Digital Commons Network^™

The Food Truck: A Multi-Product Newsvendor With Expectile Risk, Sekyiwaah Nuamah

Electronic Theses and Dissertations

The Newsvendor Problem is a fundamental model in Operation Research and Supply Chain Management used to determine the optimal order quantity under uncertain demand to minimize expected costs.
This research extends the classical Newsvendor problem to a multi--product setting, addressing the risk of asymmetric cost structures faced by a food truck. This thesis introduces expectile risk measures to quantify and manage uncertainty in demand, moving beyond traditional risk metrics. To evaluate the impact of expectile-based decision-making, we analyze three types of demand distributions--simple, symmetric, and skewed. For skewed distributions, we apply linear spline inverse interpolation to derive expectile values from …

The Impact Of Multiple Measure Placement In Determining College Readiness On Student Perceived Readiness, Steven A. Szeszko Ii

Theses & Dissertations

The purpose of this research is to propose a qualitative grounded theory study that explores the impact of multiple measures placement on determining college readiness as perceived by students, specifically within a community college located in South Central Texas. During the COVID-19 pandemic, colleges and universities found themselves needing an alternative method to the traditional college placement testing to determine student readiness for college courses. This change impacted not only the higher education sector but also students. Therefore, this study will collect data from approximately 20 students, through the use of open-ended electronic student questionnaires and interviews, filtered for patterns …

Beyond The Price Tag: Unveiling The Hidden Impacts Of Tariffs On Businesses And Consumer Behavior, Jacob D. Haas

Honors Theses

In an era marked by global trade disruptions and rising protectionist policies, firms must navigate the complex interaction between tariffs, supply chain strategy, pricing decisions, and marketing communication. This thesis investigates how three multinational corporations Walmart, Nike, and Apple responded strategically to shifting tariff environments and trade restrictions between 2018 and 2025. Drawing on primary data from corporate 10-K filings and secondary analyses from recent economic and management literature, the study examines how each firm’s decisions regarding sourcing diversification, cost management, and consumer engagement contributed to long-term resilience.

Findings reveal that companies integrating supply chain adaptability with coherent pricing and …

Synthesis Of Antibody Functionalized Polyaniline/Polystyrene/N-Gqds Composite Fibermats For Sweat Based Cortisol Biosensing Applications, Ashwin James

Honors Theses

Noninvasive, wearable biosensors capable of detecting stress biomarkers in sweat require electrodes that are flexible, conductive, insoluble in water, and highly sensitive at low concentrations of analyte. In this work, bovine serum albumin blocked and anti-cmab immobilized nitrogen doped graphene quantum dots integrated polyaniline/polystyrene composite fibermat electrodes (BSA/Anti-Cmab/N-GQDs/PANI/PS electrodes) were synthesized and evaluated as a potential platform for an electrochemical cortisol biosensor in sweat based systems. Polyaniline was utilized in order to provide electrical conductivity, while polystyrene served as a carrying polymer for mechanical support and its hydrophobicity. Composite fibermats were manufactured through Forcespinning™, followed by a secondary polyaniline graft …

A Decision Support System For Global Vaccine Funding: Data-Driven Proposal Scoring, Epidemiological Risk Modeling, And Portfolio Optimization, Ashutosh Kumar

Theses

Global health financing must continually stretch limited immunization resources across competing priorities, and Gavi, the Vaccine Alliance, plays a central role in this landscape. This work reframes Gavi’s funding decisions as a multi-objective portfolio optimization problem that jointly considers health impact, equity, cost-effectiveness, sustainability, and epidemiological interdependence. To operationalize this approach, this study develops a decision support system grounded in Modern Portfolio Theory, treating each proposal as an asset characterized by expected return and risk. Proposal returns are estimated through a heterogeneous data-fusion pipeline that generates quantitative, multi-objective scores aligned with Gavi’s strategic priorities, while epidemiological risk is quantified using …

Multidimensional Sorting: Comparative Statics, Joe Boerma, Andrea Ottolini, Aleh Tsyvinski

Cowles Foundation Discussion Papers

In sorting literature, comparative statics for multidimensional assignment models with general output functions and input distributions is an important open question. We provide a complete theory of comparative statics for technological change in general multidimensional assignment models. Our main result is that any technological change is uniquely decomposed into two distinct components. The first component (gradient) gives a characterization of changes in marginal earnings through a Poisson equation. The second component (divergence-free) gives a characterization of labor reallocation. For U.S. data, we quantify equilibrium responses in sorting and earnings with respect to cognitive skill-biased technological change.

Improving Data Quality In Survey Research: The Role Of Machine Learning In Handling Inconsistent Responses, Patrick Ndungutse

Information Systems and Quantitative Analysis Theses, Dissertations, and Student Creative Activity

This project aims to strengthen Gallup’s survey data preprocessing by integrating machine learning methods to detect inconsistent responses, complementing existing rule-based checks. The study benchmarks techniques such as Isolation Forest, clustering-based outlier scores, and autoencoders against current approaches to spot inconsistencies more efficiently and with reduced manual effort.

We will evaluate models using a dataset of survey responses previously flagged for inconsistency by Gallup, focusing on accuracy, coverage, and efficiency validated through expert review. The goal is to automate response classification into pass, review, or fail stages, aiming to reduce manual review time by about 25%, or 15 hours weekly, …

Exploring The Integration Of Social And Emotional Learning In Chinese High School Music Courses, Yao Lu

Dissertations

Social and emotional learning has become increasingly important in recent years, especially after the COVID-19 pandemic. The mental health and emotional well-being of students have received unprecedented attention. However, in China, social and emotional learning is still a relatively new concept. High school students are in a critical period for self-identification and the development of values. Academic competition and peer comparisons have increased significantly, making them more in need of systematic, operational SEL support. Music, as a “natural carrier” of emotions, can externalize, identify, and regulate individual emotions, and can also cultivate empathy and relationship skills in collaborative settings such …

Thermodynamic Evaluation Of The Thermal Methane Pyrolysis Process, Chinaecherem S. Okwuonu

Theses and Dissertations

Natural gas flaring is a persistent challenge which undermines global sustainability and decarbonization efforts as it leads to the waste of valuable energy resources alongside the release of harmful greenhouse gases into the environment. Even when natural gas is utilized through commonly adopted pathways, significant emission of carbon dioxide tends to be realized. Methane pyrolysis offers a promising route in which methane can be decomposed into solid carbon and hydrogen gas with no direct CO2 emissions. However, despite extensive studies of the methane pyrolysis process, a fundamental thermodynamic rationale of the process behavior remains insufficiently explored. This study 1) develops …

Employers’ Perceptions Of Workplace Readiness Skills, Tabitha S. Young, Natalie K. Ferand

Journal of Research in Technical Careers

Employability skills are continually changing, and the workforce provides the transparency needed for the success of business employment. Workplace readiness skills and human capital theory form the backbone for organizational success and sustainability. This study examined employers’ perceptions of workplace readiness skills at the expected proficiency level of an entry-level employee, the average level of skill for an entry-level employee, and the level of importance of the skill to their industry. The Virginia Workplace Readiness Skills have impacted employers and prepared students for the workplace. The results indicated that the workplace readiness skills mentioned in the literature align with the …

Reported Value Of Culturally Responsive Teaching Practices Of Virginia Agricultural Education Teachers, Natalie K. Ferand, Kendrick Spencer, Bradley Bowen

Journal of Research in Technical Careers

To address the increasing diversity in schools and the monolithic culture of teachers, researchers have called for pedagogies that reflect the diverse and pluralistic identities of students. While core academic areas have long adopted culturally relevant pedagogy, school-based agricultural education (SBAE) has lagged behind. This study aimed to determine the views of agricultural education teachers in Virginia on culturally responsive pedagogy dispositions and identify areas of professional development need. Teachers valued the differences among students and the communities in which their schools are located. However, results revealed a need for professional development in using the local community as a resource …

Online Experiential Learning In Career And Technical Education, Matthew Bornak

Journal of Research in Technical Careers

This scoping review investigates the integration of OEL into Career and Technical Education (CTE) programs. Using Arksey and O’Malley’s five-step scoping review framework, articles were identified through ERIC and Google Scholar and managed in Zotero. MAXQDA was used for coding, revealing thematic clusters related to modalities (synchronous, asynchronous, hybrid), technologies (LMS, AR/VR, simulation tools), and learner characteristics (nontraditional students, CTE-specific learning styles). The review highlights the conceptual anchors of Kolb’s Experiential Learning Theory, Carver et al.’s Experiential E-Learning Model, and Baasanjav’s online experiential design. Findings reveal that while OEL in CTE remains underexplored, it offers potential to increase accessibility, inclusivity, …

Extraction Of Cellulose From Paper Towels For Sustainable Bio-Based Polyurethane Adhesives, Yashkumar J. Patel

Electronic Theses & Dissertations

The increasing consumption of paper towels generates significant waste, necessitating sustainable recycling solutions. This study investigates the extraction of cellulose from waste paper towels and its application in bio-based polyurethane (PU) adhesives. The extraction process includes alkali treatment, bleaching, and acid hydrolysis to obtain recycled cellulose (rCL). The extracted cellulose is then used in PU synthesis alongside castor oil polyol (COP) and methylene diphenyl diisocyanate (MDI), with performance compared to industrial cellulose-based PU. The obtained rCL and synthesized PU adhesives have been characterized with FT-IR spectra for structural confirmation. In addition, the synthesized PU adhesives demonstrated improved mechanical and thermal …

Data-Driven Evaluation Of Sustainable Waste-To-Energy Pathways For Intelligent Urban Systems, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The handling of municipal solid waste (MSW) in swiftly urbanizing Philippine cities poses intricate energy and governance challenges. In Baguio City, reliance on landfills has reached critical levels due to diminishing capacity, rising transport costs, and opposition to trash transfers by nearby LGUs. Although shaped by unique topographical and governance constraints, Baguio’s situation reflects issues faced by other rapidly growing Philippine cities; therefore, analyzing it offers insights for national MSW decision-making. This study applies a triple bottom line (TBL) framework to assess three management scenarios: (1) Status Quo, where all MSW is landfilled with no energy recovery; (2) Landfill with …

Engineering Risk And Indigenous Resilience Toward Intelligent Decision Support For Mining In Ancestral Lands, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

Mining within ancestral territories reveals an ongoing conflict between technical viability and Indigenous consent. This collaborative study, conducted by an engineering scholar and a policy researcher of Indigenous heritage in Benguet among the Ibaloi and Kankanaey peoples, investigates how risk transparency and policy alignment can bridge existing divides, while formulating principles applicable to other Indigenous mining contexts. The study provides an initial evaluation of the feasibility of a proposed large-scale mining operation within a risk-informed, data-driven governance framework. Three elements of engineering risk were assessed utilizing literature-derived and proxy parameters: (1) Land degradation is indicated by a Soil Productivity Index …

Comprehensive Drought Analysis: Machine Learning-Based Meterological Drought Forecasting And Pca-Driven Agricultural Drought Monitoring., Bishal Poudel

Theses

Drought is a long-term natural disaster that affects many aspects of human life from health, water supply to ecosystems and agriculture. Drought’s occurrence and intensity has increased in recent years because of global warming, which urges for proper and accurate monitoring and forecasting of drought. For better understanding of droughts, this study uses two approaches. In first part, the study uses the historical temperature and precipitation data from period of 1960 to 2021 as input features for three different machine learning models – Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest (RF). The research focuses on calculating …

Prediction Of Geometric Deviation In Additively Manufactured Tpms Lattice Structures Using Non-Destructive Evaluation And Conditional Generative Adversarial Networks, Prateek Neupane

Theses

Metal 3D printing has emerged as a widely used additive manufacturing method, finding applications across numerous industries and research areas. However, its application is often hindered by geometric inaccuracies and surface quality issues resulting from the complex interplay of laser power, melt pool behavior, and cooling characteristics. These inconsistencies have a significant impact on the design and functionality of printed parts, affecting structural integrity and dimensional accuracy. Thus, an effective data-driven approach is crucial to predict these deviations before manufacturing. This study proposes a methodology that incorporates Non-destructive evaluation techniques, like in-situ monitoring and X-ray CT scan, with Conditional Generative …

Visionglow: Evaluating Minimal-Disruption Smart-Home Control In Apple Vision Pro, Hongxiao Zheng

Dartmouth College Master’s Theses

Smart-home control in mixed-reality environments like Apple Vision Pro often relies on disruptive, application-based paradigms, such as using a smartphone or a windowed virtual interface. These methods create a “mode switch” that imposes cognitive load and pulls users from their primary tasks. We present VisionGlow, a minimal-disruption spatial interaction technique for Vision Pro. VisionGlow represents devices as spatially-anchored “orbs.” To control a device, the user looks at its orb and performs a pinch gesture, which invokes a compact, contextual control panel. We conducted a within-subjects study (N=18) comparing VisionGlow against two baselines: the standard Apple Home app on a smartphone …

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Reinsuring Ai: Energy, Agriculture, Finance & Medicine As Precedents For Governance Of Frontier Artificial Intelligence, Nicholas Stetler

Southern Illinois University Law Journal

Federal reinsurance for advanced artificial intelligence offers a credible foundation for managing risk at scale. Traditional legal tools such as regulation, litigation, and voluntary guidelines, lack the institutional capacity to address deep uncertainty, widespread spillover effects, and low-probability but catastrophic harms. A public financial infrastructure distributes risk, incentivizes responsible development, and enables earlier detection of emerging threats. Precedent exists in nuclear energy, agriculture, healthcare, and finance, where federal reinsurance enabled markets to function despite underlying volatility. The same institutional logic applies to frontier AI.

Part I explains how general-purpose and frontier AI models work, and why they have become a …

Proverag: Provenance-Driven Vulnerability Analysis With Automated Retrieval-Augmented Llms, Reza Fayyazi, Stella Hoyos Trueba, Michael Zuzak, Jay Yang

Institute for Informatics and Applied Technology Scholarship

In cybersecurity, security analysts constantly face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 vulnerabilities identified since 1999. The sheer volume of known vulnerabilities complicates the detection of patterns for unknown threats. While LLMs can assist, they often hallucinate and lack alignment with recent threats. Over 40,000 vulnerabilities have been identified in 2024 alone, which are introduced after most popular LLMs’ (e.g., GPT-5) training data cutoff. This raises a major challenge of leveraging LLMs in cybersecurity, where accuracy and up-to-date information are paramount. Therefore, we aim to improve the adaptation of LLMs in vulnerability analysis by …

2025 Fall Commencement, Tennessee State University

TSU Commencements 2025-Present – Mr. Dwayne Tucker, President

No abstract provided.

Position Sensor Offset Fault Calibration In Speed-Regulated Pmsm Drives, Ujala Anuradhi Maha Gamage

Masters Theses

Speed regulation of electro-mechanically actuated systems is common across broad application segments, including industrial and residential sectors. The increasing demand for efficient energy conversion has made permanent magnet synchronous machines (PMSM) a preferred choice in modern applications. Vector controlled PMSMs in speed regulation mode being the dominant form of control, accurate speed and position measurement is crucial. However, a misalignment in the position sensor with respect to the true rotor zero position in speed regulated PMSM drives leads to inefficient energy conversion with the possibility of unstable motor behavior. The considered position sensor offset error fault, under severe fault modes, …

Vaping Insights Perceptions And Experiences On A College Campus, Willard G. Jackson

Masters Theses and Doctoral Dissertations

The purpose of this study was to determine if relationships existed between student vaping habits in proximity to a college campus and current tobacco related bans implemented by the institution. Determining these relationships provided insights that can be utilized to maximize effectiveness of campus tobacco policy. Research outcomes represented a framework for educating current and potential tobacco consumers on campus regarding harm reduction, tobacco cessation, and resources available to prevent a lifetime of nicotine addiction or other tobacco related harm to health. The study addressed research questions in a mixed-methods design. Quantitative research questions included: Does a relationship exist between …

A Comparative Analysis Of Statistical And Machine Learning Models With Application In Ai-Powered Stroke Risk Prediction, Megan Mccoy

Masters Theses and Doctoral Dissertations

Rapid detection of large vessel occlusion (LVO) is critical due to its high mortality and narrow treatment window. Although machine learning (ML) and deep learning tools show promise for LVO prediction, their clinical use is hindered by inconsistent pre-hospital data, variable LVO rates, limited interpretability, and high costs. This study introduces a hybrid neural network (HNN) that integrates classical statistical learning with neural networks to combine interpretability and structure with flexibility and regularization. The model was validated through simulations using NIHSS scores, demographics, and medical history across diverse sample sizes and LVO prevalence rates, and benchmarked against logistic regression, Naive …

The Application Of Evidence-Based Practices In Diverse Environments, Emily R. Simon

Undergraduate Honors Thesis Collection

Much research supports the argument that students and educators perform better when evidence-based practices are used in the classroom. However, applying these practices across diverse environments can be a challenge. Each class and school is unique, and these differences affect the transferability of these methods in the classroom. This thesis examines how research-based methods on relationship building and instructional practices are implemented and/or modified across different school settings: suburban, urban, special education, general education, and multicultural/multilingual spaces.

Through research on current educational practices, this thesis identifies commonly used evidence-based practices for building relationships between teachers, students, and families, as well …

Bridging The Gap Between Network Science And Network Systems To Identify And Mitigate Cyber Risk: Identify And Mitigate Backdoor Attacks On Graph Neural Networks And On Complex Systems, Sabah Ettahri

Electrical & Computer Engineering Projects for D. Eng. Degree

This doctoral project aims to bridge the gap between graph theory and network science to identify and mitigate cyber risk, represented as a CY-Triangular Network that connects different networks. The CY-Triangular Framework is a cybersecurity system that integrates graph theory and network science through an interoperable learning approach. The objective of this project is to bridge the gap between two domains: network science and network systems. Accordingly, it examines one representative network from each field, focuses on a complex system network, and explores Graph Neural Networks (GNNs). The connection between these domains lies in graph theory. This research demonstrates that …

Greenhouse Gas Accounting For Western Australian Agriculture 2023, Johnny Machon, Christophe D'Abbadie

Climate Science Published Reports

This report presents new modelling of the greenhouse gas emissions attributable to Western Australia’s agricultural industries and provides an overview of sequestration at the state level. The report updates the estimates from previous technical reports by the Department of Primary Industries and Regional Development (DPIRD). It presents not only emissions from agricultural activities in Western Australia (WA) but also from the production of agricultural inputs and energy use. This broader picture of emissions aligns with frameworks for emissions reporting at the business and product level.

Total on-farm and pre-farm emissions are estimated to have been about 12.6–13.3 million tonnes of …

Flux Crystal Growth Of A Series Of Calcium Rare Earth Silicate Chlorides Calnsio4Cl (Ln = Pr, Nd, Sm, Eu, Gd, And Tb): Mixed Anion Materials With A Spodiosite-Type Structure, Maria Goncalves, Mark D. Smith, Hans Conrad Zur Loye

Faculty Publications

A series of calcium rare earth silicate chlorides, CaLnSiO4Cl (Ln = Pr, Nd, Sm, Eu, Gd, and Tb), was obtained as single crystals from flux crystal growth. The structures were determined by single crystal X-ray diffraction and were found to be related to the spodiosite/Wagnerite mineral structure, Ca2PO4F. The obtained compositions are variations of the spodiosite structure that result from two simultaneous elemental substitutions. Replacing one calcium for one rare earth element and the simultaneous replacement of one VO4³⁻ or PO4³⁻ with one SiO4⁴⁻. CaEuSiO4Cl was found to luminesce, and its photoluminescence spectrum is reported.

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Faculty Publications

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …