Digital Commons Network^™

Body Mass Index Has No Impact On Complications And Mortality For Patients With Stage Iv Pancreatic Ductal Adenocarcinoma, Ren Bryant, Hannah Darnell, Megan Hall, Kelsey N. Karnik, Kristen J. Mcquerry, Ruben R. Plentz

Biostatistics Faculty Publications

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of United States (USA) cancer death. Overweight and obesity developing into a growing global medical and socio-economic problem, affecting approximately 42% of adults in the USA population. The aim of our analysis was to evaluate the influence of overweight and obesity on complications and clinical outcome in patients with stage IV PDAC.

Methods: We retrospectively reviewed electronic health records of patients diagnosed with stage IV PDAC (n=162) who followed with the University of Kentucky from January 2017–October 2024. Comparisons were based on the body mass index (BMI): low BMI …

The Multidimensional Impacts Of Poverty On Adolescent Outcomes, Klarence Baker

Graduate Research Papers

Poverty is a pervasive, multidimensional phenomenon that extends beyond financial scarcity to encompass a lack of both tangible and intangible resources necessary for healthy development. This research article synthesizes current literature to explore the profound impacts of poverty on adolescents specifically examining how economic hardship influences long term outcomes in financial attainment, educational success, and physical and mental health. This study investigates how cooccurring risk factors can disrupt neural development and social trajectories. The primary purpose of this study is to assess the duration and severity of poverty exposure and its lasting effects extending into adulthood. This research examines three …

Digital Lover: Insecure Attachment Styles And Romantic Parasocial Relationship Among Chinese Female Otome Game Playersdigital Lover: Insecure Attachement Styles And Romantic Parasocial Relationship Among Chinese Female Otome Game Players, Weifan (Kyrie) Zhang M.S.

Selected Full Text Dissertations, 2011-

The existing literature has explored the relationship between insecure attachment styles and parasocial relationships, particularly focusing on traditional media such as television. However, it has largely overlooked the novel form of media represented by contemporary Chinese otome games, which offer an idealized digital environment potentially more appealing to players with insecure attachment styles. Moreover, previous studies have not sufficiently differentiated between general parasocial interactions and the specific nuances of parasocial romantic relationships unique to romantic video games (RVGs). This study seeks to bridge these gaps by examining the psychological underpinnings of Chinese female players' engagement with female-oriented romantic video games. …

Skin Type Diversity In Image Datasets, Neda Alipour

Doctoral

Image-based AI systems that analyse human skin are increasingly used in healthcare and computer vision applications. However, many human skin-based image datasets do not provide reliable information about skin type, making it difficult to assess whether these systems perform consistently across the full spectrum of skin colour. The objective of this thesis is to examine how skin type diversity is represented and measured in image datasets, and to evaluate the reliability of image-based skin type measurement methods under different imaging conditions. Using publicly available skin lesion image datasets as a well-defined and widely used sub-class of skin image datasets, this …

Selling Ideals: Sexualization In Teen Girl Magazines, 2007-2017, Megan Coogan

Honors Theses - Providence Campus

Magazines are made to sell more than just a product; they sell lifestyles and ideals. Teen girl magazines target adolescents starting as young as twelve years old, but is the content in its pages appropriate and identifiable for that demographic? This study investigated how levels of perceived sexualization changed between 2007, 2012, and 2017, in Seventeen and Teen Vogue magazines. A decrease in perceived sexualization was expected across the ten-year period of time. This window of time reflects the last ten years of publication for both magazines. Research was conducted by creating and utilizing a grading system for non-explicit sexualized …

The Lived Experience Of Intimate Partner Violence For Females In Emerging Adulthood: A Qualitative Study, Laurel Dobkin M.S.

Selected Full Text Dissertations, 2011-

Emerging adulthood is the developmental period between ages 18 to 25 where individuals begin to explore their worldviews and develop intimate relationships. This period is important for developing a sense of identity and self (Arnett, 2000, 2014). During this period, negative events or relationships, such as intimate partner violence (IPV), may have detrimental effects (Erikson, 1968; Barreto & Frazier, 2012). While literature suggests that IPV has high rates and negative consequences in emerging adulthood (Bhattacharjee & Gopal, 2022; Centers for Disease Control and Prevention [CDC], 2024; Shen & Kusunoki, 2019), there is little research on the subjective experience of females …

Flood Risk Prediction System For Irish River Networks, Fernando Adalberto Naatz Heringer, Hugo Rodrigues De Freitas

ICT

Flooding costs the Irish economy more than 300 million euros annually; however, the hydrometric and meteorological data needed to predict dangerous river rises is already collected and freely available. This project applies machine learning to a decade of hourly observations from OPW Station 09001 on the River Liffey at Leixlip and Met Eireann Casement Aerodrome to build a flood risk prediction system with a 72-hour forecast horizon.

A two-phase modelling pipeline was built following the CRISP-DM framework. Phase 1 compared LSTM and GRU recurrent neural networks on the task of forecasting the river level in metres 72 hours ahead. LSTM …

Machine Learning System For Cereal Yield Prediction In South America., Victor Gabriel Oliveira, Kelvin Henrique Ferreira Dumas

ICT

This project developed a machine learning solution to predict cereal yield in South America using FAOSTAT agricultural data. The objective was to estimate yield in kg/ha for rice, maize, and wheat based on variables such as country, crop type, year, harvested area, producer price, pesticide use, and nutrient indicators.

The project followed the CRISP-DM methodology, covering business understanding, data understanding, data preparation, modelling, evaluation, and deployment. Several regression models were tested, including Random Forest, Gradient Boosting, AdaBoost, XGBoost, KNN, and SVR.

The models were evaluated using MAE, MSE, RMSE, and R² score. The results showed that tree-based ensemble models performed …

A Comparative Analysis Of Supervised Machine Learning Techniques For Predicting It Incident Resolution Time, Ammad Hussain, Hussnain Yaqoob

ICT

IT support teams are facing the persistent challenge in estimating how long an incident will take to resolve. The lack of reliable predictions, planning decisions around staffing, escalation and user communication are largely guesswork. This project set out to address that gap by building a machine learning solution capable of predicting incident resolution time from details available at the point a ticket is logged.

Using the UCI IT Incident Event Log dataset, which contains 141,712 records from a real service management system, the project followed the CRISP-DM framework across six phases from business understanding through to deployment. After thorough data …

A Comprehensive Study Of Sarima And Xgboost Models For Short-Term Traffic Volume Forecasting At A Melbourne Intersection (Victoria), Australia, Douglas Vinicius Dierings, Felipe Fontanive Marques

ICT

Traffic congestion is an increasing challenge in modern cities, impacting transportation efficiency and urban sustainability. This project focuses on short-term traffic volume forecasting, using 15-minute Sydney Coordinated Adaptive Traffic System (SCATS) data collected from the State of Victoria, Australia. The study compares two forecasting approaches: SARIMA, a statistical time-series model, and XGBoost, a decision-tree machine-learning model. Historical traffic data from 2022 to 2024 was analysed to identify traffic patterns, seasonal trends, and peak traffic periods. The models were evaluated for their effectiveness in handling urban traffic behaviour. The results of this study aim to support smarter traffic management, infrastructure planning, …

Identifying New Programme Development Viability, Grant Goodwin

ICT

Higher Education Institutions (HEIs) face the challenge of developing programmes that respond to changing labour market needs while providing graduates with relevant employment opportunities and ensuring institutional financial viability. Rapid technological and economic changes make it increasingly important for HEIs to use reliable data to identify emerging skills and workforce demands. This project explores the use of machine learning and nationally collected employment data to support evidence-based decision-making in higher education programme development. By analysing patterns and relationships within labour market data, machine learning models can help identify areas of growing demand and provide insights into the potential alignment between …

Seasonal Dublin Airport Passenger Arrivals Forecast For The Economy Sector Of Dublin Airport, Roberto Tavares De Oliveira Neto

ICT

Dublin Airport plays a significant role in Ireland’s tourism and commercial sectors, with passenger demand directly influencing retail, hospitality, car rental and other airport-related businesses. Accurate forecasting of passenger numbers can support these sectors in planning marketing activities, managing stock levels and making evidence-based operational decisions. This project develops a monthly forecasting framework for passenger arrivals at Dublin Airport using data from the Central Statistics Office (CSO). Building on previous exploratory data analysis, the study evaluates five time series forecasting approaches: ARIMA, SARIMA, Holt-Winters Triple Exponential Smoothing, TBATS, and an automated model comparison pipeline using PyCaret. The models are assessed …

Machine Learning For Early Obesity Risk Prediction, Giuseppe Cutugno

ICT

Obesity is a major global public health concern, with significant implications for individual health, healthcare systems, and wider economic outcomes. Early identification of obesity risk can support preventive strategies and encourage healthier lifestyle choices before health conditions become more severe. This project develops a machine learning framework for estimating obesity levels using data relating to individuals’ physical characteristics, eating habits, lifestyle behaviours, and demographic factors. Following the CRISP-DM framework, the project examines the structure and limitations of the dataset, including its mixture of objective measurements, survey-based variables, and synthetically generated observations. Two modelling approaches are considered, one including BMI as …

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 …

Characterizing Cyber Intrusions In Critical Infrastructure Networks Using Discrete-Event Simulation, Lawrence M. Dilworth

Dissertations, Master's Theses and Master's Reports

Over the past two decades, cybersecurity compliance frameworks such as the North American Electric Reliability Corporation Critical Infrastructure Protection (CIP) have introduced prescriptive measures for protecting power system networks, emphasizing restricted access, segmentation, and minimizing routable exposure. While effective for baseline cyber hygiene, these approaches do not capture system-level risks or adversarial propagation across interconnected infrastructure. In contrast, Cyber-Informed Engineering (CIE), advanced by Idaho National Laboratory, embeds security in system design by considering threat vectors and physical constraints.

Despite CIP guidance, many deployments rely on IP-routable, bidirectional communication that enables handshaking, allowing adversaries to infer reachable targets. This work presents …

Comparison Of Fixed Tilt And Single Axis Tracking Solar Photovoltaics During Winter, Isobel R. Bowker

Dissertations, Master's Theses and Master's Reports

As solar projects are built in northern climates, it is necessary to understand how snow cover impacts power generation. While there are validated models that predict snow shedding for fixed tilt projects, there is not one for single axis tracking systems. This report aims to characterize the differences between fixed tilt and single axis tracking systems under the same snow conditions. Generation data was collected over four winter months for fixed tilt and tracking systems at Michigan Technological University. Models were created for both systems using weather information from the site, in which losses were set to zero to create …

Design, Modeling, And Experimental Development Of Nanoscale Confinement Structures On Planar Silicon-Based Microelectrode Arrays For Single-Entity Electrochemical Sensing, Parinaz Eskandari

Dissertations, Master's Theses and Master's Reports

Electrochemical sensing is widely used for chemical and biological detection due to its high sensitivity, label-free operation, and compatibility with miniaturized electronic systems. However, conventional microelectrode platforms operate in an ensemble-averaged regime in which the measured current represents the collective response of many molecules interacting with the electrode surface. This ensemble averaging masks localized nanoscale electrochemical events and limits the ability to detect rare interactions, such as single molecules or nanoparticles. Achieving single-entity electrochemical detection therefore requires strategies that confine electrochemical reactions to nanoscale regions while maintaining compatibility with scalable planar microfabrication.

This dissertation investigates nanoscale electrochemical confinement on planar …

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 …

Measurement Of Wave Elevation Using Piezo-Electric Hydrophone, Ace D. Hobbs

Dissertations, Master's Theses and Master's Reports

Water surface waves exert a pressure oscillation that decreases with depth. Pressure measurements can be used to estimate wave elevation and frequency, which can then be used to (1) implement feedback for wave energy converter control strategies and (2) quantify the potential for converting waterbed pressure fluctuations into electrical energy. This report examines the use of an off-the-shelf piezo-electric hydrophone to estimate wave elevation from pressure data. Experiments were carried out in a wave tank with various wave amplitudes, frequencies, and hydrophone depths. Wave gauges, with a resolution of $\pm 0.5$ mm, measured the wave height above the hydrophone. The …

Experimental Characterization Of Photonic Crystal Based Invisibility Cloak Under Tm-Polarized Microwaves, Muhammad Danyal

Dissertations, Master's Theses and Master's Reports

Electromagnetic invisibility cloaks guide waves around an object so that the transmitted wavefront remains undisturbed. Most experimental microwave cloaking studies have focused on transverse electric (TE) polarization due to established measurement techniques. In this thesis, the experimental realization and characterization of a dielectric photonic crystal cloak operating under transverse magnetic (TM) polarization are presented. A measurement system operating in the X-band was developed to map the electric field distribution of the transmitted waves. Cloaking performance was first evaluated qualitatively by comparing numerical and experimental field distributions, where restoration of a flat wavefront indicated effective cloaking. Quantitative evaluation was performed by …

Exploring Fructose Mimetics As Chemotherapeutic Potentiators: Impact On Glut5-Mediated Cancer Cell Vulnerability, Vedant Buwa

Dissertations, Master's Theses and Master's Reports

Metabolic reprogramming toward increased sugar uptake is a hallmark of cancer, and fructose-specific uptake through the facilitative transporter GLUT5 is selectively upregulated in several adenocarcinomas, including breast and lung cancer. This dissertation develops and characterizes a panel of fluorescent fructose mimetics – the coumarin-based ManCou probes and the quinolinone-based ManQuin probes – as GLUT5-targeted reporters, cytotoxic effectors, and chemosensitization adjuvants, and establishes the boundaries within which each role holds.

The central experimental strategy pairs each GLUT5-targeted glycoconjugate with its sugar-free aglycone control, isolating transporter-mediated cytotoxicity from cytotoxicity intrinsic to the fluorophore itself. In luminal (MCF7) and triple-negative (MDA-MB-231) breast carcinoma, …

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 …

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 …

Public Perception Of Environmental Contamination And Its Implications For Fish And Community Health In West Bengal, India, Libia Hazra

Dissertations, Master's Theses and Master's Reports

In West Bengal, India, the highest fish-consuming state in the country, fish are woven into everyday life, including ceremonies of birth and marriage, prayers offered during harvesting and the cultural memory of communities whose identities are inseparable from aquatic life. However, the rivers, wetlands, and ponds that sustain these fish-human relationships are increasingly threatened by environmental contamination resulting from industrial discharge, agricultural runoff, and inadequate environmental management. Understanding how communities perceive these environmental changes is essential for developing effective conservation and public health strategies.

In collaboration between the Indian Institute of Technology (ITT) Kharagpur, India, and Michigan Technological University (USA), …

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 …

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 …

Coupled Shrinking Core And Bubble Dynamics Model For Enhancement Of Metal-Water Reactions With Acoustic Cavitation, Troy Metz

Dissertations, Master's Theses and Master's Reports

Hydrogen is a valuable fuel. Hydrogen can be produced in several ways including thermochemical cycles, electrolysis, and metal-water reactions. Thermochemical cycles typically use high temperatures, often with corrosive species. Electrolysis requires high purity water. Metal-water reactions do not have these drawbacks. Activators such as lithium and gallium are often used to enhance metal-water reactions. However, these activators add to the complexity of metal-water reactions and may not work for all metals. A novel method to improve metal-water reactions is cavitation. During bubble collapse, shock waves and microjets are produced that can cause surface erosion. The objective of this work is …