Physical Sciences and Mathematics Commons^™

Using The Schism Model And Hf Radar Data To Study Surface Currents In Texas Bays: A Case Study Of Sabine Lake (Sl) And Galveston Bay (Gb)., Cletus Ozoemena Ogbodo

Open Access Theses & Dissertations

Surface currents study provides invaluable understanding into the physical dynamics of oceans, bays, estuaries, and nearshore environments, offering critical insights about water movement and related coastal processes. These currents play a fundamental role in understanding the state of estuarine and marine systems, such as their effects on sediment transport, heat distribution and climate change, nutrient distribution, and pollutant dispersal. In addition, surface current data provides significant economic and ecological implications for coastal communities essential for managing resources effectively and ensuring the resilience of coastal regions against environmental and anthropogenic pressures. This study was driven by the need to address the …

The United States National Security And Policy Implications Of Desertification, Eric Olvera

Open Access Theses & Dissertations

Contemporary climate security literature reveals that desertification appears to be overlooked as a climate change security threat to the United States (US). This investigation demonstrates that an inequity exists between sea-level-rise- and desertification-based climate security literature. This inequity may reveal that the US may be ignoring desertification at a time when land use in some dryland areas is reaching a critical point where it can no longer support human activity. Due to the interdisciplinary nature (science and security) of this work, a review of the terminology used in the article is provided to establish a baseline understanding of “desertification” and …

Computational Investigation Of Boundary-Layer Transition Mechanisms In A Blunt Cone, Arturo Rodriguez

Open Access Theses & Dissertations

In this study, we have performed two-dimensional steady-state hypersonic CFD and one-and-two-dimensional steady-state heat conduction numerical simulations. We are using them to guide and study hypersonic boundary-layer transition ground testing physical experiments to be performed at Holloman High-Speed Test Track. We use surface heat transfer and fluid flow spot signatures to identify fluid flow regimes using laminar and turbulent numerical simulation solvers to understand boundary-layer transition thermocouple temperatures and fluid flow-forming structures. We have also analyzed the fluid flow in the geometries to be inviscid. We passed the CFD solution into the boundary-layer Harris code developed by NASA to explore …

Why Geological Angular Unconformity Is Usually Horizontal: A Geometric Explanation, Julio C. Urenda, Aaron Velasco, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In several locations, geologists have observed the presence of two differently oriented rock masses, one horizonal (or almost horizontal) and the other somewhat inclined; this phenomenon is known as angular unconformity. Based on the detailed analysis of geophysical processes, geologists conclude that usually, horizontal rock masses are much newer. This is known as the law of original horizontality. From the fundamental viewpoint, it is desirable to take into account that geophysics is a developing science, its models get modified and adjusted as time progresses. It is therefore desirable to come up with an explanation of this phenomenon that would be …

Two Is Enough, But Three (Or More) Is Better: In Ai And Beyond, Olga Kosheleva, Vladik Kreinovich, Victor L. Timchenko, Yury P. Kondratenko

Departmental Technical Reports (CS)

At present, the most successful AI technique is deep learning -- the use of neural networks that consist of multiple layers. Interestingly, it is well known that neural networks with two data processing layers are sufficient -- in the sense that they can approximate any function with any given accuracy. Because of this, until reasonably recently, researchers and practitioners used such networks. However, recently it turned out, somewhat unexpectedly, that using three or more data processing layers -- i.e., using what is called deep learning -- makes the neural networks much more efficient. In this paper, on numerous examples from …

A Full Description Of All Commutative Associative Polynomial Operations On Probabilities, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

When two events are independent, the probability that both events occur is equal to the product p1 * p2 of the probabilities of each of these events. The probability that at least one of these events will occur is equal to p1 + p2 − p1 * p2. In both cases, we have a commutative associative polynomial operation. A natural question is: how can we describe all possible operations of this type? These operations are described in this paper.

Why Kolmolgorov-Arnold Networks (Kan) Work So Well: A Qualitative Explanation, Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

In the usual deep neural network, weights are adjusted during training, but the activation function remains the same. Lately, it was experimentally shown that if, instead of using the same activation function always, we train the activation functions as well, we get a much better results -- i.e., for the networks with the same number of parameters, we get a much better accuracy. Such networks are called Kolmogorov-Arnold networks. In this paper, we provide a general explanation of why these new networks work so well.

How To Check Continuity Based On Approximate Measurement Results, Inese Bula, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, a reasonable conjecture is that, e.g., the dependence of some quantity on the spatial location is continuous, with an appropriate bounds on the difference between the values at nearby points. If we knew the exact values of the corresponding quantity, checking this conjecture would be very straightforward. In reality, however, measurement results are only approximations to the actual values. In this paper, we show how to check continuity based on the approximate measurement results.

Three Applications Of Geometric Reasoning: Why Metastasis Is Mostly Caused By Elongated Cancer Cells? How Body Shape Affects Curiosity? Why Ring Fractures In Ice?, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we describe three applications of geometric reasoning to important practical problems ranging from micro- to macro-level. Specifically, we use geometric reasoning to explain why metastasis is mostly caused by elongated cancer cell, why curiosity in fish is strongly correlated with body shape, and why ring-shaped fractures appear in Antarctica.

To Which Interdisciplinary Research Collaborations Should We Pay More Attention?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Interdisciplinary research is very important in modern science. However, such a research is not easy, it often needs support and help. Resources that can be used for such a support are limited, so we need to decide which of many possible collaborations we should support. In this paper, we provide a natural simple model of collaboration effectiveness. Based on this model, we conclude that we should support collaborations for which the vector product of the participants' knowledge vectors attains the largest values.

Why Decisions Based On The Results Of Worst-Case, Most Realistic, And Best-Case Scenarios Work Well?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, Chon Van Le

Departmental Technical Reports (CS)

Often, to make an appropriate decision, people try three scenarios: the worst case, the most realistic case, and the best case. This three-scenarios approach often leads to reasonable decisions. A natural question is: why worst case and best case? These extreme cases mean that all numerous independent random factors work in the same direction: either are all stacked for or are all stacked against. Such stacking of random factors is highly improbable. So, at first glance, it would be more beneficial to use more realistic scenarios than the worst case and the best case. However, empirically, decisions based on the …

Why Green Wavelength Is Closer To Blue Than To Red And How It Is Related To Computations: Information-Based Explanation, Victor L. Timchenko, Yury P. Kondratenko, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

In our previous papers, we analyzed the idea of using light signals of three basic color -- red, green, and blue -- to speed up computations, in particular fuzzy-related computations. A natural question is: why red, green, and blue? Why not select some other colors: e.g., from the wavelength viewpoint, green is much closer to blue than to green, so why not select colors whose distribution is more even? In this paper, we show that if we consider this problem from the information viewpoint, then the corresponding equal-information criterion indeed implies that the intermediate wavelength should be closer to the …

Training Neural Networks On Interval Data: Unexpected Results And Their Explanation, Edwin Tomy George, Vladik Kreinovich, Christoph Lauter, Martine Ceberio, Luc Jaulin

Departmental Technical Reports (CS)

In many practically useful numerical computations, training-and-then-using a neural network turned out to be a much faster alternative than running the original computations. When we applied a similar idea to take into account interval uncertainty, we encountered two unexpected results: (1) that while for numerical computations, it is usually better to represent an interval by its midpoint and half-width, for neural networks, it is more efficient to represent an interval by its endpoints, and (2) that while usually, it is better to train a neural network on the whole data processing algorithm, in our problems, it turned out to be …

What If The Resulting Interval Is Too Wide: From A Heuristic Fuzzy-Technique Idea To A Mathematically Justified Approach, Marc Fina, Vladik Kreinovich

Departmental Technical Reports (CS)

In engineering designs, we usually need to make sure that the values of some characteristics y do not exceed a certain threshold y0 – e.g., that the stress at each location does not exceed a certain critical value. Usually, we know how each of these characteristics y depends on the design parameters x1, . . . ,xn, i.e., we know the function y= f (x1, . . . ,xn). However, it is not enough to use the nominal values of the design parameters in our analysis, since the actual values are, in general, somewhat different from the nominal values. Often, …

Shapley Value Under Interval Uncertainty And Partial Information, Kittawit Autchariyapanikul, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In the 1950s, the future Nobelist Lloyd Shapley solved the problem of how to fairly divide the common gain. Namely, he showed that some reasonable requirements determine a unique division -- which is now known as the Shapley value. The main limitation of Shapley's solution is that it assumes that for each subgroup of the original group of participants, we know exactly how much this group could gain if it acted by itself, without involving others. In practice, we rarely know these exact values. At best, we know the bounds on each such value -- i.e., in other words, an …

Zebra Limestone From The Gypsum Valley Salt Diapir, Colorado, Rebecca Navarrette

Open Access Theses & Dissertations

Zebra rocks displaying alternating light and dark-colored millimeter to centimeter thick bands of crystals have been found at the Gypsum Valley salt diapir, Colorado in the Paradox Basin where they are associated with gypsic diapiric caprock. Elucidating their origin may provide crucial information about intermittent fluid flow at the margin of salt diapirs and about Zebra rock formation, which often is associated with carbonate-hosted lead-zinc mineralization (Mississippi Valley Type, MVT) and hydrothermal dolomite -hosted hydrocarbon reservoirs.

The Gypsum Valley Zebra rocks consist of calcite, i.e., it is a Zebra limestone. It shows a finely crystalline light banding and coarsely crystalline …

Investigation Of Seasonal Trends And Source Apportionment Of Particulate Matter (Pm2.5) In El Paso-Juarez Airshed, Fatema Tuz Zohora

Open Access Theses & Dissertations

Using the data from Texas Commission on Environmental Quality (TCEQ) for the El Paso city throughout the years from 2021 to 2024 Particulate Matter (PM2.5) was measured to examine the seasonal distribution and sources. This study aims to understand the seasonal variability of PM2.5 concentrations, identify the significant impact of wildfire events on this and source apportionment.The analysis begins with a comprehensive examination of PM2.5 data from TCEQ highlighting the seasonal pattern, it was found that fine particulate matter was more prevalent in winter and tends to be down in spring, and in summer it is relatively lower, subsequently in …

Experimental And Computational Investigation Of Green Laser Propagation Through Turbulent Medium In A Water Tank, Richard Owusu Adansi

Open Access Theses & Dissertations

Turbulence medium poses significant challenges to the propagation of laser beams, impacting applications such as free-space optical communication, remote sensing, and laser weapons systems. Therefore, comprehending and mitigating turbulence effects are vital for enhancing the performance of these systems. Analysis of a strong turbulence impact on electromagnetic wave propagation requires extensive knowledge of the Earth's atmospheric and Oceanic phenomena and Maxwell's electromagnetic theory of light as a propagating wave of electric and magnetic fields. Optical systems' propagation often encounters Strong Turbulence, causing interference and diffraction. Nonetheless, light propagation through randomly fluctuating media has been an exciting and active area of …

Staying Fresh: Unconventional Approaches Towards Advancing Energy Sustainability, Water Resources, And Community Resiliency In The Southwestern United States, Judith Hoyt

Open Access Theses & Dissertations

This dissertation addresses critical challenges in urban heat management, sustainable energy resource utilization, and water quality communication through three studies. Study 1 investigates the impact of roof color on urban heat islands in Tucson, Arizona where approximately 70% of roofs display high albedo (i.e., light) colors. Energy consumption simulations conducted indicate that converting dark- to light-colored roofs could save Tucson approximately $1,400,000 annually in energy costs, highlighting the potential of cool roofs for energy savings and improved thermal comfort. Study 2 assesses the sources of lithium in subsurface waters in West Texas and South Central New Mexico. Water chemistry data …

Neural Networks For Decisions Under Uncertainty, Edwin Tomy George

Open Access Theses & Dissertations

Neural networks are used in many real-world applications, ranging from classification tasks to medical diagnostics. For each task, a neural network is typically able to make predictions due to its ability to extract meaningful patterns from processing large amounts of data. Thus, given the increases in available data in recent decades, the performance of neural networks in making accurate predictions has greatly increased. However, this data often comes with ingrained uncertainties due to measurement errors or the inherent variability of individual data points. Neural networks can learn despite the errors in the overall data, but what if we want them …

Semantic Linguistic User Profiles For Automatic Computational Narrative Creation For Scientific Models, Angel Uriel Ortega Castillo

Open Access Theses & Dissertations

The outcomes of scientific models can be hard to understand given the need for context, domain knowledge, and many variables and data being used. This research aims to provide users of scientific models with understandable information that can be automatically generated. For the context of this research, understandable is defined as being correctly interpreted (i.e., with respect to the original intent of the data). Scientific information can be conveyed to users in the form of a narrative or visualizations, and these are not necessarily separate from each other, but rather complimentary. One of the objectives of this research is to …

Random Forest For High-Dimensional Data, George Ekow Quaye

Open Access Theses & Dissertations

The exponential growth of data has led to a rapid increase in high-dimensional datasets across various domains, presenting significant challenges in data analysis, particularly in predictive modeling tasks. Traditional Random Forest (RF), while robust, often struggles with datasets filled with numerous noisy or non-informative features, compromising both performance and accuracy. This study introduces an advanced algorithm, High-Dimensional Random Forests (HDRF), designed to address these challenges by integrating robust multivariate feature selection techniques directly into the decision tree construction process. Unlike standard RF, HDRF incorporates ridge regression-based variable screening at each decision split, enhancing its ability to identify and utilize the …

Quantum Circuit Optimization Leveraging Multi-Qubit Exchange Interactions In Spin Qubits, Miguel Gonzalo Rodriguez

Open Access Theses & Dissertations

This thesis looks into how multi-qubit exchange interactions can be used to improve quantumcircuits in semiconductor quantum devices. Pairwise interactions between qubits are a common tenet of traditional quantum computing paradigms, although they can impose complexity and depth constraints on circuits. In order to improve the efficiency and scalability of quantum circuits, this research explores the theoretical underpinnings and practical uses of multi-qubit interactions. A thorough theoretical framework is formulated, outlining the mathematical equivalence of a unitary matrix representing interactions between multiple qubits. We obtain the timeevolution operator by analyzing the Hamiltonian of three spin-1/2 particles. A number of quantum …

Seismic Imaging Of Mcmurdo Ice Shelf Near Williams Airfield, Yeshey Seldon

Open Access Theses & Dissertations

Seismic exploration has played a crucial role in understanding the Earth's interior and has been successfully employed in various regions, including Antarctica. This research focuses on analyzing a 1000-m seismic line on McMurdo Ice Shelf near Williams Airfield, as part of the Thwaites Interdisciplinary Margin Evolution (TIME) project. The McMurdo Ice Shelf, covering an expansive area within the Ross Ice Shelf, has undergone significant changes due to evolving oceanic and atmospheric conditions. The presence of Circumpolar Deep Water (CDW) has recently impacted the ice shelf, with warmer ocean waters causing basal melting and changes in wind patterns affecting ice flow …

Investigating Styles Of Contraction And Overprinting By Rio Grande Rift Extension In The Southern Indio Mountains, Western Texas, David W. West

Open Access Theses & Dissertations

Laramide-style intracontinental deformation occurred throughout a large area in the western United States from the late Cretaceous through the Eocene. This event is largely investigated and viewed from classic exposures in Colorado and Wyoming, extending south to southern New Mexico. In this region the Laramide orogen merges with the Mexican fold and thrust belt (MFTB) and the northern limits of the Mexican orogen along a blurry boundary. In the Indio Mountain range in western Texas, Cretaceous sediments were deposited in the Jurassic-Cretaceous Chihuahua trough. They were inverted due to contraction and emplaced adjacent to the Diablo Plateau. This region lies …

Determining Heterogeneous Growth Rates Of Brucite On Magnesia Using Multiharmonic Qcm-D And X-Ray Scattering Methods, Pedro Josue Hernandez Penagos

Open Access Theses & Dissertations

The Earth’s temperature has increased in the last six decades mainly due to the emissions of greenhouse gases, including carbon dioxide (CO2). Mineral looping using magnesium oxide (MgO) is a promising approach for direct air capture (DAC) of CO2 from the atmosphere at the GtCO2/yr scale. The presence of humidity during the carbonation process will lead to a reaction between the MgO and water resulting in magnesium hydroxide formation, Mg(OH)2, growing over the MgO surface forming a shell-like structure. The influence of temperature and relative humidity variation on heterogeneous nucleation and crystal growth kinetics of Mg(OH)2 on MgO is not …

Robust Multivariate Estimation And Inference With The Minimum Density Power Divergence Estimator, Ebenezer Nkum

Open Access Theses & Dissertations

The estimation of the location vector and scatter matrix plays a crucial role in many multivariate statistical methods. However, the classical likelihood-based estimation is greatly influenced by outliers, potentially leading to unreliable decisions. Hence, a fundamental challenge in multivariate statistics is to develop robust alternatives that can maintain performancein the presence of outliers and deviations from the assumed data distribution. Unfortunately, methods with good global robustness often substantially sacrifice efficiency. To address this, we propose the adoption of Minimum Density Power Divergence (MDPD) estimation, a well-established robust technique known for its efficiency and statistical robustness to outliers and model violations. …

Method Development For The Quantification Of Critically Valuable Elements In Permian Basin Produced Waters, Carley Oliver

Open Access Theses & Dissertations

Produced waters (PW) are a major byproduct of the oil and gas industrial hydraulic fracturing processes that create a major waste disposal issue with a need for disposal, treatment, and reuse method developments. The current primary disposal method is subsurface injection, which can lead to high pressures in the subsurface. PWs are often highly saline from mineral leaching due to long residence in subsurface reservoirs. According to the USGS National Minerals Information Center, bromine, calcium chloride, iodine, lithium, magnesium, and sodium chloride have been found in and extracted from these domestic subsurface brines, suggesting that there may be other economically …

Improving Cyber Defense Using Detailed Bayesian Models Of Attacker Reconnaissance., Nazia Sharmin

Open Access Theses & Dissertations

The continued success of cyber-attacks motivates the need for continued innovation in cyber defense. In particular, there is a need for novel methods to mitigate attacker reconnaissance, usually the first stage in planning an attack. One of the few general approaches in this stage is using deception and information manipulation to affect what the attacker can learn about a system or network. Existing work in moving target defense, game-theoretic models of cyber deception/camouflage, and adversarial learning has provided a framework for optimizing deception strategies. However, most of the current literature is based on limited models of how attackers actually perform …

Design Of Engineered Nanomaterials For Pfas Adsorption And Catalytic Degradation From Relevant Environmental Conditions, Sheng Yin

Open Access Theses & Dissertations

Poly- and per-fluoroalkyl substances (PFAS) are a class of artificially made chemicals whose carbon chains are fully or partially fluorinated. Due to their persistent and pervasive distribution and their adverse effects on human health, the removal of PFAS from the environment has been the focus of current research. This project explores the use of engineered nanomaterials for the effective removal of PFAS through various adsorption and catalytic degradation methods. First, a comprehensive review of recent studies highlights the significant potential of various nanomaterials, including carbon-based, non-metal, single-metal, and multi-metal nanomaterials, for PFAS remediation. These materials are evaluated for their performance, …