Automatic Annotation of Subsea Pipelines Using Deep Learning

Autor: Anastasios Stamoulakatos, Javier Cardona, Chris McCaig, David Murray, Hein Filius, Robert Atkinson, Xavier Bellekens, Craig Michie, Ivan Andonovic, Pavlos Lazaridis, Andrew Hamilton, Md Moinul Hossain, Gaetano Di Caterina, Christos Tachtatzis

Publikováno v: Sensors, Vol 20, Iss 3, p 674 (2020)

Regulatory requirements for sub-sea oil and gas operators mandates the frequent inspection of pipeline assets to ensure that their degradation and damage are maintained at acceptable levels. The inspection process is usually sub-contracted to surveyo

Externí odkaz: https://doaj.org/article/3a345fbd6c8e4549a4f21dccf621295d

Large scale three-dimensional modelling for wave and tidal energy resource and environmental impact: Methodologies for quantifying acceptable thresholds for sustainable exploitation

Autor: Michael R. Heath, Iain Fairley, David McKee, Ian M. Davies, Chris McCaig, Antonia Chatzirodou, Arne Vögler, Michael Bell, Simon Mark Waldman, Mark James, Alessandro D. Sabatino, Susana Baston, T. Z. Yung, Alejandro Gallego, R. O'Hara Murray, Vengatesan Venugopal, R. MacIver, Michael T. Burrows, Reddy Nemalidinne, Harshinie Karunarathna, Jonathan Charles Side

Publikováno v: Gallego, A, Side, J, Baston, S, Waldman, S, Bell, M, James, M, Davies, I, O'Hara Murray, R, Heath, M, Sabatino, A, McKee, D, McCaig, C, Karunarathna, H, Fairley, I, Chatzirodou, A, Venugopal, V, Nemalidinne, R, Yung, T Z, Vögler, A, MacIver, R & Burrows, M 2016, ' Large scale three-dimensional modelling for wave and tidal energy resource and environmental impact: Methodologies for quantifying acceptable thresholds for sustainable exploitation ', Ocean & Coastal Management . https://doi.org/10.1016/j.ocecoaman.2016.11.025

We describe a modelling project to estimate the potential effects of wave & tidal stream renewables on the marine environment. • Realistic generic devices to be used by those without access to the technical details available to developers are descr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd9d4926359ead025cb2b45adda9abdb
https://doi.org/10.1016/j.ocecoaman.2016.11.025

Modelling wave–current interactions off the east coast of Scotland

Autor: Michael R. Heath, Chris McCaig, Alessandro D. Sabatino, Rory O'Hara Murray

Publikováno v: Ocean Science, Vol 12, Iss 4, Pp 875-897 (2016)

Densely populated coastal areas of the North Sea are particularly vulnerable to severe wave conditions, which overtop or damage sea-defences leading to dangerous flooding. Around the shallow southern North Sea, where the coastal margin is low-lying a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0450a115fefe333d520c8de20d6c483
http://www.ocean-sci.net/12/875/2016/os-12-875-2016.pdf

Modelling diet composition dynamics among North Sea predatory fish using a length-structured partial ecosystem model

Autor: Chris McCaig, Douglas Speirs, Michael Heath

Publikováno v: 6th World Fisheries Congress
University of Strathclyde

Multispecies fisheries management approaches must take account of the array of trophic interactions within the ecosystem. Studies of the gut contents of fish stocks in the North Sea show decadal changes in diet composition, as might be expected when

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c522d68894baacfe9c7948e62df0482b
https://strathprints.strath.ac.uk/41930/1/Modelling_diet_composition_dynamics.pdf

A symbolic investigation of superspreaders

Autor: Michael Begon, Chris McCaig, Rachel Norman, Carron Shankland

Publikováno v: Bulletin of mathematical biology. 73(4)

Superspreaders are an important phenomenon in the spread of infectious disease, accounting for a higher than average number of new infections in the population. We use mathematical models to compare the impact of supershedders and supercontacters on

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afc7bd2bbc2e329f9555a320586864f8
https://pubmed.ncbi.nlm.nih.gov/21181505