Physical Sciences and Mathematics Commons^™

Phoneme Recognition For Pronunciation Improvement, Matthew Heywood

Theses/Capstones/Creative Projects

This project aims to improve English pronunciation by investigating speech errors and developing a tool to provide precise feedback. The study focuses on creating a new pronunciation tool that offers localized feedback, identifies specific errors, and suggests corrective measures. By addressing the shortcomings of current methods, this research seeks to enhance pronunciation refinement.

Utilizing cutting-edge technology, the tool leverages speech-to-phoneme AI models and modified lazy string matching algorithms to compare the user's spoken input with the intended pronunciation. This allows for a detailed analysis of discrepancies, providing users actionable insights into their phonetic errors. The speech-to-phoneme AI models mark a …

Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon

Mechanical Engineering

This report aims to allow our sponsor, to review our design process of the Hitch Cart Landing Gear Prototype. In the design overview section of this report, we discuss the primary design modifications we made to the wheel mechanism of the existing hitch cart prototype, including the addition of the ACME screws and the folding brackets. This allows our sponsor to see the intended improvements made to the past prototype and understand the primary goal of our project. Then, in the implementation section, we cover the entire manufacturing process to allow our sponsor to understand what manufacturing steps must be …

Optimizing Mobility On Demand Systems: Multiagent Reinforcement Learning Approaches To Order Assignment And Vehicle Guidance, Jiyao Li

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation explores ways to improve Mobility on Demand (MoD) systems, which are services like ride-sharing and autonomous taxi systems. The main goal is to make these services more efficient and reliable, benefiting both passengers and drivers by better matching the number of available vehicles with the number of people needing rides.

For ride-sharing services, a new method called T-Balance helps match riders with drivers and guides empty taxis to areas where more people need rides. This reduces wait times for passengers and increases earnings for drivers. Another method, called GRL-HM, looks at how riders and drivers behave to further …

The Mongolian Remodeling And The Structure Of Anoplocephalid Cestode Diversity, Mackenzie Grover

All NMU Master's Theses

Ecological disruption plays an important role in structuring diversity of flora, fauna, and their parasites. At the end of the Eocene, climatic change across Asia resulted in a faunal turnover (the Mongolian Remodeling) as rodents diversified and larger mammals declined. Throughout the Oligocene, the landscape in Asia was characterized by episodic climatic and landscape changes resulting in pulses of rodent diversification. The role of historical ecological disruption in Central Asia in structuring the diversity of parasites of small rodents has not been thoroughly investigated. The hyper-diverse Paranoplocephala species complex (family: Anoplocephalidae) infect rodents throughout the Holarctic and present an opportunity …

Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma M. Watts

All Graduate Theses and Dissertations, Fall 2023 to Present

Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different …

Impact Of Snow Accumulation On Structural Integrity: Present And Future Perspectives, Kenneth K. Pomeyie

All Graduate Theses and Dissertations, Fall 2023 to Present

In the United States, accommodating the weight of accumulated snow on buildings is a crucial consideration in building design. Engineers are tasked with determining the design snow load, which is defined as the weight of accumulated snow that a structure should withstand to limit the risk of building collapse to an acceptably low level. Typically, this process involves analyzing historical data of the annual maximum snow accumulations for each snow season. However, accurately assessing these design snow loads entails navigating through a series of statistical challenges. This dissertation, composed of three papers, is dedicated to addressing these statistical hurdles in …

Quantitative Evaluation Of Baseflow Separation Methods Using An Integrated Hydrologic Model: A Case Study In A Snow-Dominated Watershed, Jihad Othman

All Graduate Reports and Creative Projects, Fall 2023 to Present

Baseflow, commonly referred to as the groundwater contribution to streamflow, constitutes approximately 50% of streamflow in mountainous regions of the Western United States. Accurately quantifying the amount of baseflow is critical for water management and decision-making, as it significantly impacts stream water quality, low flow availability, and ecosystem health. Traditionally, baseflow has been estimated using conceptual and automated baseflow separation methods, which are known to be both arbitrary and ambiguous, posing a challenge to validate them. In this study, we developed an integrated hydrologic model that seamlessly integrated the exchange between surface and subsurface flows to physically quantify the baseflow …

Interpreting Neural Networks For Particle Tracing In Fluid Simulation Ensembles: An Interactive Visualization Framework, Maanav Choubey

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding the internal mechanisms of neural networks, particularly Multi-Layer Perceptrons (MLP), is essential for their effective application in a variety of scientific domains. In particular, in the scientific visualization domain their adoption has recently shown to be a promising tool to predict particle trajectories in fluid dynamics simulation and aid the interactive visualization of flows. This research addresses the critical challenge of interpretability of such models.

While interpretability has been extensively explored in fields like computer vision and natural language processing, its application to time series data, particularly for particle tracing (or prediction of trajectories), has not garnered sufficient attention. …

Testing For Patterns Of Deformation From The Yellowstone Hotspot Along The Gallatin River, Sw Montana, Jack Willard

All Graduate Theses and Dissertations, Fall 2023 to Present

Yellowstone has fascinated humans for thousands of years. Geologists have addressed many of the region’s mysteries, including the underlying mantle hotspot, the chain of calderas tracking the motion of the North American Plate over this hotspot, and the risks posed by the super volcano. However, the way that the hotspot impacts regional tectonics and topography remains under-studied. Influential previous work recognized the Yellowstone Crescent of High Terrain (YCHT), an arc of high topography around the Yellowstone Plateau with limbs extending to the west and south into central Idaho and northern Utah. The YCHT is also hypothesized to be the pattern …

Enzyme Encapsulation Within The Hk97 Virus-Like Particle: An Investigation Of Substrate Inhibition Kinetics Within A Confined And Crowded Environment, Joseph B. Lively

Chemistry Theses

Substrate inhibition is a paradoxical phenomenon observed in enzyme kinetics where increasing substrate concentrations lead to a marked decrease in the rates of enzyme-catalyzed reactions. Affecting an estimated 20% of studied enzymes, substrate inhibition poses significant challenges to the understanding of their function in essential biological processes and to their exploitation in industrial and therapeutic contexts. Studies show substrate inhibition to be a real limitation in vitro and rational conclusions have been drawn to explain the relevance of substrate inhibition in the self-regulation of biological pathways. However, there is currently no consensus on what role substrate inhibition plays in vivo …

Bioluminesence-Induced Photoredox Catalysis And Its Mechanisms, Dominic Jeffrey Bates

Theses and Dissertations

The bioluminescence-induced photoredox reaction (BIPR) is a novel methodology developed to overcome the limitations of photo-induced chemistry by initiating chemical work using bioluminescent Escherichia coli as a photon source. In industry, photochemistry is superseded by thermochemical reaction processes. Despite its massive potential, there are very few applications in industry for photochemistry. Unlike thermochemistry, reaction scale-ups are not as easy as simple dimensional increases in a reaction vessel due to the nature of light. This deficiency is seemingly overcome through the development of flow technologies; however, the overall yield of such methods remains incomparable with those utilizing thermochemistry. This thesis focuses …

Optimizing Neural Network Architecture Using Kernel Principal Component Analysis, Saige Simcox

Theses and Dissertations

Neural networks have proven to be powerful tools for modeling a wide range of problems across applications. However, one of the challenges in implementing a neural network model lies in determining the neural network architecture, i.e. the appropriate number of hidden layers and the number of neurons per hidden layer. It has been suggested that one way to determine the number of hidden layers is by using information on the variability captured by each principal component. In this research, we expand on this idea and propose a new approach to determine the neural network architecture for a multilayer perceptron used …

Variational Bayesian Inference For Functional Data Clustering And Survival Data Analysis, Chengqian Xian

Electronic Thesis and Dissertation Repository

Variational Bayesian inference is a method to approximate the posterior distribution under a Bayesian model analytically. As an alternative to Markov Chain Monte Carlo (MCMC) methods, variational inference (VI) produces an analytical solution to an approximation of the posterior but have a lower computational cost compared to MCMC methods. The main challenge of applying VI comes from deriving the equations used to update the approximated posterior parameters iteratively, especially when dealing with complex data. In this thesis, we apply the VI to the context of functional data clustering and survival data analysis. The main objective is to develop novel VI …

Economic Impacts Of Establishing A Neutron Source Facility In Windsor, Abdur Rahman

Major Papers

Cancer poses a significant health challenge in Canada, with two in five individuals likely to develop the disease. This paper explores the economic impacts of establishing a prototype compact accelerator-based neutron source (PC-CANS) facility in Windsor that will produce medical isotopes locally in Windsor, Ontario, rather than relying on centralized production and transportation from London, Ontario. Fluorine-18 medical isotopes, crucial for positron emission tomography (PET) scans, experience significant decay losses during transportation due to their short half-life of 109.8 minutes, increasing costs and restricting availability. Using a differential analysis approach, the study quantifies economic benefits, focusing on three main impacts: …

Computational And Experimental Advances In Nuclear Magnetic Resonance For High Resolution Structures, Ryan Toomey

Theses and Dissertations

Since its inception, nuclear magnetic resonance (NMR) has been a valuable tool for determining chemical structure. In recent years, the field of NMR has been advanced forward by the ability to calculate theoretical parameters with increasing accuracy and efficiency. These calculations are compared to experimental data to produce high resolution structures. The progression of these applications has been made possible by improved instrumentation, data processing methods, probe and experiment design, better quality functionals and basis sets, as well as increased computational power. This research is especially relevant with the emergence of artificial intelligence, which has great potential to expedite steps …

Minimal Separating Sets In Surfaces, Christopher Nelson Aagaard

Dissertations and Theses

Given a connected topolgical space X, we say that L ⊆ X is a minimal separating set if removing L from X gives a disconnected surface, butremoving any proper subset of L leaves the surface connected. We classify which embeddings of topological graphs are minimal separating in an orientable surface X with genus g, and construct a computer program to compute the number of such embeddings, and the number of topological graphs which admit such an embedding for g ≤ 5.

Locating Diversity In Reservoir Computing Using Bayesian Hyperparameter Optimization, Whitney Lunceford

Theses and Dissertations

Reservoir computers rely on an internal network to predict the future state(s) of dynamical processes. To understand how a reservoir's accuracy depends on this network, we study how varying the networ's topology and scaling affects the reservoir's ability to predict the chaotic dynamics on the Lorenz attractor. We define a metric for diversity, the property describing the variety of the responses of the nodes that make up reservoir's internal network. We use Bayesian hyperparameter optimization to find optimal hyperparameters and explore the relationships between diversity, accuracy of model predictions, and model hyperparameters. The content regarding the VPT metric, the effects …

Incorporating Solvation Thermodynamic Mapping In Computer-Aided Drug Design, Yeonji Ji

Dissertations, Theses, and Capstone Projects

Advancements in computational techniques have revolutionized structure-based drug design, substantially improving the efficiency and effectiveness of the drug discovery process by reducing time, costs, and labor requirements. These advancements include various methods, such as investigating small molecule ligands binding to proteins, exploring alternative protein conformations, and solvation mapping on the protein surfaces. Among these methods, understanding the correlation between protein-ligand binding and the role of solvation is important.

A fundamental concept in protein-ligand binding is shape and electrostatic complementarity, which is complicated by the inherent flexibility of proteins. In the absence of small molecule ligands, proteins are complementary to surface …

Coastal Flood Risk In The Context Of Climate Change And Urbanization In Northeastern South Carolina, Hongyuan Zhang

Electronic Theses and Dissertations

Researchers and the public now widely recognize the seriousness of coastal flood risks. Various changes in natural processes, such as altered rainfall patterns, increased tropical cyclone intensities, and sea-level rise, are consequences of global warming induced by heightened greenhouse gas concentrations. To comprehensively understand coastal compound flooding, it is crucial to consider multiple processes and their interactions. Moreover, the growth of coastal cities and the concentration of people and assets in these areas make them increasingly vulnerable to flooding events. Accurately estimating the future flood risks faced by coastal communities necessitates addressing the compounding effects on coastal flood risk, taking …

Limit Theorems For L-Functions In Analytic Number Theory, Asher Roberts

Dissertations, Theses, and Capstone Projects

We use the method of Radziwill and Soundararajan to prove Selberg’s central limit theorem for the real part of the logarithm of the Riemann zeta function on the critical line in the multivariate case. This gives an alternate proof of a result of Bourgade. An upshot of the method is to determine a rate of convergence in the sense of the Dudley distance. This is the same rate Selberg claims using the Kolmogorov distance. We also achieve the same rate of convergence in the case of Dirichlet L-functions. Assuming the Riemann hypothesis, we improve the rate of convergence by using …

Protein And Water Modeling In Computer-Aided Drug Discovery, Mossa Ghattas

Dissertations, Theses, and Capstone Projects

The field of Computer-Aided Drug Design (CADD) is continuously evolving to improve protein modeling, a crucial step in the drug discovery process. However, limitations exist in how CADD accounts for the various configurations a protein can adopt due to different rotamer and protonation states of its residues. This thesis explores advancements in CADD to address this challenge, focusing on protein modeling and water interactions.

In Chapter 1, I introduce the drug discovery process with a brief overview of its history, the purpose of FDA clinical trials, and the cost and time duration for bringing a drug to the market. I …

Some Studies On Mathematical Morphology In Remotely Sensed Data Analysis, Geetika Barman

Doctoral Theses

The application of Mathematical Morphology (MM) techniques has proven to be beneficial in the extraction of shapebased and texture-based features during remote sensing image analysis. The characteristics of these techniques, such as nonlinear adaptability and comprehensive lattice structure, make them useful for contextual spatial feature analysis. Despite the advancements, there are still persistent challenges, including the curse of dimensionality, maintaining spatial correlation, and the adaptability of morphological operators in higher dimensions. The focus of this thesis is to explore the potential of MM-based methods to analyse spatial features in addressing these challenges, specifically in the context of spatialcontextual feature analysis …

Reclaiming Healing Spaces: A Phenomenological Study On The Transformative Power Of Outdoor Therapy From The Lived Experiences Of Black Clinicians Working With Black Clients, Lynn Murphy

Dissertations

This phenomenological study involved assessing the experiences of Black therapists who engaged Black clients in outdoor therapeutic contexts. The study was founded on the existing literature that shows the quality of the therapeutic relationship is pivotal for client retention and the Western standards that have historically favored treatment within indoor environments. To contextualize this research, a comprehensive literature review was commenced, covering topics such as the decolonization of therapy, the historical and present-day relationship between Blacks and the outdoors in the United States, sedentary lifestyles, the psychological benefits of time spent in nature, various types of outdoor therapy, and the …

Enabling Emg-Based Silent Speech Transcription Through Speech-To-Text Transfer Learning, Alexander T. Garcia

Master's Theses

In recent years, advances in deep learning have allowed various forms of electrographic signals, such as electroencephalography (EEG) and electromyography (EMG), to be used as a viable form of input in artificial intelligence applications, particularly for applications in the medical field. One such topic that EMG inputs have been used is in silent speech interfaces, or devices capable of processing speech without an audio-based input. The goal of this thesis is to explore a novel method of training a machine learning model to be used for silent speech interface development: using transfer learning to leverage a pre-trained speech recognition model …

Dynamic Difficulty Adjustment For Combat Systems In Role-Playing Genre Video Games, Cheuk Man Chan

Dissertations, Theses, and Capstone Projects

Static difficulty adjustment has been applied to video games since their inception. However, dynamic difficulty adjustment did not become a topic of interest in either the academic fields or the industry until the turn of the century with sufficient advancement in processing power of computers and console systems. Amongst the work done in this area, most of the focus has either been placed on the action/adventure or the strategy game genre. However, there are only a limited number of studies regarding the role playing game genre which, by the nature of such games, generates a massive amount of data regarding …

Representation Theory Arising From Groups In Physics, Jaxon Green

Master's Theses

A representation is a group homomorphism whose image is a group of invertible matrices. Representations and their associated matrices are analyzed through well-established techniques from linear algebra. We characterize representations by a unique decomposition into irreducible representations just as we characterize the decomposition of matrices into their eigenspaces. Through the study of these representations, we uncover mathematical relationships that underlie groups with physical applications. Due to physical symmetries, we study how the irreducible representations of groups that embody the actions of even the most basic rotations are utilized in the computation of irreducible representations groups that reflect more complicated mechanics, …

Some New Properties Of Random Groups In The Density And Few-Relator Models, Anastasiia Chorna

Dissertations, Theses, and Capstone Projects

In this dissertation, we delve into the subjects that lie in the intersection of random group theory and first-order theory, or as traditionally referred to in the field, the first-order theory of free groups (Sela (2006) and Kharlampovich and Myasnikov (2006), among others). In particular, we establish the following two findings. First, we demonstrate that for fixed k > 2, among finitely generated groups, those without finite index subgroups of index k are prevalent in the density model (as discussed in Chapter 3). Second, we show that a first-order universal sentence in the language of groups is almost surely true in …

From Stars To Moons: Investigating Stellar Rotations, Planetary Interactions, And Exoplanetary Prospects, Rosario Cecilio-Flores-Elie

Dissertations, Theses, and Capstone Projects

The thesis is divided into two key sections. The first chapter presents the results of analyzing TESS light curves for 99 targets within the Carina-Near moving group. By deriving rotational periods, this analysis supports stellar age estimation, contributing to the broader efforts of the Backyard Worlds: Planet 9 citizen project in determining age parameters for 89 newly identified systems, including ultracool dwarf companions. These findings enhance our understanding of stellar rotation and evolution, offering new insights into the development of secondary co-moving objects like brown dwarfs.

The second chapter investigates planet-moon interactions within our solar system by examining mass ratios, …

Advanced Predictive Analytics On Financial Donations To Nonprofit Organizations, Fhamida Keya

Dissertations, Theses, and Capstone Projects

Non-profit organizations rely on donation contributions to carry out their social driven agenda. In the context of fundraising and donor management, it is crucial to uncover complex insights about donor behavior for optimizing strategies and enhancing donor engagement. This project employed advanced analytical techniques on the dataset Donations Received by City Agencies sourced from NYC Open Data by implementing predictive modeling, clustering segmentation, and time series analysis and forecasting. The project will attempt to uncover patterns in donation behavior, identify factors that influence donation amounts, and segment out donor profiles all of which can be leveraged to optimize strategy decisions, …

Who Are You Rooting For? T20 Cricket World Cup 2024, Usa & Wi, Purvesh Desai

Dissertations, Theses, and Capstone Projects

The T20 Cricket World Cup '24 played in USA & WI will bring immense excitement to the cricket lovers around the world and have a question to themselves “Who shall I Root for?” How do people or fans support their favorite teams and on what criteria do they pick these teams will discuss in here.

Patriotism, tradition, and favorite individual players, are the main reasons for the fans to choose their and support the team. Nation is the biggest pride of an individual and many people choose their pride over everything. People celebrate when the home team plays on the …