Index Catalog // ScholarsArchive@OSU

Predictive mapping of landtype association maps in three Oregon national forests

Creator:: Peterman, Wendy L.
Abstract:: This study explores the use of predictive mapping techniques in developing Landtype Association (LTA) maps for use in natural resource management. These maps are produced for the USDA Forest Service on a regional basis at a 1:100,000 scale. The goal of this study is to develop and test a method...
Resource Type:: Masters Thesis

Combining coordination mechanisms to improve performance in multi-robot teams

Creator:: Nasroullahi, Ehsan
Abstract:: Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
Resource Type:: Masters Thesis

Predicting activity type from accelerometer data

Creator:: Zheng, Yonglei
Abstract:: The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
Resource Type:: Masters Thesis

A study of methods for fine-grained object classification of arthropod specimens

Creator:: Lin, Junyuan
Abstract:: Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
Resource Type:: Masters Thesis

Active learning of constraints for semi-supervised clustering

Creator:: Xiong, Sicheng
Abstract:: Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
Resource Type:: Masters Thesis

Learning greedy policies for the easy-first framework

Creator:: Xie, Jun
Abstract:: Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
Resource Type:: Masters Thesis

Object detection in biological images using a search-based framework

Creator:: Lam, Michael
Abstract:: This thesis addresses a basic problem in computer vision, that of semantic labeling of images. Our work is aimed at object detection in biological images for evolutionary biology research. In particular, our goal is to detect nematocysts in Scanning Electron Microscope (SEM) images. This biological domain presents challenges for existing...
Resource Type:: Masters Thesis

Improving robotic grasping performance using machine learning techniques

Creator:: Goins, Alex Keith
Abstract:: Robots are being utilized in ever more complex tasks and environments to help humans with difficult or dangerous tasks. However, robotic grasping is still in its infancy and is one of the limiting factors which prevent the deployment of robots in the home and other assisted living scenarios. Traditional methods...
Resource Type:: Masters Thesis

Towards a national map of soil liquefaction susceptibility : modeling with heuristic and geotechnical methods

Creator:: Lindsley, Adam E.
Abstract:: This study investigates the use of predictive mapping techniques as well as geotechnical criteria in developing a multiregional soil liquefaction model and subsequent maps. The maps were produced using National Cooperative Soil Survey data, in the gSSURGO format, combined with soil liquefaction data gathered from studies, articles, and traditional seismic...
Resource Type:: Masters Thesis

Special Nuclear Material Analysis Using Temporal Gamma-Ray Spectroscopy and Machine Learning Methods

Creator:: Curtis, Jessica R.
Abstract:: Following thermal neutron induced fission, supervised machine learning and temporal gamma-ray spectroscopy methods were used to identify differences in the delayed gamma-ray spectra of Pu-239 and U-235. The temporal gamma-ray spectroscopy method takes advantage of the time-dependent decay of fission products. Employing Spearman's rank-order correlation coefficient and without prior knowledge...
Resource Type:: Masters Thesis

The Pursuit of Hoppiness : Propelling Hop into the Genomic Era

Creator:: Hill, Steven T.
Abstract:: Hop (Humulus lupulus L. var lupulus) is a plant of great cultural significance, used as a medicinal herb for thousands of years, and for flavor and as a preservative in brewing beer. Studies of the medicinal effects of the unique compounds produced by hop have led to interest from the...
Resource Type:: Masters Thesis

Simultaneous segmentation and classification of bird song using CNN

Creator:: Narasimhan, Revathy
Abstract:: In bioacoustics, automatic animal voice detection and recognition from audio recordings is an emerging topic for animal preservation. Our research focuses on bird bioacoustics, where the goal is to segment bird syllables from the recording and predict the bird species for the syllables. Traditional methods for this task addresses the...
Resource Type:: Masters Thesis

Image Based Crypto

Creator:: Basa, Gungor
Abstract:: The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a...
Resource Type:: Masters Thesis

Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

Creator:: Hooper, Samuel
Abstract:: Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
Resource Type:: Masters Thesis

ScholarsArchive@OSU

Predictive mapping of landtype association maps in three Oregon national forests

Combining coordination mechanisms to improve performance in multi-robot teams

Predicting activity type from accelerometer data

A study of methods for fine-grained object classification of arthropod specimens

Active learning of constraints for semi-supervised clustering

Learning greedy policies for the easy-first framework

Object detection in biological images using a search-based framework

Improving robotic grasping performance using machine learning techniques

Towards a national map of soil liquefaction susceptibility : modeling with heuristic and geotechnical methods

Special Nuclear Material Analysis Using Temporal Gamma-Ray Spectroscopy and Machine Learning Methods

The Pursuit of Hoppiness : Propelling Hop into the Genomic Era

Simultaneous segmentation and classification of bird song using CNN

Image Based Crypto

Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

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