Physical Sciences and Mathematics Commons^™

Characterizing Spatial Variability In Soil Co2 Fluxes In The Chihuahuan Desert Using Geostatistical Techniques, Viridiana Orona

Open Access Theses & Dissertations

Spatial variability in soil CO2 efflux across landscapes is an important feature of the â??Critical Zoneâ?? within dryland ecosystems. In dryland critical zones, resources are often distributed in patches or resource islands. Although this is particularly true in natural settings, the significance of spatial variability in CO2 efflux and its patterns also extends to dryland agriculture. In both irrigated and unirrigated systems, human management practices can significantly impact both organic and inorganic carbon cycling processes, highlighting the importance of studying CO2 efflux in these systems. We examined the spatial patterns of soil CO2 efflux and quantified the magnitude and scale …

The Intersection Of Urban Heat Islands And The Cdc Social Vulnerability Index In Two Border Cities, Ileana Morales

Open Access Theses & Dissertations

No abstract provided.

Temporal Trends In Dryland Soil Carbon Fluxes In Response To Artificial And Natural Pulsed Moisture Events, Briana Alyce Salcido

Open Access Theses & Dissertations

Critical zone processes in drylands play a crucial role in the global carbon cycle, and one of the most important processes is soil CO2 efflux at the interface between soils and the atmosphere, which represents a main pathway for loss of carbon. Predicting the carbon dynamics at this interface is challenging due to the complexity of belowground processes, which include both biotic (soil respiration) and abiotic (calcite precipitation) production of CO2, as well as transport processes that include both diffusive and advective components. In this study, we aimed to investigate the contribution of soil air displacement to soil CO2 efflux …

A Framework To Build Secure Microservice Architecture, Wai Yan Elsa Tai Ramirez

Open Access Theses & Dissertations

Microservice architecture has become a popular architecture style in recent years. According to a series of surveys conducted by IBM Market Development & amp; Insights in 2021, microservices are heavily used in many industries worldwide. With an increase in the adoption of microservice architecture in the development of applications, such as Netflix, Amazon, Uber, Ebay, Twitter, DoorDash, Capital One, and Monzo, and the increase in security breaches in microservice based systems (e.g., the DoorDash data breaches in 2019 and 2022, Twitter data breach in 2022, and compromises to Netflixâ??s infrastructure), there is a need to examine and understand security issues …

Modeling And Predicting Emerging Threats Using Disparate Data, Ismael Villanueva Miranda

Open Access Theses & Dissertations

Early detection is crucial to mitigate the impact of emerging threats. This work proposes four innovative frameworks that build machine learning and deterministic epidemiological models using multiple domain-specific datasets to detect the onset of emerging threats in two domains: infectious diseases and cybersecurity. Our models are designed to detect infectious disease outbreaks, model their spread, detect malware activity, and analyze the relationship between software/hardware weaknesses and attack techniques.

First, we present a novel framework to detect multiple infectious disease outbreaks by integrating standardized disease-specific domain knowledge and public search trend data. Our framework showed high performance in identifying infectious disease …

Spatially Adaptive Estimation Of Spectrum, Yi Xie

Open Access Theses & Dissertations

A time series may be analyzed either in the time or in the frequency domain. When working in the frequency domain, the main objective is to estimate the underlying spectrum. Various approaches have been proposed to this end, but most are based on smoothing the periodogram using a single smoothing parameter across all Fourier frequencies. Such a global smoothing parameter may result in a biased estimate. To improve the estimation, in this paper, we smooth the log periodogram by placing a dynamic shrinkage prior, such that varying degrees of smoothing may be applied to different regions of the Fourier frequencies, …

Detecting Complex Cyber Attacks Using Decoys With Online Reinforcement Learning, Marcus Gutierrez

Open Access Theses & Dissertations

Most vulnerabilities discovered in cybersecurity can be associated with their own singular piece of software. I investigate complex vulnerabilities, which may require multiple software to be present. These complex vulnerabilities represent 16.6% of all documented vulnerabilities and are more dangerous on average than their simple vulnerability counterparts. In addition to this, because they often require multiple pieces of software to be present, they are harder to identify overall as specific combinations are needed for the vulnerability to appear.

I consider the motivating scenario where an attacker is repeatedly deploying exploits that use complex vulnerabilities into an Airport Wi-Fi. The network …

Enhancing Basic Geology Skills With Artificial Intelligence: An Exploration Of Automated Reasoning In Field Geology, Perry Ivan Quinto Houser

Open Access Theses & Dissertations

This thesis explores the use of Artificial Intelligence, specifically semantics, ontologies, and reasoner techniques, to improve field geology mapping. The thesis focuses on two use cases: 1) identifying a geologic formation based on observed characteristics; and 2) predicting the geologic formation that might be expected next based upon known stratigraphic sequence. The results show that the ontology was able to correctly identify the geologic formation for the majority of rock descriptions, with higher search results for descriptions that provided more detail. Similarly, the units expected next were correctly given and if incorrect, would provide a flag to the field geologist …

Theoretical And Computational Aspects Of Robust Cluster Analysis For Multivariate And High-Dimensional Datasets, Andrews Tawiah Anum

Open Access Theses & Dissertations

Multivariate and high-dimensional datasets typically contain subgroups that may not be immediately apparent. To reveal these groups, cluster analysis is performed. Cluster analysis is an unsupervised machine learning technique commonly employed to partition a dataset into distinct categories referred to as clusters. The k-means algorithm is a prominent distance-based clustering method. Despite overwhelming popularity, the algorithm is not invariant under non-singular affine transformations and is not robust, i.e., can be unduly influenced by outliers. To address these deficiencies, we propose an alternative model-based clustering procedure by minimizing a “trimmed” variant of the negative log-likelihood function. We develop a “concentration step”, …

Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data., Peter Kwadwo Asante

Open Access Theses & Dissertations

This dissertation aims to assess the performance of Ornstein-Uhlenbeck-type models by examining the fractal characteristics of time series data from various sources, including finance, volcanic and earthquake events, US COVID-19 reported cases and deaths, and two simulated time series with differing properties. The time series data is categorized as either a Gaussian or a Lévy process (Lévy walk or Lévy flight) by using three scaling methods: Rescaled range analysis, Detrended fluctuation analysis, and Diffusion entropy analysis. The outcomes of this analysis indicate that the financial indices are classified as Lévy walks, while the volcanic, earthquake, and COVID-19 data are classified …

Development Of Multi-Configuration Methods On Density Functional Theory Orbitals And Application On The Study Of Dimers, Jose Gustavo Bravo Flores

Open Access Theses & Dissertations

The configuration interaction (CI) methods is an exact method to solve the non relativistic Schrodinger equation, describing the wave function as a linear combination of Slater determinants. Because the computation time grows factorially as the number of electrons, CI is mostly used for relatively small systems. Density functional theory (DFT) rose as one of the most used methods for computational quantum chemistry in the last 30 years. DFT can describe a system's properties with the electron density, which only depends of of three coordinates. Due to its low computational costs it allows one to study bigger systems than CI, however …

Comparison Of Different Robust Methods In Linear Regression And Applications In Cardiovascular Data, Jagannath Das

Open Access Theses & Dissertations

Due to advanced technology and wide source of data collection, high-dimensional data is available in several fields, including healthcare, bioinformatics, medicine, epidemiology, economics, finance, sociology, and climatology. In those datasets, outliers are generally encountered due to technical errors, heterogeneous sources, or the effect of some confounding variables. As outliers are often difficult to detect in high-dimensional data, the standard approaches may fail to model such data and produce misleading information. In this thesis, we studied Huber and Tukey's M-estimators for linear regression that automatically down-weight outliers and provide a good fit. We also investigated two variable selection methods -- LASSO …

Analysis Of The Electrostatic Characteristics Of The Zika Virus Capsid Using Computational Methods, Cassandra Guadalupe Del Rio De Avila

Open Access Theses & Dissertations

Zika virus (ZIKV) is a flavivirus that is usually transmitted through the bite of infected mosquitoes. This virus can cause a variety of neurological disorders, the most common being Guillain-Barré syndrome in adults. Moreover, it is of great concern in pregnant women, since can cause deformities in the brain and other organs of newborns.Studying the structural characteristics of the virus during its mature and infectious phase can provide crucial information on the mechanisms by which it enters and replicates within host cells, as well as its evolution, transmission, and interaction with other living organisms. The symmetric pattern present in the …

Evaluating The Impact Of Climate Variability And Landcover Changes On Hydrologic Responses, Marisol Dominguez

Open Access Theses & Dissertations

Projected climate and land cover changes in the 21st century profoundly impact the functioning of the earth’s water cycle. Identifying the components that contribute to the persistence and resilience of watersheds in light of climate change constitutes a research priority of global relevance, and will enable detect the areas most sensitive to climate variability and landcover changes. Global vulnerability of ecosystem services, particularly water service provision, needs to be urgently and continually assessed, given the unceasing human and climate-induced changes in land cover conditions worldwide. Given the increasing rate of extreme weather events, we present three interrelated research studies evaluating …

Development Of A Cost-Constrained Intelligent Prosthetic Knee With Real-Time Machine Learning, Predictive Stumble Control, Lucas Jonathan Galey

Open Access Theses & Dissertations

The field of biomechatronics is evolving quickly with advances in computer science, biology, and electrical and mechanical engineering. Coupled with increased interests in machine learning (ML) across all industry sectors, there are opportunities to leverage advanced analytics in uniquely complex problems. This study aimed to deploy real-time ML predictions in a novel microprocessor-controlled prosthetic knee (MPK) device capable of identifying and responding to stumble-events to reduce amputee fall prevalence. Innately, stumbling is a chaotic event. Current MPKs operate by detecting gait characteristics and reacting to preprogrammed states. While these systems are beneficial in significant ways, such as energy expenditure and …

Thermal Behavior Of Plain And Fiber-Reinforced Rigid Concrete Airfield Runways, Arash Karimi Pour

Open Access Theses & Dissertations

The environmental condition and temperature gradient are important factors resulting in concrete airfield runways cracking during the time. Rigid concrete airfield runways experience different thermal gradients during the day and night due to changes in air temperature. Curling and thermal expansion stresses are the main consequences resulting in various types of cracking over the surface and thickness of concrete airfield runways and increasing maintenance costs. The curvature of concrete slabs increases with an increase in the temperature gradient which is amplified when runways open to traffic. Additionally, the combination of the curling and shrinkage stresses, in rare circumstances, can be …

Geological Mapping Of Ferric And Ferrous Irons In The Apache Hills, New Mexico: Applying Landsat 8 (Oli), Spectrometry, And Geographic Information System (Gis) Methods, Sergio Gerardo Macias

Open Access Theses & Dissertations

Mineral discoveries are typically tangible on surface studies. Previous research describes mineral deposits of ferric and ferrous irons in the lithology, structures, and alluvial fans in the Apache Hills in southwest New Mexico. The research for this thesis combines and models four methods for validating and mapping the presence of Ferric and Ferrous Irons developed in weathered zones above mineral deposits. A beneficial steppingstone before exploration and discovery begins with extensive research. This study began with data acquisition and reviewing previous research and was essential for the project methods. The study combines four techniques: spectral geology (e.g., remote sensing and …

Isotopic Insights Into Water Of Condensation, Cross-Formation Water Flow, And Natural Hydrocarbon Migration In Sedimentary Basins, Lisa J. Molofsky

Open Access Theses & Dissertations

This dissertation applies geochemical tools to track the movement, transformation, and behavior of water and gases in hydrocarbon-bearing sedimentary basins. During petroleum exploration and production, hydrocarbons are generated at the surface along with other fluids naturally present in the formation, such as formation water. In addition, where hydraulic fracturing is used to stimulate shale gas and oil production, a percentage of the injected fracturing fluid also returns to the surface. Understanding the origin and movement of these water sources, as well as targeted and non-targeted hydrocarbon gases is critical to evaluating reservoir performance and properly managing fluids at the surface. …

Catalytic Water Photolysis For Generating Renewable Hydrogen Fuel, Dr. Niveditha Nanda

Open Access Theses & Dissertations

Modern advances have enabled rapid industrialization and urbanization. However, the consequences of global modernization have included significant pollution to the air and water resources. Consequently, many changes to energy use must come to address and mitigate damages to our future. Solar energy derived hydrogen gas is a clean, renewable fuel that does not produce carbon dioxide or other pollutants. My research investigates the use of heterogeneous photocatalysis, by focusing on solar photochemical energy conversion, which is the making of hydrogen from water using sunlight. The production of clean, renewable hydrogen fuel will enable the utilization of low-cost, pollution-free energy resources …

Analyzing Software Maintenance Through Machine Learning And Mining Software Repositories Approaches, Sayed Mohsin Reza

Open Access Theses & Dissertations

The rapid growth of software systems demands meticulous planning and maintenance to accommodate the evolution of the code base over extended periods. Without maintenance, software systems will become more complex, low in quality, and hence unsustainable. Software engineers who perform maintenance often strive to optimize code quality or minimize code smells in a timely manner. Several techniques have been used to detect code quality or code smells as a part of software maintenance. Most of these techniques are based on heuristics, which create detection rules using a few metrics. These approaches have reasonable accuracy but do not work in cross-project …

Outlier Detection In Multivariate And High-Dimensional Datasets, Yuanhong Wu

Open Access Theses & Dissertations

Accurate detection of outliers is crucial in the field of statistical analysis. Using classical statisticalmodels without considering the presence of outliers in the data can lead to misleading outcomes. There exist a myriad of procedures to detect outliers in statistics. We concentrate on the statistical techniques that can robustly identify outliers in data sets. To this end, we pursue two aims. First, we give an extensive overview of robust statistical methods which are still popular in recent years for outlier detection. We provide the definitions, algorithms and also discuss some important properties of these methods. Second, two real examples are …

Structure Study Of Small Heat Shock Protein 27, Zhaobo Li

Open Access Theses & Dissertations

Molecular chaperones are a class of oligomeric proteins that play a critical role inpreventing the aggregation of non-native protein so that these proteins can later be refolded. Chaperones are ubiquitously expressed in all the kingdoms of life where their function is to counteract cellular stress and to maintain protein homeostasis. One subgroup of molecular chaperones is characterized by low molecular weight and are termed small heat shock proteins. The focus of the proposed research is the small heat shock protein 27 (Hsp27). Hsp27 is an ATP independent chaperone that is overexpressed in response to heat shock, radiation damage, oxidative damage, …

Enhancing Earthquake Detection Through Machine Learning- An Application To The 2017 Mw 8.2 Tehuantepec Earthquake In Mexico, Marc Adrian Garcia

Open Access Theses & Dissertations

The Tehuantepec seismic gap, located off the southern shore of Oaxaca and Chiapas, Mexico, was previously thought to be an aseismic zone due to no significant event in 100 years. The September 8, 2017 (M8.2) Tehuantepec earthquake disproved this idea and added many questions surrounding the Mexican subduction zone. Specifically, the earthquake did not occur at the subduction megathrust. It ruptured the subducting plate below the megathrust and appeared to stop at the megathrust. Following this event, as well as the September 19, 2017 (M7.1) Morelos-Puebla earthquake, researchers from the University of Texas at El Paso (UTEP), Universidad Autónoma Cuidad …

Grid Independence Studies Of Eddy-Resolving Models At The Scale Of A River Reach Along A Transect In Marble Canyon Of The Colorado River, Arizona, Rosa Elena España Urresty

Open Access Theses & Dissertations

This study presented a novel approach for evaluating the impact of changes in spatial resolution on field-scale models to identify turbulent flow patterns in hydraulic features in canyon-bound rivers. The methodological framework incorporated seven different computational domain resolutions to analyze the sensitivity of field-scale models to spatial resolution changes by employing techniques such as turbulent kinetic energy spectrum, spatiotemporal analysis of eddy structures, divergent Kullback-Leibler (KL) divergence, Nash-Sutcliffe (NS) model efficiency coefficient, wavelet power spectrum, and GCI calculation. Statistical and physical-based skill metrics are employed to quantifying information loss to evaluate a set of domain resolutions. Grid independence studies have …

Decision Making Under Uncertainty With A Special Emphasis On Geosciences And Education, Laxman Bokati

Open Access Theses & Dissertations

In many practical situations, we need to make a decision. In engineering, we need to decideon the best design of a system, and, for existing systems - on the best control strategy. In financial applications, we need to decide what is the best way to invest money. In geosciences, we need to decide whether we should explore a possible mineral deposit - or whether we should perform more experiments and measurements (and what exactly). In some cases, we can compute the exact consequences of each decision - e.g., if we are controlling a satellite. However, in many other cases, we …

Generation Of Phase Transitions Boundaries Via Convolutional Neural Networks, Christopher Alexis Ibarra

Open Access Theses & Dissertations

Accurate mapping of phase transitions boundaries is crucial in accurately modeling the equation of state of materials. The phase transitions can be structural (solid-solid) driven by temperature or pressure or a phase change like melting which defines the solid-liquid melt line. There exist many computational methods for evaluating the phase diagram at a particular point in temperature (T) and pressure (P). Most of these methods involve evaluation of a single (P,T) point at a time. The present work partially automates the search for phase boundaries lines utilizing a machine learning method based on convolutional neural networks and an efficient search …

Rational Design Of Precisely Tailored Electrocatalysts For Efficient And Durable Electrocatalytic Devices, Mohmed Sanad Noufal

Open Access Theses & Dissertations

Due to their superior conversion efficiency, high power density, and green nature, sustainable energy technologies such as Fuel cells and Zinc-air batteries, once installed to produce green hydrogen fuel as well as energy storage devices, are expected to play an essential role in reducing the environmental effect of human transportation by replacing fossil fuels. However, the current bottleneck for the low-temperature polymer membrane fuel cells that dominate the fuel cell vehicle market is the sluggish kinetics of the oxygen reduction reaction (ORR) at the cathode. The slow ORR kinetics significantly reduce the efficiency of chemical-electrical energy conversion. Similarly, hydrogen production …

Identifying Particulate Matter Spatial Variation In The El Paso Del Norte Region Using Land-Use Regression Modeling And Data Obtained From A Network Of Low-Cost Sensors, Leonardo Demetrio Vazquez-Raygoza

Open Access Theses & Dissertations

The emergence and rise in popularity of low-cost sensors for atmospheric observation aresetting a new precedent in identifying emission hotspots and providing high-resolution spatial and temporal data. Furthermore, low-cost sensors are becoming popular among institutions and the public, allowing community scientists to become more involved in air quality monitoring. However, concerns about the accuracy and precision of low-cost sensors have been questioned. Most recent research has focused on the utility of real-time monitoring and calibration requirements for these sensors. A low-cost monitoring project has deployed sensors in the El Paso del Norte region in low and high annual average daily …

Radio Frequency Fingerprinting And Its Application To Scada Environments, Evan White

Open Access Theses & Dissertations

With the introduction of IoT into ICS and smartgrid environments there has been a mod-ernization of communication protocols through the internet. This has led to the use of features such as TCP/IP but with it comes modernized attack vectors against these sys- tems. These attacks can be Man In the Middle (MITM), rogue device communication and device cloning. To prevent these attacks, this thesis deploys Radio Frequency Fingerprint- ing (RFF) techniques to verify the uniqueness and legitimacy of known devices. It is crucial to employ security measures within ICS that do not add to the network complexity as this effects …

Applications Of Micro-X-Ray Fluorescence (Μxrf) Techniques To Ore Formation Questions In Economic Geology, Hannah Adwoa Buamono

Open Access Theses & Dissertations

Advances in x-ray optics over the past decade have enabled a new generation of benchtop micro energy-dispersive x-ray fluorescence (µXRF/EDS) instruments to analyze samples with an x-ray spot size of 25 microns or less and detection limits of tens to hundreds of parts per million. The analysis of samples from mineral (ore) deposits may illustrate some of the capabilities and limitations of these instruments applied to geoscience problems. The qualitative elemental analysis process allows the production of detailed elemental maps which, together with line scan profiles and other petrographic and geochemical evidence, leads to a better definition of key chemical, …