Digital Commons Network^™

Understanding Host Behaviour And Property Review Characteristics Using New York City Airbnb Dataset, Anna Szkwara

ICT

This project applies strategic thinking and the CRISP-DM methodology to analyse Airbnb listings in New York City and identify patterns associated with host performance and market vulnerability. Airbnb has become a major global accommodation platform, creating opportunities for individual hosts while also increasing competition within the short-term rental market. The project focuses on whether data-driven analysis can identify factors that may influence host success and provide useful insights for hosts with less experience or expertise than larger hospitality organisations. The dataset contains 85 variables, many of which require careful evaluation due to redundancy, high cardinality, sensitivity, or limited relevance to …

Predicting Product Returns In Online Retail, Mihaela Cristina Stefanache

ICT

Product returns are a significant challenge for online retailers, contributing to additional operational costs and affecting inventory management and profitability. This project develops and evaluates three machine learning models to predict product returns for a UK online retailer, building on the data understanding and preparation completed in the previous CA2 capstone project. Following the CRISP-DM framework, the study extends the analysis through enhanced exploratory data analysis, feature engineering, model development, hyperparameter optimisation, cross-validation, and model interpretability. Logistic Regression, a Tuned Random Forest, and XGBoost are evaluated, with the Tuned Random Forest achieving the strongest overall performance, obtaining an F1 score …

Development Of Stronger, More Extrudable 6xxx Series Alloys For Automotive Applications, Eli A. Harma

Dissertations, Master's Theses and Master's Reports

6xxx alloys are widely used in automotive extrusion structures for their high specific strength and formability. Advanced designs require greater formability and strength, creating an opportunity for high-strength, formable alloys. The 6xxx series forms β”-Mg₅Si₆ precipitates during age hardening and develops a fibrous microstructure during extrusion, both strengthening the alloy. Increasing Mg and Si to form more β” decreases formability. Thus, modifying texture can increase strength without reducing formability. Current alloys like 6005A add Mn and Cr to form dispersoids that inhibit recrystallization and promote strengthening textures; however, high Mn and Cr concentrations reduce formability. Replacing Mn …

Aqueous Iron Electrowinning: From Electrolyte Engineering To The Unexplored Potential Of Acetate Systems, Chodwell N. Verenga

Dissertations, Master's Theses and Master's Reports

Iron electrowinning and electrodeposition sit at the intersection of classical metallurgy and developing sustainable manufacturing. With the iron and steel industry responsible for 7 - 9% of global CO₂ emissions, low-temperature electrochemical pathways for iron production have garnered significant research interest. This review examines the fundamental electrochemical principles governing iron deposition, the thermodynamic constraints imposed by the iron-water system, and the kinetic challenges posed by the parasitic hydrogen evolution reaction (HER). The three key electrolyte systems are objectively evaluated: acidic sulfate and chloride electrolytes, alkaline suspension electrolytes and water-in-salt electrolytes. Their operating parameters, faradaic efficiencies, energy consumption and deposit characteristics …

First-Principles And Thermodynamic Modeling Of Hydrogen Storage In Mxenes, Yi Zhi Chu

Dissertations, Master's Theses and Master's Reports

Hydrogen storage is a critical component of the emerging hydrogen economy, playing a central role in enabling the global transition from fossil fuels to a sustainable, green energy system. With advances in materials research, increasing attention has been directed toward the development of promising hydrogen storage materials. Due to their diverse and advantageous physicochemical properties, MXenes have attracted significant interest in this regard. A fundamental understanding of the hydrogen interactions with the MXenes structure is crucial for explaining and predicting their hydrogen storage performance. In this work, first-principles density functional theory (DFT) combined with a revised thermodynamic model is employed …

Designing With Foresight: Premortem And Human-Centered Evaluation Of Emerging Technologies, Anusha Kannan

Dissertations, Master's Theses and Master's Reports

Artificial intelligence is increasingly embedded in safety-critical systems, including transportation, where people must make fast decisions under uncertainty and high risk. As AI takes on a larger role in supporting human judgment, researchers and designers must evaluate more than just its technical performance, they must ask whether people can understand the system and use it effectively in high-risk settings.

This dissertation presents two distinct evaluation methodologies. First, the Human-Centered Evaluation, examines how intelligent in-vehicle alert systems influence driver decision behavior across two experiments. In Experiment 1 (n=24) and Experiment 2 (n=26), participants completed a driving simulator study in which our …

Experimental Rate Feedback Control Of A Model-Scale Hourglass-Shaped Heaving Point Absorber, James R. Halverson

Dissertations, Master's Theses and Master's Reports

Buoy geometry greatly affects a point absorber wave energy converter's dynamic response to waves. Finding the optimal buoy shape and control method remains an open research area focused on maximizing the conversion of wave kinetic energy into electricity. This work presents an experimental comparison of closed-loop energy extraction between a cylindrical and a truncated cone buoy, both with the same submerged volume, across various wave frequencies and amplitudes. To ensure a fair comparison, the optimal rate feedback gain is calculated for each buoy at each wave condition. Multiple metrics, including power output, capture width, and actuator force, are used to …

Numerical And Experimental Evaluation Of A Simple, Low-Energy Lunar Volatile Separation Technology, Eleanor L. Zimmermann

Dissertations, Master's Theses and Master's Reports

In-situ resource utilization (ISRU) is the practice of finding, extracting, and using the local resources found on extraterrestrial bodies, such as the Moon and Mars. ISRU enables in-situ production of mission consumables—such as rocket fuel and potable water—which will be critical for establishing a sustainable human presence on the Moon, a goal NASA intends to accomplish by 2028 with the Artemis missions. The separation and liquefaction of locally extracted volatiles—such as water, CO₂, and Methane—is an essential component in lunar surface sustainability, but there are very few technologies being developed for this purpose. This report introduces the Radiative …

Spatiotemporal Patterns Of Migratory Songbird Habitat Use: An Analysis Of Environmental Drivers At The Net Level, Garrett Kucharski

Dissertations, Master's Theses and Master's Reports

Many eastern North American migratory songbirds are declining at alarming rates, and growing evidence suggests that events occurring away from the breeding grounds, particularly during migration, can be major drivers of these trends. Stopover sites are a key component of migration because they are where birds rest, refuel, and recover before continuing long-distance movements, yet the ecological factors that shape how broadly different species use stopover habitat remain unresolved. From both an applied perspective, identifying habitat attributes associated with use by the greatest diversity of migrants will help land managers prioritize and restore stopover sites, actions that may contribute to …

Nondestructive Evaluation Of Additively Manufactured Parts Using Resonant Inspection And Frequency Domain-Based Correlation Criteria, Gita Deonarain

Dissertations, Master's Theses and Master's Reports

Additive manufacturing (AM) enables the production of highly customized and geometrically complex components; however, these parts remain susceptible to a wide range of defect types and severities. The combination of complex geometries and distributed defects presents a significant challenge for post-process nondestructive evaluation (NDE). Conventional inspection techniques, such as computed tomography and ultrasonic testing, are often limited by geometry, material, accessibility, and cost, while in situ monitoring is not yet sufficiently mature to replace post-process inspection.

This dissertation establishes the Frequency Domain Assurance Criterion (FDAC) as a quantitative, vibration-based framework for defect detection in AM components. FDAC captures spatial–spectral correlations …

Reconciling Discretion With The Rule Of Law: A Rawlsian Analysis Of Civil Disobedience By State Actors In Liberal-Democratic Schemes, Reid Devoge

Dissertations, Master's Theses and Master's Reports

This dissertation starts from the position that the stability of liberal-democratic political schemes relies on its citizens mutually accepting a basic conception of political justice. While these conceptions of justice may vary, most incorporate the inter-connected concepts of autonomy, liberty, liberalism, and the rule of law. Within this conception of a liberal democracy, a potentially destabilizing issue arises when a legislatively passed law is put into effect, but a portion of the citizens perceive it as unjust. If legitimate (i.e., lawful) actions do not sufficiently resolve the concern, civil disobedience (i.e., disobeying the law) is a potential recourse, but this …

The Excess Path Length Distribution: A Stochastic Model For Sample-Based Path Planners, Chaz B. Cornwall

Dissertations, Master's Theses and Master's Reports

Through random sampling, sample-based path planners enable autonomous agents to quickly find paths without human intervention. However, due to the paths' randomness, sample-based path planners currently require additional verification, partially nullifying agents' ability to act autonomously. I set out to characterize this uncertainty so humans know what to expect from these path planners and know how to alter the path planner to desired specifications. To ensure the results are theoretical as well as practical, I first create a stochastic model of path length uncertainty using the trade-off between sampling time and optimality. By leveraging this model, my proposed algorithm reduces …

Shm For Incipient Buckling Detection In Overloaded Structures Using Nonlinear System Identification Algorithms On Redundant Data Sets, Padmanabh Shridhar Desai

Dissertations, Master's Theses and Master's Reports

Structural health monitoring (SHM) detects and characterizes damage to predict failure, but failures such as buckling, which are not predicated on traditional damage modalities, are harder to detect. Direct load measurements are costly and difficult to implement (especially for dead loads) as they require copious numbers of sensors, which must be installed before loading is present. Vibration-based detection is a good alternative because it can infer global structural characteristics with relatively few sensors. This dissertation presents an SHM approach for detecting incipient buckling in structures under excessive loads based on non-linear models fit from measurements of small lateral vibrations due …

Mechanical Fractionation Of Wheat Middlings For Application In Pyrolysis And Animal Feed, Okwudili I. Obiakor

Dissertations, Master's Theses and Master's Reports

Wheat middlings are grain byproducts that are underused for bioenergy production despite having a high lignocellulose content. Its use as a feedstock for catalytic pyrolysis depends on effective and sustainable fractionation to enhance efficiency and product yield. This study tested mechanical pre-fractionation (sieving and air classification) to reduce ash content of certain fractions to < 1% for catalytic pyrolysis and enrich nutrient levels of other fractions for feed applications. Wheat middlings were separated into 11 fractions using screen sizes from 106 µm to 1651 µm, and the composition of each fraction was characterized (ash, protein, structural carbohydrates, lignin, starch, and simple sugars). For cyclone separation, a full factorial design was used to study the effect of air velocity (15,18, 20 m/s) and feed rate (33, 35, 38 kg/h) on the amount of material collected in the underflow and overflow, and the composition of these fractions was characterized. Sieving showed a pronounced segregation of ash content, from 4.5% to 6.5% in wheat middlings fractions, with 5.7% being the lowest for coarse fractions which has higher lignocellulose content, and 4.5% in the fine fraction (150-212 µm). The same defined enrichment was observed in all nutrients except for protein. Starch enrichment zone were defined in the fine fractions (212 µm and below), for structural carbohydrates and lignin in the coarse fractions (600 µm and above), and for ash in coarse fractions (1180-1651 µm). In contrast, protein content was not significantly different between various fractions (p value=0.787). The fiber rich fraction (> 600 µm), suitable for pyrolysis, which have a composite ash value of 6.0% can be sorted and mixed with intermediate fractions to reduce ash to 5.3% and the remaining fractions rich in digestible nutrients used for animal feed formulation. Compared to sieving, cyclone separations did not …

Digital Technology And Women’S Health In Nigeria: A Feminist Sts Walkthrough Analysis Of Mdoc Digital Health, Edith Michael Ogbodo

Dissertations, Master's Theses and Master's Reports

This thesis critically examines how a Nigerian digital health platform, mDoc, represents and constructs women’s health. Drawing on Feminist Science and Technology Studies (STS) and Light et al.’s (2018) walkthrough method, the study interrogates the values, assumptions, and power relations embedded in mDoc’s design, language, and governance structures. The analysis reveals that mDoc, despite positioning itself as an equitable solution to Nigeria’s health crisis, reproduces and depoliticizes the structural inequalities it claims to address. Through its neoliberal emphasis on self-care, the individualization of structurally produced suffering, and the datafication of women’s bodies, the platform encodes gendered, colonial, and class-based assumptions …

Fluctuation Of Organochlorine Concentrations In Bull Sharks At Different Life Stages, Mackenzie R. Phillips

Dissertations, Master's Theses and Master's Reports

For Carcharhinid species such as the bull shark (Carcharhinus leucas), the maternal offloading of nutrients is essential for pup development and growth, however, significant amounts of OCs are also transferred. As a top predator in aquatic food webs, bull sharks can potentially bioaccumulate high concentrations of pollutants such as dichloro-diphenyl-trichloroethane (DDT) that biomagnify through aquatic food webs. These pollutants are also hydrophobic and fat soluble and therefore pose toxicity risks to developing young bull sharks. In this study, liver tissues collected from juvenile bull sharks inhabiting Florida’s coastal waters were analyzed for a suite of organochlorine pesticides (OCs) …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Changing Snow Hydrology In The Great Lakes And Resilience Through Adaptive Management, Aradea R. Hakim

Dissertations, Master's Theses and Master's Reports

A number of studies have found that global snow cover is generally decreasing, but a closer examination at regional scales shows greater complexity. In the Great Lakes basin, contrasting trends have been identified. While snow cover is generally decreasing basinwide, leeward (downwind) regions have experienced increases in snowfall and snow cover. Changes in snow dynamics are also associated with shifts in runoff timing and volume due to earlier snowmelt and changing precipitation patterns. Streamflow analyses at gauges across the Great Lakes basin indicate trends toward earlier peak runoff and longer runoff periods, although these patterns vary among watersheds and lake …

Path-Conservative Numerical Methods For A Variable-Radius One-Dimensional Arterial-Flow Model, Daniel Henderson

Dissertations, Master's Theses and Master's Reports

This report studies a one-dimensional arterial-flow model with a variable reference radius, the two-component state $U=(a,q)^{\mathsf T}$, and diagnostic pressure. The geometry-dependent momentum term is interpreted with a declared Dal Maso--LeFloch--Murat path along a straight line. A path-conservative finite-volume method (FVM) and a complete modal discontinuous Galerkin (DG) method use the three-stage, third-order strong-stability-preserving Runge--Kutta (SSPRK) scheme SSPRK(3,3), residual-subtracted rest preservation, overintegrated nonlinear volume terms, and mean-preserving area positivity scaling. Code verification uses manufactured solutions with separate dimensionless area and flow errors, temporal refinement, represented-rest fixed-point checks, independent governing-expression evaluations, and an independently assembled DG residual. The smooth degree-three (P3) …

Machine Learning And Multi-Scale Optimization For Control And Energy Management In Connected And Automated Vehicle Propulsion Systems, Joshua D. Orlando

Dissertations, Master's Theses and Master's Reports

This dissertation presents a multi-scale optimization framework leveraging machine learning (ML) to enhance energy efficiency in connected and automated vehicle (CAV) propulsion systems. As transportation transitions toward hybridization and automation, the integration of vehicle-to-everything (V2X) connectivity and advanced control algorithms offers unprecedented opportunities for energy reduction. This research addresses three critical scales of vehicle energy management: multiple vehicle-level coordination, component-level powertrain dynamics, and real-time vehicle parameter estimation.

First, the research investigates the energy consumption characteristics of heterogeneous propulsion systems—ranging from internal combustion engines to battery electric vehicles across light- and heavy-duty sectors—on arterial roadways. Utilizing Particle Swarm Optimization (PSO) and …

Application Of Reactive Power Theory To Wave Energy Converters Under Multi-Frequency Excitation: Analysis And Experimentation, Mckenna R. Collins

Dissertations, Master's Theses and Master's Reports

There is abundant energy surging in the oceans across the globe. However, there have been technological challenges in extracting that energy for use. Wave energy converter (WEC) technology is being developed to find innovative ways to convert wave kinetic energy into electricity, but there are still efficiency obstacles that inhibit large-scale use. Focusing on heave-point absorber control theory, this thesis continues the work to improve the efficiency of WECs. This is done by leveraging a superposition of linear mass-spring-damper models to analyze a WEC under multi-frequency excitation and applying proportional-derivative gains to each linear model. However, to analyze this system, …

Reading Between The Lines: Protected, But Not From Interpretation, Hooriya Habib

Dissertations, Master's Theses and Master's Reports

In the realm of television, audiences are interactive viewers who decode meaning based on their lived experiences. Given that each culture has its own set of cultural codes it uses as a lens to navigate life, meanings do not remain constant. This cultural media study breaks down three advertisements to study the effectiveness of these advertisements in relation to religious and cultural codes. Using Stuart Hall’s (1980) encoding/decoding model, an oppositional reading was employed to understand the disconnect that may be caused between an audience of rural Pakistani women and the producers. Objects of focus were nonverbal codes such as …

Open Source Tools For Ecological Research, Alex P. Riebe

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of an open source wireless sensor network for hibernacula manipulation with an emphasis on accessibility and reproducibility. It addresses the design of the electrical hardware, guidance on antennas and RF implementation, and design of an application-specific communication protocol, all with the explicit goal of enabling ecologists and other conservationists to be able to manufacture, deploy, operate, and maintain the system for their research. The resulting sensor network designed in this thesis is to control the temperature inside bat hibernacula during the winter to study the relationship between temperature and bat mortality rate due to White …

Design And Experimental Evaluation Of A Custom Vision-Guided Approach To 2d Part Localization For Industrial Robots, Faisal Ali

Dissertations, Master's Theses and Master's Reports

Vision-guided robots offer a clear advantage over teach-pendant programming for battery handling, where modern packs hold thousands of cells and teaching each position by hand does not scale. Commercial vision systems address this need, but their calibration, detection, and coordinate-conversion stages are closed to the user, making it hard to incorporate newer learning-based methods. This work presents a modular, custom-built vision-guided system using an Orbbec Gemini 435Le eye-in-hand camera, an NVIDIA Jetson Orin Nano, an Allen-Bradley Micro850 PLC, and a FANUC LR Mate 200iC, communicating over Modbus TCP and EtherNet/IP. A per-hole classification model resolves each known hole into a …

Design And Validation Of A Low-Cost Wearable Electromyography (Emg) System For Monitoring Exercise-Induced Changes In Muscle Activity, Ingrid E. Halverson

Dissertations, Master's Theses and Master's Reports

Wearable technologies have expanded opportunities for monitoring athletic performance, but many existing systems remain costly and confined to laboratory or medical settings. This thesis presents the design, development, and evaluation of a low-cost, wearable EMG platform for monitoring neuromuscular activity during exercise. A wireless device incorporating a surface EMG sensor, an ESP32 microcontroller, and Wi-Fi transmission was developed to acquire muscle activation data. Signal processing techniques, including filtering, root-mean-square (RMS), mean frequency (MNF), and median frequency (MDF) analyses, were used to evaluate changes in muscle activation. Experimental testing demonstrated reliable wireless data acquisition and successful capture of physiological changes before …

Bayesian Analysis Of Nominal Outcomes With Missing Values Using Multinomial And Multivariate Multinomial Probit Models, Suwash Silwal

Dissertations, Master's Theses and Master's Reports

Nominal outcomes frequently arise in health sciences, transportation, economics, market research, and related fields. These data often contain missing values, while longitudinal and panel studies generate multiple correlated nominal responses. Bayesian estimation of multinomial probit (MNP) and multivariate multinomial probit (MMNP) models provides a flexible framework for analyzing such data but remains computationally challenging due to high-dimensional likelihood integration, restrictive covariance identification constraints, and poor mixing of Markov chain Monte Carlo (MCMC) algorithms, particularly in the presence of missing data. This dissertation develops parameter-expanded data augmentation (PX-DA) methods for MNP and MMNP models with missing nominal outcomes by incorporating parameter …

High-Performance Circuit Manufacturing And Testing Exercises, Benjamin S. Keppers

Dissertations, Master's Theses and Master's Reports

An advanced demonstrator Printed Circuit Board (PCB) has been designed and implemented providing a framework for advancing students’ knowledge in hands-on PCB design and manufacturing process through industry recognized test coupons, stack ups, and transmission lines. Students are guided through several key aspects of design and simulation relating to manufacturing and qualifications. Manufacturing allows students to refine process development and analyze performance data with respect to qualification tests specified by Global Electronics Association standards. Results are then used to build a stackup model, and complete a design activity for calculating expected test results for a series of controlled impedance electrical …

Robust State Estimation And Scene Understanding For Autonomous Ground Vehicles In Challenging Environments, Nader J. Abu-Alrub

Dissertations, Master's Theses and Master's Reports

Autonomous ground vehicles require reliable state estimation and scene understanding to operate safely in challenging environments. Poor illumination, adverse weather, degraded visibility, snow-covered roads, and sensor noise can reduce the reliability of conventional localization and perception pipelines. Addressing these challenges requires sensing and algorithmic strategies that exploit the complementary strengths of different modalities. Radar is particularly attractive because of its resilience to lighting and weather variations, while inertial, camera, and lidar measurements provide additional motion, appearance, and geometric information. This dissertation investigates compact radar-based and sensor-fusion approaches for improving autonomous ground-vehicle state estimation and scene understanding under degraded sensing conditions. …

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Spatial skills are vital in many STEM disciplines, starting at or prior to university training, and often extending throughout one’s career. The most widely used spatial ability measures (e.g., PSVT: R, MRT) rely on what I refer to as receptive skills: examining an object or design, mentally transforming it, and comparing it to given alternatives. But because work in many STEM disciplines also involves productive spatial skill such as drawing, I hypothesize that a productive measure of spatial skill may predict distinct aspects of spatial ability. This research investigates the relationship between traditional receptive Spatial Visualization (SV) assessments, such as …

Identifying Controls On The Biodegradation Of Dissolved Organic Matter To Inform Microbial Fuel Cell Applications, Lily N. O'Hagan

Dissertations, Master's Theses and Master's Reports

Microbial fuel cells (MFCs) harness dissolved organic matter (DOM) biodegradation to generate power. To evaluate effects of DOM source, nutrients (nitrate and phosphate), and oxygen on DOM biodegradation, we conducted 4-day DOM biodegradation experiments with water and sediments from the Chesapeake Bay. Compared to soil-derived DOM, algal-derived DOM composition changed more and nearly doubled carbon dioxide (CO₂) production, peak CO₂ rates, and carbon removal, indicating MFC site selection should target regions with algal-rich DOM. Aerobic conditions increased CO₂ production by ca. 16%, doubled peak CO₂ rates, and reached peak rates 1 hour faster than anaerobic …