All Outputs (2001)

Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles (2022)
Data
Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. [Dataset]. https://doi.org/10.3390/jsan11030035

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETs In such a widespread safety-critical application, security is paramount to the implementation of the networks. We view new autonomous veh... Read More about Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles.

Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles (2022)
Journal Article
Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. Journal of Sensor and Actuator Networks, 11(3), Article 35. https://doi.org/10.3390/jsan11030035

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETS. In such a widespread safety critical application, security is paramount to the implementation of the networks. We view new autonomous ve... Read More about Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles.

A Collaborative Learning Tracking Network for Remote Sensing Videos (2022)
Journal Article
Li, X., Jiao, L., Zhu, H., Liu, F., Yang, S., Zhang, X., …Qu, R. (2023). A Collaborative Learning Tracking Network for Remote Sensing Videos. IEEE Transactions on Cybernetics, 53(3), 1954-1967. https://doi.org/10.1109/TCYB.2022.3182993

With the increasing accessibility of remote sensing videos, remote sensing tracking is gradually becoming a hot issue. However, accurately detecting and tracking in complex remote sensing scenes is still a challenge. In this article, we propose a col... Read More about A Collaborative Learning Tracking Network for Remote Sensing Videos.

Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task (2022)
Journal Article
Kok, Y. E., Woodward, S., Özcan, E., & Torres Torres, M. (2022). Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task. Molecular Informatics, 41(12), Article 2200068. https://doi.org/10.1002/minf.202200068

Chirality, the ability of some molecules to exist as two non-superimposable mirror images, profoundly influences both chemistry and biology. Advances in deep learning enable the automatic recognition of chemical structure diagrams, however, studies o... Read More about Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task.

Understanding Trust and Sustained Use or Abandonment after a Year with the NHS Covid-19 Contact Tracing App in the United Kingdom: A Longitudinal Mixed-Method Study (2022)
Preprint / Working Paper
Pepper, C., Reyes-Cruz, G., Pena, A. R., Dowthwaite, L., Babbage, C. M., Wagner, H. G., …Fischer, J. E. Understanding Trust and Sustained Use or Abandonment after a Year with the NHS Covid-19 Contact Tracing App in the United Kingdom: A Longitudinal Mixed-Method Study

Background: Digital contact tracing (DCT) apps have been recently implemented widely as a response to the Covid-19 pandemic. Research has focused on understanding the acceptance and adoption of these apps, but more work is needed to understand which... Read More about Understanding Trust and Sustained Use or Abandonment after a Year with the NHS Covid-19 Contact Tracing App in the United Kingdom: A Longitudinal Mixed-Method Study.

DCMS Response To Call Connected Tech Smart Or Sinister Horizon (2022)
Other
McAuley, D., Crabtree, A., Piskopani, A. M., Chen, J., & Urquhart, L. DCMS Response To Call Connected Tech Smart Or Sinister Horizon

Perceptions of Cognitive Training Games and Assessment Technologies for Dementia: Acceptability Study with Patient and Public Involvement Workshops (2022)
Journal Article
Harrington, K., Craven, M. P., Wilson, M. L., & Landowska, A. (2022). Perceptions of Cognitive Training Games and Assessment Technologies for Dementia: Acceptability Study with Patient and Public Involvement Workshops. JMIR Serious Games, 10(2), Article e32489. https://doi.org/10.2196/32489

Background: Cognitive training and assessment technologies offer the promise of dementia risk reduction and a more timely diagnosis of dementia, respectively. Cognitive training games may help reduce the lifetime risk of dementia by helping to build... Read More about Perceptions of Cognitive Training Games and Assessment Technologies for Dementia: Acceptability Study with Patient and Public Involvement Workshops.

Navigating Incommensurability Between Ethnomethodology, Conversation Analysis, and Artificial Intelligence (2022)
Preprint / Working Paper
Reeves, S. Navigating Incommensurability Between Ethnomethodology, Conversation Analysis, and Artificial Intelligence

Like many research communities, ethnomethodologists and conversation analysts have begun to get caught up -- yet again -- in the pervasive spectacle of surging interests in Artificial Intelligence (AI). Inspired by discussions amongst a growing netwo... Read More about Navigating Incommensurability Between Ethnomethodology, Conversation Analysis, and Artificial Intelligence.

Experiencing mundane AI futures (2022)
Presentation / Conference Contribution
Pilling, M., Coulton, P., Lodge, T., Crabtreeb, A., & Chamberlain, A. (2022). Experiencing mundane AI futures. . https://doi.org/10.21606/drs.2022.283

Whilst popular visions of Artificial Intelligence (AI) are often presented through the lens of sentient machines, our lived experience of AI is more mundane and exemplified by so-called ‘smart’ products and services. Whilst this mundane reality is of... Read More about Experiencing mundane AI futures.

Exploring self-tracking practices for those with lived experience of bipolar disorder: Learning from combined principles of Patient and Public Involvement and HCI (2022)
Presentation / Conference Contribution
Majid, S., Morriss, R., Figueredo, G., & Reeves, S. (2022). Exploring self-tracking practices for those with lived experience of bipolar disorder: Learning from combined principles of Patient and Public Involvement and HCI. In DIS '22: Designing Interactive Systems Conference (1907-1920). https://doi.org/10.1145/3532106.3533531

Bipolar Disorder (BD) is a complex, cyclical and chronic mental illness where self-tracking is central to self-management. Mobile technology is often leveraged to support this. Limited research has investigated the everyday practices of self-tracking... Read More about Exploring self-tracking practices for those with lived experience of bipolar disorder: Learning from combined principles of Patient and Public Involvement and HCI.

Crafting Trajectories of Smart Phone Use at the Opera (2022)
Journal Article
Greenhalgh, C., Hazzard, A., Benford, S., Cliffe, L., & Kelly, E. (2022). Crafting Trajectories of Smart Phone Use at the Opera. ACM Transactions on Computer-Human Interaction, 29(6), 1-37. https://doi.org/10.1145/3531007

Losing Her Voice is a new opera which highlights the challenges of subtly interweaving digital technologies into established cultural forms. Audience members were encouraged to use their own mobile phones to interact with on-stage projections before,... Read More about Crafting Trajectories of Smart Phone Use at the Opera.

Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response (2022)
Journal Article
Sondag, M., Turkay, C., Xu, K., Matthews, L., Mohr, S., & Archambault, D. (2022). Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response. Computer Graphics Forum, 41(3), 29-41. https://doi.org/10.1111/cgf.14520

Epidemiologists use individual-based models to (a) simulate disease spread over dynamic contact networks and (b) to investigate strategies to control the outbreak. These model simulations generate complex ‘infection maps’ of time-varying transmission... Read More about Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response.

Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning (2022)
Presentation / Conference Contribution
Serhan, B., Pandya, H., Kucukyilmaz, A., & Neumann, G. (2022). Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. In IEEE International Conference on Robotics and Automation (ICRA 2022) (1513-1519). https://doi.org/10.1109/ICRA46639.2022.9811645

Efficient robotic manipulation of objects for sorting and searching often rely upon how well the objects are perceived and the available grasp poses. The challenge arises when the objects are irregular, have similar visual features (e.g., textureless... Read More about Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning.

Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships (2022)
Journal Article
Wallace, K. J., Wagner, C., Pannell, D. J., Kim, M. K., & Rogers, A. A. (2022). Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships. Journal of Environmental Management, 317, Article 115352. https://doi.org/10.1016/j.jenvman.2022.115352

Inadequate definition of key terms and their relationships generates significant communication and analytical problems in environmental planning. In this work, we evaluate an ontological framework for environmental planning designed to combat these p... Read More about Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships.

Responsible AI, SDGs, and AI Governance in Africa (2022)
Presentation / Conference Contribution
Wakunuma, K., Ogoh, G., Eke, D. O., & Akintoye, S. (2022). Responsible AI, SDGs, and AI Governance in Africa. In 2022 IST-Africa Conference (IST-Africa). https://doi.org/10.23919/IST-Africa56635.2022.9845598

More than ever before, AI is now an area of national strategic importance. This has become quite evident with the proliferation of national AI strategies since the first was launched in Canada in 2017. There is now an ever-growing body of national AI... Read More about Responsible AI, SDGs, and AI Governance in Africa.

Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities (2022)
Journal Article
Calderon-Ramirez, S., Yang, S., Elizondo, D., & Moemeni, A. (2022). Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities. Applied Soft Computing, 123, Article 108983. https://doi.org/10.1016/j.asoc.2022.108983

In the context of the global coronavirus pandemic, different deep learning solutions for infected subject detection using chest X-ray images have been proposed. However, deep learning models usually need large labelled datasets to be effective. Semi-... Read More about Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities.

Modelling the emergence of cities and urban patterning using coupled integro-differential equations (2022)
Journal Article
Whiteley, T. D., Avitabile, D., Siebers, P. O., Robinson, D., & Owen, M. R. (2022). Modelling the emergence of cities and urban patterning using coupled integro-differential equations. Journal of the Royal Society, Interface, 19(190), Article 20220176. https://doi.org/10.1098/rsif.2022.0176

Human residential population distributions show patterns of higher density clustering around local services such as shops and places of employment, displaying characteristic length scales; Fourier transforms and spatial autocorrelation show the lengt... Read More about Modelling the emergence of cities and urban patterning using coupled integro-differential equations.

A Study on the Effects of Cognitive Overloading and Distractions on Human Movement During Robot-Assisted Dressing (2022)
Journal Article
A, C., S, D., & P, C.-S. (2022). A Study on the Effects of Cognitive Overloading and Distractions on Human Movement During Robot-Assisted Dressing. Frontiers in Robotics and AI, 9, Article 815871. https://doi.org/10.3389/frobt.2022.815871

For robots that can provide physical assistance, maintaining synchronicity of the robot and human movement is a precursor for interaction safety. Existing research on collaborative HRI does not consider how synchronicity can be affected if humans are... Read More about A Study on the Effects of Cognitive Overloading and Distractions on Human Movement During Robot-Assisted Dressing.

A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications (2022)
Journal Article
Pearcy, N., Garavaglia, M., Millat, T., Gilbert, J. P., Song, Y., Hartman, H., …Minton, N. P. (2022). A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications. PLoS Computational Biology, 18(5), Article e1010106. https://doi.org/10.1371/journal.pcbi.1010106

Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly prom... Read More about A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications.

Sensitive Pictures: Emotional Interpretation in the Museum (2022)
Presentation / Conference Contribution
Benford, S., Sundnes Løvlie, A., Ryding, K., Rajkowska, P., Bodiaj, E., Paris Darzentas, D., …Spanjevic, B. (2022). Sensitive Pictures: Emotional Interpretation in the Museum. In CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3491102.3502080

Museums are interested in designing emotional visitor experiences to complement traditional interpretations. HCI is interested in the relationship between Affective Computing and Affective Interaction. We describe Sensitive Pictures, an emotional vis... Read More about Sensitive Pictures: Emotional Interpretation in the Museum.