Physical Sciences and Mathematics Commons^™

The Tidal Prism, Viable Eelgrass Habitat, And The Effects Of Sea Level Rise In Morro Bay, Kaden A. Caliendo

Master's Theses

The tidal prism, or the volume of water exchanged from the sea to an estuary from mean low to mean high tide, influences system hydrodynamics and ecological functioning. Since 1884, the tidal prism in Morro Bay, California has been estimated to be decreasing over time due to sedimentation from upstream practices. What is the current tidal prism in Morro Bay and how will that change with sea level rise? How will eelgrass respond to rising sea levels?

For this study, inexpensive tidal gauges were deployed at four locations in Morro Bay from March to August 2023 to measure spatially varying …

Interactive Water Vortex Exhibit, Simon Way, Emily Laing, Roqaya Naseri, Makenzie Kan

Mechanical Engineering

The San Luis Obispo Children’s Museum requested an interactive water vortex exhibit to both engage and entertain inquisitive guests, ages two to eight. The goal was to design and manufacture an exhibit that would educate its users on the fluid mechanics behind water vortices. They activate the mechanics by spinning a wheel, which is perceived as the catalyst to manipulate the flow of water to successfully create a whirlpool. Our team has created an interactive display that will enlighten young minds, providing the museum with an educational exhibit which shares a concept not currently taught by any other. Our project …

Robust And Uncertainty-Aware Image Classification Using Bayesian Vision Transformer Model, Fazlur Rahman Bin Karim

Theses and Dissertations

Transformer Neural Networks have emerged as the predominant architecture for addressing a wide range of Natural Language Processing (NLP) applications such as machine translation, speech recognition, sentiment analysis, text anomaly detection, etc. This noteworthy achievement of Transformer Neural Networks in the NLP field has sparked a growing interest in integrating and utilizing Transformer models in computer vision tasks. The Vision Transformer (ViT) model efficiently captures long-range dependencies by employing a self-attention mechanism to transform different image data into meaningful, significant representations. Recently, the Vision Transformer (ViT) has exhibited incredible performance in solving image classification problems by utilizing ViT models, thereby …

Hypothyroid Disease Analysis By Using Machine Learning, Sanjana Seelam

Electronic Theses, Projects, and Dissertations

Thyroid illness frequently manifests as hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier. To properly monitor and cure this illness, accurate detection is essential. In order …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Patterned Heating Induced Propulsion, Saajid A. Aman

Electronic Thesis and Dissertation Repository

This study explores propulsion effects generated by patterned heating acting on smooth and corrugated surfaces. The model problem assumes that the upper plate moves freely, and the lower plate is stationary, equipped with grooves, and exposed to spatially distributed heating. Our findings identify two distinct propulsion effects: thermal streaming and thermal drift. Thermal streaming occurs when given sufficient heating intensity with net flow in the left or right direction characterized by a pitchfork bifurcation. The efficiency of this technique can be controlled using the wavelength of heating. Thermal drift represents a pattern interaction effect. Its strength depends on the relative …

Tidal Bed Stress Asymmetry And Sediment Transport In Estuaries, Austin Scott Hudson

Dissertations and Theses

Rivers and estuaries provide numerous ecological, economic, and cultural resources. The value of these resources is greatly influenced by sediment transport processes, which can be affected by human activities and climate variability. A key driver of sediment transport in tidal rivers and estuaries is tidal asymmetry of velocity and bed stress, which can manifest from both non-linear tidal interactions and linear interactions among astronomical tidal constituents.

In this study, an analytical framework is developed to examine and describe the dynamics of bed stress asymmetry in semidiurnal, diurnal, and mixed-tide estuaries (Chapter 1). While tidal velocity asymmetry has been previously analyzed, …

Integration Of Algae And Biomass Processes To Synthesize Renewable Bioproducts For The Circular Economy, Jessica Martin

USF Tampa Graduate Theses and Dissertations

Rapid population growth and global industrialization have substantially heightened the demand for fossil-based fuels and products in various sectors of the global economy, including energy production, transportation fuels, and as raw materials for petrochemicals. The intense consumption of fossil fuels has caused immense environmental impacts, especially pertaining to carbon dioxide emissions. Shifting to renewable feedstocks (raw materials) is expected to reduce these emissions by lowering the carbon footprint of fuels and products compared to traditional fossil-derived alternatives. This transition aligns with the goal of creating a sustainable and circular economy, emphasizing efficient resource use, and reducing waste generation through recycling …

Integration Of Algae And Biomass Processes To Synthesize Renewable Bioproducts For The Circular Economy, Jessica Martin

USF Tampa Graduate Theses and Dissertations

Rapid population growth and global industrialization have substantially heightened the demand for fossil-based fuels and products in various sectors of the global economy, including energy production, transportation fuels, and as raw materials for petrochemicals. The intense consumption of fossil fuels has caused immense environmental impacts, especially pertaining to carbon dioxide emissions. Shifting to renewable feedstocks (raw materials) is expected to reduce these emissions by lowering the carbon footprint of fuels and products compared to traditional fossil-derived alternatives. This transition aligns with the goal of creating a sustainable and circular economy, emphasizing efficient resource use, and reducing waste generation through recycling …

Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov

Doctoral Dissertations

Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …

Machine Learning Modeling Of Polymer Coating Formulations: Benchmark Of Feature Representation Schemes, Nelson I. Evbarunegbe

Masters Theses

Polymer coatings offer a wide range of benefits across various industries, playing a crucial role in product protection and extension of shelf life. However, formulating them can be a non-trivial task given the multitude of variables and factors involved in the production process, rendering it a complex, high-dimensional problem. To tackle this problem, machine learning (ML) has emerged as a promising tool, showing considerable potential in enhancing various polymer and chemistry-based applications, particularly those dealing with high dimensional complexities.

Our research aims to develop a physics-guided ML approach to facilitate the formulations of polymer coatings. As the first step, this …

Thermal Conductivity And Mechanical Properties Of Interlayer-Bonded Graphene Bilayers, Afnan Mostafa

Masters Theses

Graphene, an allotrope of carbon, has demonstrated exceptional mechanical, thermal, electronic, and optical properties. Complementary to such innate properties, structural modification through chemical functionalization or defect engineering can significantly enhance the properties and functionality of graphene and its derivatives. Hence, understanding structure-property relationships in graphene-based metamaterials has garnered much attention in recent years. In this thesis, we present molecular dynamics studies aimed at elucidating structure-property relationships that govern the thermomechanical response of interlayer-bonded graphene bilayers.

First, we present a systematic and thorough analysis of thermal transport in interlayer-bonded twisted bilayer graphene (IB-TBG). We find that the introduction of interlayer C-C …

Syntheses, Photophysics, & Application Of Porphyrinic Metal-Organic Frameworks, Zachary L. Magnuson

USF Tampa Graduate Theses and Dissertations

Porphyrins are a group of heterocyclic macrocycles that play crucial roles in various biological processes such as electron transfer, catalysis, and sensing. Hemoglobin, which carries oxygen in the blood of mammals, and chlorophyll, which drives photosynthesis in plants and algae, are both porphyrins. The ability of porphyrins to bind metal ions and their unique electronic and photophysical properties make them an excellent platform for designing functional materials for various applications, often drawing inspiration from their function in nature. Metal-organic frameworks (MOFs) are a class of porous materials that have been extensively studied in recent years due to their high surface …

Syntheses, Photophysics, & Application Of Porphyrinic Metal-Organic Frameworks, Zachary L. Magnuson

USF Tampa Graduate Theses and Dissertations

Porphyrins are a group of heterocyclic macrocycles that play crucial roles in various biological processes such as electron transfer, catalysis, and sensing. Hemoglobin, which carries oxygen in the blood of mammals, and chlorophyll, which drives photosynthesis in plants and algae, are both porphyrins. The ability of porphyrins to bind metal ions and their unique electronic and photophysical properties make them an excellent platform for designing functional materials for various applications, often drawing inspiration from their function in nature. Metal-organic frameworks (MOFs) are a class of porous materials that have been extensively studied in recent years due to their high surface …

Determining The Preparedness Of Nursing Programs And Faculty For The Next Generation Nclex-Rn, Heather Hartness

ATU Theses and Dissertations 2021 - Present

Fifty-two nursing faculty from ADN (Associate Degree Nursing) and BSN (Bachelor of Science in Nursing) programs in the state of Arkansas were surveyed to examine the preparedness resources and interventions to prepare for the Next Generation NCLEX-RN (NGN) and to explore the perceptions of nursing faculty on their readiness to teach critical thinking, clinical judgment, and their competency with NGN item writing. A quantitative cross-sectional descriptive design was used for this study utilizing a self-created survey. The survey revealed 40% of participants felt adequately prepared with item writing, and 35% reported feeling adequately prepared to test using the new NGN …

Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen

Electronic Theses and Dissertations

Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …

Quantitative, Photocurrent Multidimensional Coherent Spectroscopy, Adam Halaoui

Electronic Theses and Dissertations

Multidimensional coherent spectroscopy (MDCS) is a quickly growing field that has a lot of advantages over more conventional forms of spectroscopy. These advantages all come from the fact that MDCS allows us to get time resolved correlated emission and absorption spectra using very precisely chosen interactions between the density matrix and the excitation laser. MDCS spectra gives the researcher a lot of information that can be extracted purely through qualitative analysis. This is possible because state couplings are entirely separated on the spectra, and once we know how to read the data, we can see how carriers transport in the …

Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver

Master's Theses

Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …

Deep Learning-Based Automatic Stereology For High- And Low-Magnification Images, Hunter Morera

USF Tampa Graduate Theses and Dissertations

Quantification of the true number of stained cells in specific brain regions is an important metric in many fields of biomedical research involving cell degeneration, cytotoxicology, cellular inflammation, and drug development for a wide range of neurological disorders and mental illnesses. Unbiased stereology is the current state-of-the-art method for collecting the cell count data from tissue sections. These studies require trained experts to manually focus through a z-stack of microscopy images and count (click) on a hundred or more cells per case, making this approach time consuming (~1 hour per case) and prone to human error (i.e., inter-rater variability). Thus, …

Deep Learning-Based Automatic Stereology For High- And Low-Magnification Images, Hunter Morera

USF Tampa Graduate Theses and Dissertations

Quantification of the true number of stained cells in specific brain regions is an important metric in many fields of biomedical research involving cell degeneration, cytotoxicology, cellular inflammation, and drug development for a wide range of neurological disorders and mental illnesses. Unbiased stereology is the current state-of-the-art method for collecting the cell count data from tissue sections. These studies require trained experts to manually focus through a z-stack of microscopy images and count (click) on a hundred or more cells per case, making this approach time consuming (∼1 hour per case) and prone to human error (i.e., inter-rater variability). Thus, …

Experimental And Simulation Study Of Reactive Silver Ink Droplet Evaporation, Weipeng Zhang

Electronic Thesis and Dissertation Repository

The evaporation of particle-free silver ink droplets on heated substrates directly impacts the morphology of the resultant silver particles and films. In this thesis, COMSOL Multiphysics simulations of the solvent (water-ethylene glycol mixture) droplet evaporation process are used to explain the microflows, mass transfers, and heat distribution responsible for the experimental observations. The reactive ink incorporates fluoro-surfactant FS-31 and poly (acrylamide) (PAM) to suppress the coffee-ring effect that negatively impacts the electrical conductivity. Experiments show that the droplet evaporation process results in varied silver particle morphology, depending on the locations within the droplet, leading to uneven surfaces. Large particles (3 …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles, Brennan S. Mccann

Doctoral Dissertations and Master's Theses

Rigid body motion requires formulations where rotational and translational motion are accounted for appropriately. Two Lie groups, the special orthogonal group SO(3) and the space of quaternions H, are commonly used to represent attitude. When considering rigid body pose, that is spacecraft position and attitude, the special Euclidean group SE(3) and the space of dual quaternions DH are frequently utilized. All these groups are Lie groups and Riemannian manifolds, and these identifications have profound implications for dynamics and controls. The trajectory optimization and optimal control problem on Riemannian manifolds presents significant opportunities for theoretical development. Riemannian optimization is an attractive …

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

Machine Learning Approach To Activity Categorization In Young Adults Using Biomechanical Metrics, Nathan Q. C. Holland

Mechanical & Aerospace Engineering Theses & Dissertations

Inactive adults often have decreased musculoskeletal health and increased risk factors for chronic diseases. However, there is limited data linking biomechanical measurements of generally healthy young adults to their physical activity levels assessed through questionnaires. Commonly used data collection methods in biomechanics for assessing musculoskeletal health include but are not limited to muscle quality (measured as echo intensity when using ultrasound), isokinetic (i.e., dynamic) muscle strength, muscle activations, and functional movement assessments using motion capture systems. These assessments can be time consuming for both data collection and processing. Therefore, understanding if all biomechanical assessments are necessary to classify the activity …

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Faster, Cheaper, And Better Cfd: A Case For Machine Learning To Augment Reynolds-Averaged Navier-Stokes, John Peter Romano Ii

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, the field of machine learning (ML) has made significant advances, particularly through applying deep learning (DL) algorithms and artificial intelligence (AI). The literature shows several ways that ML may enhance the power of computational fluid dynamics (CFD) to improve its solution accuracy, reduce the needed computational resources and reduce overall simulation cost. ML techniques have also expanded the understanding of underlying flow physics and improved data capture from experimental fluid dynamics.

This dissertation presents an in-depth literature review and discusses ways the field of fluid dynamics has leveraged ML modeling to date. The author selects and describes …

Modeling Leaf-Level Transpiration: Exploring The Consequences Of Assumed Saturated Vapor Pressure In Leaves, Danlyn L. Brennan

Dissertations and Theses

Understanding the dynamics of water transport through leaf intercellular airspaces (IAS) and its impact on transpiration is crucial for accurate predictions of plant water use and ecosystem response to changing climates. This study investigates the implications of assuming undersaturation of water vapor in the IAS for transpiration predictions and explores potential modifications to standard modeling approaches.

A dynamic 1D soil-plant-atmosphere continuum using a stomatal optimization model (SPAC-SOT) framework was used to simulate the response of tree species, P. edulis, to prolonged drought and varying environmental conditions. Comparisons between two model assumptions (saturated vs. undersaturated IAS) reveal notable differences in …

Uncertainties In Retrieval Of Remote Sensing Reflectance From Ocean Color Satellite Observations, Eder I. Herrera Estrella

Dissertations, Theses, and Capstone Projects

Ocean Color radiometry uses remote sensing to interpret ocean dynamics by retrieving remote sensing reflectance (𝑅𝑟𝑠) from satellite imagery at different scales and over different time periods. 𝑅𝑟𝑠 spectrum characterizes the ocean color that we observe, and from which we can discern concentrations of chlorophyll, organic and inorganic particles, and carbon fluxes in the ocean and atmosphere. 𝑅𝑟𝑠 is derived from the total radiance at the top of the atmosphere (TOA). However, it only represents up to ten percent of the total signal. Hence, the retrieval of 𝑅𝑟𝑠 from the total radiance at TOA involves the application of atmospheric correction …

Tunable Linear And Nonlinear Metasurfaces Based On Hybrid Gold-Graphene Plasmons, Matthew Feinstein

Dissertations, Theses, and Capstone Projects

Optical Metasurfaces are planar structures that are patterned with subwavelength structures and are very thin compared to the wavelength of light. Despite their thinness, these structured materials can strongly interact with incident light to effect the functionalities of conventional optical components, such as rotation of the polarization state, beam steering, lensing, spectral filtering, and holography, to name a few. Metasurfaces can also facilitate nonlinear optical effects, such as the mixing of beams at different frequencies to generate a beam at a new frequency.

The ability to alter the behavior of a metasurface during operation is highly desired for applications such …