Digital Commons Network^™

Peer Culture Of Block Play In An Early Childhood Classroom, Missi Jacobson

Dissertations

This is an ethnographic study of peer culture in the block play area of an early childhood classroom. Researchers have continued to position block play as an essential activity in early childhood classrooms. William Corsaro’s (1985, 1990, 1992, 2003, 2020) work on peer culture in young children and theory of interpretive reproduction is the framework that guided the methods and theoretical lens of this study. I was a participant-observer, using an “atypical adult” technique, in the block play area in a 4-5-year-old classroom with 22 children during a full school year. The children navigated how to build and play socially …

Parenting And Psychosocial Functioning In Youth With Spina Bifida: Making Connections With Other Cns-Related Chronic Health Conditions, Adrien M. Winning

Dissertations

Parenting practices have been linked to psychosocial outcomes in children who have chronic health conditions that affect the central nervous system (CNS), such as spina bifida (SB). However, there remains a need for (1) more evidence-based assessments that capture parenting in SB, (2) additional research focused on parenting in early childhood in SB, as this is a critical developmental period that has been understudied, and (3) systematic reviews that synthesize parenting research across CNS-related conditions to guide future work. This dissertation includes three papers that aim to address each of these gaps in the current literature. Specifically, the first study …

Administrator Perspectives On Teacher Recruitment And Retention During A Pandemic, Matthew Aaron Carr

Dissertations

The global COVID-19 pandemic fundamentally changed education across the United States leaving a shortage of highly qualified teachers to fill positions in classrooms (Nguyen et al., 2022; Schmitt & deCourcy, 2022). This research study utilized the theoretical framework of the Four-Capital Theoretical Model of Teacher Retention and Attrition (Mason & Matas, 2015). This qualitative study utilized open-ended survey questions and follow-up interviews to elicit the impacts of the COVID-19 pandemic and to determine effective strategies to the recruitment and retention of high-quality teachers. Sixty-two public school administrators shared their perspectives through the survey, while eight administrators participated in follow-up interviews. …

Using Industry Sector Entropy To Predict Economic Community Disaster Resilience: Real-World Verification From The Covid-19 Pandemic, Thomas Brindle

Dissertations

The COVID-19 pandemic has presented an opportunity for disaster science researchers to gain insight into the underlying nature of community resilience through comparing the socioeconomic effects of government action to a common threat across urban population centers of varying economic compositions. For example, the negative effects of the COVID-19 pandemic on employment related to public health mitigation efforts in the leisure and hospitality sector of Las Vegas, NV, during the onset of the pandemic were well publicized. In comparison, other population centers of similar size but with different economic sector composition varied in the degree to which employment were affected, …

A Delphi Study Of Effective Strategies For Addressing The Most Significant Challenges To Creating Gender-Balanced High School Career Technical Education (Cte) Pathways, Jon Black

Dissertations

Purpose: The purpose of this Delphi study was to identify what expert high school Career Technical Education (CTE) administrators see as challenges to creating gender-balanced classes across all high school CTE pathways, to rate the significance of the identified challenges according to the experts, and to describe the most effective strategies for addressing the five most significant challenges identified in creating balanced CTE enrollment across all high school pathways. Methodology: This study used a three-round Delphi method to collect data from expert high school CTE administrators. In Round 1, the expert panel was asked to identify challenges to creating gender-balanced …

Learning Science: Physical And Life Sciences In Curricula Across U.S. Schools Of Nursing, Valerie C. Sauda

Dissertations

Nursing educators are being challenged to provide curriculum that meets the changing healthcare environment and demand for creative, innovative nurses to assist in transforming healthcare into the future (Benner, Sutphen, Leonard, & Day, 2010; Institute Of Medicine, 2011). The liberal education provided within a baccalaureate of science in nursing (BSN) degree program provides a diversity of courses within the curriculum, including courses in the natural, physical, mathematical, and social sciences (American Association of Colleges of Nursing [AACN], 2008). Although nursing programs have included science courses in curriculum since the early 1900s (Nutting & Dock, 1907), there is lack of nursing …

A Quantitative Study Of Perceived Fitness And Nutrition Levels Of Secondary Educators In Relation To Their Overall Job Satisfaction Program At A Private Midwestern University, Jessica Arico

Dissertations

The profession of education traditionally embodies an idea of educating children on math, science, social studies, and English along with other elective course areas. In recent decades, however, the burnout rates and mental health of educators have become a subject of media attention and the basis for many new professional development programs. The one element wholly ignored in this space is the physiological wellbeing of educators and the impact physical health has on mental health and job satisfaction. This study set out to provide a baseline for beginning the discussion and future research on the physiological impact on educators and …

Molecular Mechanisms Of Amyloid-Like Fibril Formation, Sharareh Jalali

Dissertations

Proteins play a critical role in living systems by performing most of the functions inside cells. The latter is determined by the protein's three-dimensional structure when it is folded in its native state. However, under pathological conditions, proteins can misfold and aggregate, accounting for the formation of highly ordered insoluble assemblies known as amyloid fibrils. These assemblies are associated with diseases like Parkinson's and Alzheimer's. Strong evidence suggests that three mechanisms are critical for forming amyloid fibrils. These mechanisms are the nucleation of amyloid fibrils in solution (primary nucleation) as well as on the surface of existing fibrils (secondary nucleation) …

Exploring Topological Phonons In Different Length Scales: Microtubules And Acoustic Metamaterials, Ssu-Ying Chen

Dissertations

The topological concepts of electronic states have been extended to phononic systems, leading to the prediction of topological phonons in a variety of materials. These phonons play a crucial role in determining material properties such as thermal conductivity, thermoelectricity, superconductivity, and specific heat. The objective of this dissertation is to investigate the role of topological phonons at different length scales.

Firstly, the acoustic resonator properties of tubulin proteins, which form microtubules, will be explored The microtubule has been proposed as an analog of a topological phononic insulator due to its unique properties. One key characteristic of topological materials is the …

Models And Algorithms For Promoting Diverse And Fair Query Results, Md Mouinul Islam

Dissertations

Ensuring fairness and diversity in search results are two key concerns in compelling search and recommendation applications. This work explicitly studies these two aspects given multiple users' preferences as inputs, in an effort to create a single ranking or top-k result set that satisfies different fairness and diversity criteria. From group fairness standpoint, it adapts demographic parity like group fairness criteria and proposes new models that are suitable for ranking or producing top-k set of results. This dissertation also studies equitable exposure of individual search results in long tail data, a concept related to individual fairness. First, the dissertation focuses …

Quantifying Balance: Computational And Learning Frameworks For The Characterization Of Balance In Bipedal Systems, Kubra Akbas

Dissertations

In clinical practice and general healthcare settings, the lack of reliable and objective balance and stability assessment metrics hinders the tracking of patient performance progression during rehabilitation; the assessment of bipedal balance plays a crucial role in understanding stability and falls in humans and other bipeds, while providing clinicians important information regarding rehabilitation outcomes. Bipedal balance has often been examined through kinematic or kinetic quantities, such as the Zero Moment Point and Center of Pressure; however, analyzing balance specifically through the body's Center of Mass (COM) state offers a holistic and easily comprehensible view of balance and stability.

Building upon …

Advanced Traffic Video Analytics For Robust Traffic Accident Detection, Hadi Ghahremannezhad

Dissertations

Automatic traffic accident detection is an important task in traffic video analysis due to its key applications in developing intelligent transportation systems. Reducing the time delay between the occurrence of an accident and the dispatch of the first responders to the scene may help lower the mortality rate and save lives. Since 1980, many approaches have been presented for the automatic detection of incidents in traffic videos. In this dissertation, some challenging problems for accident detection in traffic videos are discussed and a new framework is presented in order to automatically detect single-vehicle and intersection traffic accidents in real-time.

First, …

Learning Representations For Effective And Explainable Software Bug Detection And Fixing, Yi Li

Dissertations

Software has an integral role in modern life; hence software bugs, which undermine software quality and reliability, have substantial societal and economic implications. The advent of machine learning and deep learning in software engineering has led to major advances in bug detection and fixing approaches, yet they fall short of desired precision and recall. This shortfall arises from the absence of a 'bridge,' known as learning code representations, that can transform information from source code into a suitable representation for effective processing via machine and deep learning.

This dissertation builds such a bridge. Specifically, it presents solutions for effectively learning …

Fortifying Robustness: Unveiling The Intricacies Of Training And Inference Vulnerabilities In Centralized And Federated Neural Networks, Guanxiong Liu

Dissertations

Neural network (NN) classifiers have gained significant traction in diverse domains such as natural language processing, computer vision, and cybersecurity, owing to their remarkable ability to approximate complex latent distributions from data. Nevertheless, the conventional assumption of an attack-free operating environment has been challenged by the emergence of adversarial examples. These perturbed samples, which are typically imperceptible to human observers, can lead to misclassifications by the NN classifiers. Moreover, recent studies have uncovered the ability of poisoned training data to generate Trojan backdoored classifiers that exhibit misclassification behavior triggered by predefined patterns.

In recent years, significant research efforts have been …

Bacterial Motion And Spread In Porous Environments, Yasser Almoteri

Dissertations

Micro-swimmers are ubiquitous in nature from soil and water to mammalian bodies and even many technological processes. Common known examples are microbes such as bacteria, micro-algae and micro-plankton, cells such as spermatozoa and organisms such as nematodes. These swimmers live and have evolved in multiplex environments and complex flows in the presence of other swimmers and types, inert particles and fibers, interfaces and non-trivial confinements and more. Understanding the locomotion and interactions of these individual micro-swimmers in such impure viscous fluids is crucial to understanding the emergent dynamics of such complex systems, and to further enabling us to control and …

Diversification And Fairness In Top-K Ranking Algorithms, Mahsa Asadi

Dissertations

Given a user query, the typical user interfaces, such as search engines and recommender systems, only allow a small number of results to be returned to the user. Hence, figuring out what would be the top-k results is an important task in information retrieval, as it helps to ensure that the most relevant results are presented to the user. There exists an extensive body of research that studies how to score the records and return top-k to the user. Moreover, there exists an extensive set of criteria that researchers identify to present the user with top-k results, and result diversification …

Human-Ai Complex Task Planning, Sepideh Nikookar

Dissertations

The process of complex task planning is ubiquitous and arises in a variety of compelling applications. A few leading examples include designing a personalized course plan or trip plan, designing music playlists/work sessions in web applications, or even planning routes of naval assets to collaboratively discover an unknown destination. For all of these aforementioned applications, creating a plan requires satisfying a basic construct, i.e., composing a sequence of sub-tasks (or items) that optimizes several criteria and satisfies constraints. For instance, in course planning, sub-tasks or items are core and elective courses, and degree requirements capture their complex dependencies as constraints. …

Program Analysis For Android Security And Reliability, Sydur Rahaman

Dissertations

The recent, widespread growth and adoption of mobile devices have revolutionized the way users interact with technology. As mobile apps have become increasingly prevalent, concerns regarding their security and reliability have gained significant attention. The ever-expanding mobile app ecosystem presents unique challenges in ensuring the protection of user data and maintaining app robustness. This dissertation expands the field of program analysis with techniques and abstractions tailored explicitly to enhancing Android security and reliability. This research introduces approaches for addressing critical issues related to sensitive information leakage, device and user fingerprinting, mobile medical score calculators, as well as termination-induced data loss. …

Fluid Dynamics Of Interacting Particles: Bouncing Droplets And Colloid-Polymer Mixtures, Lauren Barnes

Dissertations

Interacting particles are a common theme across various physical systems, particularly on the atomic and sub-atomic scales. While these particles cannot be seen with the human eye, insight into such systems can be gained by observing macroscopic systems whose physical behavior is similar. This dissertation consists of three different chapters, each presenting a different problem related to interacting particles, as follows:

Chapter 1 explores chaotic trajectories of a droplet bouncing on the surface of a vertically vibrating fluid bath, with a simple harmonic force acting on the droplet. The bouncing droplet system has attracted recent interest because it exhibits behaviors …

Boundary Integral Equation Methods For Superhydrophobic Flow And Integrated Photonics, Kosuke Sugita

Dissertations

This dissertation presents fast integral equation methods (FIEMs) for solving two important problems encountered in practical engineering applications.

The first problem involves the mixed boundary value problem in two-dimensional Stokes flow, which appears commonly in computational fluid mechanics. This problem is particularly relevant to the design of microfluidic devices, especially those involving superhydrophobic (SH) flows over surfaces made of composite solid materials with alternating solid portions, grooves, or air pockets, leading to enhanced slip.

The second problem addresses waveguide devices in two dimensions, governed by the Helmholtz equation with Dirichlet conditions imposed on the boundary. This problem serves as a …

Data-Driven 2d Materials Discovery For Next-Generation Electronics, Zeyu Zhang

Dissertations

The development of material discovery and design has lasted centuries in human history. After the concept of modern chemistry and material science was established, the strategy of material discovery relies on the experiments. Such a strategy becomes expensive and time-consuming with the increasing number of materials nowadays. Therefore, a novel strategy that is faster and more comprehensive is urgently needed. In this dissertation, an experiment-guided material discovery strategy is developed and explained using metal-organic frameworks (MOFs) as instances. The advent of 7r-stacked layered MOFs, which offer electrical conductivity on top of permanent porosity and high surface area, opened up new …

Variable Resolution Smoothed Particle Hydrodynamics Schemes For 2-D And 3-D Viscous Flows, Francesco Ricci

Dissertations

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian particle-based method for the numerical solution of the partial differential equations that govern the motion of fluids. The main aim of this thesis work is to better enable the applicability of SPH to problems involving multi-scale fluid dynamics. In the first part of the thesis, the capability of the SPH method to simulate three-dimensional isotropic turbulence is investigated with a detailed comparison of Lagrangian and Eulerian SPH formulations. The main reason for this first investigation is to provide an assessment of the error introduced by the particle disorder on the SPH discrete operators …

Computational And Experimental Investigation Of Elemental Sulfur And Polysulfide, Jyoti Sharma

Dissertations

Petroleum processing results in the generation of significant quantities of elemental sulfur (S₈), leading to a surplus of sulfur worldwide. Despite its abundance and low cost, the use of sulfur in value-added organic compound synthesis is limited due to its unpredictable and misunderstood reactivity. This dissertation aims to address this issue by tackling it from two angles. Firstly, by utilizing Density Functional Theory (DFT) calculations, the reactivity of sulfur in the presence of nucleophiles is studied. This facilitates the identification of organic polysulfide intermediates that can be generated under different conditions, as well as the corresponding reactivity for …

Synergistic Effect Of Air Sparging In Separation Via Nano-Carbon Immobilized Membrane Distillation Process And Optimization, Mitun Chandra Bhoumick

Dissertations

Membrane distillation (MD) has gained significant popularity as a separation and purification technique in diverse domains, such as saline/brackish water treatment, organic recovery, and wastewater treatment. The objective of this research is to advance MD by developing a novel air sparged membrane distillation in treating saline water, recovering solvents, and achieving preconcentration. To optimize the flux and selectivity in membrane distillation, the study also employed a response surface method based on a central composite rotatable design.

In this study, a novel air-sparged membrane distillation (ASMD) is introduced for the treatment of saline water, utilizing a nanocarbon immobilized membrane. The performance …

On Explainability Of Neural Networks, Cem Benar

Dissertations

It is widely reported that deep neural networks outperform most competitors for a range of applications. The state-of-the-art neural networks have built-in inductive bias of architectural choices, regularizations, optimizer types, and initialization methods. Using inductive bias is intuitive to enhance the model approximation. Deep neural networks are mostly dense and heavily overparameterized. They tend to be biased towards low-rank solutions to reduce complexity and improve generalization performance, known as implicit regularization. The implicit regularization as observed in specific architectures and various real-world data sets suggests to overparameterize neural networks judiciously and learn compressed representations (lower rank approximation) with improved performance. …

Toward Smart And Efficient Scientific Data Management, Jinzhen Wang

Dissertations

Scientific research generates vast amounts of data, and the scale of data has significantly increased with advancements in scientific applications. To manage this data effectively, lossy data compression techniques are necessary to reduce storage and transmission costs. Nevertheless, the use of lossy compression introduces uncertainties related to its performance. This dissertation aims to answer key questions surrounding lossy data compression, such as how the performance changes, how much reduction can be achieved, and how to optimize these techniques for modern scientific data management workflows.

One of the major challenges in adopting lossy compression techniques is the trade-off between data accuracy …

Local Labor Markets Exposure To Artificial Intelligence, Greg Call

Dissertations

As more evidence builds that artificial intelligence (AI) is a new general-purpose technology driving a fourth industrial revolution, scholars have begun to consider its potential impact on labor markets. The current debate among researchers is centered on whether AI will ultimately produce net new job gains or losses and what type of workers will benefit or be displaced. While no consensus has developed yet within the literature on AI’s predicted net employment impact, a majority of studies are forecasting that a skill-biased technological change will occur.

This exploratory study contributes to the current literature by operationalizing Webb’s objective patent-based AI …

Exploring Relationships Between Practicing Registered Nurses (Rns) Pharmacology Knowledge And Medication Errors, Coleen Kumar

Dissertations

Medication errors result in significant negative patient outcomes and major costs to the health care system. Registered nurses (RNs) assume a major role in the medication administration process demanding high-level knowledge and skills.

This study aimed to determine if there was a relationship between practicing RNs' pharmacology knowledge and medication error occurrence.

Atrial Fibrillation Management In Hispanic Adults, Tania Borja

Dissertations

Background: Research has found atrial fibrillation (AF) to be the primary or a contributing cause of death on 183,321 death certificates, and an underlying cause of death for 26,535 Americans in 2019. Findings indicate an increased AF diagnosis in White people compared to racial and ethnic minorities, contrasting widespread findings of increased prevalence of cardiovascular disease and ischemic strokes in minorities. Significant disparities—by race and socioeconomic status in disease distribution and access to testing and lifesaving treatments—have been documented, specifically associated with social determinants of health (SDOH); i.e., the conditions in which people are born, grow, live, work, and age. …

Cumulative Advantage And Student Performance In General Chemistry: An Empirical Study At A Midwest Tier 1 University (2016-2019), Nicole Barvian

Dissertations

General chemistry (GC) plays a crucial role in the academic and career outcomes of students interested in postsecondary science, engineering and medicine. As a whole, chemistry education research literature has reported student attrition rates averaging from 25% to 35% for nearly a century. Student attrition rates can be attributed to a number of factors, including high school preparation (e.g. Tai et al. 2006), opportunity to learn (Carroll, 1989) and accumulated time and practice in a domain (e.g. Ericsson et al. 1993). The factors, in turn, are affected by mechanisms of social stratification, in particular, the social mechanism of cumulative advantage …