 Announcements |
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Evita Version 0.14 Released
fowler - 2002-07-23 12:04 - Evita
With this release, feature detection is now denoised using a multiscale
feature detector. That is, features are detected within basebands at various
resolutions, and those that persist across all scales are retained.
Evita Version 0.13 Released
fowler - 2002-07-09 11:44 - Evita
Evita now fully supports the coding and visualization of datasets with both
rectangular and curvilinear grids. Rectangular grids are implicit; that is,
an identifier in the ds file header indicates the presence of a rectangular
| About EVITA |
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The Efficient Visualization and Interrogation of Terascale Datasets (EVITA) project is a three-year research effort funded by the Large Data and Scientific Software Visualization Program of the National Science Foundation and is composed of research teams at Mississippi State University, The Ohio State University, and Rensselaer Polytechnic Institute. The EVITA project is designing a prototype, integrated system to facilitate exploration of terascale datasets by using a wavelet-based representational scheme allowing ranked access to macroscopic data features. The EVITA system provides a general visualization environment for terascale data on rectilinear and curvilinear grids, and is applicable to computational-field-simulation and experimental datasets arising in applications such as computational fluid dynamics, environmental sciences, electromagnetics, and structural mechanics.
| General Information & Resources |
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The following information & resources are available for the general EVITA user:
| Information & Resources for Developers |
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The following resources are available for EVITA developers or potential EVITA developers:
- Source Code -- the latest development version of EVITA available via CVS
- Project Page @ SourceForge -- the page for the EVITA project maintained by SourceForge
| Resources for Team Evita Members |
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The resources are only available for EVITA team members.
| Acknowledgments |
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This work is funded primarily by the National Science Foundation (NSF) through the Large Data and Scientific Software Visualization Program, Grant No. ACI-9982344, with additional funding from an NSF CAREER Award (ACI-9734483), an NSF ITR Award (ACI-0085969), and the Engineering Research Center (ERC) at Mississippi State University. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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