Dissertation Defense Announcements

Candidate Name: Faizeh Hatami
Title: URBAN DYNAMICS: LONGITUDINAL CAUSAL RELATIONSHIPS AND FUTURE TIME SERIES FORECASTING
 April 06, 2023  10:00 AM
Location: Contact student for Zoom link
Abstract:

Studying urban dynamics is essential given the ever-increasing changes in urban areas with all its ensuing consequences, whether negative or positive. It is of paramount importance to take into account the temporal dimension of urban dynamics when studying its patterns and processes. Nevertheless, the majority of studies overlook this consideration and take cross-sectional research approaches. Moreover, a large body of literature in urban dynamics is dedicated to the explanatory analysis and causal inference only, neglecting the importance of predictive analysis. Addressing these two main gaps, this research explores urban dynamics through both causal inference and predictive modeling using longitudinal research designs. Urban dynamics are studied from two aspects in this work; transportation/land-use interactions, and economic growth. In the first article, the impact of built environment on commuting duration is assessed in 2000 and 2015 in Mecklenburg County, NC using spatial panel data models. Results show that the built environment has a statistically significant impact on commuting duration. However, it is important to note that the practical magnitude of the impact is small. In the second and third articles, the business performance of businesses are forecasted for non-business services and business services respectively in Mecklenburg County, NC, using recurrent neural networks long short-term memory deep learning method. After building and training the sequential model, its predictive performance is assessed using out-of-sample evaluation.



Candidate Name: Kathryn Kavanagh
Title: How Nature Can Nurture: Examining the Role of Environment Naturalness in Recovery During Work Breaks.
 April 11, 2023  1:00 PM
Location: https://www.google.com/url?q=https://charlotte-edu.zoom.us/j/93185792394&sa=D&source=calendar&ust=1680470761476620&usg=AOvVaw10IthIlzt6GefYPgyLePHr


Candidate Name: Anjia Wang
Title: REX: A Source-to-Source OpenMP Compiler for Productive Research of Parallel Programming
 April 11, 2023  3:00 PM
Location: WOODW 237
Abstract:

The growing complexity of high-performance computing (HPC) systems has led to the development of parallel programming models, such as OpenMP and OpenACC, to make it easier to utilize modern HPC architectures. These models provide a higher-level interface for specifying parallelism patterns and reducing programming effort, but performance optimization and customization are left to the compilers. Despite the availability of state-of-the-art OpenMP compilers, including LLVM, GCC, and ROSE, there remains a need for a compiler that is easily usable and extendable by researchers and students who are not in the field of compiler development, supports multiple parallel programming models, and has comparable performance to mainstream compilers.
The REX compiler has been proposed as a solution to these challenges. It is built upon the ROSE compiler and uses a unified parallel intermediate representation (UPIR), targeting the LLVM OpenMP runtime for optimal performance. REX provides essential OpenMP 5.0/5.1 constructs and preliminary support for OpenACC 3.2. Its source-to-source transformation capabilities offer flexibility and ease of use with minimal overhead. It can be installed as a Docker image or used through a cloud service. The REX compiler's performance has been evaluated using an enhanced version of the parallel benchmark, Rodinia, which compares GPU offloading performance across different parallel programming models and compilers. In conclusion, the REX compiler provides a unique solution for parallel programming research and education, balancing performance, portability, flexibility, and usability.



Candidate Name: Jennifer Bates
Title: A Study of Factors Underlying Vehicle Collisions Involving Raptors
 April 06, 2023  2:30 PM
Location: McEniry 329
Abstract:

The increasing prevalence of roads and vehicle traffic, most particularly in urban areas, has a corresponding impact on road mortality, especially for avian species that make use of foraging opportunities along roadside verges. In many cases, raptors, or birds of prey, are vulnerable to vehicle collisions because they forage along roads. The purpose of my research was to conducted a comprehensive investigation into the traffic, habitat and road verge factors that influence collision risk for both nocturnal and diurnal raptors. In addition, I examined the impact that species and individual traits have on the location of vehicle collisions involving birds of prey. I expected to find a notable difference in collision vulnerability between nocturnal and diurnal species. I also expected that road verge vegetation would play a significant role in vehicle collision risk for birds of prey.
Although I did not observe a significant difference in collision risk for raptors based on time of activity, I did find that prey cover in the form of complex vegetation along road verges was an important predictor of collision risk. Dense brush, shrubs or tall grass provide habitat for prey items such as small birds and mammals, which in turn attracts foraging raptors to roadsides, thus increasing the risk of being struck by a passing vehicle.
My analysis of species and individual traits showed that body size and reproductive output were the most important predictors of collision risk. Larger species and those with smaller clutch sizes were most likely to be hit by cars, regardless of road and road verge conditions or habitat characteristics.



Candidate Name: Keondra Mitchell
Title: Executive Leadership Style and Firm Corporate Social Responsibility Engagement
 April 11, 2023  11:00 AM
Location: Zoom (virtual)
Abstract:

Firms have to think creatively and strategically to inform corporate social responsibility that benefits essential stakeholders. Not only is doing good vital for business, but it has become the responsibility of firms to create initiatives that incorporate different stakeholders. Prior research has shown a relationship between CEO leadership styles and CSR initiatives to determine their impact on stakeholders. However, more literature needs to look at different types of leadership styles and different types of CSR focus. This dissertation explores the relationship between executive leadership styles and firm corporate social responsibility engagement with different focuses on philanthropic, operational effectiveness, and business model transformation. It also incorporates the potential moderating effect of CEO narcissism to determine if it amplifies the relationship between a particular leadership style and CSR focus. Stakeholder and Upper echelon theory provide the framework for this study as it explores leadership style and decision-making when leaders consider CSR engagement. This study empirically investigates three leadership styles: servant, transactional, and transformational. The data was collected using a quantitative survey, and the findings provide theoretical and practical insight.



Candidate Name: Sandra Varney
Title: Perceived Overqualification of Work Among State Employees: A Replication and Extension
 April 13, 2023  8:30 AM
Location: Friday Building 222 -Wubben Conference Room


Candidate Name: Alexandra Patton
Title: Exploring the Impacts of State Level Indicators and COVID-19 Response Measures on Mental Health Outcomes Among Adults with Mental Illness in the United States
 April 10, 2023  3:00 PM
Location: Zoom
Abstract:

The COVID-19 pandemic has exacerbated unmet mental health needs among adults in the U.S and resulted in significant strains on the U.S. healthcare system. This descriptive, quantitative study aims to investigate reports of unmet mental health needs among adults in the U.S. prior to, and after the onset of the COVID-19 (SARS-CoV-2) pandemic. The purpose of this study is to critically examine state level characteristics and public health response approaches to better understand the contributing factors to mental illness and unmet mental health needs in the U.S. The specific objectives of this study include 1) To create a comprehensive national, longitudinal dataset; 2) To investigate state level variability in regards to mental health outcomes, contrasting states with better and worse mental health indicators; 3) To examine COVID-19 response legislation on mental illness (depression), contrasting states with more restrictive and less restrictive COVID-19 response measures, and 4) To provide an in-depth comparison of the best and worst ranked states.

A major component of this dissertation is the development of a comprehensive state-level dataset that links key state characteristics related to mental illness and COVID-19 response measures to aggregate individual self-report mental health data. The dataset (n=50) consists of 206 total variables sourced from 8 data sources. Descriptive statistics, frequencies, and bivariate analyses were run in SPSS Statistics 28 to determine if there were any correlations among state level characteristics, COVID-19 response measures, and unmet mental health needs. Findings suggest slight correlations among meso- and macrosystem level variables which could be indicative of the impacts of the COVID-19 pandemic on economic and mental health outcomes. Economic characteristics at the macro-system level, such as household income and healthcare spending, look to be associated with better mental health rankings.

This dissertation research provides an original contribution to the field of public health as there is minimal existing literature pertaining to the influence of state level variability on mental illness and unmet mental health needs. This research also provides the groundwork for future studies to build upon the data collected on state level factors which influence mental health outcomes, and to explore the inter-relationships between the U.S. healthcare and economic systems. In terms of health policy, this data and subsequent research will provide guidance for improvements regarding mental health advocacy and reform efforts.



Candidate Name: Jeffrey Foster
Title: An Autoethnography: Culturally Responsive School Leadership through the Concientized Critical Lens of an African American Male School Administrator
 April 03, 2023  3:00 PM
Location: Zoom
Abstract:

Although significant research has been conducted on opportunity gaps between White and racially minoritized students, the percentage of minority students has reached 53% of the United States K-12 public schools (NCES, 2022). While the percentage of minority students now constitute the majority of public schools, the teacher workforce and school leadership remains majority White. As such, there is a need for additional investigations examining the role of culturally responsive classroom and school leadership practices in public schools. In particular, in the research, less is known about African American males and their culturally responsive school leadership practices. Thus, this study uses autoethnography to explore the experiences of a Black male school leader and the role of culturally responsive school leadership (CRSL) and conscientization in promoting effective school practices. As a member of a minority group, the school leader had relevant life and educational experiences of struggles and triumphs that impacted his leadership practices. These practices included but are not limited to fostering empathy, care, relevance, and rigor, which impacted the overall school climate and achievement. With the use of these practices that are grounded in CRSL, this urban school outperformed schools in the neighboring district. In sum, the findings suggest that there remains a need for more investigations on the role of CRSL in promoting urban school success.



Candidate Name: Xi Ning
Title: Statistical inference of semiparametric Cox-Aalen transformation models with failure time data
 April 07, 2023  10:00 AM
Location: Fretwell 315
Abstract:

In this dissertation, we propose a broad class of so-called Cox-Aalen transformation models that incorporate both multiplicative and additive covariate effects on the baseline hazard function through a transformation framework. The proposed model offers a high degree of flexibility and versatility, encompassing the Cox-Aalen model and transformation models as special cases. For right-censored data, we propose an estimating equation approach and devise an Expectation-Solving (ES) algorithm that involves fast and robust calculations. The resulting estimator is shown to be consistent and asymptotically normal via empirical process techniques. Finally, we assess the performance of the proposed procedures by conducting simulation studies and applying them in two randomized, placebo-controlled HIV prevention efficacy trials.

We also consider the regression analysis of the Cox-Aalen transformation models with partly interval-censored data, which comprise exact and interval-censored observations. We construct a set of estimating equations and implement an ES algorithm that ensures stability and fast convergence. Under regularity assumptions, we demonstrate that the estimators obtained are consistent and asymptotically normal, and we propose using weighted bootstrapping techniques to estimate their variance consistently. To evaluate the proposed methods, we perform thorough simulation experiments and apply them to analyze data from a randomized HIV/AIDS trial.



Candidate Name: Krista Engemann
Title: Safety, Reliability, and “That Magic Second”: A Grounded Practical Investigation of Dilemmatic Talk in Pit Crews’ Post-Competition Debriefs
 April 04, 2023  4:00 PM
Location: https://charlotte-edu.zoom.us/j/94642660226
Abstract:

Safety, often understood as freedom from unacceptable loss, and reliability, the capacity to accomplish particular outcomes repeatedly through operational sensitivity, are compelling performance objectives for high-risk organizations. If either is absent, people, organizations, and their external environments are potentially at unnecessary risk. Focused on continuous performance improvement, debriefs are team meetings that are often implemented to enable safe, reliable outcomes in these settings through post-incident discussion. Historically, research has presumed debriefs to support the capacity of teams to pursue the twin objectives of safety and reliability simultaneously without contradiction. However, this theoretical assumption has never been assessed according to how a team’s discourse in debriefs constitutes safety and reliability as distinct outcomes. This research adopts Craig and Tracy’s (2021) grounded practical theory methodology to analyze talk in post-competition debriefs among stock car racing pit crews. Analysis framed debrief participants’ talk according to problem and technical levels of grounded practical reconstruction, suggesting a central dilemma that constrains pit crews’ efforts for safety and reliability in these meetings, namely a contradiction among performance expectations for regulatory adherence and for boundary pushing. Results also feature several discursive techniques that pit crews employ during debriefs in response to this dilemma. A model of dilemmatic talk in debriefs situates these outcomes in the context of fragility, an implicit value of this complex, dynamic work environment made explicit.




The Graduate School and the Graduate Admissions office in the Reese Building, Fifth Floor, is temporarily closed to allow contractors to complete some needed work in the space safely.

Learn More