Dissertation Defense Announcements

Candidate Name: Courtney Skipper
Title: INCREASING KNOWLEDGE AND CONFIDENCE IN THE CARE OF PATIENTS WITH GASTROSTOMY TUBES
 April 03, 2024  9:00 AM
Location: CHHS 102
Abstract:

Patients requiring admission to the Trauma Intensive Care Unit (TICU) represent some of
the most critically ill and complex cases within intensive care. These patients, often suffering
from significant trauma to vital areas, may necessitate prolonged enteral feeding, frequently
leading to the insertion of gastrostomy tubes. Despite the critical nature of gastrostomy tube
management for patients with severe trauma and the need for enteral feeding, there is a gap in
knowledge and confidence in this area. This gap necessitates targeted educational programs to
improve patient outcomes. This quality improvement project focused on the nursing staff in the
Trauma Intensive Care Unit (TICU) at a large academic medical center. The nurses received a
comprehensive education module developed according to Lippincott standards, which covered
the different types of gastrostomy tube types, nursing interventions, and documentation practices.
The module included a didactic component and hands-on practice with gastric tube models. A
pre-and post-test knowledge check was conducted to evaluate the learning outcomes. All 43
TICU staff registered nurses at the facility participated. After the educational module's
implementation, significant improvements were observed in nursing staff knowledge regarding
gastrostomy tubes. The median score for the pre-test was 70%, increasing to 100% on the post-
test. Wilcoxon sign-rank test showed a statistically significant difference between pre- and post-
test scores, z = 5.207, p < .001. The results demonstrate the effectiveness of the education
module in improving TICU nurses' knowledge of gastric tube care.



Candidate Name: Elaine Gorom
Title: Multiscale Modeling for Crystalline Materials: A Comprehensive Study in Statics and Dynamics
 April 04, 2024  2:30 PM
Location: Fretwell 315
Abstract:

Computational materials science plays a crucial role in advancing new and improved materials. To leverage the advantages of local and nonlocal methods and aid in the advancement of predictive capabilities for materials, multiscale models have been introduced. Many such methods have been proposed to overcome computational challenges in accuracy and efficiency. In this work, I begin by presenting a review of some multiscale methods for crystalline modeling to provide context for this dissertation.

Together with my advisor Dr. Xingjie Helen Li, we explore the static behavior of a bottom-up nonlocal-to-local coupling method, Atomistic-to-Continuum coupling, and explore the dynamic behavior of a nonlocal method, Peridynamics, to explore a bimaterial interface.

Inspired by the blending method developed by \cite{Seleson2013} for nonlocal-to-local coupling, we create a symmetric and consistent blended force-based Atomistic-to-Continuum (AtC) scheme for one-dimensional atomistic chains. AtC coupling schemes have been introduced to utilize the accuracy of atomistic models near known defects and the computational efficiency of continuum models elsewhere. The conditions for the well-posedness of the underlying model are established by analyzing an optimal blending size and blending type to ensure the stability of the $H^1$ seminorm for the blended force-based operator. We present several numerical experiments to test and confirm the theoretical findings.

Then, we create a Peridynamics-to-Peridynamics scheme to model a bimaterial bar in one dimension. Peridynamics (PD) naturally allows for the simulation of crack propagation in its model due to its use of integro-differentials and time derivatives instead of the spatial derivatives typical of classical models. Although PD can be computationally intensive, its ability to accurately model fracture behavior, especially at material interfaces, makes it a valuable tool for achieving high accuracy in simulations, especially due to the susceptibility of fracture where differing materials meet. We prove the conservation laws, derive the dispersion relation, and estimate the coefficient of reflection near the interface for this nonlocal-to-nonlocal problem. We seek an optimal nonlocal interaction kernel in the governing equation for the cross-material interaction to reduce spurious artifacts when the kernel is assumed to be constant.

Lastly, I discuss potential future development in Atomistic-to-Continuum coupling and Peridynamics.



Candidate Name: Amber Greenwood
Title: “I’m Just So Busy:” The Creation of a Busyness Façade as an Impression Management Tactic
 April 09, 2024  2:30 PM
Location: Cone 110
Abstract:

Busyness, or how busy someone is, has increasingly become a topic of conversation in day-to-day life. Research has previously explored how people use their time and how people perceive their available time, or lack thereof, but there is no clear answer as to why people tell others that they are busy and what it is they are trying to accomplish by doing so. Drawing on impression management research, this paper proposes that people signal to others that they are busy so that the audience has a positive impression of them. The concept of the busyness façade is introduced, which includes behaviors and verbal statements that are intentionally enacted by individuals to signal to others that they have a lot to do or limited available time. Exactly how and why people engage in this busyness façade is explored in two studies using semi-structured interviews and an online, vignette survey. Overall, evidence is found for the existence of busyness façades and a better understanding of how people display busyness is gained, but the studies are unable to identify a clear motive for why busyness façades would be used as an impression management tactic. Additional findings and research directions are discussed.



Candidate Name: Hussein Hazazi
Title: Understanding and Improving the Usability, Security, and Privacy of Smart Locks from the Perspective of the End User
 April 08, 2024  12:30 PM
Location: Zoom https://charlotte-edu.zoom.us/j/91075751264?pwd=dnhpbjBncWRSdTJ1cGlKSzZ5ZVk2dz09
Abstract:

Over the past two decades, the Internet of Things (IoT) has seen a significant expansion in both the sophistication and variety of its applications. These applications span several domains, including enhancing and automating services in healthcare, advancing smart manufacturing processes, and elevating home living standards through smart home technologies. These technologies empower individuals with greater control over their home appliances. Smart locks are smart home devices that were introduced as replacements for traditional locks. Smart locks, designed to go beyond the basic functionality of traditional locks by offering additional features, have seen a surge in market growth and competitiveness. According to the Statista Research Department, it is projected that the global market for smart locks will surpass four billion dollars by 2027.
A number of studies have examined end users' concerns, needs, and expectations regarding smart homes in general. However, little research has been conducted to examine these aspects of the smart lock in particular. To address this gap, we conducted a series of user studies that aim to elucidate how smart locks are integrated and interact within smart home environments, focusing on user interactions both with the locks themselves and when they are part of broader automation scenarios. This dissertation contributes to a deeper understanding of smart lock technology from a user-centric viewpoint. It offers insights into user motivations, concerns, and preferences regarding smart lock usage and automation. It also highlights the importance of balancing convenience and security, the pivotal role of trust, and the complexities of integrating smart locks into broader smart home systems.



Candidate Name: Johnine Willamson
Title: THE UNTOLD STORY: AFRICAN AMERICAN MEN WITH LEARNING DISABILITIES AT THE POSTSECONDARY LEVEL A MULTI-CASE STUDY FROM TWO PERSPECTIVES PARENT AND STUDENT
 April 08, 2024  10:30 AM
Location: COED 259
Abstract:

Fifty percent of African American men with learning disabilities will not persist past their first year of college (Newman et al., 2011). A bachelor’s degree for an African American man means he is five times less likely to be incarcerated than his peers with a high school diploma and will make approximately $32,000 more per year on average than his counterparts without a bachelor’s degree (Trostel, 2015). Frequently neglected and inadequately represented in the existing literature on learning disabilities are the experiences of African American men with learning disabilities in higher education. The purpose of this phenomenological multi-case study was to examine the postsecondary educational experiences of African American men with learning disabilities by exploring the perspectives of both parents and students.

Ten semi-structured interviews were conducted; Six parent interviews and four student interviews. The study answered the following research questions (1) What are the psychosocial experiences of parents of African American young men with learning disabilities at the postsecondary level? (2) What are the primary roles of parents of African American young men with learning disabilities at the postsecondary level? (3) What do parents perceive about the intersecting identities of disability, race, and gender on the social and academic experiences of their African American young man with learning disabilities at the postsecondary level? (4) What are the psychosocial experiences of African American men with learning disabilities attending a Postsecondary Institution? (5) What are the experiences of African American men with learning disabilities attending a Postsecondary Institution regarding social and academic supports?

Based on the data analysis, three parent themes and two student themes emerged respectively: (1) Bubble Wrap Parenting, (2) The Changing of the Guard, and (3) In the Intersection of Black and Disabled; (1) Right in the Middle of the Dichotomy, and (2) The Juggling Act. The findings underscore that when Black men with learning disabilities receive services that segregate them from their peers, they face a forced choice between preserving their identity and accessing necessary support. One recommendation arising from these findings is to make support services universally available. This entails granting all students access to supports such as assistive technology and note-taking apps that have traditionally been exclusively available for the disabled population. By doing so, any stigma surrounding segregated support would be eliminated.



Candidate Name: Anthony Davis
Title: Student Conduct Administrators' Perceptions of Support
 April 09, 2024  1:00 PM
Location: COED 321C
Abstract:

Within the context of higher education, student conduct administration is drenched in risk, compliance with local and federal laws (Glick & Haug, 2020). In short, student conduct is a complex, and challenging functional area to work in, as administrators to balance educating students, protecting the campus community, and mitigating institutional risk (Miller & Sorochty, 2015; Lancaster & Waryold, 2008).

This qualitative, phenomenological study aimed to explore the lived professional experiences of student conduct administrators; to better understand their struggles and needs, as they would describe. Semi-structured interviews were used to capture depth in the shared experiences of ten participants and describe the meaning assigned to the phenomenon being explored.

The findings of this study were captured in 4 main themes: (1) Clashing with the Regime, which looks at SCAs challenges navigating political ecosystems within their respective institutions and states, (2) Encountering Turbulence, which captures common challenges SCAs experience while resolving cases (3) Nurtured by Leadership, which looks at the role of SCAs direct supervisor in fostering support and (4) Leaning on the Village, which captures the network of support SCAs receive outside of their direct supervisor.



Candidate Name: Shadab Anwar Shaikh
Title: Machine Learning-Based Approaches for Forward and Inverse Problems in Engineering Design
 April 03, 2024  12:00 PM
Location: DUKE 324
Abstract:

The battery enclosures of current electric vehicles are made of metallic alloys, specifically aluminum or steel. Replacing these metallic alloys with a lightweight material, such as carbon fiber composite, may offer significant weight savings due to its comparable strength-to-weight ratio. Carbon fiber is corrosion-resistant and can be engineered for fire resistance and electrical insulation. It can also be fine-tuned for specific applications and performance needs, such as "crashworthiness".

Designing a carbon fiber-based battery enclosure for crash performance through trial-and-error experiments can be extremely laborious and inefficient. This inefficiency can be alleviated by using virtual manufacturing and structural analysis software. A simulation software chain allows for the virtual manufacturing and crash-testing of the battery enclosure in a single process. However, these numerical simulations are computationally expensive, time-consuming, and may require significant user interaction. Finding optimal design parameters within a reasonable time-frame can be extremely challenging.

The first part of this dissertation addresses the forward problem of accelerating the design of battery enclosures for crash performance. It involves developing a machine learning-based surrogate model of the simulation workflow that can provide quick, approximate results in a fraction of seconds. This can further support design space exploration studies.

Physical phenomena in engineering design are governed by differential equations, typically solved in a forward manner with known physical parameters, initial and/or boundary conditions, and a source term. However, there is often a need to reconstruct the source term from available measurement data, which may be corrupted with noise, along with the initial and/or boundary conditions, and physical parameters. These types of problems are known as inverse problems, more specifically, inverse source problems. Inverse source problems are often ill-posed and are usually solved by iterative schemes and optimization techniques with regularization, which can be time-consuming. In recent years, machine learning approaches have shown promise in managing ill-posed problems and handling noisy data.

The second part of this dissertation addresses a specific type of inverse source problem, known as the dynamic load identification problem, which involves determining the time-varying forces acting on a mechanical system from the sensor measurements. The study begins with the development of a deep learning model that leverages physics information to infer the forcing functions of both linear and nonlinear oscillators from observational data. Furthermore, the study leads up to a development of a physically consistent surrogate model that is capable of providing robust predictions from the noisy observations without the need to explicitly solve the differential equation.



Candidate Name: Paula Shuping Williams
Title: EFFECTS OF TEACHERS’ USE OF A CONFERENCING STRATEGY ON FAMILY ENGAGEMENT
 April 08, 2024  1:00 PM
Location: COED 110
Abstract:

Family engagement with schools has been shown to be a predictor of student success (Powell et at., 2010) and federal statute supports school/ family relationships through the Family Engagement in Education Act. For students with disabilities (SWD), family engagement may be even more critical. Unfortunately, data has suggested that family engagement may be limited due to barriers families of SWD may face (Van Haren & Fiedler, 2008). Teacher invitation, teacher beliefs about family involvement and quality of communication are factors related to family engagement. The purpose of this study was to investigate an in-service teacher's use of a step-by-step strategy during family/ teacher conferences to increase family engagement during the conference, improve quality teacher communication and positively impact teacher beliefs on family involvement. The step-by-step conferencing strategy was called PIQUE and was developed through a review of prior research and feedback from experts in the field. This case study used both quantitative and qualitative methods to determine the effectiveness of the PIQUE strategy. Within an AB single-case design, I noted an increase in the 5-second intervals of the family speaking during the conference from baseline to post-intervention phase. This increase was immediate and demonstrated an accelerating trend. The teacher and parent completed surveys and interviews, which were analyzed thematically alongside descriptive and inferential field notes recorded by the researcher. Through this analysis, two primary themes were identified as Misunderstanding Communication as Equal to Engagement and Bias as a Barrier to Engagement. A secondary theme of Lack of Confidence When Engaging with Families was also identified. Triangulation was achieved across quantitative and qualitative data sources. Conclusions point to an increase in equity of power during conferences and positive change in teacher beliefs about family involvement and engagement after the implementation of the intervention. A conclusion that PIQUE implementation led to these changes should be interpreted with caution due to the threats to internal and external validity of case studies. The study concluded with implications for practice, limitations and suggestions for future research.



Candidate Name: Jesse Redford
Title: Interpretable Methods for Quantitative Measurement and Classification of Surface Topography
 April 04, 2024  4:00 PM
Location: Duke 324
Abstract:

The functionality of manufactured components is intricately linked to their surface topography, a characteristic profoundly shaped by the fabrication process. Repeatable quantitative characterization of surfaces is essential for detecting variations, defects, and predicting performance. However, the plethora of surface descriptors presents challenges in optimal selection of the correct assessment metric. This work addresses two of these aspects: automatic selection of surface descriptors for classification and an application-specific approach targeting scan path strategies in laser-based powder bed fusion (LPBF) additive manufacturing.

A framework, titled Surface Quality and Inspection Descriptors (SQuID), was developed and shown to provide an effective systematic approach for identifying surface descriptions capable of classifying textures based on process or user-defined differences. Using a form of univariate analysis rooted in signal detection theory, the predictive capability of a discriminability value, d', is demonstrated in the classification of mutually exclusive surface states. A discrimination matrix that offers a robust feature selection algorithm for multiclass classification challenges is also introduced. The generality of the approach is validated on two datasets. The first is the open-source Northeastern University dataset consisting of intensity images from six different surface classes commonly found in cold-rolled steel strip operations. The application of signal detection theory's measure, d', proved successful in quantifying a texture parameter's ability to discriminate between surfaces, even amidst violations of normality and equal variance assumptions regarding the data.

To further validate the approach, SQuID is leveraged to classify different grades of surface finish appearances. ISO 25178-2 areal surface metrics extracted from bandpass filtered measurements of a set of ten visual smoothness standards obtained from low magnification coherent scanning interferometry are used to quantify different grades of powder-coated surface finish. The highest classification accuracy is achieved using only five multi-scale descriptions of the surface determined by the SQuID selection algorithm. In this case, spatial and hybrid parameters were selected over commonly prescribed height parameters such as Sa, which proved ineffective in characterizing differences between the surface grades.

Expanding surface metrology capabilities into LPBF additive manufacturing, additional studies developed a methodology to comprehend the relationship between scanning strategies, interlayer residual heat effects, and atypical surface topography formation. Using a single process-informed surface measurement, a critical cooling constant is derived to link surface topography signatures directly to process conditions that can be calculated before part fabrication. Twelve samples were manufactured and measured to validate the approach. Results indicate that the methodology enables accurate isolation of areas within the parts known to elicit heterogeneity in microstructure and surface topography due to overheating. This approach provides not only a new surface measurement technique but also a scalable parameterization of LPBF scan strategies to quantify track-to-track process conditions. The methodology demonstrates a powerful application of surface texture metrology to characterize LPBF surface quality and predict process outcomes.

Overall, this thesis contributes a systematic approach for identifying discriminatory parameters for surface classification and a novel process-informed surface measurement for predicting track-scale overheating during LPBF-AM of a nickel superalloy.



Candidate Name: Chelse Spinner
Title: Striving for optimal care: Understanding the determinants and experiences of Black women after cesarean birth using a public health critical race praxis lens
 April 05, 2024  11:00 AM
Location: https://charlotte-edu.zoom.us/j/93158630404?pwd=N2RzVnJOeFZmcFF5Njh4bnRHRnZ5QT09
Abstract:

In the United States (U.S.), Black women are more likely to undergo a cesarean birth in comparison to other racial and ethnic groups. Previous research has identified individual-level factors, such as health behaviors, comorbidities, and socioeconomic status to be associated with cesarean birth among Black women. However, those individual-level factors do not fully account for the variation in cesarean births. The three-manuscript dissertation explores factors that influence cesarean rates among Black women in the US. The first manuscript provided a scoping review of peer reviewed research on the risk and protective factors associated with cesarean birth among Black women in the U.S. In the second manuscript, logistic regression was utilized to examine the association between experiencing racial discrimination and delivery method using data from the 2016-2021 Pregnancy Risk Monitoring System (PRAMS). The third manuscript applied a qualitative, phenomenological approach to understand the experiences, perceptions, and needs of Black women following a cesarean birth. The findings contribute to the understanding of racial disparities in cesarean births and can inform evidence-based practice and research. There is opportunity to provide all women with the chance to receive optimal maternity care and Black women are no exception.




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