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Missouri University of Science and Technology

Masters Theses

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Full-Text Articles in Physical Sciences and Mathematics

The Deep Bsde Method, Daniel Kovach Jan 2024

The Deep Bsde Method, Daniel Kovach

Masters Theses

"The curse of dimensionality is the non-linear growth in computing time as the dimension of a problem increases. Using the Deep Backwards Stochastic Differential Equation (Deep BSDE) method developed in [HJE18], I approximate the solution at an initial time to a one-dimensional diffusion equation. Although we only approximate a one-dimensional equation, this method extends well to higher dimensions because it overcomes the curse of dimensionality by evaluating the given partial differential equation along "random characteristics''. In addition to the implementation, I also present most of the mathematical theory needed to understand this method"-- Abstract, p. iii


A New Proper Orthogonal Decomposition Method With Second Difference Quotients For The Wave Equation, Andrew Calvin Janes Jan 2024

A New Proper Orthogonal Decomposition Method With Second Difference Quotients For The Wave Equation, Andrew Calvin Janes

Masters Theses

"Recently, researchers have investigated the relationship between proper orthogonal decomposition (POD), difference quotients (DQs), and pointwise in time error bounds for POD reduced order models of partial differential equations. In \cite {Sarahs}, a new approach to POD with DQs was developed that is more computationally efficient than the standard DQ POD approach and it also retains the guaranteed pointwise in time error bounds of the standard method. In this thesis, we extend the new DQ POD approach from \cite {Sarahs} to the case of second difference quotients (DDQs). Specifically, a new POD method utilizing DDQs and only one snapshot and …


Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan Jan 2024

Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan

Masters Theses

"Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such as lack of ground truth labels, presence of complex temporal patterns, and generalizing over different datasets. In this work, we propose TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. To achieve these goals, we convert each input time-series into a sequence of 2D images using two encoding techniques with …


Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi Jan 2024

Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi

Masters Theses

"Atmospheric dispersion and transmission play an important role in the behavior and effects of air pollution. Human health can be adversely affected by air pollution in a variety of ways, both immediately and over time. The Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) modeling program, a computer model and software package, tracks the transport trajectories and distributions of air pollution and various pollutants, including radioactive pollutants, in the atmosphere. It also facilitates research on pollution sources. This study simulated the transport of hazardous aerosols in St. Louis region for the years 2020, 2021, and 2022 using the HYSPLIT modeling …


Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula Jan 2023

Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula

Masters Theses

"Ridesharing platforms rely on connecting available taxi drivers to potential passengers to maximize their revenue. However, predicting the stopping decision made by every driver, i.e., the final task performed during a given day, is crucial to achieving this goal. Unfortunately, little research has been done on predicting drivers’ stopping decisions, especially when they deviate from expected utility maximization behavior. This research proposes a Dynamic Discounted Satisficing (DDS) heuristic to model and learn the task at which human agents will stop working for that day, assuming that the human agents are taking sequential decisions based on their preference order. We apply …


Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson Jan 2023

Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson

Masters Theses

"Aluminum Nitride is an active element of sensors that monitor the performance and well-being of the nuclear reactors due to its piezoelectric properties. Yet, the variations of its properties under irradiation are largely unexplored. We report the results of the molecular dynamics simulations of the structural changes in AlN under irradiation via the knock-on atom technique. By creating and evolving the irradiation cascades due to energetic particle interaction with the atom of the crystalline lattice we determine the rate of the defect production as a function of the deposited energy. Further, we determine a displacement energy, a key characteristic that …


Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara Jan 2023

Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara

Masters Theses

"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.

The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …


The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott Jan 2023

The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott

Masters Theses

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and …


Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric Jan 2023

Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric

Masters Theses

"Vulnerability to adversarial attacks is a recognized deficiency of not only deep neural networks (DNNs) but also multi-task deep neural networks (MT-DNNs) that attracted much attention in the past few years. To the best of our knowledge, all multi-task deep neural network adversarial attacks currently present in the literature are non-targeted attacks that use gradient descent to optimize a single loss function generated by aggregating all loss functions into one. On the contrary, targeted attacks are sometimes preferred since they give more control over the attack. Hence, this paper proposes a novel targeted multi-objective adversarial ATtack (MAT) based on genetic …


Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields Jan 2023

Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields

Masters Theses

"The prevalence of gene expression microarray datasets in public repositories gives opportunity to analyze biologically interesting datasets without running the laboratory aspect in house. Such experimentation is expensive in terms of finances, time, and expertise, which often results in low numbers of replicates. Meta-analysis techniques attempt to overcome issues due to few biological or technical replicates by combining separate experiments together to increase statistical power. Proper statistical considerations help to offset issues like simultaneous testing of thousands of genes, unintended hybridization, and other noises.

Microarrays contain light intensities from tens of thousands of hybridized probes giving a measure of gene …


Maximising Social Welfare In Selfish Multi-Modal Routing Using Strategic Information Design For Quantal Response Travelers, Sainath Sanga Aug 2022

Maximising Social Welfare In Selfish Multi-Modal Routing Using Strategic Information Design For Quantal Response Travelers, Sainath Sanga

Masters Theses

"Traditional selfish routing literature quantifies inefficiency in transportation systems with single-attribute costs using price-of-anarchy (PoA), and provides various technical approaches (e.g. marginal cost pricing) to improve PoA of the overall network. Unfortunately, practical transportation systems have dynamic, multi-attribute costs and the state-of-the-art technical approaches proposed in the literature are infeasible for practical deployment. In this paper, we offer a paradigm shift to selfish routing via characterizing idiosyncratic, multiattribute costs at boundedly-rational travelers, as well as improving network efficiency using strategic information design. Specifically, we model the interaction between the system and travelers as a Stackelberg game, where travelers adopt multi-attribute …


Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch Jan 2022

Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch

Masters Theses

"This research presents studies of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X's USim® software to quantify the nozzle's capabilities. A2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T's Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were …


Adsorption Of Arsenic Onto River Sediments, Leticia Augusta Dos Santos Ferreira Jan 2022

Adsorption Of Arsenic Onto River Sediments, Leticia Augusta Dos Santos Ferreira

Masters Theses

“Previous studies have noted the relationship between shallow groundwater rich in sodium (Na) and bicarbonate (HCO3) and elevated levels of dissolved arsenic. However, most experimental work on arsenic adsorption in the presence of HCO3 and differing Na/Ca ratios has proven difficult to extrapolate to natural systems because of differences in tested mineral compositions and component concentrations. In this study, I performed a series of adsorption experiments using river sediments to evaluate the influence of HCO3 and monovalent/divalent cations on the extent of arsenic adsorption onto natural sediment in groundwater.

Batch adsorption (kinetics, equilibrium, and metal loading) …


Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac Jan 2022

Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac

Masters Theses

“Critical experiments are used by nuclear data evaluators and criticality safety engineers to validate nuclear data and computational methods. Many of these experiments are designed to maximize the sensitivity to a certain nuclide-reaction pair in an energy range of interest. Traditionally, a parameter sweep is conducted over a set of experimental variables to find a configuration that is critical and maximally sensitive. As additional variables are added, the total number of configurations increases exponentially and quickly becomes prohibitively computationally expensive to calculate, especially using Monte Carlo methods.

This work presents the development of a particle swarm optimization algorithm to design …


Several Problems In Nonlinear Schrödinger Equations, Tim Van Hoose Jan 2022

Several Problems In Nonlinear Schrödinger Equations, Tim Van Hoose

Masters Theses

“We study several different problems related to nonlinear Schrödinger equations….

We prove several new results for the first equation: a modified scattering result for both an averaged version of the equation and the full equation, as well as a set of Strichartz estimates and a blowup result for the 3d cubic problem.

We also present an exposition of the classical work of Bourgain on invariant measures for the second equation in the mass-subcritical regime”--Abstract, page iv.


Pressure Relief Wells: Analysis Of Subsurface Heterogeneity To Evaluate Relief Well Locations For Mississippi River Levees, Emma Marie Young Jan 2022

Pressure Relief Wells: Analysis Of Subsurface Heterogeneity To Evaluate Relief Well Locations For Mississippi River Levees, Emma Marie Young

Masters Theses

“When designing pressure relief well systems, it is imperative to understand what major geomorphology and heterogenies features are present, such as buried oxbow lakes, especially when the feature is parallel to the source, such as the Mississippi River. When present, there is a notable greater increase in head pressures, especially on the landward tow of the levee. This can cause erosional features that originally thought of to have been protected from by installing pressure relief wells. When comparing the effective hydraulic conductivities of horizontal clay layers and vertical clay layers spanning the length of the model, little to no noticeable …


Using Lake Sediment Chemistry In The Exploration For Nickel Laterite Deposits In Tropical Regions, Gabriela Yvonne Ramirez Jan 2022

Using Lake Sediment Chemistry In The Exploration For Nickel Laterite Deposits In Tropical Regions, Gabriela Yvonne Ramirez

Masters Theses

"Developing reliable geochemical indicators to guide the search for ore deposits is a long-standing goal. This particularly applies to tropical regions that are often heavily vegetated which hampers boots-on-the ground exploration efforts. Here we present the preliminary results of a study that investigates the usefulness of lake sediment chemistry in the exploration for nickel laterite ore deposits in tropical regions using Lake Izabal, Guatemala, as a case study. Lake Izabal’s catchment area contains Ni laterite deposits along its northern shore, whereas no Ni-laterite discoveries have been made in the south except for a Ni mine in the southern region that …


Lithofacies Characterization Of Marine Shelf Shale And Implicaitons On Depositional Conditions And Processes On The Continental Shelf — A Case Study Of The Upper-Cretaceous Tuscaloosa Marine Shale In Louisiana And Mississippi, U.S.A., Efren Mendez Jr Jan 2022

Lithofacies Characterization Of Marine Shelf Shale And Implicaitons On Depositional Conditions And Processes On The Continental Shelf — A Case Study Of The Upper-Cretaceous Tuscaloosa Marine Shale In Louisiana And Mississippi, U.S.A., Efren Mendez Jr

Masters Theses

"The Upper Cretaceous Tuscaloosa Marine Shale (TMS) is an unconventional shale reservoir deposited on the continental shelf of the northern Gulf of Mexico Basin. Previous studies have focused on sequence stratigraphy, thermal modeling, and well-log correlations. However, a limited understanding of the stratigraphic heterogeneity of the TMS is yet to be studied. This study aims to characterize the stratigraphic heterogeneity of the TMS using core, petrographic, and well-log analyses to better understand the depositional conditions and processes that occur on the continental shelf. The TMS has been classified into four lithofacies of very fine sands – coarse silts (LF1), medium-fine …


Continuous And Discrete Models For Optimal Harvesting In Fisheries, Nagham Abbas Al Qubbanchee Jan 2022

Continuous And Discrete Models For Optimal Harvesting In Fisheries, Nagham Abbas Al Qubbanchee

Masters Theses

"This work focuses on the logistic growth model, where the Gordon-Schaefer model is considered in continuous time. We view the Gordon-Schaefer model as a bioeconomic equation involved in the fishing business, considering biological rates, carrying capacity, and total marginal costs and revenues. In [25], the authors illustrate the analytical solution of the Schaefer model using the integration by parts method and two theorems. The theorems have many assumptions with many different strategies. Due to the nature of the problem, the optimal control system involves many equations and functions, such as the second root of the equation. We concentrate on Theorem …


Man-In-The-Middle Attacks On Mqtt Based Iot Networks, Henry C. Wong Jan 2022

Man-In-The-Middle Attacks On Mqtt Based Iot Networks, Henry C. Wong

Masters Theses

“The use of Internet-of-Things (IoT) devices has increased a considerable amount in recent years due to decreasing cost and increasing availability of transistors, semiconductor, and other components. Examples can be found in daily life through smart cities, consumer security cameras, agriculture sensors, and more. However, Cyber Security in these IoT devices are often an afterthought making these devices susceptible to easy attacks. This can be due to multiple factors. An IoT device is often in a smaller form factor and must be affordable to buy in large quantities; as a result, IoT devices have less resources than a typical computer. …


Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii Jan 2021

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …


Biochemical Assay Invariant Attestation For The Security Of Cyber-Physical Digital Microfluidic Biochips, Fredrick Eugene Love Ii Jan 2021

Biochemical Assay Invariant Attestation For The Security Of Cyber-Physical Digital Microfluidic Biochips, Fredrick Eugene Love Ii

Masters Theses

“Due to the devastating global impact that infectious diseases have had, especially in developing countries, the demand for access to adequate resources to combat sickness continues to be a heavy burden. Reliable and affordable diagnostics is a vital first line of defense in fighting outbreaks and providing accurate treatment. Digital microfluidics biochips capable of running multiple diagnostic tests on a single platform are an emerging technology that are increasingly being evaluated as a viable platform for rapid diagnosis and point-of-care field deployment. Although these systems offer many benefits, processing errors are inherent. Therefore, cyber-physical digital biochips are being investigated that …


Values Of Trust In Ai In Autonomous Driving Vehicles, Ru Lian Jan 2021

Values Of Trust In Ai In Autonomous Driving Vehicles, Ru Lian

Masters Theses

“Automation with artificial intelligence technology is an emerging field and is widely used in various industries. With the increasing autonomy, learning, and adaptability of intelligent machines such as self-driving cars, it is difficult to regard them as simple tools in human hands. At the same time, a series of problems and challenges such as predictability, interpretability, and causality arise. Trust in self-driving technology will impact the adoption and utilization of autonomous driving technology. A qualitative research methodology, Value-Focused Thinking, is used to identify the values of trust in autonomous driving vehicles and analyze the relationship between these values”--Abstract, page iii.


Preclassic Cultural Eutrophication Of Lake Petén Itzá, Lowland Guatemala, By The Early Maya Of Nixtun-Ch'ich', Brooke A. Birkett Jan 2021

Preclassic Cultural Eutrophication Of Lake Petén Itzá, Lowland Guatemala, By The Early Maya Of Nixtun-Ch'ich', Brooke A. Birkett

Masters Theses

"Paleolimnological evidence indicates the ancient Maya transformed lowland terrestrial ecosystems by felling forest vegetation to construct large civic-ceremonial centers and expand agriculture. The effects of prehistoric Maya land alterations on lake trophic status, however, remain poorly understood. We analyzed a 515-cm-long sediment core from Lake Petén Itzá, lowland Guatemala, to infer paleoenvironmental changes resulting from Maya occupation of the riparian archaeological site of Nixtun-Ch'ich'. Substantial increases in charcoal and fecal stanol concentrations indicate Maya occupation of the Candelaria Peninsula by the late Early Preclassic period beginning ca. 1400 cal yr Before the Common Era (hereafter BCE), despite scant archaeological evidence …


A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang Jan 2021

A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang

Masters Theses

"Raman scattering is called a photonic - molecular interaction based on the kinetic model of the analytic. Due to the uniqueness of the Raman scattering technique, it can provide a unique fingerprint signal for molecular recognition. However, a serious challenge often encountered in Raman measurement comes from the requirements of fast, real-time remote sensing, background fluorescence suppression, and micro-environmental detection.

A new Miniaturized Fiber-Optic Raman Probe (MFORP) for Raman spectroscopy, used especially for eliminating background fluorescence and enhancing sampling, is presented. Its main purpose is to provide an overview of excellent research on the detection of very small substances and …


Predator Scent And Presence Alter Mammal Assemblages In The Missouri Ozarks, Usa, Cara Jean Yocom-Russell Jan 2021

Predator Scent And Presence Alter Mammal Assemblages In The Missouri Ozarks, Usa, Cara Jean Yocom-Russell

Masters Theses

"Species that are vulnerable to predation exhibit a host of behavioral and physiological adaptations toward the avoidance of this outcome: Heightened awareness of surroundings through visual, olfactory, and auditory senses are common ways in which these species avoid detection by predators. While links between direct predator-prey relationships are well established, less is known about how predators can shape overall community structure or the populations of secondary or less frequently consumed prey items. As humans expand into rural areas, the frequency of wildlife conflicts rises. In response, humans look to prevent these events with a variety of methods. One such method …


Multiple Generations Of Phlogopite In An Alnöite Diatreme: Insights Into The Petrogenesis Of The Avon Alkaline Igneous Province, Missouri, Nathan Gregory Limbaugh Jan 2021

Multiple Generations Of Phlogopite In An Alnöite Diatreme: Insights Into The Petrogenesis Of The Avon Alkaline Igneous Province, Missouri, Nathan Gregory Limbaugh

Masters Theses

“Alkaline Ultramafic Carbonatite (AUC) complexes, although rare, are valued for diamonds and REEs, and as windows into subcontinental and mantle processes as recorded by rock fabrics, mineral spatial relationships, and mineral compositions. We report specifically on olivine and phlogopite petrographic relationships and compositions from the Devonian alnoite diatreme-facies of the Avon Alkaline Igneous Province, Missouri. The diatreme alnoite is a mixture of domains of olivine magmaclasts (OM) set in a crystal-rich melilite matrix. OM are highly fractured, serpentinized olivine pseudomorphs with variable amounts of pristine olivine fragments. Larger olivine domains typically exhibit clear crystal faces and irregular “channels” indicative of …


A Compact Wavelength Meter Using A Multimode Fiber, Ogbole Collins Inalegwu Jan 2021

A Compact Wavelength Meter Using A Multimode Fiber, Ogbole Collins Inalegwu

Masters Theses

“Wavelength meters are very important for precision measurements of both pulses and continuous-wave optical sources. Conventional wavelength meters employ gratings, prisms, interferometers, and other wavelength-sensitive materials in their design. Here, we report a simple and compact wavelength meter based on a section of multimode fiber and a camera. The concept is to correlate the multimodal interference pattern (i.e., speckle pattern) at the end-face of a multimode fiber with the wavelength of the input lightsource. Through a series of experiments, specklegrams from the end face of a multimode fiber as captured by a charge-coupled device (CCD) camera were recorded; the images …


Relationships Among Mineralogy, Geochemistry, And Oil And Gas Production In The Tuscaloosa Marine Shale, Hayley Roxana Beitel Jan 2021

Relationships Among Mineralogy, Geochemistry, And Oil And Gas Production In The Tuscaloosa Marine Shale, Hayley Roxana Beitel

Masters Theses

"The Tuscaloosa Marine Shale (TMS) is an unconventional shale reservoir located in southeast Louisiana and southwest Mississippi. Limited mineralogical and geochemical data for the TMS have been published. The data that do exist indicate that the formation is heterogeneous. Consequently, previous investigators and oil and gas companies have not managed to effectively link mineralogical and chemical changes to oil and gas production in the TMS. These linkages are critical to establish for future exploration efforts. In this study, we attempt to establish these relationships by gathering all existing mineralogical and chemical data in the TMS, including newly acquired data from …


Strain Partitioning Across The Polochic-Motagua Fault System In Guatemala: Insight From Kinematic Modeling, Qiaoqi Sun Jan 2020

Strain Partitioning Across The Polochic-Motagua Fault System In Guatemala: Insight From Kinematic Modeling, Qiaoqi Sun

Masters Theses

”The Polochic-Motagua Fault System in Guatemala is the on-land segment of the sinistral transform plate boundary between the North American Plate and the Caribbean Plate. Three major seismically active strike-slip faults in this fault system pose significant earthquake threats to surrounding populated cities. The assessment of seismic hazard requires a better understanding of the kinematics of the fault system. GPS monitoring indicates that seventy-five percent of the ~20 mm/yr. plate motion is accommodated by the Motagua Fault and less than twenty-five percent is accommodated by the Polochic Fault. However, the Polochic Fault documents a lateral offset of ~132 ± 5 …