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Filtering by: Committee Member Jones, Julia Remove constraint Committee Member: Jones, Julia Degree Field Computer Science Remove constraint Degree Field: Computer Science

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A General Framework for Predicting the Geospatial Distribution of Botanical Species

Creator:

Chick, Jesse S.

Abstract:

The local presence or absence of individual botanical species can be predicted with high accuracy by a simple feed-forward neural network, using only local climate data to make inference. This study proposes a framework for learning these predictive models, demonstrates highly accurate predictions for species with a sufficiently large area...

Resource Type:

Honors College Thesis
3D Voronoi Subdivision for Simulating Destructible and Granular Materials

Creator:

Clothier, Matthew M.

Abstract:

In many traditional computer graphics applications, rendered scenes typically utilize 3D meshes to represent objects within an environment. As the demand to further improve the realism of graphics applications increases, such as for movies and games, it is becoming more important to represent the inner volumes of object meshes. In...

Resource Type:

Dissertation
Interactive visualization of diversity in multivariate data sets unified across fields of study

Creator:

Pham, Tuan N. T.

Abstract:

The study of the diversity of multivariate objects shares common characteristics across disciplines, including ecology and organizational management. Nevertheless, experts in these two disciplines have adopted somewhat separate diversity concepts and analysis techniques, limiting the ability of potentially sharing and cross comparing these concerns. Moreover, while complex diversity data may...

Resource Type:

Dissertation
Probabilistic models for quality control in environmental sensor networks

Creator:

Dereszynski, Ethan W.

Abstract:

Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...

Resource Type:

Dissertation
Detection and Segmentation of Bird Song in Noisy Environments

Creator:

Neal, Lawrence W.

Abstract:

Recent work in machine learning concerns the detection and identification of bird species from audio recordings of their vocalizations. Such analysis can yield valuable ecological information concerning the activity and distribution of species in the wild. Current species-identification methods require individual syllables of bird audio as input, but field-collected audio...

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Honors College Thesis

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Academic Affiliation

Electrical Engineering and Computer Science3

Advisor

Alder, Jay1
Bailey, Mike1
Dietterich, Thomas G.1
Fern, Xiaoli Z.1
Metoyer, Ronald1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2012 to 2021

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Committee Member

Jones, Julia[remove]5
Yeh, Harry2
Zhang, Eugene2
Burnett, Margaret1
Coakley, James1
more Committee Members »

Creator

Chick, Jesse S.1
Clothier, Matthew M.1
Dereszynski, Ethan W.1
Neal, Lawrence W.1
Pham, Tuan N. T.1

Date

Date range begin – Date range end

Current results range from 2012 to 2021

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Decade

2020-20291
2010-20194

Degree Field

Computer Science[remove]5

Degree Level

Doctoral3
Bachelor's2

Degree Name

Doctor of Philosophy (Ph.D.)3
Honors Bachelor of Science (H.B.S.)2

Language

English [eng]5

License

All rights reserved4

Non-Academic Affiliation

Oregon State University. Graduate School2
Oregon State University. Honors College2

Peer Reviewed

No5

Resource Type

Dissertation3
Honors College Thesis2

Rights Statement

In Copyright5

Subject

Biodiversity -- Statistical methods1
Cluster analysis1
Data transmission systems -- Quality control1
Detectors -- Quality control1
Environmental monitoring -- Quality control1
more Subjects »

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