Data-driven Koopman Theory for Transient Stability and Safety Analysis of Power Systems with Renewable Penetration

This dissertation presents a novel approach to analyzing and controlling nonlinear systems using the Koopman operator framework and data-driven methods. Nonlinear power systems, characterized by complex behaviors and sensitivity to initial conditions, pose significant challenges for stability and safety assessment, especially during transient events. The first part of this work focuses on reachability analysis using the spectral properties of the Koopman operator. By leveraging eigenfunctions extracted from sampled trajectory data, the approach computes forward and backward reachable sets efficiently, even in high-dimensional nonlinear systems, without requiring dense state-space sampling. This method is validated through numerical examples, demonstrating its ability to recover nonconvex reachable sets in both stable and unstable regimes. Building on this, the dissertation develops a Koopman spectrum-based method for identifying stability boundaries in nonlinear systems. This method, applied to power system models, enables accurate computation of critical clearing times and transient stability analysis by constructing unstable eigenfunctions through a path integral formulation. Finally, the dissertation addresses voltage safety under renewable generation uncertainty. A data-driven Koopman-based model is constructed using Extended Dynamic Mode Decomposition (EDMD), and a control barrier function is synthesized to enforce voltage safety. The resulting formulation is posed as a constrained optimization program, through which the minimum rated power capacity is computed to ensure safe operation across all disturbance scenarios. The proposed methodologies provide scalable, data-driven tools for stability analysis and safe control in nonlinear systems, with practical applications in power system analysis and control

The Impact School Leaders Have On Special Education Teacher Retention: A Cross-Case Analysis of Two Elementary School Leaders

School leaders shape school culture and job satisfaction, impacting teachers’ decisions to remain or exit schools. The demand for special education teachers has continued to increase. I studied the impact school leaders have on increasing special education teacher retention by answering the following research question: How can school leaders increase the retention rates of special education teachers? This qualitative case study was guided by two theoretical frameworks, transformational leadership theory and critical disability theory, which informed the research design. I conducted the research at two public elementary schools in a suburban community in South Carolina. The findings revealed school leaders can increase special education teacher retention rates through intentional support, job acknowledgement, and advocacy. Findings also identified transformational leadership practices that improve special education teacher experiences

The Dark Side of Great LMX Relationships: Why Your Best Employees Might Be Burning Out

While workplace relationships are widely considered beneficial for employee well-being, a paradox emerges when employees with the strongest leader relationships experience burnout despite receiving excellent support. This contradiction suggests that these very same relationships may create psychological pressure to reciprocate support and result in employee burnout. Drawing on Social Exchange Theory and Conservation of Resources theory, I examine whether felt obligation resulting from Leader-Member Exchange (LMX) relationships contributes to employee burnout across the full spectrum of LMX quality relationships. I argue that LMX quality creates felt obligation to reciprocate leader support. This obligation, in turn, depletes emotional resources and leads to increased burnout. I tested a mediation model where LMX quality would increase felt obligation, which then would predict burnout (measured as emotional exhaustion). I collected data from 364 full-time employees across diverse industries using a three-wave longitudinal design with one-week intervals to establish temporal precedence and reduce common method bias. LMX quality strongly predicted felt obligation as predicted. However, the results contradicted my remaining hypotheses, revealing an unexpected “bright side” mechanism rather than the hypothesized “dark side”. The mediation pathway was not supported as felt obligation did not significantly relate to burnout and displayed a protective trend. Moreover, independent of felt obligation, LMX quality directly buffered against burnout. These findings challenge assumptions about workplace relationships, demonstrating that LMX relationships and the obligation they generate protect against employee burnout rather than contribute to it. The results present a paradigm shift from viewing workplace relationships as sources of strain to protective resources of employee well-being. Theoretically, it challenges “too-much-of-a-good-thing” assumptions by showing linear rather than curvilinear relationships across the full spectrum of LMX quality. Practically, it provides support for relationship-focused burnout prevention strategies. Additional theoretical and practical implications, as well as avenues for future research, are also discussed

Striped Bass (Morone Saxatilis) Movement and Habitat Selection in the Edisto River, South Carolina

Striped Bass (Morone saxatilis) are a commercially and recreationally important fish native to the Atlantic Coast of the United States. They possess a diversity of life history strategies, with northern populations tending to be anadromous and southern populations being primarily river residents. In general, southern populations are less studied, posing challenges for effective management. Between 2019 and 2024, we tagged 37 Striped Bass with acoustic telemetry transmitters in order to study seasonal migration patterns and summer habitat selection. We estimated migration probability for both the spring and fall Striped Bass migrations using data from an array of passive acoustic receivers within the Edisto River and with generalized linear mixed models. We also manually tracked 14 Striped Bass on the Edisto River between June and August of 2024, collecting used and available microhabitat data in a discrete choice framework. . Our analysis found that warming water temperatures are the primary environmental factor cuing spring migrations, and that increases in river discharge can have a moderating effect on migration probability even when temperatures are otherwise warm enough to cue an upstream migration. Our results also indicated that the upstream forks of the Edisto River represent critical summer habitat for Striped Bass, and that preservation of these habitat areas is likely to be a focus of future management of the populatio

Transforming Text to Images: Prompt Engineering Principles for Generative AI Use in Extension

Generative AI (GenAI) systems facilitate the creation of visual images by utilizing extensive datasets to interpret text-based instructions. Effective prompt engineering is essential for optimizing the output of AI-generated images. This article examines various GenAI systems and their functionalities, explores text-to-image prompt engineering principles and their application in Extension work, aiming to enhance the effectiveness of visual content creation with respect to educational materials, data visualization, and promotional content. The article also provides guidance and examples to assist Extension professionals in leveraging GenAI for improved communication and engagement. Recommendations include crafting detailed prompts and continuously refining them for desired results, ultimately fostering innovation in Extension work

Bringing to Life Our Mission and Vision: the Role of Professional Development in Instructional Technology

Despite improved access to digital tools and increased demand to prepare students for the 21st-century workforce, K-12 educators still have difficulty balancing technology, pedagogy, and content in the classroom. In the rural school district of Pleasant County, there is variation in the utilization of instructional technology to engage students as content creators, collaborators, critical thinkers, and communicators. This problem was substantiated as evidenced by the study of the Effective Learning Observation Tool, which identified the domain of engaging, learning-centered instruction as an area of opportunity for the district, with the lowest score in digital learning (Cognia, 2023). In this study, our team utilized the seven effective elements of professional learning to design a learning cohort and implement student-centered coaching cycles to impact teachers’ knowledge, skills, beliefs, and self-efficacy (Darling-Hammond et al., 2017). This study aims to examine how student-centered coaching cycles, in addition to learning workshops, impacted teachers’ knowledge as defined by TPACK, self-efficacy, and the utilization of instructional technology tools in the classroom. Using a mixed-methods design, data points were collected from a pre-post survey, classroom work plans, and run charts during each coaching cycle with five different teachers. Teachers who participated in the coaching cycles in addition to the learning cohort showed a statistically significant growth in the areas of technological knowledge (TK), technological content knowledge (TCK), and technological pedagogical knowledge (TPK), with greater growth across all domains of TPACK when compared with elementary eachers who did not participate in the cohort. Similarly, teachers participating in job-embedded coaching experienced greater gains in self-efficacy and instructional technology tool utilization as evidenced by larger effect sizes. These findings support the utilization of a student-centered coaching framework as a methodology for implementing job-embedded coaching for instructional technology. Additionally, this study provides evidence of effective, sustainable professional development practices to positively impact instructional technology usage in a rural district

Melts to Solutions: Structure, Dynamics, and Response of Polyelectrolytes

The current research elucidates the changes in the structure and motion of polyelectrolytes as they are perturbed by solvents and shear flows. Polyelectrolytes are macromolecules whose backbone consists of long, predominantly hydrocarbon chains, substituted by ionizable groups, which tend to dissociate into ions in polar solvents. Their properties result from a delicate balance of elastic energy that arises from the polymeric backbone and electrostatic forces, which stem from the ionizable groups. Though polyelectrolytes have an immense potential to propel numerous technologies, from clean energy to drug delivery systems, understanding the delicate balance between the properties of the polymer backbone and the effects of the electrostatic interactions remains an open fundamental science challenge with an immense impact. The current study uses computational methods, particularly large-scale atomistic molecular dynamics simulations, to understand the balance between chain characteristics and electrostatic forces on a model polyelectrolyte, polystyrene sulfonate-sodium salt in the presence of solvents and under shear. As polymers are processed from molecules to viable materials under shear and in the presence of solvents, these studies resolve fundamental principles that directly contribute to the response of polyelectrolytes. The effects of two classes of solvents were studies, tetrahydrofuran (THF) that represents organic solvents and water which is an environmentally friendly, prevalent solvent. The structure and motion of these polymers were studied in their quiescent state, without any disruption, and under shear forces, because most polymeric molecules are transformed into actual materials under shear. We find that sulfonated polystyrene polyelectrolytes form distinctive branched ionic aggregates and form ionic networks as the sulfonation fraction increases. The addition of THF breaks some of the larger clusters, enhancing the polymer dynamics while having minimal effect on the ionic network. When perturbing these systems at high shear rates, the ionic clusters break, and almost all the chains elongate, while at the low shear rates, only some of the chains are affected. By introducing shear forces in the presence of a solvent, one can further disrupt and reshape these complex systems, enabling them to reassemble in new ways. As the water content increases, the polymer chains become more extended conformation but are not fully extended, even at very dilute polymer concentrations. When perturbing these solutions under shear, the chains undergo rapid coil-stretched-recoil cycles with a characteristic time that depends on the shear rate and polymer concentration. Understanding the behavior of polymer solutions under shear enables advancing the material processing to gain valuable properties from them

Navigating Digital Participation: How Social Dynamics, Cognitive Factors, and Age Shape User Engagement?

As digital technologies become deeply integrated into daily life, understanding what drives meaningful engagement has become a central concern in information systems research. This dissertation addresses this issue through two essays on digital participation. The first essay investigates user engagement in online communities by synthesizing findings from 220 empirical studies using random-effects meta-analysis and meta-analytic structural equation modeling. The results show that relational and structural forms of social capital, such as trust, social ties, and community identity, are stronger predictors of sustained participation than usability-related factors. Intrinsic motivations, including enjoyment and altruism, are generally more influential than extrinsic rewards. The effect of these factors varies across community types, suggesting context-specific mechanisms. The second essay introduces the Dual-Pathway Model of Aging and IT Use, which explains how cognitive and psychological processes jointly shape technology use in later life. Using behavioral data, panel data, and experimental evidence, the study shows that processing speed mediates the impact of working memory and aging beliefs on technology use. The analysis reveals an inverted U-shaped relationship between age and IT use, and highlights that moderately positive self-perceptions of aging are associated with higher cognitive performance. Together, the two essays show that digital engagement is shaped not only by system design or demographics but also by social relationships, mental capabilities, and beliefs. The dissertation contributes new theoretical insights and methodological approaches, and offers practical guidance for designing inclusive digital platforms and promoting digital inclusion across age groups

Silver Nanoparticles in Ammonia Sensing and Photovoltaics

Nanocomposite films (NCF) containing silver nanoparticles (AgNPs), separated by thin layers of silica/poly-4-vinylpyridine/polyvinylpyrrolidone, were fabricated via drop casting, spin coating, dip coating on glass substrate and drop casting on nylon filter membranes. The more uniform films were produced by drop casting on nylon filter membranes due to their solvent wicking properties. The films demonstrate electrical conductivity that varies in response to moist ammonia and water vapors. The changes in conductivity are attributed to hydrogen bonding between ammonia and water molecules with the silica/polymer layers, as well as the direct adsorption of ammonia onto the silver surface. Notably, NCFs with polyvinylpyrrolidone layers exhibited a limit of detection of 0.4 ppm for ammonia, even in the presence of interfering water vapor. It is proposed that the films could be further developed as ammonia sensors for environmental and biomedical applications. The novelty of this work relates to achieving low detection limit in the presence of saturated water vapor as well as a development of new simple and reproducible fabrication technique. This work is published in Sensors and Actuators B: Chemical journal. Silver nanoparticles (AgNPs) exhibit highly efficient interaction with light across visible and near IR spectral ranges due to the excitation of plasmon resonances and can potentially function as an effective light capturing antenna. Hybrid nanostructure containing Ag plasmonic core and photosensitive Ag2S semiconductor layer were fabricated and incorporated into photovoltaic (PV) devices that were expected to exhibit enhanced performance. Contrary to the initial expectations, it was established that the direct contact between Ag2S photosensitive semiconductor layer with the metallic silver core provided an additional mechanism for the recombination of photogenerated electron hole pairs thus reducing the performance of the devises. Plasmonic AgNPs were synthesized with a thin electrically insulated shell to alleviate this recombination mechanism and integrated into the PV devices containing Ag2S photosensitive semiconductor. Embedding the insulated plasmonic AgNPs into the semiconductor resulted in a 20.4% enhancement of the photo conversion efficiency (PCE) as compared to the same PV devices without plasmonic particles. The novelty of this work relates to the identification of electron hole recombination mechanism within plasmonic metal nanostructures that leads to the reduced performance of PVs. This has broad applicability to all PV devices that utilize plasmon resonances to enhance their performance. A general solution was developed based on electrically insulating plasmonic nanoparticles with a thin dielectric shell. The significant improvement of the PCE was achieved because of the locally enhanced electromagnetic field associated with plasmon oscillations. All structures were characterized using optical microscopy, atomic force microscopy, UV-Vis spectroscopy, SEM, Raman, and XRD

Connecting with Millennials: A Guide for Donor Engagement

Millennials are emerging as a vital donor demographic, yet many resource-limited nonprofits, including Clemson Community Care (CCC), struggle to effectively engage this generation. This applied thesis project investigates how CCC can build meaningful connections with millennial donors by exploring nonprofit awareness, donor motivations, communication expectations, content preferences, and common barriers to giving. Using qualitative data gathered from two focus groups of millennial participants, this study reveals that millennials represent a diverse and distinct audience with unique expectations for nonprofit communication. Grounded in public relations theories of stewardship and organization-public relationships (OPR), the research highlights the importance of flexibility and autonomy in building trust and long-term engagement with millennial donors. Participants indicated a desire for personal and community-oriented connections, user-friendly digital donation systems, and control over how and when they receive communications. The findings informed the development of a millennial donor engagement guide tailored specifically for CCC, offering actionable strategies that align with the organization’s limited resources. By implementing the recommendations from this guide, CCC can enhance millennial donor retention, foster stronger community ties, and ensure the sustainability of its donor outreach efforts. This study contributes to the broader conversation on nonprofit communication and engagement strategies, offering practical insights for organizations aiming to cultivate long-term relationships with a new generation of donors