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Articles 571 - 582 of 582
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The Parent Influence: The Relationship Among Family Communication Patterns, Student Financial Literacy, And College Choice, Casey Lynn Hillon
The Parent Influence: The Relationship Among Family Communication Patterns, Student Financial Literacy, And College Choice, Casey Lynn Hillon
Masters Theses
Student financial literacy is a growing national concern in the United States of America, especially in the realm of higher education and student debt. The purpose of this study is to understand the relationship among students' perceived family communication patterns, financial literacy, and college choice. Family financial socialization theory was the lens through which these constructs were examined. This study combined revised family communication patterns (RFCP), expanded conformity orientation scale (ECOS), and college student financial literacy scale (CSFLS) measures along with a college choice question in an electronic survey shared with traditional undergraduate students at a land-grant university in the …
A Multi-Proxy Record Of Paleoenvironmental Change From A Southern Belizean Pine Savanna, Jacob Cecil
A Multi-Proxy Record Of Paleoenvironmental Change From A Southern Belizean Pine Savanna, Jacob Cecil
Masters Theses
While tropical savannas are naturally fire-prone ecosystems, anthropogenic burning can influence their distribution. Precisely when human activity in southern Belize began to significantly alter regional fire regimes is unknown, but savannas there are composed of fire-adapted species and are regarded as having evolved with both anthropogenic and natural fire. This thesis presents a multiproxy record from lake sediment cores that documents the complex interaction between fire, people, climate, and vegetation during the late Holocene. The dataset derives from 1) high-resolution analysis (1-cm interval sampling) of local fire history based on macroscopic (>125 μm) charcoal; 2) pollen analysis to determine …
Zone-Based Manufacturing, Abhay Rajendra Bajpai
Zone-Based Manufacturing, Abhay Rajendra Bajpai
Masters Theses
The biggest improvement possible with productivity and profit in a manufacturing environment is to decrease the production time or cycle time and increase the takt time without any significant or no loss to product quality. But this could come at a cost of unequal work distribution if it is a people-based manufacturing process. This paper provides the best possible schedule by using a heuristic model that gives an optimal schedule. Based on jobs precedence the schedule is made to have the least possible makespan for the process at any given station in an assembly line. Furthermore, the objective is to …
Tuning Photocurrent Responses From Photosystem I Via Microenvironment Alterations: Effect Of Plasmonic Electric Fields And Membrane Confinements, Ravi Pamu
Doctoral Dissertations
Robust photoelectrochemical activities of PSI make it an ideal candidate for bio-hybrid photovoltaic and optoelectronic devices. This dissertation focuses on role of microenvironment alterations around PSI in tuning its photocurrent responses when assembled with tailored plasmonic metal nanostructures and biomimetic lipid interfaces. To this end, a series of systematic studies aimed at tuning the plasmon enhanced photocurrent responses from PSI assembled with gold and silver metal nanopatterns tailored for different plasmonic absorption wavelengths. The experimental observation of plasmon-induced photocurrent enhancements in PSI is investigated using Fischer patterns of silver nanopyramids (Ag-NPs) wherein the resonant peaks were tuned to match the …
Advanced Statistical Methods For Atomic-Level Quantification Of Multi-Component Alloys, Adam Spannaus
Advanced Statistical Methods For Atomic-Level Quantification Of Multi-Component Alloys, Adam Spannaus
Doctoral Dissertations
This thesis comprises a collection of papers whose common theme is data analysis of high entropy alloys. The experimental technique used to view these alloys at the nano-scale produces a dataset that, while comprised of approximately 10^7 atoms, is corrupted by observational noise and sparsity. Our goal is to developstatistical methods to quantify the atomic structure of these materials. Understanding the atomic structure of these materials involves three parts: 1. Determining the crystal structure of the material 2. Finding the optimal transformation onto a reference structure 3. Finding the optimal matching between structures and the lattice constantFrom identifying these elements, …
Persistence Diagram Cardinality And Its Applications, Cassie Putman Micucci
Persistence Diagram Cardinality And Its Applications, Cassie Putman Micucci
Doctoral Dissertations
This dissertation studies persistence diagrams and their usefulness in machine learning. Persistence diagrams are summaries of underlying topological structure present within data. These diagrams are especially applicable for analyzing data whose shape is a relevant descriptor, as they provide unique information as sets instead of vectors. Although there are methods for vectorizing persistence diagrams, we focus instead on statistical learning schemes that use persistence diagrams directly. In particular, the cardinality of the diagrams proves itself a useful indicator, although this cardinality is variable at higher dimensions. To better understand and use the cardinality of persistence diagrams, we prove that the …
Finite Element Methods For Nonlinear, Dispersive Equations, Michael Morgan Wise
Finite Element Methods For Nonlinear, Dispersive Equations, Michael Morgan Wise
Doctoral Dissertations
The present study is concerned with the numerical approximation of solutions of systems of Korteweg-de Vries type, coupled through their nonlinear terms. We construct, analyze, and numerically validate two types of schemes that differ in their treatment of the third derivatives that appear in the system. This difference is fundamental, earning one method the moniker “conservative” due to its preservation, up to round-off error, of a fundamental invariant of the system. The other, slightly more-standard method is called “dissipative” for lack of this property. For both schemes, we prove convergence of a semidiscrete approximation from an a priori perspective and …
Data-Driven Modeling Of The Heroin And Fentanyl Epidemic And The Harvesting Of Trees In West Africa, Tricia Marie Phillips
Data-Driven Modeling Of The Heroin And Fentanyl Epidemic And The Harvesting Of Trees In West Africa, Tricia Marie Phillips
Doctoral Dissertations
The opioid epidemic has had a strong presence in the United States in recent years. Drug overdose deaths involving opioids have skyrocketed and the lacing of heroin with fentanyl has played a significant role in this. In order to investigate the dynamics behind the opioid epidemic and predict its trajectory, we formulate a system of ordinary differential equations that incorporate the movement of individuals among classes of opioid use. We estimate parameter values by fitting to Tennessee data since the time the epidemic was established in the state. The trajectory of the epidemic suggests the number of addicts and overdose …
Mapping And Identification Of Qtl Associated With Soybean Seed Protein, Oil, And Yield In 5601t × U99-310255 Ril Population Using Snp Genotyping, Mia Justina Cunicelli
Mapping And Identification Of Qtl Associated With Soybean Seed Protein, Oil, And Yield In 5601t × U99-310255 Ril Population Using Snp Genotyping, Mia Justina Cunicelli
Doctoral Dissertations
Soybean [Glycine max (L.) Merr.] is the world’s leading source of vegetable oil and high quality protein meal. However, soybean protein and oil and protein and yield are negatively genetically correlated. Agronomic and seed quality traits of soybean lines are important because they lead to increased soybean value. Molecular markers have played and will continue to play a major role in the genetic characterization and improvement of soybeans. Quantitative trait loci (QTL) are regions within a genome that contain genes that influence particular quantitative traits. Identification of QTLs through phenotypic evaluation only is not possible; therefore, to locate, identify, and …
Accelerated Quantum-To-Macro Scale Simulations With Machine Learning And Parallel Replica Dynamics For Mass And Thermal Transport, Jiaqi Wang
Doctoral Dissertations
Mass and thermal transport significantly affect the performance of engineering systems. Since various parameters in transport can be systematically controlled and investigated, multiscale simulations have been employed as powerful tools for transport analyses. Among them, quantum-scale ab initio molecular dynamics (AIMD), atomic-scale classical molecular dynamics (CMD), and macro-scale finite element method (FEM) simulations, can provide comprehensive system analysis and design by addressing electronic structures, atomic dynamics, and engineering-scale properties, respectively. However, each approach has its own limitations to overcome for more accurate analyses of mass and thermal transport. Specifically, AIMD calculation is too expensive to produce sufficient atomic data for …
Mathematical Analysis Of A Nonlocal System Of Equations Arising In Peridynamics, James Scott
Mathematical Analysis Of A Nonlocal System Of Equations Arising In Peridynamics, James Scott
Doctoral Dissertations
We analyze a strongly-coupled system of nonlocal equations. The system comes from a linearization of peridynamics, a nonlocal model in continuum mechanics. It is an analogue of the Navier-Lam\'e system of classical elasticity. The leading operator is an integro-differential operator characterized by a distinctive matrix kernel which is used to couple differences of components of a vector field.We first demonstrate the convergence of a class of nonlocal systems to the Navier-Lam\'e system in the event of vanishing nonlocality via the Fourier transform. We then study the Dirichlet problem associated with a wide class of systems. We prove well-posedness and demonstrate …
Applications Of Nonlinear Approximation For Problems In Learning Theory And Applied Mathematics, Joseph Douglas Daws Jr
Applications Of Nonlinear Approximation For Problems In Learning Theory And Applied Mathematics, Joseph Douglas Daws Jr
Doctoral Dissertations
A major pillar of approximation theory in establishing the ability of one class of functions to be represented by another. Establishing such a relationship often leads to efficient numerical approximation methods. In this work, several expressibility theorems are established and several novel numerical approximation techniques are also presented. Not only are these novel methods supported by the presented theory, but also, provided numerical experiments show that these novel methods may be applied to a wide range of applications from image compression to the solutions of high-dimensional PDE.