Physical Sciences and Mathematics Commons^™

Why Inverse Layers In Pavement? Why Zipper Fracking? Why Interleaving In Education? A General Explanation, Edgar Daniel Rodriguez Velasquez, Aaron Velasco, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, if we split our efforts into two disconnected chunks, we get better results: a pavement is stronger if instead of a single strengthening layer, we place two parts of this layer separated by no-so-strong layers; teaching is more effective if instead of concentrating a topic in a single time interval, we split it into two parts separated in time, etc. In this paper, we provide a general explanation for all these phenomena.

Fast -- Asymptotically Optimal -- Methods For Determining The Optimal Number Of Features, Saied Tizpaz-Niari, Luc Longpré, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In machine learning -- and in data processing in general -- it is very important to select the proper number of features. If we select too few, we miss important information and do not get good results, but if we select too many, this will include many irrelevant ones that only bring noise and thus again worsen the results. The usual method of selecting the proper number of features is to add features one by one until the quality stops improving and starts deteriorating again. This method works, but it often takes too much time. In this paper, we propose …

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 …

Nonparametric Estimation Of Elliptical Copulas, Panfeng Liang

Open Access Theses & Dissertations

Elliptical copulas provide flexibility in modeling the dependence structure of a random vector. They are often parameterized with a correlation matrix and a scalar function, called generator. The estimation of the generator can be challenging, because it is a functional parameter. In this dissertation, we provide a rigorous approach to estimating the generator in a Bayesian framework, which is simpler, more robust, and outperforms existing estimation methods in the literature. Based on the proposed framework in this dissertation, other researchers may modify the model for other types of generators in their own research.

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 …

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 …

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”, …

Flexible Models For The Estimation Of Treatment Effect, Habeeb Abolaji Bashir

Open Access Theses & Dissertations

Estimation of treatment effect is an important problem which is well studied in the literature. While the regression models are one of the most commonly used techniques for the estimation of treatment effect, they are prone to model misspecification. To minimize the model misspecification bias, flexible nonparametric models are introduced for the estimation. Continuing this line of research, we propose two flexible nonparametric models that allow the treatment effect to vary across different levels of covariates. We provide estimation algorithms for both these models. Using simulations and data analysis, we illustrate the usefulness of the proposed methods.

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 …

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 …

Microscopic And Spectroscopic Analysis Of Nordihydroguaiaretic Acid Effect On Astrocytes, Lizbeth Vanessa Martinez Lopez

Open Access Theses & Dissertations

Astrocytes, one of the most abundant cell components in the central nervous system (CNS), have been a research target in the last few years. Several studies have found that astrocytes are not only mere supporters of neurons but also of essential processes developed in the CNS. Their malfunction could induce neurodegenerative diseases and brain tumors. Thus, further understanding of astrocytes and their role is of high interest to develop possible new treatments and methods of disease diagnosis, especially in brain cancer. The plant Larrea tridentata (La Gobernadora in Mexico or Creosote bush in the United States) is known to have …

Linking Decomposition Reactions In Arctic Soils To Microbial Enzyme Production, Jane Karen Martinez

Open Access Theses & Dissertations

Microbial processes such as soil enzyme production are a major driver of decomposition and a current topic of interest in arctic soils due to the effects of climate warming. Despite the advances in understanding soil enzymes, there are still knowledge gaps regarding the role of enzymes in decomposition. In this dissertation, I addressed three of those gaps in the following chapters: (Ch.2) to explore the location of enzymes within the soil matrix, (Ch.3) to identify peptides matched to soil enzymes produced by microorganisms for organic matter decomposition, and (Ch.4) understand the longevity of enzymes in the soil after microbial production. …

Differentiating Biotic Vs. Abiotic Co2 In The Formation Of Pedogenic Carbonate In Agriculture And Natural Dryland Soils, Valeria Isabel Molina

Open Access Theses & Dissertations

Drylands, characterized by low and sporadic precipitation, require irrigation for crop growth. However, irrigation practices can lead to salt accumulation in soil due to high evaporation rates and reduced leaching. In addition to loading salts to soil, irrigation promotes the accumulation of secondary calcite. In natural systems, the formation of pedogenic carbonate (secondary calcite, CaCO3) is critical, impacting the soil properties hydrologically and biogeochemically, and modifying the global carbon cycle over geological time, albeit at a lower rate. In agricultural sites, irrigation water supplies HCO3- and Ca2+, accelerating the rates of CaCO3 formation and releasing abiotic CO2. This study investigated …

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. …

On The Predictability Of Appropriate Prosody Of Dialog Markers Directly From The Local Context, Anindita Nath

Open Access Theses & Dissertations

Today's state-of-the-art spoken dialog systems lack context-appropriate prosody in their responses, often making them sound unnatural. Better modeling of this contextual dependency would enable natural prosodic responsiveness. Accordingly, this dissertation explores the extent to which the prosody of a dialog marker can be predicted directly from the prosody of its local context. The prediction performance was evaluated in terms of the similarity between the predicted and the observed prosodic features as measured by the reduction of root mean square error from the baseline. This prediction task was accomplished for multiple combinations of various sets of context features and different machine …

Developing A Risk Assessment Instrument For Immigration Cases Under Federal Supervision, Mayra Eydie Pacheco

Open Access Theses & Dissertations

No abstract provided.

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 …

Developing And Applying Computational Methods On Biomolecules, Shengjie Sun

Open Access Theses & Dissertations

Computational biophysics is an interdisciplinary subject that uses numerical algorithms to study the physical principles underlying biological phenomena and processes. Electrostatic interactions play an important role in computational molecular biophysics and their potential impact on disease mechanisms. At distances larger than several Angstroms, electrostatic interactions dominate all other forces, while the alteration of short-range electrostatic pairwise interactions can also have significant effects. The dual nature of electrostatic interactions, being dominant at long-range and specific at short-range, underscores their profound implications for wild-type structure and function. Any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could …

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 …

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 …

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, …

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, …

Recursive Forms For Determinant Of K-Tridiagonal Toeplitz Matrices, Eugene Agyei-Kodie

Open Access Theses & Dissertations

Toeplitz matrices have garnered renewed interest in recent years due to their practical applications in engineering and computational sciences. Additionally, research has shown their connection to other matrices and their significance in matrix theory. For example, one study demonstrated that any matrix can be expressed as the product of Toeplitz matrices \citep{ye2016every}, while another showed that any square matrix is similar to a Toeplitz matrix \citep{mackey1999every}.

Numerous studies have examined various properties of Toeplitz matrices, including ideals of lower triangular Toeplitz matrices \citep{dogan9some}, matrix power computation with band Toeplitz structures \citep{dogan2017matrix}, and norms of Toeplitz matrices. Moreover, the use of …

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 …

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 …

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 …

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 …