Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Sunil Movva"'
Autor:
Manil Maskey, Udaysankar S. Nair, Sunil Movva, Rahul Ramachandran, Helen Conover, Ajinkya Kulkarni
Publikováno v:
Earth Science Informatics. 5:33-41
“Open science,” where researchers share and publish every element of their research process in addition to the final results, can foster novel ways of collaboration among researchers and has the potential to spontaneously create new virtual resea
Autor:
Michael D. Lueken, Steven M. Lazarus, Sunil Movva, Bradley Zavodsky, Sara Graves, Michael E. Splitt, Xiang Li, Rahul Ramachandran
Publikováno v:
Weather and Forecasting. 25:837-851
Data reduction tools are developed and evaluated using a data analysis framework. Simple (nonadaptive) and intelligent (adaptive) thinning algorithms are applied to both synthetic and real data and the thinned datasets are ingested into an analysis s
Autor:
Budhendra L. Bhaduri, Devin A. White, Neil Thomas, Adrian S. Z. Chase, Aaron T Myers, Rajasekar Karthik, Sunil Movva
Publikováno v:
SIGSPATIAL/GIS
The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more
Autor:
Xiang Li, Sarita Khaire, Sara Graves, Sunil Movva, Helen Conover, K. Keiser, Rahul Ramachandran
Publikováno v:
Computers & Geosciences. 31:1126-1134
This paper proposes a novel metadata solution to allow applications to intelligently use science data in an automated fashion. The solution provides rich syntactic and semantic metadata, where the semantic metadata is linked with an ontology to defin
Autor:
Sundar A. Christopher, Sunil Movva, K. Keiser, Helen Conover, Xiang Li, Richard T. McNider, Rahul Ramachandran, Sara Graves
Publikováno v:
Bulletin of the American Meteorological Society. 86:791-794
Publikováno v:
2009 International Symposium on Collaborative Technologies and Systems.
A small but growing number of scientists and researchers are beginning to harness Web 2.0 technologies as a transformative way of doing science. Since communication is at the heart of science, these technologies provide researchers easy mechanisms to
Publikováno v:
IGARSS (5)
On the emerging “Social Web,” millions of people offer their knowledge online in a collective knowledge system comprising an active community of motivated members posting problems and solutions in blogs, forums, mailing lists, collaborative porta
Publikováno v:
CEC/EEE
There is a need for specialized search engines focused on specific disciplines that can use domain knowledge to guide the user to find exactly the resources they are searching for. In addition, these engines should be able search multiple and heterog
Autor:
Xiang Li, Rahul Ramachandran, William M. Lapenta, Michael E. Splitt, Sunil Movva, M. Lueken, Steven M. Lazarus, B. Zavodsky, Sara Graves
Publikováno v:
IGARSS (3)
This paper presents a study on intelligent data thinning for satellite data. In particular, the focus is on the thinning of the Atmospheric Infrared Sounder (AIRS) profiles. A direct thinning method is first applied to a synthetic data set in order t
Autor:
Bilahari Akkiraju, Juan-Carlos Jusem, Sara Graves, Xiang Li, J. Terry, Robert Atlas, Sunil Movva, David Emmitt, Rahul Ramachandran, Steven Greco
Publikováno v:
KDD
Fronts are significant meteorological phenomena of interest. The extraction of frontal systems from observations and model data can greatly benefit many kinds of research and applications in atmospheric sciences. Due to the huge amount of observation