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  • NRNC05 Automatic defect recognition of single-v welds using full matrix capture data, computer vision and multi-layer perceptron artificial neural networks

    The British Institute of Non-Destructive Testing

    This paper describes the development of an automatic defect recognition system applicable to full matrix capture (FMC) imaged data. Computer vision principles were used on FMC-reconstructed images for feature extraction and combined with a multi-layer perceptron artificial neural network for classification.

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  • NRN024 Intra-cavity chromatic dispersion impacts on 10Gb/s optical OFDM transmissions over 25km dual-RSOA-based self-seeded PON systems

    IEEE Xplore

    • Sensors and Devices, 
    • Modelling

    In this paper, based on our recently reported real-time dual-reflective semiconductor optical amplifier (RSOA)- based self-seeded adaptive optical orthogonal frequency-division multiplexing (OOFDM) transmitters, detailed experimental explorations are undertaken.

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  • NRNC05 Automatic defect recognition of single-v welds using full matrix capture data, computer vision and multi-layer perceptron artificial neural networks

    Insight - Non-Destructive Testing and Condition Monitoring,

    • Materials

    This paper describes the development of an automatic defect recognition system applicable to full matrix capture (FMC) imaged data. Computer vision principles were used on FMC-reconstructed images for feature extraction and combined with a multi-layer perceptron artificial neural network for classification. A wide variety of single-v weld training samples were used to train the artificial neural network, which was then tested to determine its accuracy. Automatic defect classification of real single-v weld inspections achieved a high level of success

  • NRN106 - A new framework for large strain electromechanics based on convex multi-variable strain energies: Conservation laws, hyperbolicity and extension to electro-magneto-mechanics

    Science Direct

    • Modelling, 
    • Knowledge Transfer, 
    • Materials

    This work is the third on a series of papers by Gil and Ortigosa (Gil and Ortigosa 2016; Ortigosa and Gil 2016) on the development of a new computational framework for the analysis of Electro Active Polymers, where the concept of polyconvexity (Ball 1976) is extended to the case of electro-magneto-mechanical energy functionals. Specifically, four key novelties are incorporated in this paper.

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  • NRN073 Technique for the Comparison of Light Spectra from Natural and Laboratory Generated Lightning Current Arcs

    Applied Physics Letters

    • Sensors and Devices

    This work highlights the potential use for spectrographic techniques in the study of lightning interactions with surrounding media and materials, and in natural phenomena such as recently observed ball lightning.

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