Physical Sciences and Mathematics Commons^™

Phenotyping Cotton Compactness Using Machine Learning And Uas Multispectral Imagery, Joshua Carl Waldbieser

Theses and Dissertations

Breeding compact cotton plants is desirable for many reasons, but current research for this is restricted by manual data collection. Using unmanned aircraft system imagery shows potential for high-throughput automation of this process. Using multispectral orthomosaics and ground truth measurements, I developed supervised models with a wide range of hyperparameters to predict three compactness traits. Extreme gradient boosting using a feature matrix as input was able to predict the height-related metric with R2=0.829 and RMSE=0.331. The breadth metrics require higher-detailed data and more complex models to predict accurately.

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey

Theses and Dissertations

Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …

Designing An Artificial Immune Inspired Intrusion Detection System, William Hosier Anderson

Theses and Dissertations

The domain of Intrusion Detection Systems (IDS) has witnessed growing interest in recent years due to the escalating threats posed by cyberattacks. As Internet of Things (IoT) becomes increasingly integrated into our every day lives, we widen our attack surface and expose more of our personal lives to risk. In the same way the Human Immune System (HIS) safeguards our physical self, a similar solution is needed to safeguard our digital self. This thesis presents the Artificial Immune inspired Intrusion Detection System (AIS-IDS), an IDS modeled after the HIS. This thesis proposes an architecture for AIS-IDS, instantiates an AIS-IDS model …

Characterization Of Isomeric States In Neutron-Rich Nuclei Approaching N = 28, Timilehin Hezekiah Ogunbeku

Theses and Dissertations

The investigation of isomeric states in neutron-rich nuclei provides useful insights into the underlying nuclear configurations, and understanding their occurrence along an isotopic chain can inform about shell evolution. Recent studies on neutron-rich Si isotopes near the magic number N = 20 and approaching N = 28 have revealed the presence of low-lying states with intruder configurations, resulting from multiple-particle, multiple-hole excitations across closed shell gaps. The characterization of these states involves measuring their half-lives and transition probabilities.

In this study, a new low-energy (7/2⁻₁) isomer at 68 keV in ³⁷Si was accessed via beta decay …

A Conceptual Decentralized Identity Solution For State Government, Martin Duclos

Theses and Dissertations

In recent years, state governments, exemplified by Mississippi, have significantly expanded their online service offerings to reduce costs and improve efficiency. However, this shift has led to challenges in managing digital identities effectively, with multiple fragmented solutions in use. This paper proposes a Self-Sovereign Identity (SSI) framework based on distributed ledger technology. SSI grants individuals control over their digital identities, enhancing privacy and security without relying on a centralized authority. The contributions of this research include increased efficiency, improved privacy and security, enhanced user satisfaction, and reduced costs in state government digital identity management. The paper provides background on digital …

Study Of Augmentations On Historical Manuscripts Using Trocr, Erez Meoded

Theses and Dissertations

Historical manuscripts are an essential source of original content. For many reasons, it is hard to recognize these manuscripts as text. This thesis used a state-of-the-art Handwritten Text Recognizer, TrOCR, to recognize a 16^th-century manuscript. TrOCR uses a vision transformer to encode the input images and a language transformer to decode them back to text. We showed that carefully preprocessed images and designed augmentations can improve the performance of TrOCR. We suggest an ensemble of augmented models to achieve an even better performance.

A Four-Pronged Approach To Addressing A Wild Pig Invasion In A Bottomland And Upland Forested Landscape, Tyler Scott Evans

Theses and Dissertations

Among exotic species that are capable of invading, establishing, and reaching pest status, few pose the range of impacts to biotic (e.g., competition with native species, predation, herbivory, introduction of other exotics) and abiotic (e.g., soil, hydrology) ecosystem components that can be attributed to the wild pig (Sus scrofa). Despite the presence of wild pigs throughout the southeastern United States for centuries, new invasions continue to occur in previously uninhabited and often under-investigated landscapes, including bottomland and upland forests. The recent invasion of the Sam D. Hamilton Noxubee National Wildlife Refuge (hereafter, NNWR) in east-central Mississippi represents an …

Improved Stoichiometric Synthesis Of Ccc-Nhc Pincer Rh Complexes And Catalytic Activity Towards Dehydrogenative Silylation And Hydrosilylation Of Alkenes, Enock Amoateng

Theses and Dissertations

N-Heterocyclic carbenes (NHCs) have attracted growing interest not only as successful ancillary ligands in a wide variety of transition-metal-catalyzed reactions but have also shown to offer photophysical and electrochemical properties. The metalation/transmetalation strategy using [Zr(NMe₂)₄] as initial metalating reagent offers an efficient approach to the preparation of CCC-NHC pincer complexes of the late transition metals such as Rh and Ir. In the process of investigating an intermediate and the mechanism of the metalation/transmetalation to Rh sequence, a mixed valent bimetallic CCC-NHC pincer Rh complex with two chloro ligands bridged between a [(CCC-NHC)Rh(III)] and a [Rh(I)(COD)] fragment …

Investigating The Role Of Plant Traits And Interactions In Emergent Wetland Nutrient Removal, Andrew Ryan Sample

Theses and Dissertations

Increasing wetland restoration in the Lower Mississippi Alluvial Valley has been identified as a method to reduce nutrient loading in the Gulf of Mexico. Wetlands have historically been used to treat water through processes facilitated by wetland plants, and relatively few species and plant traits have been identified as important in carrying out these processes. This study focuses on some of those species and traits and aims to identify species differences and plant traits that may be important for wetland nutrient mitigation. Chapter I provides background information on nutrient pollution, wetland biogeochemical mechanisms for nutrient sequestration, and the focal species …

Expanding One-Dimensional Game Theory-Based Group Decision Models: Extension To N-Dimension And Integration Of Distributed Position Function, Mirhossein Mousavi Karimi

Theses and Dissertations

This dissertation aims to expand the current one-dimensional game theory based model to a multidimensional model for multi-actor predictive analytics and generalize the concept of position to address problems where actors’ positions are distributed over a position spectrum. The one-dimensional models are used for the problems where actors are interacting in a single issue space only. This is less than an ideal assumption since, in most cases, players’ strategies may depend on the dynamics of multiple issues when dealing with other players. In this research, the one-dimensional model is expanded to N-Dimensional model by considering different positions, and separate salience …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …

Visual And Spatial Audio Mismatching In Virtual Environments, Zachary Lawrence Garris

Theses and Dissertations

This paper explores how vision affects spatial audio perception in virtual reality. We created four virtual environments with different reverb and room sizes, and recorded binaural clicks in each one. We conducted two experiments: one where participants judged the audio-visual match, and another where they pointed to the click direction. We found that vision influences spatial audio perception and that congruent audio-visual cues improve accuracy. We suggest some implications for virtual reality design and evaluation.

Direct Measurement Of The 114cd(��, ��)115cd Cross Section In The 1 Ev To 300 Kev Energy Range, Kofi Tutu Addo Assumin-Gyimah

Theses and Dissertations

The large thermal cross section of cadmium makes it ideal for many practical applications where screening of thermal neutrons is desired. For example, in non-destructive assay techniques, or for astrophysical studies of the s-process. All such applications require precise knowledge of the neutron-capture cross section on cadmium. Although there are some data on neutron-capture cross sections particularly at thermal energies and at energies relevant for astrophysics, there is very little data at most other energies. Further, the evaluated cross sections from the ENDF and JENDL databases disagree at high energies. Therefore, there is a critical need for precise knowledge of …

Optimizing Edge-Of-Field Water Quality Monitoring Methods To Determine The Effects Of Best Management Practices On Nutrient And Sediment Runoff, Mark Hill

Theses and Dissertations

This study investigates the impact on water quality of combined agricultural best management practices cover crop and minimum tillage, alongside an examination of techniques used to collect those samples. Edge-of-field (EOF) water quality samples were collected from 11 working farms during a two-year paired field experiment. Results showed significant reductions in nutrient concentrations, increased discharge, and mixed findings regarding nutrient mass transport post-treatment. A suite of EOF collection techniques were compared using in-situ automated water sampling systems sampling the same runoff events. Sampling protocols influenced nutrient concentrations in composite samples, but unexpected variance in velocity sensors affected measured discharge, making …

Signings Of Graphs And Sign-Symmetric Signed Graphs, Ahmad Asiri

Theses and Dissertations

In this dissertation, we investigate various aspects of signed graphs, with a particular focus on signings and sign-symmetric signed graphs. We begin by examining the complete graph on six vertices with one edge deleted ($K_6$\textbackslash e) and explore the different ways of signing this graph up to switching isomorphism. We determine the frustration index (number) of these signings and investigate the existence of sign-symmetric signed graphs. We then extend our study to the $K_6$\textbackslash 2e graph and the McGee graph with exactly two negative edges. We investigate the distinct ways of signing these graphs up to switching isomorphism and demonstrate …

Monolithic Multiphysics Simulation Of Hypersonic Aerothermoelasticity Using A Hybridized Discontinuous Galerkin Method, William Paul England

Theses and Dissertations

This work presents implementation of a hybridized discontinuous Galerkin (DG) method for robust simulation of the hypersonic aerothermoelastic multiphysics system. Simulation of hypersonic vehicles requires accurate resolution of complex multiphysics interactions including the effects of high-speed turbulent flow, extreme heating, and vehicle deformation due to considerable pressure loads and thermal stresses. However, the state-of-the-art procedures for hypersonic aerothermoelasticity are comprised of low-fidelity approaches and partitioned coupling schemes. These approaches preclude robust design and analysis of hypersonic vehicles for a number of reasons. First, low-fidelity approaches limit their application to simple geometries and lack the ability to capture small scale flow …

Secure And Efficient Federated Learning, Xingyu Li

Theses and Dissertations

In the past 10 years, the growth of machine learning technology has been significant, largely due to the availability of large datasets for training. However, gathering a sufficient amount of data on a central server can be challenging. Additionally, with the rise of mobile networking and the large amounts of data generated by IoT devices, privacy and security issues have become a concern, resulting in government regulations such as GDPR, HIPAA, CCPA, and ADPPA. Under these circumstances, traditional centralized machine learning methods face a problem in that sensitive data must be kept locally for privacy reasons, making it difficult to …

Evaluating The Relationship Between Methane Seeps And Seafloor Geomorphology On The Northern Us Atlantic Margin, Gabriel Hernandez

Theses and Dissertations

Methane seeps are a transport pathway for carbon from seafloor sediments to the marine environment with important implications for global biogeochemical cycling. Accordingly, there is substantial interest in better understanding the processes that control seep location and predicting the distribution of seeps with existing seafloor datasets. Visual evaluation of methane seeps, in multibeam sonar water column data, suggests a spatial relationship between seeps and specific seafloor morphologic features such as ridge crests. In this thesis, seafloor geomorphology at 1996 seep detection sites on the US Atlantic margin was quantitatively characterized by geomorphologic phonotype, bathymetric position index, slope, rugosity, and aspect …

Protecting The Vulnerable: Tornado Sheltering And Communication Of Public Shelters With A Case Study From The Covid-19 Pandemic, Craig Douglas Croskery

Theses and Dissertations

One of the greatest natural hazards that is faced with in much of the United States are tornadoes. Despite improvements in the warning processes, the risk of significant loss of life remains high. That is particularly true with vulnerable communities which have higher proportions of mobile homes; however, violent tornadoes are very difficult to manage in permanent homes or buildings as well. As a result, tornado shelters have been built in some communities and have become available to the public. However, their presence is intermittent, and there are many tornado-prone areas that lack such shelters.

After a public survey, it …

Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest

Theses and Dissertations

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.

Variational And Adaptive Non-Local Image Denoising Using Edge Detection And K − Means Clustering, Shiraz Mujahid

Theses and Dissertations

With the increased presence of image-based data in modern applications, the need for robust methods of image denoising grows greater. The work presented herein considers two of the most ubiquitous approaches towards image denoising: variational and non-local methods. The effectiveness of these methods is assessed using quantitatively using peak signal-to-noise ratio and structural similarity index measure metrics. This study employs ��−means clustering, an unsupervised machine learning algorithm, to isolate the most dominant cluster centroids within the incoming data and propose the introduction of a new adaptive parameter into the non-local means framework. Motivated by the fact that a majority of …

Determining The Impact Of Post-Harvest Water Management On Chironomid Abundance, Agrochemical Biomass And Potential Trophic Biomagnification, Mason Thomas

Theses and Dissertations

Agriculture has diminished shorebirds’ natural habitat in the Mississippi Alluvial Valley. Remaining natural stopover sites are supplemented with agricultural fields during the fall and winter. This study evaluates the impact of 4 different post-harvest water management strategies on shorebird food abundance and potential agrochemical biomagnification. Chironomid samples estimated abundance, biomass, and chironomid agrochemical concentration in each field. A risk assessment of agrochemical biomagnification to shorebirds was made across all treatments. Of treatments represented on all study sites, winter treatment had greatest chironomid abundance and biomass. Models indicated that days since flood initiation, start date, and temperature are significant predictors of …

Beyond Algorithms: A User-Centered Evaluation Of A Feature Recommender System In Requirements Engineering, Oluwatobi Lasisi

Theses and Dissertations

Several studies have applied recommender technologies to support requirements engineering activities. As in other application areas of recommender systems (RS), many studies have focused on the algorithms’ prediction accuracy, while there have been limited discussions around users’ interactions with the systems. Since recommender systems are designed to aid users in information retrieval, they should be assessed not just as recommendation algorithms but also from the users’ perspective. In contrast to accuracy measures, user-related issues can only be effectively investigated via empirical studies involving real users. Furthermore, researchers are becoming increasingly aware that the effectiveness of the systems goes beyond recommendation …

Quantifying Seasonal And Annual Precipitation Variability On San Salvador Island, Bahamas Using Surface Observations And Satellite Estimates., John Bryson Wells

Theses and Dissertations

San Salvador Island is a small Bahamian island located in the subtropics just north of the Tropic of Cancer. Due to its subtropical location, the island is influenced by both mid-latitude and tropical weather patterns. These weather patterns vary in scale from localized convective uplift to synoptic-scale systems. This study compares satellite-derived estimates of precipitation and rain gauge observations from June 2019 through September 2021 to evaluate the relationship between the two datasets. This study then uses the satellite-derived estimates of precipitation over a 20-year period to quantify annual and seasonal variability in precipitation on San Salvador. Corroborating past research, …

Halide Substitution Of Ternary Bismuth Chalcogenides For Photovoltaic Applications, Thomas Boggess

Theses and Dissertations

Semiconductors play an integral part in modern society. From computing to LEDs their use is ubiquitous, and no field is more reliant on them than that of power generation. Current political movements have seen a push to decrease reliance on traditional forms of power generation, which relies on fossil fuels, to renewable sources such as solar power. However, current commercial solar panels, based on silicon, are lacking in efficiency, only reaching between 18% and 22% efficiency.¹ In recent years, materials called perovskites have been garnering significant attention as possible replacements for silicon cells due to their favorable optoelectronic properties. …

Oxidation Resistance Of An Atomically Flat Cu(111) Surface: A First-Principles Study, Bipin Lamichhane

Theses and Dissertations

The first-principles calculation based on density functional theory (DFT) was used to study the oxidation resistance of atomically flat and atomic-step edges of Cu(111), diffusion of Cu atoms in different surfaces of alumina and interface properties of alumina and Cu(111), and magnetic properties of Mn-substituted strontium hexaferrite. The dissociation of oxygen molecules is the primary reason for the corrosion of metals, which deteriorates their application. Cu(111) flat surface, mono-atomic, and multi-atomic step edges were used to study oxygen diffusion. Penetration of oxygen on a Cu(111) flat surface requires high energy, indicating oxidation resistance. Our DFT result of oxygen diffusion into …

Pruning Ghsom To Create An Explainable Intrusion Detection System, Thomas Michael Kirby

Theses and Dissertations

Intrusion Detection Systems (IDS) that provide high detection rates but are black boxes lead
to models that make predictions a security analyst cannot understand. Self-Organizing Maps
(SOMs) have been used to predict intrusion to a network, while also explaining predictions through
visualization and identifying significant features. However, they have not been able to compete with
the detection rates of black box models. Growing Hierarchical Self-Organizing Maps (GHSOMs)
have been used to obtain high detection rates on the NSL-KDD and CIC-IDS-2017 network traffic
datasets, but they neglect creating explanations or visualizations, which results in another black
box model.
This paper offers …

Verification Of The Localized Aviation Mos Program (Lamp) At Major Us Airports For Ifr Conditions, Mackenzie O'Rourke

Theses and Dissertations

The objective of this research is to quantify the LAMP’s performance when forecasting for IFR conditions at specific major airports for forecast hours one, three, six, and twelve, and further determine how the LAMP performs seasonally at those specific airports and forecast hours. Two by two contingency tables were used to calculate the Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Heidke Skill Score (HSS), and Bias score. The results show that the LAMP performs relatively better in the cool season compared to the warm season consistently at each chosen airport, and that the LAMP performs …

Tornado Outbreak False Alarm Probabilistic Forecasts With Machine Learning, Kirsten Reed Snodgrass

Theses and Dissertations

Tornadic outbreaks occur annually, causing fatalities and millions of dollars in damage. By improving forecasts, the public can be better equipped to act prior to an event. False alarms (FAs) can hinder the public’s ability (or willingness) to act. As such, a probabilistic FA forecasting scheme would be beneficial to improving public response to outbreaks.

Here, a machine learning approach is employed to predict FA likelihood from Storm Prediction Center (SPC) tornado outbreak forecasts. A database of hit and FA outbreak forecasts spanning 2010 – 2020 was developed using historical SPC convective outlooks and the SPC Storm Reports database. Weather …

Analysis Of Weather-Related Flight Delays At 13 United States Airports From 2004-2019 Using A Time Series And Support Vector Regression, Caroline E. Sleeper

Theses and Dissertations

This study seeks to investigate weather-related flight delay trends at 13 United States airports. Flight delay data were collected from 2004-2019 and normalized by airport operations data. Using Support Vector Regression (SVR), visual trends were identified. Further analysis was conducted by comparing all four meteorological seasons through computing 95% bootstrap confidence intervals on their means. Finally, precipitation and snowfall data were correlated with normalized delays to investigate how they are related. This study found that the season with the highest normalized delay values is heavily dependent upon location. Most airports saw a decrease in the SVR line at some point …