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...
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...
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...
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...
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...
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...
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...
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...
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...
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...