Physical Sciences and Mathematics Commons^™

Investigating The Effects Of A Southward Flow In The Southeastern Florida Shelf Using Robotic Instruments, Alfredo Quezada

All HCAS Student Capstones, Theses, and Dissertations

We deployed a Slocum G3 glider fitted with an acoustic Doppler current profiler (ADCP), a Conductivity-Temperature-Depth sensor (CTD), optics sensor channels, and a propeller on the Southeastern Florida shelf. The ADCP and CTD provide continuous measurements of Northern and Eastern current velocity components, salinity, temperature, and density, throughout the water column in a high-current environment. The optics sensor channels are able to provide measurements of chlorophyll concentrations, colored dissolved organic matter (CDOM), and backscatter particle counts. Additionally, for one of the glider deployments, we deployed a Wirewalker wave-powered profiling platform system also fitted with an ADCP and a CTD in …

Climate Change Impact On Bridge Scour Risk In Ny State: A Gis-Based Risk Analysis Model, Muhammad Hassan Butt

Publications and Research

Bridge scour, the primary cause of bridge failure in the United States, escalates post-severe storms, necessitating effective mitigation. This study employs a GIS-based risk analysis model to assess climate change's impact on bridge scour and associated risks in New York State. Data from the National Bridge Inventory, climate hazard maps, and geospatial data are integrated.

Development Of An App For The Kalamazoo Nature Center, Ernest Au

Honors Theses

Kalamazoo Nature Center (KNC), which has been recognized by its peers as one of the top nature centers in the country, is home to over 14 miles of hiking trails winding through woods, wetlands, and prairies. There are numerous places/plots in KNC that have an interesting and impressive history besides being home to a variety of animals and hundreds of wildflowers and other plant life. To improve the visitor’s experience at KNC, we will design a software app via the senior capstone project at the department of Computer Science at WMU. As the first step towards establishing a reference model …

Teaching Reproducibility To First Year College Students: Reflections From An Introductory Data Science Course, Brennan L. Bean

Journal on Empowering Teaching Excellence

Access the online Pressbooks version of this article here.

Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study where students are asked to complete a “reproducible” final project in an introductory data science course using the R programming language. A reproducible project is one where an instructor can easily regenerate the results and conclusions from the submitted …

Analyzing The Efficacy Of Covid-19 Travel Bans: A Regression Analysis Approach, Mallory Kochanek

Honors Projects

Some might associate the term ‘public health’ with the pandemic that occurred in 2020. COVID-19 spread like most have never seen in their lifetime. It is useful to look at the effectiveness of the travel re- strictions in mitigating the spread of the global pandemic. Using linear regression and network regression, we obtain parameter estimates to determine the relation of predictors, such as network effect, percentage of urban population and GDP, on the COVID-19 incidence rate for the months January to April of 2020. Linear regression does not ac- count for the correlation structure of the data. Network regression, on …

Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin

Introduction to Research Methods RSCH 202

This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …

Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede

Doctoral Dissertations

The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …

Metrics For Comparison Of Complex Networks, Clarissa Reyes

Open Access Theses & Dissertations

Heuristic network statistics are used as a preliminary approach to identify change across networks. In networks where there is known node correspondence (KNC), conventional network comparison methods include taking a norm of the difference matrix, or calculating dissimilarity measures like DeltaCon and cut distance. Since different KNC measures provide varying insight to the network comparison problem, we propose employing Rank Score Characteristic Functions (RSCFs) and the rank-score process as a method for reaching a consensus when ranking quantified change across multiple pairs of networks â?? which is particularly useful for ranking change across subpopulations or subgraphs. Additionally, we propose a …

Exploration And Statistical Modeling Of Profit, Caleb Gibson

Undergraduate Honors Theses

For any company involved in sales, maximization of profit is the driving force that guides all decision-making. Many factors can influence how profitable a company can be, including external factors like changes in inflation or consumer demand or internal factors like pricing and product cost. Understanding specific trends in one's own internal data, a company can readily identify problem areas or potential growth opportunities to help increase profitability.

In this discussion, we use an extensive data set to examine how a company might analyze their own data to identify potential changes the company might investigate to drive better performance. Based …

The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion, Grace Y. Ng, Ritesh Karsalia, Ryan S. Gallagher, Austin J. Borja, Jianbo Na, Scott Mcclintock, Neil R. Malhotra

Mathematics Faculty Publications

INTRODUCTION: The relationship between socioeconomic status and neurosurgical outcomes has been investigated with respect to insurance status or median household income, but few studies have considered more comprehensive measures of socioeconomic status. This study examines the relationship between Area Deprivation Index (ADI), a comprehensive measure of neighborhood socioeconomic disadvantage, and short-term postoperative outcomes after lumbar fusion surgery. METHODS: 1861 adult patients undergoing single-level, posterior-only lumbar fusion at a single, multihospital academic medical center were retrospectively enrolled. An ADI matching protocol was used to identify each patient's 9-digit zip code and the zip code-associated ADI data. Primary outcomes included 30- and …

Models Of Shared Care For The Management Of Psychotic Disorder After First Diagnosis In Ontario., Joshua C. Wiener, Rebecca Rodrigues, Jennifer N S Reid, Kelly K. Anderson

Epidemiology and Biostatistics Publications

OBJECTIVE: To describe the provision of care for young people following first diagnosis of psychotic disorder.

DESIGN: Retrospective cohort study using health administrative data.

SETTING: Ontario.

PARTICIPANTS: People aged 14 to 35 years with a first diagnosis of nonaffective psychotic disorder in Ontario between 2005 and 2015 (N=39,449).

MAIN OUTCOME MEASURES: Models of care, defined by psychosis-related service contacts with primary care physicians and psychiatrists during the 2 years after first diagnosis of psychotic disorder.

RESULTS: During the 2-year follow-up period, 29% of the cohort received only primary care, 30% received only psychiatric care, and 32% received both primary and …

Random Variable Spaces: Mathematical Properties And An Extension To Programming Computable Functions, Mohammed Kurd-Misto

Computational and Data Sciences (PhD) Dissertations

This dissertation aims to extend the boundaries of Programming Computable Functions (PCF) by introducing a novel collection of categories referred to as Random Variable Spaces. Originating as a generalization of Quasi-Borel Spaces, Random Variable Spaces are rigorously defined as categories where objects are sets paired with a collection of random variables from an underlying measurable space. These spaces offer a theoretical foundation for extending PCF to natively handle stochastic elements.

The dissertation is structured into seven chapters that provide a multi-disciplinary background, from PCF and Measure Theory to Category Theory with special attention to Monads and the Giry Monad. The …

Bingroup2: Statistical Tools For Infection Identification Via Group Testing, Christopher R. Bilder, Brianna D. Hitt, Brad J. Biggerstaff, Joshua M. Tebbs, Christopher S. Mcmahan

Department of Statistics: Faculty Publications

Group testing is the process of testing items as an amalgamation, rather than separately, to determine the binary status for each item. Its use was especially important during the COVID-19 pandemic through testing specimens for SARS-CoV-2. The adoption of group testing for this and many other applications is because members of a negative testing group can be declared negative with potentially only one test. This subsequently leads to significant increases in laboratory testing capacity. Whenever a group testing algorithm is put into practice, it is critical for laboratories to understand the algorithm’s operating characteristics, such as the expected number of …

Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu

Undergraduate Honors Theses

In this paper, we study the Poisson-gamma model for recruitment time in clinical trials. We proved several properties of this model that match our intuitions from a reliability perspective, did simulations on this model, and used different optimization methods to estimate the parameters. Although the behaviors of the optimization methods were unfavorable and unstable, we identified certain conditions and provided potential explanations for this phenomenon and further insights into the Poisson-gamma model.

Implementation Of Hierarchical And K-Means Clustering Techniques On The Trend And Seasonality Components Of Temperature Profile Data, Emmanuel Ogedegbe

Electronic Theses and Dissertations

In this study, time series decomposition techniques are used in conjunction with Kmeans clustering and Hierarchical clustering, two well-known clustering algorithms, to climate data. Their implementation and comparisons are then examined. The main objective is to identify similar climate trends and group geographical areas with similar environmental conditions. Climate data from specific places are collected and analyzed as part of the project. The time series is then split into trend, seasonality, and residual components. In order to categorize growing regions according to their climatic inclinations, the deconstructed time series are then submitted to K-means clustering and Hierarchical clustering with dynamic …

Wavelet Compression As An Observational Operator In Data Assimilation Systems For Sea Surface Temperature, Bradley J. Sciacca

University of New Orleans Theses and Dissertations

The ocean remains severely under-observed, in part due to its sheer size. Containing nearly billion of water with most of the subsurface being invisible because water is extremely difficult to penetrate using electromagnetic radiation, as is typically used by satellite measuring instruments. For this reason, most observations of the ocean have very low spatial-temporal coverage to get a broad capture of the ocean’s features. However, recent “dense but patchy” data have increased the availability of high-resolution – low spatial coverage observations. These novel data sets have motivated research into multi-scale data assimilation methods. Here, we demonstrate a new assimilation approach …

Good Practices And Common Pitfalls In Climate Time Series Changepoint Techniques: A Review, Robert B. Lund, Claudie Beaulieu, Rebecca Killick, Qiqi Lu, Xueheng Shi

Department of Statistics: Faculty Publications

Climate changepoint (homogenization) methods abound today, with a myriad of techniques existing in both the climate and statistics literature. Unfortunately, the appropriate changepoint technique to use remains unclear to many. Further complicating issues, changepoint conclusions are not robust to perturbations in assumptions; for example, allowing for a trend or correlation in the series can drastically change changepoint conclusions. This paper is a review of the topic, with an emphasis on illuminating the models and techniques that allow the scientist to make reliable conclusions. Pitfalls to avoid are demonstrated via actual applications. The discourse begins by narrating the salient statistical features …

Interactions Between Sediment Mechanical Structure And Infaunal Community Structure Following Physical Disturbance, William Cyrus Roger Clemo

<strong> Theses and Dissertations </strong>

Shallow, river-influenced coastal sediments are important for global carbon storage and nutrient cycling and provide a habitat for diverse communities of invertebrates (infauna). Elevated bed shear stress from extreme storms can resuspend, transport, and deposit sediments, disrupting the cohesive structure of muds, and sorting and depositing sand eroded from beaches. These physical disruptions can also resuspend or smother infauna, decreasing abundances and changing community structure. Infaunal activities such as burrowing, tube construction, and feeding can impact sediment structure and stability. However, little is known about how physical disturbance impacts short and long-term sediment habitat suitability and whether disturbance-tolerant infauna influence …

Integrating Machine Learning Methods For Medical Diagnosis, Jazmin Quezada

Open Access Theses & Dissertations

Abstract:The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing …

Bayesian Strategies For Propensity Score Estimation In Causal Inference., Uthpala I. Wanigasekara

Electronic Theses and Dissertations

Causal inference is a method used in various fields to draw causal conclusions based on data. It involves using assumptions, study designs, and estimation strategies to minimize the impact of confounding variables. Propensity scores are used to estimate outcome effects, through matching methods, stratification, weighting methods, and the Covariate Balancing Propensity Score method. However, they can be sensitive to estimation techniques and can lead to unstable findings. Researchers have proposed integrating weighing with regression adjustment in parametric models to improve causal inference validity. The first project focuses on Bayesian joint and two-stage methods for propensity score analysis. Propensity score modeling …

Causal Inference For The Effect Of Continuous Treatment On Time-To-Event Outcomes And Mediation Analysis On Health Disparities In Observational Studies., Triparna Poddar

Electronic Theses and Dissertations

The dissertation comprises two projects related to causal inference based on observational data. In healthcare research, where abundant observational data such as claims data and electronic records are available, researchers often aim to study the treatment effect and the pathway of that effect. However, estimating treatment effects in observational data presents challenges due to confounding factors. The first project focuses on estimating continuous treatment effects for survival outcomes, while the second concentrates on mediation analysis, allowing the exploration of the pathway of the causal effect. Both projects involve addressing confounding variables. In the first project, I investigate estimation of the …

Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown

Graduate Theses and Dissertations

Single case research design (SCRD) is a common methodology used across clinical disciplines to determine treatments effectiveness by comparing treatment conditions to baseline conditions in individual cases, usually among researchers working with smaller samples. Although popular within behavioral disciplines such as special education and behavioral analysis, studies have begun to emerge in counseling. However, guidance and current understanding of the use of SCRD in counseling is limited. A content analysis of counseling journals from 2003 to 2014 yielded only 7 studies using SCRD. In 2015, the flagship counseling journal, Journal of Counseling and Development, published a special issue on the …

Comparative Analysis Of Teacher Effects Parameters In Models Used For Assessing School Effectiveness: Value-Added Models & Persistence, Merlin J. Kamgue

Graduate Theses and Dissertations

Longitudinal measures for students have become increasingly popular to estimate the effects of individual teachers and schools. Value-added models are one of the approaches using longitudinal data to evaluate teachers and schools. In the value-added model (VAM) literature, many statistical approaches have been developed and used to estimate teacher or school effects on student learning. This study opted to use a Bayesian multivariate model for evaluating teacher effects. The generalized persistence models can handle longitudinal data, not vertically scaled, allowing for a below-par teacher’s effects correlation across test administrations. This study first generated longitudinal students’ test score data and used …

Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas

Graduate Theses and Dissertations

Over the last several decades, plastic waste has gradually accumulated while slowly degrading in terrestrial and oceanic environments. Recently, there has been an increased effort to identify the possible sources of plastic to understand how they affect vulnerable beaches. This issue is of particular concern in the Gulf of Mexico due to the presence of oil, natural gas, and plastic production. In this thesis, we expand upon existing Bayesian plastic attribution models and develop a rigorous statistical framework to map observed beached microplastics to their sources. Within this framework, we combine Lagrangian backtracking simulations of floating particles using nurdle beaching …

The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin

Theses and Dissertations

This study examined the relationship between a set of targeted factors and the total flight time students needed to become ready to take the private pilot check ride. The study was grounded in Ebbinghaus’s (1885/1913/2013) forgetting curve theory and spacing effect, and Ausubel’s (1963) theory of meaningful learning. The research factors included (a) training time to proficiency, which represented the number of training days needed to become check-ride ready; (b) flight training program (Part 61 vs. Part 141); (c) organization offering the training program (2- or 4-year college/university vs. FBO); (d) scheduling policy (mandated vs. student-driven); and demographical variables, which …

Stochastic Optimal Control Of Conditional Mckean-Vlasov Equations With Jump And Markovian Switching, Charles Samuel Conly Sharp

Theses and Dissertations

This thesis obtains a number of results in stochastic optimal control for conditional McKean-Vlasov equations with jump and Markovian switching. First, we prove the uniqueness of the solutions and derive a relevant version of Itô's formula. We provide the dynamic programming principle and prove the associated verification theorem. A stochastic maximum principle is established. Further, we derive the relationship between dynamic programming and the stochastic maximum principle. Additionally, we utilize our stochastic maximum principle result for a mean-variance portfolio selection problem.

Aspects Of Stochastic Geometric Mechanics In Molecular Biophysics, David Frost

All Dissertations

In confocal single-molecule FRET experiments, the joint distribution of FRET efficiency and donor lifetime distribution can reveal underlying molecular conformational dynamics via deviation from their theoretical Forster relationship. This shift is referred to as a dynamic shift. In this study, we investigate the influence of the free energy landscape in protein conformational dynamics on the dynamic shift by simulation of the associated continuum reaction coordinate Langevin dynamics, yielding a deeper understanding of the dynamic and structural information in the joint FRET efficiency and donor lifetime distribution. We develop novel Langevin models for the dye linker dynamics, including rotational dynamics, based …

Radiation Exposure Calibration Of The Al2o3:C With Radium-226 And Cesium-137 Using The Osl Method, Selma Tepeli Aydin

All Theses

Optically stimulated luminescence (OSL) dosimetry was utilized to calibrate Al₂O₃:C powder dosimeters, available commercially as the nanoDot® from Landauer Inc., and compare the dosimeter response to radium-226 (²²⁶Ra) and cesium-137 (¹³⁷Cs). The signal from the OSL was quantified using a microSTARii^® OSL reader also produced by Landauer Inc. Dose-response curves were developed for ²²⁶Ra and ¹³⁷Cs experiments (5 dosimeters each) at thirteen absorbed doses. Individual dosimeter response was tracked by serial number. Linear regression analysis was performed to determine if there were significant differences between the intercepts of the …

Generative Adversarial Game With Tailored Quantum Feature Maps For Enhanced Classification, Anais Sandra Nguemto Guiawa

Doctoral Dissertations

In the burgeoning field of quantum machine learning, the fusion of quantum computing and machine learning methodologies has sparked immense interest, particularly with the emergence of noisy intermediate-scale quantum (NISQ) devices. These devices hold the promise of achieving quantum advantage, but they grapple with limitations like constrained qubit counts, limited connectivity, operational noise, and a restricted set of operations. These challenges necessitate a strategic and deliberate approach to crafting effective quantum machine learning algorithms.

This dissertation revolves around an exploration of these challenges, presenting innovative strategies that tailor quantum algorithms and processes to seamlessly integrate with commercial quantum platforms. A …

Examining Covid-19 Vaccine Hesitancy Among The Nevada African American Population Using The Social-Ecological Model, Katelyn Faulk

UNLV Theses, Dissertations, Professional Papers, and Capstones

In Nevada, COVID-19 vaccines have been widely available to the general population since March 2021; however, even with the wide availability of these vaccines only 40% of the African American population in Nevada has been fully vaccinated against COVID-19 as of May 2023. This is problematic as it has been shown that the African American population is disproportionately affected by COVID-19 with higher rates of cases, hospitalizations, and deaths when compared to other races or ethnicities. Through the literature, it has also been well documented that African Americans may experience hesitancy toward these vaccinations for a multitude of reasons including …