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dc.creatorSeeley, Charles Henry
dc.date.accessioned2012-06-07T22:29:25Z
dc.date.available2012-06-07T22:29:25Z
dc.date.created1992
dc.date.issued1992
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-1992-THESIS-S452
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references.en
dc.description.abstractNot availableen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectnuclear engineering.en
dc.subjectMajor nuclear engineering.en
dc.subject.lcshNeural networks (Computer science)en
dc.subject.lcshFlow visualization.en
dc.subject.lcshOptical data processing.en
dc.subject.lcshFluid dynamics.en
dc.titleNeural network approaches to tracer identification as related to PIV researchen
dc.typeThesisen
thesis.degree.disciplinenuclear engineeringen
thesis.degree.nameM.S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


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