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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 13.

Stamoulakatos, Anastasios and Cardona, Javier and McCaig, Chris and Murray, David and Filius, Hein and Atkinson, Robert and Bellekens, Xavier and Michie, Craig and Andonovic, Ivan and Lazaridis, Pavlos and Hamilton, Andrew and Hossain, Md. Moinul and Di Caterina, Gaetano and Tachtatzis, Christos (2020) Automatic annotation of subsea pipelines using deep learning. Sensors, 20 (3). 674. ISSN 1424-8220

Gallego, A. and Side, J. and Baston, S. and Waldman, S. and Bell, M. and James, M. and Davies, I. and O'Hara Murray, R. and Heath, M. and Sabatino, A. and McKee, D. and McCaig, C. and Karunarathna, H. and Fairley, I. and Chatzirodou, A. and Venugopal, V. and Nemalidinne, R. and Yung, T.Z. and Vögler, A. and MacIver, R. and Burrows, M. (2017) Large scale three-dimensional modelling for wave and tidal energy resource and environmental impact : methodologies for quantifying acceptable thresholds for sustainable exploitation. Ocean and Coastal Management, 147. pp. 67-77. ISSN 0964-5691

Heath, Michael and Sabatino, Alessandro and Serpetti, Natalia and McCaig, Chris and O'Hara Murray, Rory (2017) Modelling the sensitivity of suspended sediment profiles to tidal current and wave conditions. Ocean and Coastal Management, 147. pp. 49-66. ISSN 0964-5691

Sabatino, Alessandro and McCaig, Chris and Nemaliddine, R and Vengupal, V and O’Hara Murray, R,B. and Heath, Michael (2014) Simulating tides and waves in the east coast of Scotland. In: MASTS Annual Science Meeting 2014, 2014-09-03 - 2014-09-05, Heriot Watt University Conference Centre.

McCaig, Chris (2013) Statistical modelling of suspended sediment off Stonehaven. In: Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, 2013-08-27 - 2013-08-29.

McCaig, Chris and Fenton, A. and Graham, A. and Shankland, C. and Norman, R. (2013) Using process algebra to develop predator-prey models of within-host parasite dynamics. Journal of Theoretical Biology, 329. pp. 74-81. ISSN 0022-5193

McCaig, Chris and Speirs, Douglas and Heath, Michael (2012) Modelling diet composition dynamics among North Sea predatory fish using a length-structured partial ecosystem model. In: 6th World Fisheries Congress, 2012-05-07 - 2012-05-11.

McCaig, Chris and Begon, M. and Norman, R. and Shankland, C. (2011) A rigorous approach to investigating common assumptions about disease transmission. Theory in Biosciences, 130 (1). pp. 19-29. ISSN 1431-7613

McCaig, Chris and Norman, R. and Shankland, C. (2011) From individuals to populations: a mean field semantics for process algebra. Theoretical Computer Science, 412 (17). 1557–1580. ISSN 0304-3975

McCaig, Chris and Begon, M. and Shankland, C. and Norman, R. (2011) A symbolic investigation of superspreaders. Bulletin of Mathematical Biology, 73 (4). pp. 777-794. ISSN 0092-8240

McCaig, Chris and Norman, R. and Shankland, C. (2009) From individuals to populations : a symbolic process algebra approach to epidemiology. Mathematics in Computer Science, 2 (3). pp. 535-556. ISSN 1661-8270

Benkirane, S. and Hilston, J. and McCaig, Chris and Norman, R. and Shankland, C. (2009) Improved continuous approximation of PEPA models through epidemiological examples. Electronic Notes in Theoretical Computer Science, 229 (1). 59–74. ISSN 1571-0661

McCaig, Chris and Norman, R. and Shankland, C.; Horimoto, Katsuhisa and Regensburger, Georg and Rosenkranz, Markus and Yoshida, Hiroshi, eds. (2008) Process algebra models of population dynamics. In: Algebraic Biology. Lecture Notes in Computer Science . Springer, pp. 139-155. ISBN 978-3-540-85100-4

This list was generated on Tue Oct 15 03:42:57 2024 BST.