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Inductive learning of feature-tracking rules for scientific visualization

Descriptive

Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Genre (authority = RULIB-FS)
Other
Genre (authority = marcgt)
technical report
PhysicalDescription
InternetMediaType
application/pdf
Extent
1 online resource (8 pages) : illustrations
Note (type = special display note)
Technical report hpcd-tr-29
Name (authority = RutgersOrg-School); (type = corporate)
NamePart
School of Arts and Sciences (SAS) (New Brunswick)
Name (authority = RutgersOrg-Department); (type = corporate)
NamePart
Computer Science (New Brunswick)
TypeOfResource
Text
TitleInfo
Title
Inductive learning of feature-tracking rules for scientific visualization
Subject (authority = local)
Topic
Mechanical engineering
Subject (authority = local)
Topic
Scientific visualization
Subject (authority = local)
Topic
Decision tree induction
Abstract (type = abstract)
Numerical simulation and scientific visualization are often used by scientists to help them understand physical phenomena. One approach taken by some visualization systems is to identify and quantify coherent features in a simulation and track their trajectories as they evolve over time. Such feature-tracking systems operate either by relying on manual (human) efforts, or by utilizing ad hoc programs embodying heuristics that are computationally expensive to use. Our research demonstrates the use of inductive learning to construct feature-tracking programs for fluid flows. Our approach uses manually generated feature trajectories as training data, and applies inductive learning to construct feature-tracking rules that can then be incorporated into a feature-tracking program. This results in a more efficient system that can match up objects across large time steps without inspecting intermediate steps. We demonstrate our approach on the problem of tracking vortices in turbulent viscous fluids.
Name (type = personal)
NamePart (type = family)
Banerjee
NamePart (type = given)
Arunava
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Hirsh
NamePart (type = given)
Haym
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Ellman
NamePart (type = given)
Thomas
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
1995-04
RelatedItem (type = host)
TitleInfo
Title
Computer Science (New Brunswick)
Identifier (type = local)
rucore21032500001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-dk2t-3y08
Genre (authority = ExL-Esploro)
Technical Documentation
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This Item is protected by copyright and/or related rights.You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use.For other uses you need to obtain permission from the rights-holder(s).
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Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
Document
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1.4
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GPL Ghostscript 9.07
DateCreated (point = start); (encoding = w3cdtf); (qualifier = exact)
2018-06-06T12:36:04
DateCreated (point = start); (encoding = w3cdtf); (qualifier = exact)
2018-06-06T12:36:04
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