Dissertation Defense Announcements

Candidate Name: Timothy Scott Holcomb
Title: Lambda Coefficient of Rater-Mediated Agreement: Evaluation of an Alternative Chance-Corrected Agreement Coefficient
 April 06, 2022  2:30 PM
Location: Zoom

In this study, the performance of the Lambda Coefficient of Rater-Mediated Agreement was evaluated with other chance-corrected agreement coefficients. Lambda is grounded in rater-mediated assessment theory and was developed as an alternative to Kappa (Cohen, 1960) and other chance-corrected agreement coefficients. Lambda has two variations, a general form that is calculated similarly to how most chance-corrected agreement coefficients are calculated, such as Kappa (Lambert et al., 2021). The general form of Lambda is referred to as Lambda-1. Lambda-2 differs from Lambda-1 in the calculation of the proportion of expected chance agreement. Lambda-2 uses known population proportions when available and applies those proportions in the calculation of expected chance agreement. In total, six coefficients were calculated using generated data by varying the amount and location of agreement and disagreement between ratings across two-, three-, and four-point rating scales. The exact agreement specifications ranged from 75% to 95% across 135 planned data conditions. The simulations adjusted prevalence indices according to exact agreement specifications (Xie, 2013). Results demonstrated the robustness of Lambda-1 and Lambda-2 to data conditions that are problematic for other coefficients. Both variations of Lambda produced benchmark agreement results that maintained meaning that may be diminished by other coefficients.

Candidate Name: DOREEN CARTER
Title: Ethics Continuing Professional Education and the Potential Effect on CPAs’ Ethical Behavior and Accountability
 March 28, 2022  12:00 PM
Location: https://uncc.zoom.us/j/97061745492?pwd=QU1kejB3UW1NMlpTNnhhWGxqT1JpQT09

Based on Aristotle’s philosophy that ethics can be taught, this study examines whether the behavior of licensed accounting professionals is influenced by increased ethics Continuing Professional Education (CPE) required by state licensing boards. Since states are the licensing and oversight bodies of Certified Public Accountants (CPAs), it is important to know what actions state boards have taken to help increase the public trust of the accounting profession, and the efficacy of those actions.

States were selected based on whether they required ethics CPE hours and whether this changed during the study period 2008-2019. Fourteen states were selected (46% of U.S. CPAs). Data was obtained from publicly available resources on the individual state boards’ websites. 7,969 sanctions were hand coded, scored and analyzed for 3 variables: the sanctions rate, severity of acts conducted by CPAs and the severity of sanctions assessed on CPAs.

The results of this study identified inconsistencies in the monitoring and oversight activities of state licensing boards and the variability of publicly available information. Findings suggest that the number of sanctions may be more affected by the level of oversight of state boards of accountancy, driven by resources available to them, than the behavior of regulated accounting professionals.

Candidate Name: Oscar Barzuna Hidalgo
 March 31, 2022  9:00 AM
Location: Virtual

Resilience research within the field of entrepreneurship has increasingly received attention from academia. However, most studies have considered this construct under extreme circumstances such as war, the aftermath of natural disasters, and economic crisis. This dissertation examines resilience from an entrepreneur's perspective by examining the role that culture plays in the consequence of venture performance. Drawing from acculturation theory, this dissertation considers cultural distance, cultural conflict, and perceived discrimination of the entrepreneurs as moderating variables in the interaction between resilience and venture performance. A sample of entrepreneurs (N=158) provides insights into these interactions. Even though this study did not find support to suggest such relationships or moderating effects, it recommends possible improvements and future research agenda in cross-disciplinary studies within the field of entrepreneurship.

Candidate Name: Namwon Kim
Title: PV-Battery Series Integration for Residential Solar-plus-Storage Systems
 April 07, 2022  12:00 PM
Location: EPIC 2344

Solar-plus-storage systems provide efficient energy yield and management, resilience, and more revenue to residential houses and buildings. In solar-plus-storage systems, power electronics converters are integral components to generate the maximum output power from a solar photovoltaic (PV) array, store the generated energy into a battery, and finally deliver and manage the power to an electric load or the electric grid. Many existing solar-plus-storage systems still use and combine legacy power electronics convert topologies initially designed for a solar PV generation system or a battery energy storage system (BESS) separately. These power converters are connected in parallel to an AC or DC point of common coupling: AC-parallel and DC-parallel integration methods. Another integration method of a solar-plus-storage system is connecting a high-voltage battery to the high-voltage DC bus in parallel in a solar PV generation system having two-stages power converter architecture: In-line integration method. These methods result in increased costs and size, lower energy yields due to the increased number of power electronics converters, and the requirement of high-voltage PV strings and batteries.
This research studies new PV-battery integration methods and develops PV-battery series optimizers—power electronics converters optimally designed for different residential solar-plus-storage systems. The two PV-battery integration methods are proposed: AC-series integration and DC-series integration. The proposed integration methods are based on the series connection of PV and battery modules. The AC-series integration method assists the residential panel-level series-connected solar PV inverters in reducing the intermittent PV output fluctuations with a low-voltage-profile battery energy storage inverter. The DC-series integration enables PV voltage support, reducing the number of power converter stages, reducing the rated power of power converters, improving the system round-trip efficiency, and seamless source integration. Three PV-battery series optimizers are developed for different solar-plus-storage applications. The proposed power converter topologies and controls are discussed in this dissertation. Off-line simulation, real-time controller hardware-in-the-loop simulation, and lab-scale experiment results are included and analyzed to demonstrate the operating and design principle and the control performance of the proposed system.

Candidate Name: Fei Shen
Title: Feature-Based Automated Tool Path Planning for Discrete Geometry
 April 06, 2022  1:00 PM
Location: Duke Hall, Room 308

CNC machining is a critical manufacturing technology in effectively all modern products. Any improvement in efficiency or automation that reduces the cost of CNC machining is of tremendous value to the manufacturing industry. One of the most time-consuming steps in CNC machining, especially in a high-mix low-volume scenario, such as prototyping, is the current tool path planning workflow. The current industrial state of Computer-Aided Manufacturing (CAM) tools used to generate toolpaths requires highly trained CNC programmers. Typically, programmers manually select the features to be machined, the tools to use for each feature, the specific tool paths topology, and the feeds and speeds.

In the research community, there is a lot of focus on the automation of the tool path planning process, aiming to reduce the significant effort required to generate toolpaths. Researchers have developed novel feature recognition techniques, automated tool path generation methods, and tool selection algorithms. However, these methods all come with certain caveats and limitations. Some only work on continuous geometries. Others only work on certain feature types.

This dissertation introduces a feature based automated tool path planning system with the focus on implementing robust and generalized algorithms that work on arbitrary geometries with the full range of features based on discrete geometry. Support for discrete geometry is valuable because there are many situations where only discrete geometry is available as in models generated from 3D scanning systems. Specifically, a robust region segmentation technique is developed to simplify machining feature recognition from discrete geometry. Once the features are recognized, an automated optimal cutter set selection approach aiming at a minimum machining time is proposed to improve the machining efficiency for arbitrary features. Additionally, an automated deburring tool path planning method is introduced to eliminate the manual edge deburring and specifically to work with 3D discrete geometry. With the robust and automated algorithms as a solid foundation, a fully automated tool path planning system with limited human interactions is built and demonstrated on a series of parts with complex intersecting features. The net result is a complete 3D CAM process that goes from geometry to G-code in less than 1 minute.

Candidate Name: Saurav Agarwal
Title: Generalized Coverage Using Multiple Robots: Theory, Algorithms, and Experiments
 April 06, 2022  12:00 PM
Location: https://uncc.zoom.us/j/96535666623?pwd=dFM0amhLbVlSWlVXSExDZTZONjVJZz09

Recent technological advances have facilitated the use of mobile robots for a wide range of coverage applications such as inspection and mapping of infrastructure, precision agriculture, and disaster management. With the proliferation of these tasks comes an increasing need for autonomous systems to efficiently gather data pertinent for analyzing the state of the environment. The dissertation answers the following fundamental question: How should resource-constrained robots traverse the environment to collect data from all the relevant features? These features of interest can be represented as points, lines or curves, and areas. This dissertation unifies simultaneous coverage of all three types of features into a novel generalized coverage framework, develops algorithms for efficient coverage using multiple mobile robots, and validates them in experiments.

The dissertation comprehensively studies the line coverage problem, i.e., coverage of one-dimensional features, which lays the foundation of the generalized coverage problem. We develop algorithms to transform point and area features into linear features and use line coverage algorithms to solve generalized coverage efficiently. The algorithms substantially improve the state of the art while incorporating battery life constraints, nonholonomic constraints for robots that cannot take turns in place, and multiple home locations for large-scale environments.

Candidate Name: Nickcoy Findlater
Title: Expectancy-Value Model: Investigating Academic Success and Retention Predictors of First-Year STEM Majors
 April 05, 2022  10:00 AM
Location: Virtual

The gap in supply (i.e., shortage) and demand of the STEM workforce have prompted extensive research on identifying factors that predict STEM outcomes and retention of students. Few studies, however, have examined the relationships between STEM outcomes and predictors in an integrated model, taking into account measurement errors in the predictors. Drawing upon the Expectancy-Value Model of Achievement Related Performance and Choice, I conducted a structural equation modeling (SEM) analysis to examine the relationships among academic support, academic engagement, mathematics readiness, and hours worked and first-year STEM students’ academic success and retention. The SEM allowed me to investigate the relationships between predictors and outcomes simultaneously while accounting for the measurement error. The sample consisted of first-year STEM majors who took the National Survey of Student Engagement during 2016, 2018, and 2020 academic years. Results indicated that academic support was a statistically significant predictor of first-year STEM students’ academic success and retention. Additionally, mathematics readiness was found to be a statistically significant predictor of first-year retention. Last but not the least, results suggested that female students on average were more likely than their male counterparts to engage in academic support and academic engagement activities even though females had longer on-campus work hours than males. These results have implications for policies and practices aimed at improving STEM retention. Areas of further research are also identified.

Candidate Name: Aaron Trautman
 April 05, 2022  1:00 PM
Location: https://uncc.zoom.us/j/99382586854?pwd=QUdKZjhNNUxlTDJZMUYraVhiNGI4QT09

Diet-related diseases like obesity and type-2 diabetes are on the rise. Precision nu- trition, a way to tailor dietary requirements for each individual, is heralded as a solution to these problems. However, nutritional research is held within sparse, siloed resources that rarely connect, which leads to significant barriers hindering the progress of precision nutrition. Three knowledgebases were produced as a re- sult of this work. The ABCkb 1.0 overcomes these barriers by linking 11 separate resources in the path from plants to disease through molecular mechanisms. This resource is built in Neo4j and provides a web-based interface available for browsing (https://abckb.charlotte.edu). A second knowledgebase, ABCkb 2.0 connects micro- biota information to diet and human health through the incorporation of text-mined associations from full text articles. The final knowledgebase produced links long-covid to dietary components through possible molecular mechanisms. These three knowl- edgebases promote progress in precision nutrition to tackle the rise in diet-related disease.

Candidate Name: Jingjing Gao
Title: Impact of Health Policies and Local Political Ideology on Spatial-temporal Patterns of Public Emotions Towards COVID-19
 March 22, 2022  11:15 AM
Location: Fretwell

Social media such as Twitter enable people to interact with each other and share health-related concerns in a new and novel way, as evidenced during the COVID-19 pandemic when in-person communication became inconvenient under social-distancing policies. Little attention has been paid to the impacts of health policy and local political ideology on the trends of spatiotemporal emotions related to COVID-19. This study examines 1) the spatial-temporal clustering trends of negative emotions (or spillover effects); 2) whether health policies such as social distancing policy are associated with spatiotemporal emotion patterns towards COVID-19. This article finds that: 1) COVID-19 related negative emotions detected by social media have spillover effects and that 2) counties with staying at home policy or counties which are predominantly democratic exhibit a higher rate of negative emotional tweets toward COVID-19. These results suggest that scholars and policymakers may want to consider the impacts of interventions caused by public policy and political polarization on spatial-temporal patterns of public health concerns detected by social media.

Candidate Name: Xiaoyu Bai
Title: Energetic Theory and Hadley cells at a seasonal scale: how will ITCZ respond to a warming climate
 April 08, 2022  9:00 AM
Location: McEniry 123

The Intertropical Convergence Zone (ITCZ), a belt of convective systems around the equator with showers and thunderstorms, is an important feature not only to the tropical societies whose water budget depends on it, but also to the atmospheric science field to understand how will the Earth respond to a warming climate. Former studies found that annual and zonal mean ITCZ position is related to interhemispheric atmospheric heat transport (AHTtotal). The radiative imbalance at the top of the atmosphere (TOA) transported across the equator to the cooler hemisphere explains the ITCZ position and its shift. Using idealized model simulations with a ``slab'' ocean, researchers found that an increase in the interhemispheric TOA radiation contrast causes an increase in cross-equatorial energy flux by the Hadley circulation and a shift of the ITCZ towards the warmer hemisphere. The theory that relates AHTtotal and ITCZ position is called energetic theory.

In this dissertation, we analyze Tropical rain belts with an Annual cycle and a Continent-Model Intercomparison Project (TRACMIP) model simulations to test the energetic theory. TRACMIP is a project of idealized models that fill the gap between Couple Model Intercomparison Project Phase 5 (CMIP5) idealized aquaplanet projects and fully-coupled projects. TRACMIP models are thermodynamically coupled to a slab ocean. TRACMIP has idealized tropical continent setups with both present-day and quadruple CO2 (4xCO2) concentration experiments, which can help us understand ITCZ shift and potential precipitation changes over land under a warming scenario. Our findings suggested that TRACMIP simulations do not support energetic theory's expectations under a warming climate.

All of our models simulated a northward shift of ITCZ and mass transport under a warming scenario. Our models disagreed on the changes of the energy transported by Hadley cells and the total energy transported by the atmosphere. In general, the link between mass transport changes and energy transported by the Hadley cells changes broke down the most during Northern Hemisphere tropical wet season. The link between changes of the energy transported by the Hadley cells and total energy transported by the atmosphere broke down the most during Northern Hemisphere tropical dry season. Breakdown of one or both of these links caused the overall link between ITCZ shifts and total energy transport changes to break down.

We encourage more studies to be done on energetic theory and climate change. We look forward to combining energetic theory with monsoon theories to develop a self-contained tropical climate model.