Digital Commons Network^™

Performance Analysis Of Multivariable Control Structures Applied To A Neutral Point Clamped Converter In Pv Systems, Renato Santana Ribeiro Junior, Eubis Pereira Machado, Damásio Fernandes Júnior, Tárcio André Dos Santos Barros, Flavio Bezerra Costa

Michigan Tech Publications

This paper addresses the challenges encountered by grid-connected photovoltaic (PV) systems, including the stochastic behavior of the system, harmonic distortion, and variations in grid impedance. To this end, an in-depth technical and pedagogical analysis of three linear multivariable current control strategies is performed: proportional-integral (PI), proportional-resonant (PR), and deadbeat (DB). The study contributes to theoretical formulations, detailed system modeling, and controller tuning procedures, promoting a comprehensive understanding of their structures and performance. The strategies are investigated and compared in both the rotating ((Formula presented.)) and stationary ((Formula presented.)) reference frames, offering a broad perspective on system behavior under various operating …

Registered Nurses' Autism Knowledge And Preparedness To Care For Autistic Patients, Bronte Elisa Weissman

Theses and Dissertations

Autistic individuals frequently report negative experiences during healthcare interactions and numerous provider-level barriers to accessing quality care, including stereotyping, perceived lack of autism knowledge, challenges with communication, and insufficient accommodations. Reports of healthcare providers’ experiences caring for autistic patients in the U.S. have largely come from physicians, who endorse inadequate training, resources, and practical guidelines. Although patients spend far more time with nurses than other healthcare providers, registered nurses (RNs)’ perspectives on caring for autistic patients in the U.S. are largely unknown and autism-focused trainings for nurses are minimal. In the current study, a survey was nationally disseminated to a …

Difference In High School Geometry End-Of-Year State Exam Scores Between Three Different Retake Time Frames, Christina Noel Walton

Walden Dissertations and Doctoral Studies

A grading policy was implemented in a Northeastern suburban public school district that left it to curriculum teams to define the amount of time between the original test and its retake resulting in a slight decrease in high school students’ geometry end-of-year state exam scores. Guided by Bloom’s theory of mastery learning, the purpose of this quantitative causal-comparative study was to investigate if there were statistically significant differences between high school students’ geometry end-of-year state exam scores or between high school students’ geometry math growth scores when controlling for the preassessment score differentiated by three schemes of retake timing: short-term, …

Code Stories For Software Evolution, John Joseph Allen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Programmers spend more than half of their time comprehending code, and in particular struggle to answer questions about the rationale, intent, and history behind software artifacts. Through this dissertation, I explore how history-aware tools can help programmers understand unfamiliar software artifacts. First, I investigated how providing additional context -- historical code changes grouped by the original developer's stated subgoals and the web foraging activity of the original developer impacted the process of code reuse. I found that programmers utilized these resources to 1) make better analogies between their reuse scenario and what code was already written, and 2) anchor into …

Strategies To Use Diversity, Equity, And Inclusion Programs To Increase Employee Performance And Profitability, Kecia Bailey Alexander

Walden Dissertations and Doctoral Studies

A lack of effective strategies for implementing diversity, equity, and inclusion (DEI) programs to increase employee performance and profitability is a concern for leaders in the education industry. This problem is significant to educational leaders because, without effective strategies for implementing DEI programs, they cannot address the gap in practice that hinders improvements in employee performance and organizational profitability. Grounded in Ajzen’s theory of planned behavior, this qualitative pragmatic inquiry identified and explored the effective strategies educational leaders used to successfully implement DEI programs to increase employee performance and profitability. Participants were six leaders from both for-profit and non-profit educational …

Class A Biosolids Production Using Conventional And Low-Cost, Low-Tech Processes At Small Water Resource Recovery Facilities: A Multidimensional Sustainability Assessment, Janna Brown, Robert Handler, Eric Seagren, Jennifer Becker

Michigan Tech Publications

Producing Class A biosolids is a beneficial way to reuse wastewater treatment solids, but most conventional processes are energy-intensive and expensive. There is growing interest in the use of low-cost, low-tech (LCLT) Class A biosolids treatment processes, especially at small water resource recovery facilities (WRRFs). This study used a holistic sustainability assessment to examine the environmental, economic, and social sustainability of conventional and LCLT processes at small WRRFs. The technologies studied were Direct Heat Drying, Composting, Lagoon Storage, Air Drying, and Temperature-Phased Anaerobic Digestion (TPAD). Environmental impacts were determined by conducting life-cycle assessments for all technologies, which is described in …

Low Beta Anomaly In Some European Emerging Markets, Tadeusz Winkler-Drews, Mateusz Mogilski

Journal of Banking and Financial Economics

The aim of the study was to identify the low beta anomaly and analyse the causes of its occurrence in five European emerging markets that were components of the MSCI Emerging Markets Europe index in the period 2010–2019. It was hypothesized that the determinants of the low beta anomaly in the analysed markets are factors from at least two of the three categories of variables. Using the Betting Against Beta model proposed by A. Frazzini and L. H. Pedersen (2014), we found that this phenomenon was not identified in three markets, but occurred in the remaining two markets, for which …

La Niña Effects On The Mjo Modulation Of North Pacific Atmospheric Rivers And Associated Western North American Precipitation, L. G. Fernandes, Paul C. Loikith, M. Mora

Geography Faculty Publications and Presentations

We investigate connections between the Madden‐Julian Oscillation (MJO) and North Pacific atmospheric rivers (ARs) and associated precipitation over North America during La Niña (LN) years. Overall, AR frequency is reduced over the northeastern Pacific and western North America in phases 2–5 of the MJO. However, under LN, increased AR activity appears over those regions in phases 4–6 and across the central North Pacific in Phase 3. Distinct effects of LN on the basic state and MJO contribute to the persistence of AR anomalous patterns in phases 3–6. For instance, MJO intensifies in Phase 3 under LN, favoring the coupling between …

Insights Regarding The Role Of Administrative Support And Teacher Retention In A Suburban Arizona School District, Kristen Louise Tiffany

Walden Dissertations and Doctoral Studies

The problem that was addressed through this study is that teachers are leaving the profession in an Arizona high school district (AHSD, a pseudonym), which might be due to a lack of administrator support. The purpose of this basic qualitative study was to explore teachers’ perceptions of reasons they chose to remain in their positions as well as administrators’ perceptions on the support they provide to encourage teacher retention at AHSD. Grounded in Bandura’s social cognitive theory, semistructured interviews were conducted with six administrators and 10 teachers from AHSD. Saldana’s pattern coding was used with the following themes emerging: Teachers …

Using Exercise To Treat Anxiety In Adult Patients With Addiction, Emmanuella N. Nnadozie

Walden Dissertations and Doctoral Studies

Summary In this Doctor of Nursing Practice (DNP) project, I selected a staff education as the best intervention to improve staff knowledge in using exercise to treat anxiety disorders in adult patients at a recovery clinic for addiction. Anxiety disorders are highly prevalent among individuals undergoing substance abuse treatment, often exacerbating withdrawal symptoms and increasing relapse risks; thus, integrating the use of exercise in addition to existing standard care for anxiety treatment in individuals with substance use disorder (SUD) will lead to decreased anxiety, decreased alcohol use and drug cravings, improved quality of life and affect, increased abstinence, and improve …

Reconciling Harm Reduction Philosophy And Approaches Among Abstinence-Only Substance Abuse Treatment Professionals, Amy Rose Ashton-Williams

Walden Dissertations and Doctoral Studies

Historically, substance use disorder (SUD) treatment in the United States has been firmly grounded in abstinence-only treatment approaches. Harm reduction as a treatment model has gained additional traction. With increased rates of opioid use, overdoses, and advancements in medications for SUDs, harm reduction treatment approaches are becoming more important to improve lives of people who use drugs. Little is known about how counselors who have been educated, trained, and deliver abstinence-based SUD treatment reconcile use of harm reduction into their practice. To address this gap in literature, a generic qualitative study was conducted using the social constructivism theory. A purposive …

Enhancing Social Determinants Of Health Education In Home Health Care Including Social Determinants Of Health In Assessments And Care Plans For Home Health Clinicians, Emilia Mbanwite

Walden Dissertations and Doctoral Studies

This staff education-focused doctor of nursing practice (DNP) project addressed the critical practice problem of one southern health care facility staff’s knowledge on the integration of social determinants of health (SDOH) into home health care plans. Despite SDOH screening, clinicians lacked standardized training to effectively assess and intervene on factors such as housing, transportation, and food insecurity, contributing to preventable hospitalizations, particularly in vulnerable populations. The practice-focused question addressed whether an evidence-based education module could improve home health nurses’ knowledge and application of SDOH in assessments and care plans. The project’s purpose was to develop, implement, and evaluate this training …

A Potential New Sea Surface Temperature Proxy Based On Isomeric Highly Branched Isoprenoid Lipid Biomarkers: Ez25, Simon T. Belt, Lukas Smik, Katrine Husum, Jochen Knies

School of Geography, Earth and Environmental Sciences

Two tri-unsaturated and isomeric (E/Z) highly branched isoprenoid (HBI) diatom lipid biomarkers were quantified in 228 water column samples collected from the English Channel, West Svalbard (Arctic), the Scotia Sea (Southern Ocean) and East Antarctica. We found that the relative amounts of the two HBIs correlate well with water temperatures taken at the time of sampling. Based on these findings and some other HBI data reported previously, we suggest that the proportion of the HBI E-isomer (termed EZ25) may serve as a new proxy for palaeo sea surface temperatures, including in the polar regions. Next steps will involve determination of …

Simulated Emergency Room Sign-Outs: What They Tell Us About Diagnostic Accuracy And Opportunities For Improvement, Roni Matin, Brent R King, Amit M Mehta, Susan H Fenton, Nathan R Hoot, David J Robinson, Charles L Maddow, Amy Franklin

Faculty, Staff and Student Publications

Objective: Emergency department (ED) sign-outs provide continuity of care for patients at shift changes. However, these periods have been associated with communication breakdowns and medical errors. We explored information factors (stage-of-the-case and the explicitness of the sign-out narrative) to determine their impact on clinicians' diagnostic accuracy and confidence.

Methods: Clinicians from 2 academic ED sites reviewed patient vignettes sign-out narratives (N=69). Using a within-subjects experiment, the explicitness of the sign-out information (i.e., broad statement about labs versus stating each test) and the patient's stage in the diagnostic process (e.g., labs pending, treatment occurring, etc.) at the time of sign-out varied. …

The Impact Of Mental Health Courts On Public Attitudes Held Toward Justice-Involved Individuals With Mental Illness, Maeve Porter

Student Theses

Prior research has established that mental health court programs play an important role in reducing recidivism and mental health symptoms of defendants. However, there is a lack of understanding of the stigma that justice-involved individuals may encounter upon release from mental health court into the community, and the extent to which the general public is aware of mental health court programs. The present study sought to address public perceptions regarding mental health courts, their efficacy, and their participants based on the awareness and availability of these specialized courts in two similar states (New York and New Jersey), one in which …

Applying Machine Learning To Developmental Psychopathology, Robert Jesus Jirsaraie

McKelvey School of Engineering Graduate Student Theses & Dissertations

Psychopathology arises from a combination of many contributing factors, which can include genetic predispositions, family history, environmental stressors, developmental processes, and psychosocial dynamics. Each of these contributing factors has been researched for decades, and their influences on mental health have been well documented. In recent years, there has been a growing enthusiasm for integrating these risk factors using machine learning. However, there are a wide array of data-driven frameworks that have been implemented, and the relative strengthens of each approach is not clear. Through of series of four research studies, we examined each data-driven approach in terms of its potential …

Development Of Turbulence Models For Prediction Of Hypersonic Flows Using Compressibility Corrections And Uncertainty Quantification With Emphasis On The Wray-Agarwal Model, Aidan Robert Murphy

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate prediction of high-speed compressible turbulent flows remains one of the most significant challenges in Computational Fluid Dynamics (CFD), especially in the realm of hypersonic vehicle design. These flow regimes involve significant aerodynamic heating and shock-wave boundary layer interactions (SBLI) which remain a significant challenge for the current CFD prediction capabilities. While Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES) provide high-fidelity solutions, their computational demands limit their usability, making the Reynolds-Averaged Navier-Stokes (RANS) equations an efficient alternative for many industrial aerodynamic applications. Traditional RANS techniques, while computationally efficient, often provide limited accuracy in high-speed flows due to the presence …

Intravital Optical Imaging Of Peripheral Nerve Injury Response, Igor Luzhansky

McKelvey School of Engineering Graduate Student Theses & Dissertations

Peripheral nerve injuries in animal models require imaging approaches that can reveal the dynamic, multiscale process of regeneration over time without disrupting repair mechanisms. Traditional methods lack the ability to visualize cellular behavior and matrix remodeling continuously. We present an imaging technique based on an implantable nerve window and fluorescent labeling, enabling high-resolution, longitudinal cellular-scale observation of peripheral nerve regeneration in living mice. We first evaluated near-infrared fluorophore-conjugated fibrin as a transient marker for early regenerative tissue within nerve guidance conduits. Imaging performed upon surgical re-exposure of the nerve revealed the incorporation of fibrin into early-stage regenerative cables, with gradual …

Development, Numerical Simulation, And Optimization Of Quiet Supersonic Transport Aircraft And Extension Of The Wray-Agarwal Algebraic Transition Model To Include Compressibility And Crossflow Effects, Dean Ryan-Simmons

McKelvey School of Engineering Graduate Student Theses & Dissertations

In the first part of this thesis, the goal of the research is to implement and extend multi fidelity methods for conceptual design and optimization of a commercial supersonic transport (SST). Most modern commercial aircraft operate at a cruise condition between Mach 0.7 and 0.9, as this is the optimal trade-off of flight efficiency, operational cost, and adherence of noise regulations for overland travel. Advancements in aviation propulsion fuel efficiency and design materials suggests a primary restraint on commercial supersonic transport is noise regulations. At speeds above Mach 1, the shock waves generated by the airframe are strong enough to …

Large-Scale Modeling And Inference Of Non-Stationary Brain Dynamics, Addison Schwamb

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neural modeling has long been a tool for understanding the brain's function, in both healthy subjects and those experiencing neural pathologies. These models have captured structures in the brain ranging in spatial scale from the subcellular level to the whole-brain level, and processes ranging in temporal scale from milliseconds to multiple hours. Currently, however, there are very few dynamical systems models of whole-brain activity, and the modeling methodologies that do exist rely on neural data modalities which are impractical for use in clinical settings. At the same time, a wealth of data is being generated by patients undergoing clinical monitoring. …

Spectral Mixture Analyses Of Hematite-Rich And Clay-Bearing Terrains In Meridiani And Oxia Planum, Mars, Thomas Jake Condus

Arts & Sciences Graduate Student Theses and Dissertations

Minerals have characteristic absorption features in the visible and near-infrared wavelength range, which can be detected in remotely sensed observations using methods such as spectral parameter maps or modeled via spectral mixtures. My dissertation uses both methods on orbital and ground-based single-scattering albedo data to assess the surface compositions of Meridiani Planum and Oxia Planum, regions of Mars that are rich in secondary minerals. A probabilistic approach to spectral unmixing was adopted to account for the nonuniqueness of model solutions, with endmember abundance and grain size maps being produced for Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) orbital images. For …

The Psychology Of Sharing Experiences, Hyebin Kim

Olin Business School Graduate Student Theses and Dissertations

From dinners with family to parties with friends, consumers frequently spend time with and share experiences with other people. Sharing consumption with other people can uniquely shape people’s decisions and experiences, often in ways that differ from when individuals are on their own. In my research, I examine what kinds of experiences consumers like to share with other people, and how being the one who organizes gatherings for other people influences consumers’ decisions and experiences during shared consumption. In Chapter One, “When Sharing Experiences with Others, People Prefer Novel Experiences,” I examine how the social context of an experience, in …

Combining Code Analysis And Pedagogical Guidance: Automated Tools For Teaching Debugging In Introductory Programming, Yana Malysheva

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ability to debug code is critical to being a programmer and represents a distinct skill from writing code. Yet debugging is rarely explicitly taught in introductory programming and Computer Science courses. Instead, novices typically develop their own debugging habits and strategies when they encounter bugs in their code, which are often less effective than those of expert programmers. When students do seek help with debugging, they traditionally turn to office hours conducted by Teaching Assistants (TAs) or, increasingly, to Large Language Models such as ChatGPT. However, both sources of assistance have limitations. TAs are often students themselves with limited …

A Mechanistic Understanding Of Transcutaneous Auricular Vagus Nerve Stimulation, Kara Michelle Donovan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcutaneous auricular vagus nerve stimulation (taVNS) offers great potential as a noninvasive neuromodulation technique with expanding therapeutic potential across a range of neurological and systemic indications. Yet despite strong clinical interest, the mechanistic foundations of taVNS remain incompletely understood. In contrast to the invasive form of vagus nerve stimulation (VNS), taVNS has seen more limited parametric characterization, with many studies relying on parameters adopted from invasive protocols without systematic validation at the noninvasive level. This dissertation focuses on developing a more comprehensive understanding of the underlying mechanisms of taVNS. It extends existing literature by leveraging intracranial electrophysiology to directly quantify …

Spatial Patterns In Electronic Health Record Data-Based Predictive Modeling: A Case Study Of Prenatal Care And Preeclampsia, Abigail Lewis

McKelvey School of Engineering Graduate Student Theses & Dissertations

The electronic health record (EHR) documents interactions between patients and healthcare systems and is widely used for secondary research on health outcomes due to broad adoption. While EHR data support efficient clinical informatics research, they are subject to biases stemming from healthcare seeking behavior, health system attributes, and individual or environmental characteristics. Place-based characteristics, in particular, strongly influence when and how patients access care and shape health outcomes. These biases in EHR data can affect predictive modeling pipelines which leverage them, contributing to variation in model performance across groups. In healthcare, where predictive models are increasingly used to guide care, …

Multi-Layer Support For Component-Based Cyber-Physical Systems Applications, Oren Bell

McKelvey School of Engineering Graduate Student Theses & Dissertations

Component-based design is a paradigm meant to aid in development of software applications by modularizing different functionalities of a system. This building-block approach is used extensively in cyber–physical and robotic systems. Common and established solutions to specific problems, such as perception nodes, state estimators, and motion planners, can be developed, verified, and reused as off-the-shelf modules. These modules may be integrated atop today’s heterogeneous hardware platforms, where an application can be distributed across GPUs, FPGAs, and CPU cores. When heterogeneous computational devices share the workload of a collection of components, the very act of integration may inject timing uncertainty. For …

Harnessing Metabolic Modeling And Artificial Intelligence For Next-Generation Bioproduction, Zhengyang Xiao

McKelvey School of Engineering Graduate Student Theses & Dissertations

Bioproduction in microbial hosts faces two main challenges: (1) unique metabolism of each species is difficult to generalize, and it requires precise quantification before metabolic engineering. (2) Past experiment data are fragmented in different studies, making it difficult to combine these non-standardized data for future experiment design. These challenges lead to high costs and risks in scaling up biomanufacturing processes, where R&D requires substantial budgets and iterative experiments are expensive. This thesis addresses both challenges through two research pillars. Part I uses 13C metabolic flux analysis (MFA) and genome-scale model (GSM) to investigate metabolic limitations in bioproduction hosts. In Escherichia …

Moment Ensemble Approaches For Estimation And Robust Quantum Control, Andre Luiz Paes De Lima

McKelvey School of Engineering Graduate Student Theses & Dissertations

Large-scale population dynamics governed by ensemble systems present significant challenges due to their inherently high dimensionality. Recent advances have demonstrated the effectiveness of moment-based methods (particularly those employing polynomial bases such as Legendre and Chebyshev polynomials) when integrated with optimization techniques for control design in ensemble systems. However, these methods have not been extensively explored for enhancing robustness against systematic noise, nor have they been widely applied to complex quantum systems involving multi-parameter configurations and entanglement phenomena. In this work, we extend the application of moment methods in ensemble systems through two projects. Initially by developing a Kalman filter analogue, …

Towards Graph Foundation Models: Few-Shot And Zero-Shot Learning On Graphs, Hao Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graphs naturally model complex relationships and interactions across various domains, including social networks, biological systems, and recommender platforms. Graph Neural Networks (GNNs) have emerged as powerful tools for learning effective graph representations through iterative message passing, significantly improving performance in tasks such as node classification, link prediction, and graph classification. However, the success of GNNs largely depends on abundant labeled data, posing challenges in practical scenarios where labeled data is scarce or unavailable. This dissertation addresses these challenges by exploring few-shot and zero-shot learning within the graph domain. We first propose COLA, a self-supervised few-shot node classification method that exploits …

Computational Imaging Under Incomplete Information, Weijie Gan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging is a pivotal field that synergizes physical measurement principles with advanced algorithms to generate visual information. An important task in this field is solving imaging inverse problems that aim to reconstruct high-quality images from observed measurements. Model-based deep learning (MBDL) has emerged as a particularly powerful tool for tackling these inverse problems by integrating machine learning (ML)-driven priors with knowledge of the imaging physics. This dissertation focuses on the pervasive challenge of informational incompleteness in computational imaging, arising from various practical and physical limitations, that hinder the widespread adoption of ML-driven computational imaging algorithms in practice. This includes: …