Outputs (2058)

Deep synthesis of cloud lighting (2022)
Journal Article
Satilmis, P., Marnerides, D., Debattista, K., & Bashford-Rogers, T. (2022). Deep synthesis of cloud lighting. IEEE Computer Graphics and Applications, 42(5; 01 Sept.-Oct. 2022), 8 - 18. https://doi.org/10.1109/MCG.2022.3172846

Current appearance models for the sky are able to represent clear sky illumination to a high degree of accuracy. However, these models all lack a common feature of real-skies: clouds. These are an essential component for many applications which rely... Read More about Deep synthesis of cloud lighting.

The value of information for dynamic decentralised criticality computation (2022)
Conference Proceeding
Proselkov, Y., Herrera, M., Hernandez, M. P., Kumar Parlikad, A. K., & Brintrup, A. (2022). The value of information for dynamic decentralised criticality computation. In IFAC-PapersOnLine (408-413). https://doi.org/10.1016/j.ifacol.2022.04.228

Smart manufacturing uses advanced data-driven solutions to improve performance and operations resilience requiring large amounts of data delivered quickly, enabled by telecom networks and network elements such as routers or switches. Disruptions can... Read More about The value of information for dynamic decentralised criticality computation.

Ego-graph replay based continual learning for misinformation engagement prediction (2022)
Conference Proceeding
Bo, H., Mcconville, R., Hong, J., & Liu, W. (in press). Ego-graph replay based continual learning for misinformation engagement prediction. . https://doi.org/10.48550/arXiv.2207.12105

Online social network platforms have a problem with misinformation. One popular way of addressing this problem is via the use of machine learning based automated misinfor-mation detection systems to classify if a post is misinformation. Instead of po... Read More about Ego-graph replay based continual learning for misinformation engagement prediction.

Studying how digital luthiers choose their tools (2022)
Conference Proceeding
Renney, N., Renney, H., Mitchell, T. J., & Gaster, B. R. (2022). Studying how digital luthiers choose their tools. . https://doi.org/10.1145/3491102.3517656

Digital lutherie is a sub-domain of digital craft focused on creating digital musical instruments: high-performance devices for musical expression. It represents a nuanced and challenging area of human-computer interaction that is well established an... Read More about Studying how digital luthiers choose their tools.

Machine in the middle: Exploring dark patterns of emotional human-computer integration through media art (2022)
Conference Proceeding
Dickinson, R., Semertzidis, N., & Mueller, F. F. (2022). Machine in the middle: Exploring dark patterns of emotional human-computer integration through media art. In S. Barbosa, C. Lampe, C. Appert, & D. A. Shamma (Eds.), CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3491101.3503555

As our relationship with machines becomes evermore intimate, we observe increasing efforts in the quantification of human emotion, which has historically generated unintended consequences. We acknowledge an amplification of this trend through recent... Read More about Machine in the middle: Exploring dark patterns of emotional human-computer integration through media art.

Sensitive periods for the effect of childhood adversity on DNA methylation: Updated results from a prospective, longitudinal study (2022)
Journal Article
Lussier, A. A., Zhu, Y., Smith, B. J., Simpkin, A. J., Smith, A. D. A. C., Suderman, M. J., …Dunn, E. C. (2023). Sensitive periods for the effect of childhood adversity on DNA methylation: Updated results from a prospective, longitudinal study. Biological Psychiatry: Global Open Science, 3(3), 567-571. https://doi.org/10.1016/j.bpsgos.2022.04.002

Disclosure risks in odds ratios and logistic regression (2022)
Presentation / Conference
Derrick, B., Green, E., Ritchie, F., & White, P. (2022, April). Disclosure risks in odds ratios and logistic regression. Paper presented at Scottish Economic Society Annual Conference 2022: Special session 'Protecting confidentiality in social science research outputs', Glasgow

When publishing statistics from confidential data, there exists a risk that the statistic might inadvertently reveal confidential information. Statistical disclosure control (SDC) aims to reduce that risk to an acceptable level. Most SDC theory is co... Read More about Disclosure risks in odds ratios and logistic regression.

Vehicle detection using improved region convolution neural network for accident prevention in smart roads (2022)
Journal Article
Djenouri, Y., Belhadi, A., Srivastava, G., Djenouri, D., & Line, J. C. (2022). Vehicle detection using improved region convolution neural network for accident prevention in smart roads. Pattern Recognition Letters, 158, 42-47. https://doi.org/10.1016/j.patrec.2022.04.012

This paper explores the vehicle detection problem and introduces an improved regional convolution neural network. The vehicle data (set of images) is first collected, from which the noise (set of outlier images) is removed using the SIFT extractor. T... Read More about Vehicle detection using improved region convolution neural network for accident prevention in smart roads.

Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation (2022)
Presentation / Conference
Derrick, B., Green, E., Kember, K., Ritchie, F., & White, P. (2022, April). Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation. Paper presented at Scottish Economic Society, Glasgow

Reporting the sample mean, sample standard deviation and sample size could in some cases lead to the unique identification of the underpinning sample. The likelihood of this reveal via direct enumeration of the possible search space decreases with i... Read More about Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation.

Urinary Volatile Organic Compound Testing in Fast-Track Patients with Suspected Colorectal Cancer (2022)
Journal Article
Boulind, C. E., Gould, O., Costello, B. D. L., Allison, J., White, P., Ewings, P., …Francis, N. K. (2022). Urinary Volatile Organic Compound Testing in Fast-Track Patients with Suspected Colorectal Cancer. Cancers, 14(9), 2127. https://doi.org/10.3390/cancers14092127

Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic... Read More about Urinary Volatile Organic Compound Testing in Fast-Track Patients with Suspected Colorectal Cancer.