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Engineering

Theses/Dissertations

2023

Thesis

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Full-Text Articles in Physical Sciences and Mathematics

Breast Density Classification Using Deep Learning, Conrad Thomas Testagrose Jan 2023

Breast Density Classification Using Deep Learning, Conrad Thomas Testagrose

UNF Graduate Theses and Dissertations

Breast density screenings are an accepted means to determine a patient's predisposed risk of breast cancer development. Although the direct correlation is not fully understood, breast cancer risk increases with higher levels of mammographic breast density. Radiologists visually assess a patient's breast density using mammogram images and assign a density score based on four breast density categories outlined by the Breast Imaging and Reporting Data Systems (BI-RADS). There have been efforts to develop automated tools that assist radiologists with increasing workloads and to help reduce the intra- and inter-rater variability between radiologists. In this thesis, I explored two deep-learning-based approaches …


Towards A Prototype Paleo-Detector For Supernova Neutrino And Dark Matter Detection, Emilie Marie Lavoie-Ingram Jan 2023

Towards A Prototype Paleo-Detector For Supernova Neutrino And Dark Matter Detection, Emilie Marie Lavoie-Ingram

UNF Graduate Theses and Dissertations

Using ancient minerals as paleo-detectors is a proposed experimental technique expected to transform supernova neutrino and dark matter detection. In this technique, minerals are processed and closely analyzed for nanometer scale damage track remnants from nuclear recoils caused by supernova neutrinos and possibly dark matter. These damage tracks present the opportunity to directly detect and characterize the core-collapse supernova rate of the Milky Way Galaxy as well as the presence of dark matter. Current literature presents theoretical estimates for these potential tracks, however, there is little research investigating the experimental feasibility of this technique. At the University of North Florida, …


Extracting Road Surface Marking Features From Aerial Images Using Deep Learning, Michael Kimollo Jan 2023

Extracting Road Surface Marking Features From Aerial Images Using Deep Learning, Michael Kimollo

UNF Graduate Theses and Dissertations

The traffic and roadway safety agencies spend significant efforts each year collecting roadway data, including lane configurations and other road surface marking data, such as areas with school zone markings, sidewalks, left turns, right turns, bicycle lanes, etc., for safety analysis and planning purposes. The current manual data collection methods pose significant operational and quality control challenges as they are costly and prone to errors. In addition to that the manual data collection is labor intensive and takes too much time involving high equipment costs, questionable data accuracy guarantees, and concerns about the safety of the crew.

This study aims …


Development Of High Kinetic Inductance Superconducting Nanowire Devices On High Permittivity Strontium Titanate Substrates, Jamie Timmons Jan 2023

Development Of High Kinetic Inductance Superconducting Nanowire Devices On High Permittivity Strontium Titanate Substrates, Jamie Timmons

UNF Graduate Theses and Dissertations

This thesis involves the fabrication and characterization of devices made from two different superconducting materials: yttrium barium copper oxide (YBCO), a high-TC complex oxide, and niobium nitride (NbN), a low-TC transition metal nitride. Both types of devices are fabricated on strontium titanate substrates, which provides a good lattice match to YBCO and also an extremely large permittivity at low temperature. We demonstrate that wet etching of YBCO thin films via bromine can be a viable microfrabriation technique for the material. Using approximately 35 nm thick epitaxially grown YBCO on an STO substrate, we were able to fabricate YBCO “microwires” with …


Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes Jan 2023

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …