... Read More about Mobile app communication aid for Cypriot deaf people.

On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets (2019)
Journal Article
McCulloch, J., Ellerby, Z., & Wagner, C. (2019). On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/tfuzz.2019.2922161

Comparing fuzzy sets by computing their similarity is common, with a large set of measures of similarity available. However, while commonplace in the computational intelligence community, the application and results of similarity measures are less co... Read More about On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets.

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.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

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.