Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Zoe Guillen"'
Autor:
Kerstin Kleese van Dam, Eric G. Stephan, John E. Hathaway, Todd O. Elsethagen, Willy J. Gorrissen, Yan Liu, James A. Dirks, Ian Gorton, Zoe Guillen, Carina Lansing, Daniel C. Skorski
Publikováno v:
Building Simulation. 7:335-343
Modern workflow systems can enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve. However as a result of these new capabilities the scienc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1c731952f096b125feb9c5f377d0cb1
https://doi.org/10.1007/s12273-014-0171-x
https://doi.org/10.1007/s12273-014-0171-x
Autor:
Carina Lansing, Ellen A. Porter, Chandri Sivaramakrishnan, Karen Schuchardt, Zoe Guillen, Ian Gorton, Vicky L. Freedman
Publikováno v:
CTS
In scientific simulation, scientists use measured data to create numerical models, execute simulations and analyze results from advanced simulators executing on high performance computing platforms. This process usually requires a team of scientists
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c8fa63a57e263d038bafd1e6c65de2a
https://doi.org/10.1109/cts.2015.7210435
https://doi.org/10.1109/cts.2015.7210435
Autor:
Ingela Lanekoff, Kerstin Kleese van Dam, Julia Laskin, Carina Lansing, Zoe Guillen, Mathew Thomas, Erin A. Miller, James P. Carson, Matthew J. Marshall, Andrew P. Kuprat
Temporal and spatial resolution of chemical imaging methodologies such as X-ray tomography are rapidly increasing, leading to more complex experimental procedures and fast-growing data volumes. Automated analysis pipelines and big data analytics are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c71b2fd7e0f79360303c55fe467876a2
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-367262
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-367262
Autor:
Carina Lansing, James P. Carson, Abigail L. Corrigan, Mathew Thomas, Erin A. Miller, Craig Szymanski, Yan Liu, Andrew P. Kuprat, Julia Laskin, Daniel R. Einstein, Brandi S. Heath, Seun Ryu, Galya Orr, Ingela Lanekoff, Matthew Marshall, Dongsheng Li, Paulo Pinheiro da Silva, Kerstin Kleese van Dam, Zoe Guillen
Publikováno v:
eScience
The Chemical Imaging Initiative at the Pacific Northwest National Laboratory (PNNL) is creating a ‘Rapid Experimental Analysis’ (REXAN) Framework, based on the concept of reusable component libraries. REXAN allows developers to quickly compose an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acf24493e517a3bdfef81fadd6f8a912
https://doi.org/10.1109/escience.2012.6404463
https://doi.org/10.1109/escience.2012.6404463
Autor:
Zoe Guillen, Carina Lansing, Yan Liu, Kerstin Kleese van Dam, Jian Yin, Ian Gorton, Abigail L. Corrigan
Publikováno v:
IPDPS Workshops
Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and thei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87c4eecaf02cfbe012d145ee97ca67c3
https://doi.org/10.1109/ipdps.2011.261
https://doi.org/10.1109/ipdps.2011.261
Autor:
Freedman, Vicky, Lansing, Carina, Porter, Ellen, Schuchardt, Karen, Guillen, Zoe, Sivaramakrishnan, Chandri, Gorton, Ian
Publikováno v:
2015 International Conference on Collaboration Technologies & Systems (CTS); 2015, p280-286, 7p
Publikováno v:
2015 International Conference on Collaboration Technologies & Systems (CTS); 2015, p1-9, 9p
Autor:
Thomas, Mathew, Kleese-van Dam, Kerstin, Marshall, Matthew J., Kuprat, Andrew, Carson, James, Lansing, Carina, Guillen, Zoe, Miller, Erin, Lanekoff, Ingela, Laskin, Julia
Publikováno v:
Synchrotron Radiation News; Mar/Apr2015, Vol. 28 Issue 2, p10-14, 5p
Big Data has been much in the news in recent years, and the advantages conferred by the collection and analysis of large datasets in fields such as marketing, medicine and finance have led to claims that almost any real world problem could be solved