Outputs (2058)

Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA) (2022)
Book Chapter
Smith, B. J., Smith, A. D., & Dunn, E. C. (2022). Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA). In Sensitive Periods of Brain Development and Preventive Interventions (215-234). Springer. https://doi.org/10.1007/7854_2021_280

Sensitive periods are times during development when life experiences can have a greater impact on outcomes than at other periods during the life course. However, a dearth of sophisticated methods for studying time-dependent exposure-outcome relations... Read More about Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA).

Spontaneous and driven growth of multicellular lipid compartments to millimeter size from porous polymer structures** (2022)
Journal Article
Nomura, S. M., Shimizu, R., Archer, R. J., Hayase, G., Toyota, T., Mayne, R., & Adamatzky, A. (2022). Spontaneous and driven growth of multicellular lipid compartments to millimeter size from porous polymer structures**. ChemSystemsChem, 4(5), https://doi.org/10.1002/syst.202200006

This report describes a method to obtain multicellular shaped compartments made by lipids growing from a sponge-like porous structure. Each compartment is several tens of micrometers in diameter and separated by membranes comprised of phospholipid an... Read More about Spontaneous and driven growth of multicellular lipid compartments to millimeter size from porous polymer structures**.

Computing on wheels: A deep reinforcement learning-based approach (2022)
Journal Article
Kazmi, S. M. A., Ho, T. M., Nguyen, T. T., Fahim, M., Khan, A., Piran, M. J., & Baye, G. (2022). Computing on wheels: A deep reinforcement learning-based approach. IEEE Transactions on Intelligent Transportation Systems, 23(11), 22535-22548. https://doi.org/10.1109/TITS.2022.3165662

Future generation vehicles equipped with modern technologies will impose unprecedented computational demand due to the wide adoption of compute-intensive services with stringent latency requirements. The computational capacity of the next generation... Read More about Computing on wheels: A deep reinforcement learning-based approach.

Hybrid RESNET and regional convolution neural network for accident estimation (2022)
Journal Article
Djenouri, Y., Srivastava, G., Djenouri, D., Belhadi, A., & Jerry, C. L. (2022). Hybrid RESNET and regional convolution neural network for accident estimation. IEEE Transactions on Intelligent Transportation Systems, 23(12), 25335-25344. https://doi.org/10.1109/TITS.2022.3165156

Road safety is tackled and an intelligent deep learning framework is proposed in this work, which includes outlier detection, vehicle detection, and accident estimation. The road state is first collected, while an intelligent filter, based on SIFT ex... Read More about Hybrid RESNET and regional convolution neural network for accident estimation.

Video based convolutional neural networks forecasting for rainfall forecasting (2022)
Journal Article
Barnes, A., Rodding Kjeldsen, T., & McCullen, N. (2022). Video based convolutional neural networks forecasting for rainfall forecasting. IEEE Geoscience and Remote Sensing Letters, 19, https://doi.org/10.1109/LGRS.2022.3167456

This study presents a new methodology for improving forecasts of current monthly, regional precipitation using video-based convolutional neural networks (CNNs). Using 13 administrative regions of Great Britain as a case study, three CNN architectures... Read More about Video based convolutional neural networks forecasting for rainfall forecasting.

LSTM for periodic broadcasting in green IoT applications over energy harvesting enabled wireless networks: Case study on ADAPCAST (2022)
Conference Proceeding
Mustapha, K., Djenouri, D., Jianguo, D., & Djenouri, Y. (2022). LSTM for periodic broadcasting in green IoT applications over energy harvesting enabled wireless networks: Case study on ADAPCAST. In 2021 17th International Conference on Mobility, Sensing and Networking (MSN) (694-699). https://doi.org/10.1109/MSN53354.2021.00107

The present paper considers emerging Internet of Things (IoT) applications and proposes a Long Short Term Memory (LSTM) based neural network for predicting the end of the broadcasting period under slotted CSMA (Carrier Sense Multiple Access) based MA... Read More about LSTM for periodic broadcasting in green IoT applications over energy harvesting enabled wireless networks: Case study on ADAPCAST.

Empirical studies in end-user computer-generated music composition systems (2022)
Thesis
Hunt, S. Empirical studies in end-user computer-generated music composition systems. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/7239594

Computer music researchers dream of the perfect algorithm, in which the music generated is indistinguishable from, or even superior to, that composed by the world’s most talented composers. However, the fulfilment of this aim remains ambitious. This t... Read More about Empirical studies in end-user computer-generated music composition systems.

Exploring collaborative working of undergraduate students through virtual worlds: A study conducted in a Sri Lankan context (2022)
Thesis
Somaratne, R. Exploring collaborative working of undergraduate students through virtual worlds: A study conducted in a Sri Lankan context. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/7604202

Collaborative work is a type of learning activity given to students. This type of learning activity encourages students to work actively with their group members. Therefore, the participation of group members is important during group-based activitie... Read More about Exploring collaborative working of undergraduate students through virtual worlds: A study conducted in a Sri Lankan context.

Language of fungi derived from their electrical spiking activity (2022)
Journal Article
Adamatzky, A. (2022). Language of fungi derived from their electrical spiking activity. Royal Society Open Science, 9(4), 211926. https://doi.org/10.1098/rsos.211926

Fungi exhibit oscillations of extracellular electrical potential recorded via differential electrodes inserted into a substrate colonized by mycelium or directly into sporocarps. We analysed electrical activity of ghost fungi (Omphalotus nidiformis),... Read More about Language of fungi derived from their electrical spiking activity.

Short-Term safety outcomes of mastectomy and immediate prepectoral implant-based breast reconstruction: Pre-BRA prospective multicentre cohort study (2022)
Journal Article
Harvey, K. L., Sinai, P., Mills, N., White, P., Holcombe, C., & Potter, S. (2022). Short-Term safety outcomes of mastectomy and immediate prepectoral implant-based breast reconstruction: Pre-BRA prospective multicentre cohort study. British Journal of Surgery, 109(6), 530-538. https://doi.org/10.1093/bjs/znac077

Background: Prepectoral breast reconstruction (PPBR) has recently been introduced to reduce postoperative pain and improve cosmetic outcomes in women having implant-based procedures. High-quality evidence to support the practice of PPBR, however, is... Read More about Short-Term safety outcomes of mastectomy and immediate prepectoral implant-based breast reconstruction: Pre-BRA prospective multicentre cohort study.