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Transforming automated inspection & non-destructive testing: world-leading Open Access research on robotics, sensors & ultrasonics

Strathprints makes available scholarly Open Access content by researchers within the Centre for Ultrasonic Engineering, based within Electronic & Electrical Engineering.

Research at CUE brings together next generation robotics with sensing technology to enable inspection of high value components, such as aerospace components, at the point of manufacture. Non-destructive testing techniques using ultrasound and other sensors can then be deployed to assess components for structural faults or damage and thereby ensure they are built correctly and more efficiently. Research at CUE is to be stimulated by the construction of a new £2.5 million state-of-the-art Robotically-Enabled Sensing (RES) hub within the Department of Electronic & Electrical Engineering (EEE).

Explore the Open Access research by EEE, or explore all of Strathclyde's Open Access research...

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Jump to: 2010 | 2008
Number of items: 4.

2010

He, F. and Brown, M. and Yue, H., Chinese NSFC Project Grant Number: 30770560 (Funder) (2010) Maximin and Bayesian robust experimental design for measurement set selection in modelling biochemical regulatory systems. International Journal of Robust and Nonlinear Control, 20 (9). pp. 1059-1078. ISSN 1049-8923

He, Fei and Yue, Hong and Brown, Martin (2010) Investigating Bayesian robust experimental design with principles of global sensitivity analysis. In: 9th International Symposium on Dynamics and Control of Process Systems (DYCOPS 2010), 2010-07-05 - 2010-07-07.

2008

Yue, H. and Brown, Martin and He, Fei and Jia, J.F. and Kell, Douglas B. (2008) Sensitivity analysis and robust experimental design of a signal transduction pathway system. International Journal of Chemical Kinetics, 40 (11). pp. 730-741. ISSN 0538-8066

He, F. and Brown, M. and Yue, H. and Yeung, L.F.; (2008) Robust experimental design and feature selection in signal transduction pathway modeling. In: IEEE International Joint Conference on Neural Networks, 2008. IJCNN 2008. IEEE, CHN, pp. 1544-1551. ISBN 978-1-4244-1820-6

This list was generated on Thu Apr 2 17:42:07 2020 BST.