Outputs (20)

Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks (2022)
Journal Article
Wootton, A. J., Day, C., & Haycock, P. W. (2022). Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks. Structural Health Monitoring, 21(6), 2910-2921. https://doi.org/10.1177/14759217221080718

The degradation of roads is an expensive problem: in the United Kingdom alone, £27 billion was spent on road repairs between 2013 and 2019. One potential cost-saver is the early, non-destructive detection of faults. There are many available technique... Read More about Heterogeneous data fusion for the improved non-destructive detection of steel-reinforcement defects using echo state networks.

A new method of contrast enhancement of musculoskeletal ultrasound imaging based on fuzzy inference technique (2021)
Journal Article
Jabbar, S. I., Aladi, A. Q., Day, C., & Chadwick, E. (2021). A new method of contrast enhancement of musculoskeletal ultrasound imaging based on fuzzy inference technique. Biomedical Physics & Engineering Express, 7(5), 055003. https://doi.org/10.1088/2057-1976/ac0dce

Improving the clarity and visual quality of Musculoskeletal Ultrasound Images (MUI) can help clinicians to detect diseases more easily and accurately. In this work, we described how to enhance the contrast of MUI locally based on a fuzzy inference sy... Read More about A new method of contrast enhancement of musculoskeletal ultrasound imaging based on fuzzy inference technique.

Automated measurements of morphological parameters of muscles and tendons (2021)
Journal Article
Jabbar, S. I., Day, C., & Chadwick, E. (2021). Automated measurements of morphological parameters of muscles and tendons. Biomedical Physics & Engineering Express, 7(2), 025002. https://doi.org/10.1088/2057-1976/abd3de

Capturing accurate representations of musculoskeletal system morphology is a core aspect of musculoskeletal modelling of the upper limb. Measurements of important geometric parameters such as the thickness of muscles and tendons are key descriptors o... Read More about Automated measurements of morphological parameters of muscles and tendons.

A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers (2020)
Presentation / Conference Contribution
Day, C. R., Chadwick, E. K., & Blana, D. (2020, July). A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, Scotland, UK

Transhumeral amputation has a considerable detrimental effect on the amputee’s quality of life and independence. Previous work has already established the potential for exploiting proximal humerus myoelectric and kinematic signals for the effective c... Read More about A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers.

Digital Twin: Enabling Technologies, Challenges and Open Research (2020)
Journal Article
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 108952 - 108971. https://doi.org/10.1109/ACCESS.2020.2998358

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry... Read More about Digital Twin: Enabling Technologies, Challenges and Open Research.

Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images (2019)
Presentation / Conference Contribution
Ibraheem Jabbar, S., Day, C. R., & Chadwick, E. K. (2019, June). Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images

Edge detection in Musculoskeletal Ultrasound Imaging readily allows an ultrasound image to be rendered as a binary image. This facilitates automated measurement of geometric parameters, such as muscle thickness, circumference and cross-sectional area... Read More about Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images.

Fault Detection in Steel-Reinforced Concrete Using Echo State Networks (2018)
Presentation / Conference Contribution
Wootton, A. J., Day, C. R., & Haycock, P. W. (2018, July). Fault Detection in Steel-Reinforced Concrete Using Echo State Networks

The cost of maintaining and repairing the world's ageing reinforced concrete infrastructure continues to increase, and is expected to cost the United States economy alone $58 billion by 2020. Consequently, the use of non-destructive testing technolog... Read More about Fault Detection in Steel-Reinforced Concrete Using Echo State Networks.

Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species (2017)
Journal Article
Moore, H. E., Butcher, J. B., Day, C. R., & Drijfhout, F. P. (2017). Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species. Forensic Science International, 280, Article 233-244. https://doi.org/10.1016/j.forsciint.2017.10.001

Blowflies (Diptera: Calliphoridae) are forensically important as they are known to be one of the first to colonise human remains. The larval stage is typically used to assist a forensic entomologists with adult flies rarely used as they are difficult... Read More about Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species.

Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer (2017)
Presentation / Conference Contribution
Butcher, J. B., Rutter, A. V., Wootton, A. J., Day, C. R., & Sulé-Suso, J. (2017, September). Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. Presented at 17th Annual UK Workshop on Computational Intelligence, Cardiff, Wales, UK

Lung cancer is a widespread disease and it is well understood that systematic, non-invasive and early detection of this progressive and life-threatening disorder is of vital importance for patient outcomes. In this work we present a convergence of fa... Read More about Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer.

Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX (2017)
Journal Article
Wootton, A. J., Butcher, J. B., Kyriacou, T., Day, C. R., & Haycock, P. W. (2017). Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX. Engineering Applications of Artificial Intelligence, 64, 152-163. https://doi.org/10.1016/j.engappai.2017.05.014

Echo State Networks (ESNs) and a Nonlinear Auto-Regressive Moving Average model with eXogenous inputs (NARMAX) have been applied to multi-sensor time-series data arising from a test footbridge which has been subjected to multiple potentially damaging... Read More about Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX.