Attenuation of plane and high order modes in a circular and annular lined duct by D.J. Snow

Get full text

Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain by Christel Prudhomme, Simon J. Dadson, D. Morris, Jennifer Williamson, George Goodsell, Sue M. Crooks, Leonore Boelee, Helen N. Davies, Gwen Buys, Thomas Lafon, Glen Watts

Get full text

Shifts in the source and composition of dissolved organic matter in Southwest Greenland lakes along a regional hydro-climatic gradient by Christopher L. Osburn, Nicholas John Anderson, Colin A. Stedmon, Madeleine E. Giles, Erika J. Whiteford, Terry J. McGenity, Alex J. Dumbrell, Graham J. Underwood

Get full text

Spatial variations in snowpack chemistry, isotopic composition of NO3−and nitrogen deposition from the ice sheet margin to the coast of western Greenland by Chris J. Curtis, Jan Kaiser, Alina Marca, Nicholas John Anderson, Gavin L. Simpson, Vivienne J. Jones, Erika J. Whiteford

Get full text

FrictionSegNet: simultaneous semantic segmentation and friction estimation using hierarchical latent variable models by Mohammad Otoofi, Leo Laine, Leon Henderson, William J.B. Midgley, Laura Justham, James Fleming

Get full text

Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube by Ashleigh Filtness, Eleonora Papadimitriou, B. Leskovsek, N. Focant, Heike Martensen, V. Sgarra, D. Shingo Usami, A. Soteropoulos, S. Stadlbauer, Athanasios Theofilatos, George Yannis, A. Ziakopoulos, K. Diamandouros, C. Durso, Charles Goldenbeld, B. Loenis, G. Schermers, J.-H. van Petegem, R. Elvik, I.S. Hesjevoll, Claire Quigley, Evita Papazikou

Get full text

Use of artificial intelligence to improve resilience and preparedness against adverse flood events by Sara Saravi, Roy Kalawsky, Demetrios Joannou, Monica Rivas Casado, Guangtao Fu, Fanlin Meng

“…This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. …”
Get full text

Supplementary Information Files for "Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events" by Sara Saravi, Roy Kalawsky, Demetrios Joannou, Monica Rivas Casado, Guangtao Fu, Fanlin Meng

“…This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. …”
Get full text