Digital Commons Network^™

Retrofitting An Fdm Printer For 3d Printing With Cotton Yarn: A Novel Approach And Mechanical Property Evaluation, Muhammad Aghead Al Arnaout

Theses

The rapid rise of 3D printing in industry has intensified research into developing advanced and sustainable printing materials, as the properties of the feedstock directly influence the performance of the final product. This thesis investigates the integration of natural cotton yarn into PLA (Polylactic Acid) to enhance mechanical behavior while maintaining cost-effectiveness, using a standard 3D printer without any modifications. Experimental results across three phases demonstrated consistent improvements. In the first phase, cotton–PLA composites exhibited higher ductility (+22.27%) and toughness (+10.51%) than pure PLA, albeit with lower stress values and a slight decrease in Young’s modulus. In the second phase, …

Waveform Systematics In Moderate Mass Ratio Binary Black Hole Systems, Rachel E. Mechum

Theses

Gravitational wave (GW) observations of binary black hole (BBH) mergers by advanced LIGO (aLIGO) have transformed our understanding of compact objects (COs). As detector sensitivity improves, new populations consisting of moderate to high mass ratio binaries will become increasingly accessible. Parameter estimation (PE), a process that extracts source properties such as masses and spins from GW signals, is critically dependent on accurate waveform models. However, current models may use approximations that introduce systematic errors for binaries with mass ratios between 0.05 and 0.5, affecting parameter accuracy and scientific interpretation. Using the Rapid Iterative FiTting (RIFT) algorithm, this work quantifies waveform …

Using Probabilistic Component Separation To Measure The Sunyaev-Zel’Dovich Effect In Herschel-Spire Galaxy Cluster Observations, Daniel Jeremy Klyde

Theses

Galaxy clusters evolve over cosmic history from small gravitational over-densities at redshift z > 7 to become the most massive gravitationally bound objects in the universe today. The demographics of galaxies populating clusters have shifted significantly over this time, from sites of intense star formation at z ~ 2-4, to largely quiescent objects in the current epoch. An important phase of this evolution involves the development of a hot, ionized intracluster medium (ICM). Its formation around cosmic noon overlaps with the peak in star formation, which requires a multi-wavelength observational approach to fully characterize. One way to study the properties of …

A Web Application For Generating Argument Maps For Essays Using Llms, Alexis R. Chalmers

Theses

Argumentative writing is a critical skill that strengthens students’ reasoning, communication, and analytical abilities. However, maintaining a clear and organized argument structure while writing can be challenging. Argument maps — visual diagrams which explicitly show an argument’s structure — have been shown to improve students’ writing, but are rarely used outside of the planning stage of an essay due to the time and effort required to create them. Automatically generating argument maps from student essays helps students to evaluate the structure of their argument as they write and makes identifying unsupported claims visible. To evaluate whether large language models (LLMs) …

Real-Time Fraud Detection Using Big Data, Abdulla Matar Alketbi

Theses

In today’s digital world, fraud detection has become an important part of financial security. This study explores and compares the performance of different machine learning models in identifying fraudulent transactions using the IEEE-CIS Fraud Detection dataset. Techniques such as Random Forest, Gradient Boosting, Deep Neural Networks, and Logistic Regression were evaluated. The dataset was pre-processed using SMOTE to balance the classes and improve model sensitivity to fraud cases. Each performance of the model was assessed using accuracy, precision, recall, and F1-score. The Random Forest model achieved the highest overall performance with an F1-score of 99.23

Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink

Theses

Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.

Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …

Calibration Of Detectors For The Tomographic Ionized-Carbon Mapping Experiment, Tessalie A. Caze-Cortes

Theses

Observations of the intensity of the sky at millimeter (mm) wavelengths require accurate calibrations for the spectrometers to work with radio telescopes. However, calibrating is a complex and lengthy process for sensitive detectors that catch single photons. To improve efficiency in locating defective detectors and optimizing bias current, my research involves taking data from previous lab characterizations and creating an algorithm that analyzes and plots the code of all 1920 detectors. This thesis will discuss the importance of mm-wavelength intensity mapping and the questions the TIME research team aims to address. Also, a detailed description of mechanical and computational components …

Macroscopic Roughness Modeling Of Satellite Multi-Layer Insulation Reflectance, Kevin P. Donnelly

Theses

Reflectance modeling of specular surfaces with irregular geometries remains difficult to solve for an array of applications. In the growing space industry, there are many spacecraft materials with high specularity and varying levels of roughness. Modeling these materials in simulations becomes difficult as any realistic amount of roughness is added, necessitating more accurate physical models to represent how light is interacting with these surfaces. While some work has been done to attempt to characterize the spectral signatures of the materials themselves using hyperspectral imaging systems, the scope of these efforts has been fairly limited and not representative of the conditions …

Zoo Visitors Learn By Observing Olive Baboons (Papio Anubis) Participate In Cognitive Research Or Engage In Natural Behaviors, Anna Sofia Hege

Theses

I conducted two experiments at the baboon exhibit at the Seneca Park Zoo in Rochester, New York to measure attitudes and actual knowledge in children and adults, as well as perceived learning in adults. I also recorded caregiver-child conversations in the presence and absence of live research. Experiment 1 included 150 adult participants, and Experiment 2 included 18 caregiver-child dyads. In each experiment, the research on-scientist present and research on-scientist absent group watched the baboons engage with live cognitive research while the research off-scientist present and research off-scientist absent group watched the baboons carry out their natural behaviors. A scientist …

The Effects Of Multiple Exemplar Instruction On A Bidirectional Naming Repertoire In Children With Autism Spectrum Disorder, Madison Appelbaum

Theses

Neurotypical children normally acquire language skills in their natural environment. However, children with autism spectrum disorder (ASD) typically require specialized interventions to acquire language and communication skills (Yoon et al., 2023). A behavior repertoire that has been shown essential for the fast and incidental acquisition of language in children is bi-directional naming (BiN). Multiple exemplar instruction (MEI) has been used to facilitate the acquisition of BiN in children with ASD. In the present study, we replicated and extended previous research (e.g., Yoon et al., 2023) to evaluate the effect of MEI on the emergence of BiN repertoire in three elementary …

Effects Of Self-Monitoring On Teachers’ Behavior-Specific Praise And Students’ Behavior In A Center-Based Classroom, Samantha Walsh

Theses

The current study explores the effects of self-monitoring on teachers' use of behavior-specific praise (BSP) and its impact on student behavior in a center-based classroom. Self-monitoring, a cost-effective and time-efficient intervention, has been proven effective in previous research for enhancing educator performance. However, previous studies have often combined self-monitoring with other interventions, leaving a gap in understanding its effects in isolation. This study aims to replicate the work of Justus et al. (2023) by examining the impact of self-monitoring on paraprofessionals in a center-based classroom with students aged 6-10. Using a multiple baseline design across participants, three paraprofessionals were trained …

Protein Language Models-Based Representation For Post-Translational Modification Prediction, Suresh Pokharel

Theses

Post-translational modifications (PTMs) are chemical changes that occur after translation and play a key role in regulating protein function and cellular processes. Their dysregulation is associated with various diseases, making accurate prediction of PTM sites essential for understanding cellular mechanisms and informing therapeutic strategies. This work focuses on the computational prediction of two biologically significant PTMs, namely succinylation and O-GlcNAcylation, utilizing recent advances in protein language models (pLMs). Drawing an analogy to natural languages, amino acids are treated as words and sequences as sentences, allowing pLMs to capture contextual dependencies within protein sequences. One of the earliest contributions of this …

Dynamic Defenses To Systematically Secure Exposed Attack Surfaces In Wireless Systems, Naureen Hoque

Theses

While modern wireless systems rely on strong encryption, this alone does not secure the entire attack surface, including exposed signal attributes, pre-authentication exchanges, and protocol metadata. This dissertation challenges the assumption that existing cryptographic protections are sufficient to protect these vulnerabilities. Signal attributes, including phase and amplitude variations due to modulation, are physical-layer characteristics of encrypted data communication that remain observable and exploitable for attacks like traffic analysis. The pre-authentication phase—during which session keys are negotiated and installed—is vulnerable to spoofing and denial-of-service attacks. Protocol metadata, such as operating channel, sender’s address and location, and timestamps, is unencrypted and can …

Benedictine Art And Design: How Color Psychology Can Positively Influence Department Enrollment, Claire Pauline Fink

Theses

This thesis examines how design strategies informed by color psychology and experimental aesthetics can be used to strengthen the visual identity and recruitment efforts of the Benedictine College Art & Design Department (BCAD). Following the recent addition of Graphic Design as a major and the department’s name change in 2021, there has been a noticeable gap in public awareness and printed promotional materials tailored to prospective students. Grounded in theoretical frameworks, such as D. E. Berlyne’s optimal arousal theory, and supported by survey responses from current Art & Design students, this project identifies key needs in marketing to prospective students. …

The Evolution Of Agriculture Marketing: Harnessing Data Analytics To Understand Generational Shifts And Influencer Trends, Lexi Schweigert

Theses

The findings reveal that data analytics plays a crucial role in shaping marketing strategies in agriculture. Generational shifts, particularly among Gen Z and Alpha, are driving changes in consumer preferences and expectations. Influencers are also playing an increasingly important role in shaping the perception of agriculture and food among these generations.

Elisabetta Sirani’S Timoclea: Baroque Agency And The Aesthetics Of Feminine Rage, Shaylen Grace Gardner

Theses

This thesis examines Timoclea Kills the Captain of Alexander the Great (1659) by Elisabetta Sirani as a foundational example of feminine rage within the Baroque period. By framing Timoclea’s violent act not as an outlier or solely reactive gesture, but as a deliberate, composed assertion of power, Sirani constructs a model of feminine agency that defies patriarchal expectations of female submission and passivity. Through interdisciplinary analysis grounded in feminist theory, formal visual analysis, and retrospective cultural studies, this research argues that Sirani’s Timoclea exemplifies the Baroque’s strategic use of socially acceptable iconography to veil explicit challenges to gendered expectations. This …

Utilizing Natural Language Processing To Optimize Business Processes, Olt Kondirolli

Theses

This Capstone project explores the potential of Natural Language Processing (NLP) techniques in optimizing decision-making and organizational workflows across various domains. The Capstone project uses three case studies to demonstrate how sentiment analysis, frequency analysis, and topic modeling can analyze unstructured textual data to provide insightful findings. The first case study evaluates employee satisfaction using sentiment analysis, uncovering trends across departments and roles to guide targeted organizational interventions. The second case study focuses on student feedback at a higher education institution, using sentiment and frequency analyses to identify key areas for improvement in academic programs and services. The third case …

Development Of Nanopocket Membranes For The Isolation And Purification Of Extracellular Vesicles, Munther Alsudais

Theses

Extracellular vesicles (EVs) play a crucial role in intercellular communication and serve as significant biomarkers for various diseases. EVs carry biomolecules such as lipids, proteins, DNA, and RNA, which reflect the physiological state of their cells of origin, making them promising tools for non-invasive diagnostics and therapeutic applications. Effective isolation of EVs is essential for advancing scientific understanding of their biological roles and unlocking their clinical potential. Porous membranes have been widely used for the purification of various biological species from biological fluids. While membranes have prove highly effective for general size-based separation, recent innovations have focused on structurally refined …

Predicting & Analyzing University Success: Machine Learning Approaches To Predict Performance From Socioeconomic And Educational Data, Ali Alrais

Theses

Accurately predicting learner performance is a significant challenge in education since diverse and interrelated factors contribute to academic success. High school grades and standardized test scores remain the primary indicators used for university admissions. However, such approaches fail to capture the complexities surrounding student learning. For instance, various cognitive, cultural, socioeconomic, and environmental influences shape academic outcomes. Educators need to adopt more comprehensive predictive models that consider in-depth learner differences. Reliable academic performance prediction can help schools optimize admissions decisions, allocate resources effectively, and implement targeted interventions to support at-risk students. This study adopted a quantitative primary research approach with …

Investigating Spectral Rendering Techniques To Improve Colour Matching In Virtual Production, Vlad Simion

Theses

As rendering engines become increasingly important in film and television, with their use in virtual production (VP) to display rendered imagery, some underlying issues become more apparent. This thesis aims to investigate how we can improve asset color matching of VP elements with real-life objects found on sets. Experiments were conducted in which objects were exposed to various types of lighting setups, and digital twins were rendered using traditional computer graphics techniques. The renderings occurred in both classic RGB spaces and the spectral domain. Additionally, data reduction techniques were used for the spectral renderings to determine if any of them …

Identifying Underspecifications In Security Requirements Using A Formal Reasoning Approach, Viktoria Koscinski

Theses

Within requirements engineering, software requirements specifications tend to prioritize functional needs, potentially failing to capture critical security aspects and adequate security requirements. Security requirements engineering is a manual and error-prone activity often neglected due to the knowledge gap between cybersecurity professionals and software requirements engineers. Consequently, security requirements are especially prone to being underspecified, a condition where they lack a complete set of feature-values and are thus open to multiple interpretations. Underspecified security requirements can lead to incorrect assumptions and missing security properties, often remaining undiscovered until system deployment, thereby leaving the system vulnerable to exploitation. Furthermore, even individually well-written …

Online And Offline Multi-Variate Time Series Forecasting With Neuroevolution Based Neural Architecture Search, Zimeng Lyu

Theses

Time series forecasting plays a crucial role in various fields, ranging from financial markets and predictive maintenance in industrial settings to healthcare analytics. Traditionally, statistical approaches were employed primarily for univariate forecasting tasks, but modern applications often require robust solutions capable of handling complex, multivariate, noisy, and non-stationary data. Current state-of-the-art solutions predominantly utilize transformer-based models, which demand significant computational resources, limiting their practicality, especially in resource-constrained environments. This dissertation introduces novel and efficient approaches to multivariate time series forecasting, leveraging NeuroEvolution-based Neural Architecture Search (NAS) methodologies. Specifically, two robust algorithms---Evolutionary eXploration of Augmenting Memory Models (EXAMM) for offline forecasting …

Investigating Human Expertise In Manufacturing To Enhance Knowledge Preservation And Transfer Practices, Krzysztof Kamil Jarosz

Theses

In the US, the machining industry is a vital part of the economy, employing over 290,000 skilled machinists and over 89,000 mechanical engineers. Whilst employment figures for engineers in this crucial sector has been fairly steady, a rapid decline in machinist workforce has been observed in the last decade, along with retirement of aging expert machinists and engineers, creating workforce shortages and loss of valuable manufacturing knowledge inherent to those highly skilled and experienced individuals. As engineering design and manufacturing knowledge are closely intertwined, so is the knowledge pertaining to practical aspects of machining and design of components that are …

Identification Of Strategies To Improve Milking Parlour Efficiency: Insights From Empirical Data And Simulation Analysis, Ryan Prendergast

Theses

The abolishment of European Union milk quotas in 2015 has increased the strain on dairy farm infrastructure and labour availability. For both pasture and confinement-based production  systems, the milking process requires the largest annual labour input. Hence, this area  represents an opportunity for achieving gains in labour efficiency. The aims of this thesis were to 1) document and quantify factors that affect milking process efficiency and 2) develop models that can simulate milking parlour efficiency with respect to these factors. Data were collected from a sample of commercial, pasture-based Irish dairy farms across the Republic of Ireland that used herringbone …

Measurement, Modelling And Optimisation Of Renewable Technologies And Energy Storage Systems On Dairy Farms, Fergal Buckley

Theses

Advancing the economic and environmental performance of dairy farms requires a comprehensive assessment of renewable energy systems (RES), energy storage technologies, and demand side management (DSM) techniques. This thesis aimed to address these needs by conducting a thorough assessment of RES, DSM techniques, and energy storage systems on dairy farms, through the development of a state-of-the-art simulation tool, trained and validated using modern energy data collected from a range of commercial dairy farms as part of this project. The research was conducted in three stages. Firstly, extensive data collection was undertaken across 26 commercial dairy farms employing herringbone and rotary …

Secure Composite Digital Twin For Collaborative Ecosystems, Pasindu Kuruppuarachchi

Theses

The rise of collaborative digital ecosystems and the growing adoption of Digital Twins (DTs) in sectors like smart manufacturing, energy, and autonomous sys- tems underscore the need for secure, interoperable frameworks. This research proposes a Secure Composite Digital Twin Architecture (CDT) that enables seam- less integration and collaboration among DTs, addressing key challenges in trust, interoperability, and governance. The architecture features a trust analyser to assess DT behaviour and a repu- tation model to enhance security as the ecosystem scales. It supports centralised, decentralised, and hybrid governance via distributed ledger technology, enabling dynamic policies and secure, token-based asset management. For …

Crispr-Dcas9 Genomic Engineering For Boosting The Therapeutic Potential Of Extracellular Vesicles, Iker Martinez Zalbidea

Theses

Degenerative disc disease is a major contributor to low back pain, characterized by inflammation of the intervertebral disc (IVD), degradation of the extracellular matrix, loss of hydration, and cell death. Current therapies fail to address these underlying mechanisms, underscoring the need for regenerative strategies. Mesenchymal stem cells (MSCs) exhibit immunomodulatory and regenerative potential, but their efficacy is hampered by the harsh microenvironment of the degenerated IVD. Acellular MSC-derived extracellular vesicles (EVs) have shown therapeutic potential and offer a promising alternative for IVD regeneration. Here, we explore CRISPR-dCas9 mediated activation of TSG6 and STEAP3 to boost the therapeutic potency and biogenesis …

Personifying The Goddess: Contrasting Representation Of The Deified Body In Feminist Art, Kelly Lorraine Phillips

Theses

Goddess imagery, the representation of a female deity or a concept of divine feminine power through various forms, symbols, and narratives, has been used by artists to communicate a multitude of sentiments, from spiritual reverence to political ideology. This study probes the evolution of representations of the deified female body from the 1970s to the current era to reveal contrasts in how these icons of female power have transformed over time. The artwork of second-wave feminist and self-identified “Goddess artist” Mary Beth Edelson is examined as a foundation for second-wave Goddess sentiment. Edelson’s collage work, which incorporates figures from a …

Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra

Theses

Currently, there are thousands of man-made space objects that are orbiting the Earth. These satellites serve a host of essential purposes (scientific research, technical applications, services) and they are all required to remain within their mission parameters. Most critical for them is to maintain the orbital parameters that are specified to achieve a particular mission’s objectives. If a satellite deviates beyond a certain limit, there is not only a risk of mission failure but there is a major hazard for possible collisions with other objects such as active satellites, space debris and even natural objects in some cases. There is …

Associations Between Vitamin D Deficiency And Sociodemographic Factors, Lifestyle Behaviors, And Metabolic Conditions: A Cross-Sectional Study From The Hnnhs In Greece, Asmae Mohamad Sadek

Theses

Vitamin D deficiency (VDD) is a widespread global health concern associated with various sociodemographic, lifestyle, dietary, and metabolic factors. While previous studies examined VDD in Greece, few provided a comprehensive analysis across multiple determinants using representative national data. This study aimed to assess the prevalence and predictors of VDD among Greek adults and to examine its associations with sociodemographic, dietary, behavioral, and metabolic variables using data from the Hellenic National Nutrition and Health Survey (HNNHS). A cross-sectional analysis was conducted among 978 adults (≥19 years) from the HNNHS. Serum 25-hydroxyvitamin D [25(OH)D] concentrations < 20 ng/mL were defined as deficient and ≥20 ng/mL as normal. The median age of participants was 40.2 years, and 62.0% were female. The overall prevalence of VDD was 46.0%, with the highest rate observed among adults aged ≥60 years (62.2%). VDD was significantly associated with older age (p < 0.001), retirement status (62.9% among retired; p < 0.001), low and sedentary physical activity (32.7% and 32.6% vs. 50.8% among highly active; p < 0.001), higher HDL (median 52.0 vs. 49.0 mg/dL among VDD vs Normal; p = 0.001), elevated serum calcium (median 9.4 vs. 9.2 mg/dL among VDD vs Normal; p = 0.020), and lower insulin levels (median 7.5 vs. 8.0 μIU/mL among VDD vs Normal; p = 0.044). Dietary intake (total energy and macronutrients) and body composition were not significantly associated with VDD. In the multivariate model, significant independent predictors of VDD included being retired (AOR = 2.383; 95% CI: 1.596–3.558; p < 0.001), having higher serum calcium levels (AOR = 1.563; 95% CI: 1.078–2.266; p = 0.019), and higher HDL levels (AOR = 1.016; 95% CI: 1.005–1.027; p = 0.001). Physical activity level was also a key determinant; participants classified as sedentary or low active had significantly higher odds of deficiency compared to highly active individuals (AOR = 0.468; 95% CI: 0.319–0.690; p < 0.001). This counterintuitive result may be influenced by factors such as increased indoor physical activity, and warrants further investigation. Dietary intake and body composition were not significantly associated with VDD. The findings underscore the importance of incorporating sociodemographic and lifestyle factors into prevention strategies. Interventions should particularly focus on older adults, retired individuals, even if they have higher HDL and calcium levels, and are physically active.