All Outputs (16)

A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings (2024)
Journal Article
Cartwright, S., Rothwell, B., Figueredo, G., Medina, H., Eastwick, C., Layton, J., & Ambrose, S. (2024). A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings. Tribology International, https://doi.org/10.1016/j.triboint.2024.109670

Traditional methods of evaluating the performance of journal bearings, for example thermal-elastic-hydrodynamic- lubrication theory, are limited to simplified conditions that often fail to accurately model real-world components. Numerical models that... Read More about A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings.

An empirical critique of the low income low energy efficiency approach to measuring fuel poverty (2024)
Journal Article
Semple, T., Rodrigues, L., Harvey, J., Figueredo, G., Nica-Avram, G., Gillott, M., …Goulding, J. (2024). An empirical critique of the low income low energy efficiency approach to measuring fuel poverty. Energy Policy, 186, Article 114014. https://doi.org/10.1016/j.enpol.2024.114014

Fuel poverty is a complex socioenvironmental issue of increasing global significance. In England, fuel poverty is assessed via the Low Income Low Energy Efficiency (LILEE) indicator, yet concerns exist regarding the efficacy of this metric given its... Read More about An empirical critique of the low income low energy efficiency approach to measuring fuel poverty.

Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon (2023)
Journal Article
Memon, H., Gjerde, E., Lynam, A., Chowdhury, A., De Maere, G., Figueredo, G., & Hussain, T. (2024). Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon. Engineering Applications of Artificial Intelligence, 128, Article 107465. https://doi.org/10.1016/j.engappai.2023.107465

The first-of-its-kind use of the active learning (AL) framework in thermal spray is adapted to enhance the prediction accuracy of the in-flight particle characteristics. The successful AL framework implementation via Bayesian Optimisation is benefici... Read More about Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon.

Innate immune cell instruction using micron-scale 3D objects of varied architecture and polymer chemistry: The ChemoArchiChip (2023)
Journal Article
Vassey, M., Ma, L., Kämmerling, L., Mbadugha, C., Trindade, G. F., Figueredo, G. P., …Alexander, M. R. (2023). Innate immune cell instruction using micron-scale 3D objects of varied architecture and polymer chemistry: The ChemoArchiChip. Matter, 6(3), 887-906. https://doi.org/10.1016/j.matt.2023.01.002

To design effective immunomodulatory implants, innate immune cell interactions at the surface of biomaterials need to be controlled and understood. The architectural design freedom of two-photon polymerization is used to produce arrays of surface-mou... Read More about Innate immune cell instruction using micron-scale 3D objects of varied architecture and polymer chemistry: The ChemoArchiChip.

Feature importance in machine learning models: A fuzzy information fusion approach (2022)
Journal Article
Rengasamy, D., Mase, J. M., Kumar, A., Rothwell, B., Torres, M. T., Alexander, M. R., …Figueredo, G. P. (2022). Feature importance in machine learning models: A fuzzy information fusion approach. Neurocomputing, 511, 163-174. https://doi.org/10.1016/j.neucom.2022.09.053

With the widespread use of machine learning to support decision-making, it is increasingly important to verify and understand the reasons why a particular output is produced. Although post-training feature importance approaches assist this interpreta... Read More about Feature importance in machine learning models: A fuzzy information fusion approach.

The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout (2022)
Journal Article
Knight, H., Jia, R., Ayling, K., Blake, H., Morling, J. R., Villalon, A. M., …Vedhara, K. (2023). The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout. Perspectives in Public Health, 143(4), 220-224. https://doi.org/10.1177/17579139221094750

Aims: Development and rollout of vaccines offers the best opportunity for population protection against the SARS-CoV-2 (COVID-19) virus. However, hesitancy towards the vaccines might impede successful uptake in the United Kingdom, particularly in you... Read More about The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout.

Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion (2021)
Journal Article
Rengasamy, D., Rothwell, B. C., & Figueredo, G. P. (2021). Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion. Applied Sciences, 11(24), Article 11854. https://doi.org/10.3390/app112411854

When machine learning supports decision-making in safety-critical systems, it is important to verify and understand the reasons why a particular output is produced. Although feature importance calculation approaches assist in interpretation, there is... Read More about Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion.

The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review (2021)
Journal Article
Majid, S., Reeves, S., Figueredo, G., Brown, S., Lang, A., Moore, M., & Morriss, R. (2021). The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review. JMIR Mental Health, 8(12), Article e27991. https://doi.org/10.2196/27991

Background: The number of self-monitoring apps for bipolar disorder (BD) is increasing. The involvement of users in human-computer interaction (HCI) research has a long history and is becoming a core concern for designers working in this space. The a... Read More about The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review.

The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review (2021)
Working Paper
Majid, S., Reeves, S., Figueredo, G., Brown, S., Lang, A., Moore, M., & Morriss, R. The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review

Background: Self-monitoring applications for bipolar disorder are increasing in numbers. The application of user-centred design (UCD) is becoming standardised to optimise the reach, adoption and sustained use of this type of technology. Objectiv... Read More about The Extent of User Involvement in the Design of Self-Tracking Technology for Bipolar Disorder: Literature Review.

Machine learning to determine the main factors affecting creep rates in laser powder bed fusion (2021)
Journal Article
Sanchez, S., Rengasamy, D., Hyde, C. J., Figueredo, G. P., & Rothwell, B. (2021). Machine learning to determine the main factors affecting creep rates in laser powder bed fusion. Journal of Intelligent Manufacturing, 32(8), 2353–2373. https://doi.org/10.1007/s10845-021-01785-0

There is an increasing need for the use of additive manufacturing (AM) to produce improved critical application engineering components. However, the materials manufactured using AM perform well below their traditionally manufactured counterparts, par... Read More about Machine learning to determine the main factors affecting creep rates in laser powder bed fusion.

Discovery of (meth)acrylate polymers that resist colonization by fungi associated with pathogenesis and biodeterioration (2020)
Journal Article
Vallieres, C., Hook, A. L., He, Y., Crucitti, V. C., Figueredo, G., Davies, C. R., …Avery, S. V. (2020). Discovery of (meth)acrylate polymers that resist colonization by fungi associated with pathogenesis and biodeterioration. Science Advances, 6(23), Article eaba6574. https://doi.org/10.1126/sciadv.aba6574

© 2020 The Authors. Fungi have major, negative socioeconomic impacts, but control with bioactive agents is increasingly restricted, while resistance is growing. Here, we describe an alternative fungal control strategy via materials operating passivel... Read More about Discovery of (meth)acrylate polymers that resist colonization by fungi associated with pathogenesis and biodeterioration.

Deep Learning with Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management (2020)
Journal Article
Rengasamy, D., Jafari, M., Rothwell, B., Chen, X., & Figueredo, G. P. (2021). Deep Learning with Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management. Sensors, 20(3), https://doi.org/10.3390/s20030723

Deep learning has been employed to prognostic and health management of automotive and aerospace with promising results. Literature in this area has revealed that most contributions regarding deep learning is largely focused on the model’s architectur... Read More about Deep Learning with Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management.

Using agent-based modelling for investigating modal shift: The case of university travel (2019)
Journal Article
Olusola, F. T., Siebers, P., Faboya, O., Ryan, B., & Figueredo, G. P. (2020). Using agent-based modelling for investigating modal shift: The case of university travel. Computers and Industrial Engineering, 139, https://doi.org/10.1016/j.cie.2019.106077

© 2019 Travel mode choices are a result of several factors and how they affect individual travellers. This paper examines those factors influencing travellers’ mode choices commuting to and from a university. Furthermore, we investigate how a shift t... Read More about Using agent-based modelling for investigating modal shift: The case of university travel.

Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management (2018)
Conference Proceeding
Faboya, O., Figueredo, G. P., Ryan, B., & Siebers, P. (2018). Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management. In The 21st IEEE International Conference on Intelligent Transportation Systems (144-149). https://doi.org/10.1109/ITSC.2018.8569946

The uneven utilisation of modes of transport has a big impact on traffic in transport pathway infrastrutures. For motor vehicles for instance, this situation explains rapid road deterioration and the large amounts of money invested in maintenance and... Read More about Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management.

Deep learning approaches to aircraft maintenance, repair and overhaul: a review (2018)
Conference Proceeding
Rengasami, D., Morvan, H., & Patrocinio Figueredo, G. (2018). Deep learning approaches to aircraft maintenance, repair and overhaul: a review. In 21st IEEE International Conference on Intelligent Transportation Systemshttps://doi.org/10.1109/ITSC.2018.8569502

The use of sensor technology constantly gathering aircrafts' status data has promoted the rapid development of data-driven solutions in aerospace engineering. These methods assist, for instance, with determining appropriate actions for aircraft maint... Read More about Deep learning approaches to aircraft maintenance, repair and overhaul: a review.

A Novel Modal Shift Modelling Framework for Transport Systems (2017)
Presentation / Conference
Faboya, O. T., Siebers, P., Ryan, B., & Figueredo, G. P. (2017, September). A Novel Modal Shift Modelling Framework for Transport Systems. Paper presented at Social Simulation Conference 2017 (SSC2017)

The challenges from transport modes on human environments, health and economy, have called for investigations into how behavioural changes can be achieved for better resource utilisation. Trip makers' travel demands have been identified, and they inc... Read More about A Novel Modal Shift Modelling Framework for Transport Systems.