Digital Commons Network^™

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 …

Predicting The Next Recession With Machine Learning, David Heffernan

ICT

Economic recessions can have significant consequences for businesses, households, financial markets, and policymakers, creating a need for improved understanding of the factors associated with economic downturns. This project analyses historical US economic and financial data to examine patterns associated with previous recessionary periods and assess whether machine learning can be used to identify recession risk. The study uses a two-tier analytical approach, combining a macroeconomic dataset covering 1960 to the present with a more detailed dataset from 1987 onwards that incorporates financial markets, house prices, and consumer confidence. Building on previous exploratory analysis, the project develops and evaluates three machine …

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 …

The Impact Of Strategic Planning On Teachers' Perceptions Of Their Practice: A Mixed-Methods Study, Vivian Robert

Selected Full Text Dissertations, 2011-

Strategic planning is a vital endeavor for school districts across New York State. Often, however, significant human and financial capital is invested in these processes without investigating their impact beyond immediate student outcomes. While student success is the ultimate priority, little attention has been paid to the effect strategic planning has on the practitioners charged with implementing it, specifically teachers. This phenomenological mixed-method case study investigates how strategic planning influences teachers’ perceptions of their practice and identifies how districts can better engage educators to ensure the successful realization of district goals. In this study, district leaders participated in semi-structured interviews, …

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 …

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 …

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 …

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 …

Valuing Life And Loss: Genre Analysis Of Insurance Claims Processing In Ghana, Cornelius Fuumaale Suom-Kogle

Dissertations, Master's Theses and Master's Reports

This thesis draws on theories from rhetorical genre studies (Spinuzzi’s genre ecology and Freadman’s uptake), biopolitics, and the social justice turn in Technical and Professional Communication to examine how decisions are made in the processing of insurance claims. I adopt a qualitative, interpretive approach to analyze one hundred and twelve (112) claims processing examples from Ghana’s insurance industry. The findings indicate that insurance claims processing is a complex communicative system in which institutional power is enacted, negotiated, and, at times, contested. The findings also reveal that insurer-authored genres frequently enact forms of oppression (exploitation, marginalization, and powerlessness) through technical language …

Exploring The Prevalence Of Eating Disorders, Low Sex Drive, And Exercise Compulsion Among Professional And Non-Professional Elite Male Rugby Union Players, Gary Sweeney, Siobhain Mcardle, Danielle Logue, Nessan Costello, Kieran Collins

Research Outputs: 2025-Present

Rugby union exhibits large variations in the idealised player physical profiles across positions. The pursuit of physique ideals with limited professional support can influence eating disorder symptomology, exercise compulsion, and low sexual drive. The primary aims were to (1) explore the prevalence of elite male rugby union players who are at risk for eating disorders, low sex drive, and exercise compulsion, and (2) explore the relationship between risk and players’ professional status, weight, age, and playing position. A secondary aim was to explore the nutritional service support and dietary monitoring practices experienced by the players. Participants were recruited from four …

Real Time Waste Classification Using Deep Learning: Comparing Mobilenetv2 And Resnet 18 With Transfer Learning And Fine Tuning, Abdul Moaiz

ICT

Waste contamination is a major problem all over the world. The Environmental Protection Agency reports that over two thirds of waste found in general household and commercial bins could have been placed in the recycling or organic waste bins instead in Ireland, with food waste and plastics being the most common misplaced items. This project presents a deep learning solution to classify nine categories of waste from camera images in real time with the goal of helping users sort waste correctly at the source. Following the CRISP DM framework, two convolutional neural network architectures were trained and compared, MobilenetV2 and …

Bitcoin Prediction System Usind Machine Learning Techniques, Carolina Azevedo De Castro

ICT

This project investigated the use of machine learning techniques to predict short-term Bitcoin price direction using historical market data obtained from Yahoo Finance. Following the CRISP-DM methodology, the dataset was analysed, prepared, and transformed through feature engineering techniques including moving averages, volatility indicators, return measures and price position metrics. Multiple classification algorithms were evaluated, including Bayesian Classification, K-Nearest Neighbour, Decision Tree, Random Forest, Logistic Regression, Support Vector Machine and XGBoost. Several optimisation strategies were also tested, including feature selection, hyperparameter tuning, feature scaling and class weight balancing. Results showed that predicting short-term Bitcoin price movements remains challenging, with most models …

Predicting Loneliness Among Older Adults In Ireland Using Supervised Machine Learning, Ariadne Chaves Miranda

ICT

Over the last two decades, technology has grown exponentially and has facilitated communication that helps individuals remain connected. However, this has also contributed to social isolation and lack of physical interaction. One consequence of this phenomenon is loneliness, which is understood as an unpleasant subjective state of discrepancy between the desired amount of companionship or emotional support and what is available in the person’s environment (Prohaska and Burholt, 2020). In the European context, Ireland has emerged as the loneliest country in Europe with 20% of its population that have reported feeling lonely most or all the time (Schnepf et al., …

Southern Adventist University Annual Report 2025-2026, Southern Adventist University

Annual Reports

The Annual Report for Southern Adventist University for 2025 to 2026.

Transforming Lives For Eternity: 2026-2031 Strategic Plan, Southern Adventist University

Strategic Plans

Southern Adventist University's 2026-2031 Strategic Plan.

Animator Becomes Animated: A Short Film Uniting Animation And Traditional Film As One, Peter Francis Stahr

Honors Program Theses

Traditional filmmaking has been around since the late nineteenth century, where filmmakers would utilize black and white film and tedious developing processes, including the manual handling of chemicals, to create a feature film. Shortly after the turn of the twentieth century, the first few 2D animated films came to life. Then, almost 100 years later, the digital age struck, bringing with it the ease of access for anyone to take out a camera and snap a picture, take a video, or even create a movie. In parallel with the development of digital filmography came 3D software, opening the creative capacity …

The “Multi-Normative” Biological Weapons Convention: A Study Of The 2022 Article V Meeting In Geneva, Robert Lawless

Emory International Law Review

In September 2022, States parties to the Biological Weapons Convention (BWC) held a Formal Consultative Meeting in Geneva pursuant to Article V of the Convention, following Russia’s allegations that the United States and Ukraine had developed biological weapons in violation of BWC prohibitions. Although largely overlooked in public discourse, the Geneva meeting provides a revealing example of the BWC in practice. This article examines the Geneva meeting to assess the Convention’s normative role in contemporary international relations. It argues that States parties reaffirmed their commitment to the BWC’s core prohibition against the hostile use of biological agents against humans. Moreover, …

Consensus Decision-Making: Decision-Making Model Of Chinese Constitutional Review, Songfeng Li

Emory International Law Review

The judgment model of constitutional review in China adopts a consensus-based judgment model involving multiple stakeholders, including review authorities, drafting authorities, relevant interest parties, and the general public. Through multi-level, multi-stage, and multi-round interactive communication and negotiation, consensus is reached on constitutional judgments. This judgment model aligns with the power division political system under the NPC system, reflecting the institutional concept of people’s sovereignty and the cultural foundation of valuing harmony. It is also a result of the decentralization of constitutional review authority leading to insufficient power for actual reviewers, the parallel nature of factual and normative judgments in constitutional …