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Full-Text Articles in Artificial Intelligence and Robotics
An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly
An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they …
Hierarchical Active Learning Application To Mitochondrial Disease Protein Dataset, James D. Duin
Hierarchical Active Learning Application To Mitochondrial Disease Protein Dataset, James D. Duin
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
This study investigates an application of active machine learning to a protein dataset developed to identify the source of mutations which give rise to mitochondrial disease. The dataset is labeled according to the protein's location of origin in the cell; whether in the mitochondria or not, or a specific target location in the mitochondria's outer or inner membrane, its matrix, or its ribosomes. This dataset forms a labeling hierarchy. A new machine learning approach is investigated to learn the high-level classifier, i.e., whether the protein is a mitochondrion, by separately learning finer-grained target compartment concepts and combining the results. This …