This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
Intermodal freight transportation uses at least two different transportation modes (e.g., truck, rail, ship, air) to move freight loads that are in the same transportation unit (e.g., a shipping container) from origin to destination without handling the goods themselves. The increasing shift to intermodal transportation and the growth of freight...
Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
Software testing is of critical importance for the success of software projects. Current inefficient testing methods often still take up half or more of a software project's budget. Automatic test data generation is the most promising way to lower the software testing cost. Manually creating testing data is expensive and...
Many problems in ecology and conservation biology can be formulated and solved using machine learning algorithms for multi-label classification. This dissertation addresses three topics related to predicting the distributions of multiple species. It improves existing methods and proposes a new modeling paradigm to address the multi-species, multi-label problem. The first...
This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy
learning algorithms o er teachers little flexibility in how policies are taught. In particular,
one of two learning modes is typically considered: 1)...
Worst-case analysis is often meaningless in practice. Some problems never reach the anticipated worst-case complexity. Other solutions get bogged down with impractical constants during implementation, despite having favorable asymptotic running times. In this thesis, we investigate these contrasts in the context of finding maximum flows in planar digraphs. We suggest...
This dissertation constitutes a multi-scale quantitative and qualitative investigation of patterns of urban development in metropolitan regions of the United States. This work has generated a comprehensive data set on spatial patterns of metropolitan development in the U.S. and an approach to the study of such patterns that can be...
The thermophilic cyanobacterium Thermosynechococcus elongatus was examined for the ability to sequester CO₂ while producing hydrogen (H₂), polyhydroxybutyrate (PHB), lipids, and glycogen. H₂ was produced at a maximum rate of 188 nmol H₂ mg Chl a⁻¹ hr⁻¹. Hydrogen production occurred in the presence of methyl viologen but the cells were...
Linear transformation for dimension reduction is a well established problem in the field of machine learning. Due to the numerous observability of parameters and data, processing of the data in its raw form is computationally complex and difficult to visualize. Dimension reduction by means of feature extraction offers a strong...