Characterization Of Search Spaces And Effects On Machine Learning, Leo Ghelarducci

Doctoral Dissertations and Master's Theses

The present status of the field of Machine Learning (ML) focuses on optimization of popular models. Rarely are the effects of the problem characteristics upon the solution algorithm studied. There exists no standard for knowing when to apply ML algorithms to a given problem or how to estimate the effectiveness of results. Focusing on the search space of problems, a rigorous study was conducted to generate an in-depth understanding of the impact of search space characteristics to the performance of a ML algorithm, specifically a Genetic Algorithm (GA). The effects of specific problem characteristics, represented via solution space characteristics, on …

Drift Dynamics Of Early Life-Stage Invasive Carps, Saurav Karki

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Asian carp species pose significant ecological threats to North American freshwater systems due to their invasive nature and prolific reproduction. Their semi buoyant eggs develop while drifting downstream with the river current. Understanding early life-stage transport is therefore critical for predicting recruitment potential and guiding management efforts. Existing fluvial egg drift models, including those relying on 1-D hydraulics and fully 3-D CFD-based models, are either inadequate for complex braided rivers or too computationally demanding for large-scale application. The Platte River in Nebraska, characterized by wide, shallow, multi-threaded channels, is dominated by two-dimensional flow conditions, making a depth-averaged 2-D modeling approach …

Interpolation In Weighted Projective Spaces, Shahriyar Roshan Zamir

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Over an algebraically closed field, the double point interpolation problem asks for the vector space dimension of the projective hypersurfaces of degree $d$ singular at a given set of points.

After being open for 90 years, a series of papers by J. Alexander and A. Hirschowitz in 1992–1995 settled this question in what is referred to as the Alexander-Hirschowitz theorem. In this thesis, we use commutative algebra to prove analogous statements in the weighted projective space, a natural generalization of the projective space.

A main contribution of this work is the careful adaption of several classical algebro-geometric techniques to the …

Non-Blackbox Robust Design Of Machine Learning In Networks, Venkat Sai Suman Lamba Karanam

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Networked systems have become increasingly complex, with newer communication technologies and standards being added every day. Machine Learning (ML) and Artificial Intelligence (AI) paradigms have been adopted in networks to not only solve many fundamental problems, but also to allow seamless integration of components comprising them. The saying “let’s not reinvent the wheel” in ML/AI adoption implies that model architecture design be left for pure ML/AI researchers, while network researchers focus on input preprocessing (e.g. formatting the packet data to be fed to a model), hyperparameter fine-tuning and a trial-and-error approach to find the “best” result. …

Authentication And Message Integrity Verification For Emerging Wireless Networks, Ebuka Philip Oguchi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation presents a comprehensive body of research on authentication and message integrity verification for emerging wireless networks, focusing on secret-free and physical layer security techniques across diverse, challenging, and unconventional environments.

It comprises four first-author contributions that span underground wireless systems, over-the-air (OTA) channels, vehicular communications, and nanoscale molecular networks.

The first contribution, Soil-Assisted Trust Establishment for Underground Wireless Networks (STUN), introduces a physical-layer trust bootstrapping protocol that achieves authentication and message integrity without pre-shared secrets. Leveraging underground-to-air propagation laws and trusted relay nodes, STUN resists active signal injection attacks and demonstrates security comparable to the unbalanced oil and …

Blood-Red And Flaming And True, Kate Gaskin

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Blood-Red and Flaming and True contains poems that explore the immense feelings of love and loss tied to the relationship between parent and child. They chronicle my experience raising a neurodivergent child, as well as undergoing infant loss and navigating a U.S. medical system that is renowned for putting women and people capable of giving birth—especially BIPOC—at greater risk than other countries with similar resources. Through poems that inhabit a variety of forms, I sift through grief and joy while attempting to tap into the sublime state that underlies extreme loss and love. Throughout, I investigate how lyric poetry is …

Rhetorics Of Encounter: Toward A Biocentric Theory Of Discourse, Matthew D. Whitaker

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Encounters with more-than-human identities are transformative moments that stand to affect dispositional and bodily change in individuals. From close brushes with wild animals in National Parks to everyday interactions with local ecologies, encounters invite us to feel and think differently about the nature of our realities. In Rhetorics of Encounter: Toward a Biocentric Theory of Discourse, I draw from interdisciplinary perspectives to disrupt the idea of rhetoric as a representational medium, arguing that rhetoric occurs not just through textual exchanges of words and symbols, but through embodied moments of contact with other responsive beings. Invoking George Kennedy’s theory …

Development And Evaluation Of Supported Ionic Liquid Membrane And Porphyrin Frameworks For Carbon Capture Separation, Sarang Ismail

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The global urgency to mitigate anthropogenic CO₂ emissions has intensified the pursuit of energy-efficient separation technologies. Supported Ionic Liquid Membranes (SILMs) have emerged as promising candidates for CO₂ capture due to their tunable solubility-selectivity and low energy requirements. However, challenges such as mechanical instability, limited scalability, and trade-offs in transport performance have impeded their widespread adoption.

This thesis explores a systematic approach to designing and optimizing SILMs for enhanced CO₂ separation by tailoring polymer–ionic liquid interactions, processing conditions, and material architectures. A comprehensive set of studies were conducted using poly(vinylidene fluoride) (PVDF) with varying molecular weights, different grades of PEBAX®, …

Multivariate Mixture Regression Models With Known Group Membership And Informative Priors, Pahalapathirage Dona Kalani Hasanthika

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

We introduced couple different novel approaches to incorporate latent variable information to multivariate mixture regression models with both Gaussian and count data. We also evaluated the performance of these models with existing best approaches with simulated data from various sampling structures and also evaluated one of the models performance with rice metabolite data that provided some novel insights as well as validating existing literature about performance and behavior of these metabolites. We validated the method using extensive simulations and a real-world application. In both quantitative covariate designs and complex treatment design simulations, our method consistently outperformed established tools like limma, …

On Kernels And Antiderivatives Of Nonlocal Derivatives, Alex John Heitzman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Nonlocal operators are mathematical operators taking functions to other functions f → Df , where to evaluate the operator Df at a point x, one must know the value of f in some region around x, and that region cannot be arbitrarily small. Nonlocal derivatives are like derivatives in that they measure the deviation of a function f(z) from f(x) when z is close to x. In this thesis, we will study nonlocal operators of the form

D_kf(x) = [integral]_Ω [f(x) …

From Classroom To Content Creator: Leadership Practices And Identities Of Female Science Teachers On Tiktok, Rachel M. Benzoni

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This qualitative multiple case study investigates how four secondary science teachers use TikTok to advocate for science education and how content creation shapes their professional identities as leaders. Using interviews and video content with a framework integrating constructivist leadership, Leader Identity Construction Theory (LICT), and the Social Change Model (SCM), findings show participants enacted leadership outside formal roles through distributed and relational practices leveraging social media's affordances. Five themes emerged from the analysis: (1) Reconceptualizing Teacher Leadership on Social Media, (2) Leadership Through Equity-Driven Practice, (3) Constructing and Leading in Online Professional Learning Communities, (4) Forming and Negotiating Identities in …

Faced With Genai, Educators’ Engagement Capacity Matters More Than Ever, Thomas Menkhoff

Research Collection Lee Kong Chian School Of Business

In a commentary, SMU Professor of Organisational Behaviour & Human Resources (Education) Thomas Menkhoff stressed the need for educators to upskill so they can guide students in using generative artificial intelligence (GenAI) responsibly, rather than dismissing it. He argued that universities should move beyond prohibition and invest in AI literacy to safeguard academic integrity. Prof Menkhoff mentioned that combining the use of GenAI tools with effective prompting and Socratic questioning transforms students’ use of technology from passive consumption to active, reflective and critical engagement. To achieve this, he said that schools must set clear guidelines and design AI-compatible assessments that …

Eliciting Supplier Cooperation For Value Chain Decarbonization: A Field Experiment With Smallholder Farmers In India, Sukti Ghosh, Jasjit Singh

Research Collection Lee Kong Chian School Of Business

Many firms are attempting to reduce greenhouse gas emissions across their value chain. However, this requires convincing suppliers to adopt relevant decarbonization practices, which is challenging when the suppliers perceive such practices as risky or detrimental for their economic well-being. We employ a field experiment to examine relational investments (i.e., investments intended to promote mutual benefit for the exchange partners) as a tool for overcoming this challenge. In a research collaboration with a global firm pursuing decarbonization of its agricultural supply chain in India, we investigated the effectiveness of complementing training their supplier farmers on climate-friendly agricultural practices with also …

Chemical & Electromagnetic Signatures Of Binary Neutron Star Mergers, Benjamin Amend

All Dissertations

Binary neutron star (BNS) mergers are some of the most energetic events in the universe, producing both short gamma-ray bursts (GRBs) and kilonovae. GRBs are brief, bright flashes of gamma rays, powered by ultra-relativistic jets launched during the merger. These jets produce a prompt burst of gamma rays, followed by a broadband afterglow generated by external shocks as the outflow interacts with the surrounding medium. Kilonovae are optical-infrared transients from the radioactive decay of heavy, neutron-rich nuclei formed through the rapid neutron capture process (r-process) in the merger ejecta. Together, GRBs and kilonovae provide unique laboratories for probing fundamental physics …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

All Dissertations

The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Engaging Minds: The Impact Of Multimodal Instruction On Multiplication Facts, Ashleigh Cobey

All Dissertations

This dissertation examined the impact of a multimodal, station-based instructional approach on student engagement and multiplication fact fluency among third-grade students at Hopeful Elementary School (HES), a Title I, high-poverty school. Traditional methods of rote memorization have not consistently met the needs of all learners, particularly those from under-resourced backgrounds or with disabilities. This study explored how structured opportunities to practice multiplication through music-based, game-based, and technology-enhanced learning experiences influenced student engagement and fluency.

Using a multimethod design, the intervention group participated in the Multimodal Multiplication Intervention, rotating through three stations Monday through Wednesday and selecting a preferred station on …

Studying The Impact Of Co-Teaching On Students With Disabilities Self-Efficacy In An Algebra 1 Course., Shannon E. Sharkey

All Dissertations

ABSTRACT

Students with disabilities (SWD) at Large High School in Rural School District have consistently underperformed in Algebra 1 as compared to their non-disabled peers and SWD across South Carolina. This performance gap contributes to the school’s designation as an Additional Targeted Support and Improvement (ATSI) site, putting it at risk for state intervention. This dissertation investigates whether implementing a co-teaching model in Algebra 1 can positively impact SWD students’ self-efficacy in mathematics, with a secondary focus on potential gains in academic performance in Algebra 1 on the state End of Course (EOC).

Grounded in improvement science methodology, the study …

Improving Retention Of Students With Disabilities In Stem Through Math-Based Type Science Readiness, Eleni N. Koukoularis

All Dissertations

Abstract

This Dissertation in Practice examined the impact of a Math for Science Readiness (MSR) intervention on the science course planning behaviors of Students with Disabilities (SWD) in College Preparatory Basic (CPB) Chemistry, with the aim of increasing enrollment into Physics 1 College Placed Academic (CPA). Using an approach grounded in sociocultural theory and strength-based practices, the intervention implemented 16 short modules connecting chemistry and physics through shared math themes to reinforce math concepts across disciplines.

Data collected included physics interest surveys, common assessment exam scores, enrollment data, and counselor feedback to evaluate whether targeted math support could promote progression …

From Collaboration To Achievement: Exploring Co-Teaching As A Strategy To Close The Gap In Mathematics For Students With Disabilities, Lindsay L. Stewart

All Dissertations

This study addressed the persistent achievement gap in Algebra 1 for students with disabilities (SWD) at Popular High School (PHS), a rural high school within Sweet County School District (SCSD). In response to historical underperformance on the South Carolina Algebra 1 End-of-Course (EOC) assessment and the school’s designation for Additional Targeted Support and Improvement (ATSI), the district piloted a co-teaching intervention to provide more inclusive and supportive instruction for SWD. In this context, co-teaching refers to a collaborative instructional model in which a general education and a special education teacher share responsibility for planning, delivering, and assessing instruction in the …

Toward A Unified Theory Of Fire-Induced Spalling Of Concrete: Transcending Domain Knowledge Limitations Through Explainable Artificial Intelligence, Causal Discovery And Inference, Mohammad Al Bashiti

All Dissertations

When concrete is exposed to fire, it can suddenly break apart in a dangerous process called spalling. This can severely weaken buildings and even trigger a collapse. While researchers have studied this problem for years, we still don’t fully understand what causes it. My research uses a combination of data, and advanced AI techniques to identify and quantify the key factors that increase the risk of spalling. I collected data from over 1,000 fire tests and used AI models to predict when spalling might happen. I also applied explainable AI tools to understand why it happens.

The results showed that …

Discovering High-Redshift Bl Lacs And Localizing Grbs For Mev Missions, Yong Sheng

All Dissertations

Blazars are active galactic nuclei (AGNs) with their jets aligned towards Earth. Gamma-ray bursts (GRBs) can be classified into long and short types. Long GRBs are produced by the collapse of massive stars, while short GRBs are formed by binary mergers (neutron star - neutron star or neutron star - black hole mergers). Both objects are the key probes of extreme physics processes and cosmic evolution, providing us an unique window to understand the Universe. My research aims to measure the redshift of blazars and localize GRBs for proposed and upcoming gamma-ray telescopes. BL Lac objects (BL Lacs) are a …

12co Ro-Vibrational Spectroscopy Of Protoplanetary Disks: Inferring Planet-Disk Interactions, Janus Kozdon

All Dissertations

Observing and studying planets around young stars during their initial formation stages is essential for understanding the physics of their formation. Protoplanetary disks are the host sites of planets, and they exhibit substructures that hint towards the planets' presence, but the planet itself has rarely been detected. Analysis of the substructures in protoplanetary disks, especially towards the inner regions where most planets seem to lie, will provide information that can be used to refine theories about planet-disk interactions and, ultimately, planet formation. To probe the high-velocity inner regions, this study utilizes high-resolution spectroscopy, which has increased sensitivity with increasing velocities. …

Investigation Of Solid-State Reactive Sintering And Rapid Laser Reactive Sintering For Al-Doped Li7la3zr2o12 Solid-State Electrolyte, Aaron Santomauro

All Dissertations

As a society, we’ve exhausted an extreme amount of fossil fuels and put an overwhelming strain on Earth’s natural resources. From this, it is critical to think about the successful future of our planet and ourselves by developing energy devices such as all-solid-state lithium-ion batteries (ASSLIBs). These devices offer a greener and more efficient alternative to power our daily lives, such as electric vehicles (EVs), portable electronics, medical devices, grid-scale energy storage, and aerospace/aviation. ASSLIBs are an excellent alternative to liquid-state batteries, which pose dangerous safety concerns (e.g., flammability, electrolyte leakage, etc.). These ASSLIBs are known to have generally high …

Experimental Design And Analysis For Decision Making: Methodology And Applications, Yezhuo Li

All Dissertations

This dissertation develops and applies advanced statistical and optimization frameworks to enhance decision-making under uncertainty, particularly in engineering and manufacturing contexts. First, we introduce an approach for the optimal design of controlled experiments that accounts for observational covariates, enabling more precise and personalized decisions. Second, we explore the application of constrained Bayesian optimization, using Gaussian process surrogate models, to optimize composite cure processes, significantly reducing computational effort while maintaining high predictive accuracy. Building on this foundation, we extend Bayesian optimization to bivariate Gaussian process models that capture correlations between objective and constraint functions, offering new insights into multidimensional decision landscapes. …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

All Dissertations

Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

Tiered Structured Intervention Program To Prevent Student Pushout In High School, Toshawnka T. Mahone

All Dissertations

High school dropouts remain a challenge in the United States Educational System, particularly among students impacted by chronic attendance issues, academic struggles and persistent behavioral issues. This Dissertation in Practice (DIP) examines the implementation of ELEVATE3, an intervention program designed to prevent student pushout by addressing distinct at-risk factors: attendance, behavior and academic retention. Framed by pushout theory and grounded in goal-setting and self-efficacy literature, this study investigates how targeted structured supports influence students' motivation, academic achievement, and self-regulation. This mixed-methods research used student academic records and staff interviews to determine the impact on a rural Title 1 high school. …

Decoding The Mobile App Playbook: How Sdks And Cross-Promotions Drive Market Performance, Pranith Abbaraju

All Dissertations

This dissertation investigates the strategic determinants of mobile app success within the evolving mobile platform ecosystem, focusing on app development choices and user acquisition strategies. Drawing on large-scale longitudinal data from the iOS platform, the research comprises two empirical studies contributing to the literature on digital platforms, modular design, and mobile advertising.

The first study examines how the integration of software development kits (SDKs)—a central mechanism of modular innovation—affects app market performance. The analysis identifies SDK popularity as a dual-edged strategic attribute. While popular SDKs can enhance app quality by enabling access to reliable, widely adopted functionalities, their widespread adoption …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …