Digital Commons Network^™

Subterranean Drought Classification And Ecological Risk In Karst Systems, Shaelyn Deal

Theses

Cave ecosystems depend on stable groundwater inputs, yet no standard method exists for detecting subterranean drought. This study develops a framework to define and monitor drought in karst cave systems by adapting surface-based hydrologic indicators. Using long-term water level data from Bobcat Cave in northern Alabama, we identified drought events through percentile-based thresholds and evaluated multiple surface metrics, including the Standardized Precipitation Index (SPI) and deep-layer soil moisture, as predictors of cave drought severity. Random Forest models supported the selection of key indicators and informed classification thresholds. These thresholds were then applied across the Middle Tennessee Elk watershed to map …

Augmenting Attention : An Ooda-Centric Framework For Explainable Ai In Ar Human-Ai Teaming Applications, Dylan Wright

Theses

Artificial Intelligence (AI) is increasingly deployed in high-stakes environments where success depends on more than computational accuracy; it also requires alignment with human perception and attention. Traditional explainable AI (XAI) methods provide static, post-hoc justifications that are poorly suited to time-critical decision cycles. This thesis investigates whether perceptually aligned, real-time explanations in Augmented Reality (AR) can enhance performance, workload balance, and trust within the Observe–Orient–Decide–Act (OODA) loop. A custom AR search-and-rescue simulation tested three conditions: no assistance, static overlays, and perceptually aligned explanations using adaptive cues such as occlusion-aware tethers and urgency-based visuals. The results show that any explanation improved …

Multi-Factor Mathematical Optimization For Healthcare Referral And Facility Placement, Mitchell Moody

Theses

This thesis addresses the challenge of optimizing patient referrals in healthcare systems by integrating clinical needs, geographic proximity, and dynamic infection risk. Healthcare referral networks (HRNs), which capture patient transfers between hospitals, serve as the foundation of the study. First, a recommendation algorithm is developed to assign patients by jointly considering clinical compatibility and logistical considerations like travel distance, striking a balance between quality and accessibility. Building on this, a reinforcement learning framework is proposed to dynamically adjust referral strategies for vulnerable patients by incorporating the evolving risk of hospital-acquired infections. Finally, long-term planning is explored through methods that recommend …

Evaluating The Accuracy Of Johnson-Cook Strain Rate Sensitivity For Fcc Aerospace Structural Materials, Sydney Carlota Resnick

Theses

Understanding aerospace materials’ strain rate sensitivity is crucial for accurate designs and analysis for structural performance in dynamic loading conditions, such as rocket launches, airplane collisions, and debris impacts. Three common aerospace face-centered cubic (FCC) metals are evaluated through various strain rate tests and FEA and simulation modeling. Quasi-static and intermediate tests are performed on a hydraulic load frame, and dynamic tests are run on a split-Hopkinson pressure bar, all in tensile motion. This covers the range of strain rates from 1x10-3 s-1 to 1x103 s-1. Results reveal little strain rate sensitivity at room temperature for A286 steel and AL7075 …

Utilizing Ground-Based Radar Analyses To Investigate Ocean-To-Land Differences In The Tropical Cyclone Wind Profile And Their Impacts On Tornadogenesis, Elizabeth M. Seiler

Theses

On 20 August 2008, the MAX radar was deployed southeast of the Jacksonville, FL WSR-88D radar to monitor the boundary layer before, during, and after the landfall of TS Fay. During the 57-hour deployment, MAX sampled around a tornadic rainband that produced at least one confirmed tornado. To illustrate TCBL changes across a coastal zone, VAD profiles from MAX and KJAX are compared, and a dual- Doppler analysis is performed. One key finding from the DDA was the consistent presence of southeasterly background flow, vertical vorticity, enhanced cyclonic shear zones, and minisupercells throughout the 1650-1725 UTC analysis period. The primary …

Generation Of True Random Numbers With Actively Stabilized, Low Dimensional Chaos, Aidan Barton

Theses

True Random Number Generators (TRNGs) are heavily used and their design often relies on empirical validation from statistical test suites. Reliance solely on empirical observations to estimate entropy rates for cryptographic applications introduces risk, as accurately inferring long-term correlations demands prohibitively large datasets. Empirical validation of TRNGs must be supplemented by strong theoretical backing to justify estimated information theoretic quantities. We present an electronic, hardware TRNG scheme that produces a maximally random output guaranteed from first principles. This TRNG uses a pulse-width based hardware realization of an iterated map that produces physical entropy via low-dimensional chaotic dynamics. The simple dynamics …

A Comprehensive Study On Explainable Artificial Intelligence : A User-Centric, Cognitive Workload, And Feasibility-Driven Analysis, Josiah Taylor

Theses

Explainable Artificial Intelligence aims to open up the “black box” of artificial intelligence, thereby improving user trust, decreasing cognitive load, and improving task performance. As the number of machine learning models has grown, so has the number of explanation methods, making it necessary to select the most suitable explanation method for a given context. However, current selection methods often fail to account for all the factors that contribute significantly to an explanation method’s suitability. This thesis proposes a novel methodology for selecting and evaluating explanation methods. Subjective workload, objective performance, and feasibility are considered. This three-pronged “pitchfork” methodology is put …

Chaos-Based Thumbnail-Preserving Image Encryption, Sara Mog

Theses

As the landscape of image data usage continues to change, cloud services need to store data securely, reliably, and at times maintain a reasonable level of human usability. Thumbnail-preserving encryption (TPE) is a niche area of image encryption research that provides a balance between security and privacy. A TPE scheme encrypts an image in such a way that the thumbnail of the encrypted image is the same as or similar to the thumbnail of the original image. This work presented a chaos-based TPE scheme and explored potential pitfalls encountered when using chaos for encryption. The TPE scheme used a chaos-based …

Development Of A Constitutive Model Free Method To Determine Full-Field Stresses Based Upon Fundamental Physics Principles, Joel David Barnes

Theses

Advances in imaging techniques allow for the determination of full-field displacements and strains during materials testing. However, most analysis techniques rely on strain gages and virtual extensometers instead of utilizing all available full-field data. Those methods that do utilize the full-field strain and displacement measurements, such as Finite Element Model Updating and the Virtual Fields Method, must also rely on a user-defined constitutive material models to relate the stresses and strains. While these methods can provide accurate full-field stresses and insights into complex material behavior in some cases, they are constrained by the fact that they require a pre-selected constitutive …

Optimizing Reliability And Design Efficiency Of Liquid Rocket Engines : A Structural Margin Approach For The Early Design Lifecycle, Mason Tudor

Theses

This thesis introduces a reliability-based design methodology aimed at mitigating costs incurred during the Test-Fail-Fix cycle for Liquid Rocket Engines (LREs) by addressing the limitations of the standard Factor of Safety (FoS) approach. By integrating a neural network informed by a structural model into a Bayesian framework for uncertainty quantification, the methodology enables the characterization of structural margin and early analysis of failure risks in the design lifecycle. A generalized 3D component geometry is subjected to typical LRE loading environments within Finite Element Analysis software to gather data for stress and strength distributions. These distributions serve as a foundation for …

Application Of Machine Learning To Predict Ultrasound Wave Propagation In Biphasic Fluid–Solid Media, Jahnavi Dandamudi

Theses

The objective of this thesis is to investigate the application of Machine Learning (ML) algorithms to predict ultrasound wave propagation in the cartilage tissue of the knee joint. The learning data necessary for the ML algorithm has been generated through finite-element method (FEM)-based simulations for solving the Biot theory equations governing the propagation of continuous ultrasound through the cartilage. Specifically, we computed the ultrasound-induced dilatations and displacements in the microscale cartilage that is represented as consisting of four zones, namely the chondrocyte cell and its nucleus, the pericellular matrix (PCM) that forms a layer around the chondrocyte, and the extracellular …

Surveying The Role Of Visual Analytics In Human-Machine Teaming, Naga Datha Saikiran Battula

Theses

Humans and machines both possess their unique capabilities and have their strengths and weaknesses, which can be complementary to one another and allow them to achieve a common goal. Teaming in the modern era involves text prompts, voice commands, gesture recognition, touch interfaces, and the latest visualization techniques that allow parties/agents to interact. Communication through visualization plays a vital role in allowing robust insights to be gained through a glance. Using visualization as a medium between humans and machines can increase the communication bandwidth. Human-machine teaming has witnessed much progress, with many theories and practical examples emerging. In the report, …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Advancing Prediction Of Stimulant Medication Misuse Through Graph Representation Learning, Hamid Razavi

Theses

The misuse of stimulant prescription medications poses a significant and escalating public health concern in the United States, particularly among young adults. Addressing this issue requires sophisticated methodologies capable of uncovering complex patterns and relationships in data. Geometric Deep Learning, a paradigm designed to analyze data with non-Euclidean structures, has achieved remarkable success across various domains, offering a powerful framework for tackling complex graph structure data challenges.

This study leverages Graph Convolutional Networks (GCNs) to predict the likelihood of stimulant medication misuse using data from the National Survey on Drug Use and Health (NSDUH). Individuals are represented as nodes in …

Exploration Of The Iterative Design Process: Integrating A Requirements Matrix And Hazard Analysis Toolsexploration Of The Iterative Design Process: Integrating A Requirements Matrix And Hazard Analysis Tools, Blaine Edlefsen

Theses

The iterative design process is applied to multiple industry sectors from software development to product manufacturing. The cyclical approach integrates the steps of design, prototyping, and testing toward the realization of a user's specified needs. The use of a requirements traceability matrix and hazard analysis documentation that supports the definition of the iterative design process is explored. These design project management tools are applied to a case study involving workholding design for a Wire Electrical Discharge Machining (Wire-EDM) manufacturing process. This industry-relevant case study is conducted in collaboration with New Jersey Precision Technologies, Incorporated (NJPT). The design requirements involve both …

Utilitarian And Self-Representational: Player-To-Player Character Relationships In Final Fantasy Xiv, Zu Er Guan

Theses

This thesis studies the relationships between video game players and their player characters, the characters that they control, through the lens of player purpose and intent by conducting research using an online survey developed and analyzed using an interdisciplinary methodology based on existing studies in the field regarding avatar identification, player psychology, and queer and feminist theory. This thesis posits that are two types of player relationships with their player characters based on player intent—player characters as the personal avatar and representation of the self, and player characters as a tool for the execution of player control and gameplay experience. …

Optimizing Wind Wing Wall Ventilation In High-Rise Buildings Within Dense Urban Hot And Humid Climate., Arushi Bhatia

Theses

This study investigates how wing walls can increase natural ventilation in high-rise structures, particularly in hot, humid locations such as Mumbai, India. Using wind flow simulations and computational fluid dynamics (CFD) modeling, the study investigates how wind direction and the installation of wing walls affect airflow throughout the building. The study examines four scenarios, each analyzing how airflow varies when a building is located near surrounding structures of differing heights. It uses comprehensive CFD simulations to assess how alternative wing wall depth design can affect ventilation, as well as how wall-to-window ratio variation can contribute to airflows. Following these simulations, …

…And So It Ends In A Tie, Crystal Hou

Theses

…and so it ends in a tie is a 2D frame-by-frame animated short film produced during the course of my 3rd year as a Master of Fine Arts student in the School of Film & Animation at Rochester Institute of Technology. The film explores themes of homosexuality, female sexuality, and the history of Japanese rope bondage through the fictionalized story of a fateful encounter between a rope-wielding martial artist and a mysterious woman who captures her attention. This paper serves as a documentation of the filmmaking process, a discussion of the ideologies and goals behind its creation, and a retrospective …

I Hear A New World, Katie Christ

Theses

“I Hear a New World” is a documentary short film that reflects on the relevance and persistence of nostalgia and tradition during a time of rapid technological advancement and societal change. The film highlights the memories and musings of 8 college students, who were all Class of 2020 high school seniors and whose senior traditions were inevitably brought entirely online due to the Covid-19 global pandemic to varied degrees of success. In rambling, thoughtful delivery, the Gen Z interviewees provide insight into their pre-pandemic internet obsession that led to their teenage reclusivity and how this perspective changed greatly following the …

From Factories To Homes: A Comparative Analysis Of Adaptive Reuse In New England Industrial Buildings For Multi-Family Residential Conversion, Jeremy Weeden

Theses

The adaptive reuse of industrial buildings offers a promising path toward sustainable urban development, particularly in New England. This study investigates the feasibility and energy efficiency of converting an older, unused industrial building into a multi-family residential structure by evaluating three distinct wall assemblies that preserves the exterior brick facade: existing structural brick, a typical adapted wall assembly with interior 2x4 wood construction, and a high-efficiency adapted wall assembly with an additional interior 2x6 wood construction. Through a detailed case study analysis focusing on the building’s core and shell, this research aims to identify the most effective wall assembly for …

Comparative Analysis Of Earth-Bermed And Conventional; Single-Family, Residential Homes In The Hudson Valley Region, Beacon, New York, Michael G. Patchen

Theses

This thesis is a comparative analysis of the environmental sustainability between two similar square-foot, single-family residential homes constructed as a bermed shelter and the conventional wood frame in the Hudson Valley Region, Beacon, New York. The research will focus on the two designs' embodied carbon, cost, and energy use. To quantify the environmental impact of these two construction methods, an in-depth understanding of the diverse host climate is necessary. Climate data and the results from the experiments are collected by performing life cycle, cost, and energy analysis, providing insights into the environmental implications of residential construction methods. The methodology will …

Body Study, Annaliese "Ace" Taylor

Theses

A paper chronicling the creation of my graduate thesis film, Body Study.

Toward Prototypical Vision Clustering, James Chenhao Liang

Theses

Over the past decades, deep learning methods have emerged as the predominant approach in computer vision. Most approaches rely on complex interactions among pixels, involving heavy computations. However, Human vision possesses a unique attention mechanism that selectively focuses on relevant parts of the visual field while disregarding irrelevant information. This can be likened to a clustering approach, in which individual pixel points are decomposed and reorganized into relevant concepts to address various tasks. This dissertation explores the frontier of vision clustering by integrating innovative prototypical learning with advanced Transformer architectures, which heralds a significant paradigm shift applied to vision clustering. …

Modeling Stormwater Driven Plastic Debris In The Lake Ontario Watershed, Jayson A. Kucharek

Theses

Stormwater-driven plastic debris has emerged as a significant contributor to environmental pollution, particularly in urbanized watersheds like the Lake Ontario basin. This study focuses on developing a comprehensive framework to quantify and predict anthropogenic debris (AD) inputs and transport pathways across Monroe County, NY, using stormwater systems as a key vector. Over two years, empirical data on plastic debris were collected from storm drains retrofitted with LittaTrap™ devices across urban and suburban areas. Debris was weighed, categorized by material and use, and paired with spatial and temporal variables such as land use, rainfall, temperature, and wind events. A Support Vector …

Pixel Personalities Ai, Patrick Casey

Theses

The Pixel Personality AI project explores how AI characters can be embedded in augmented reality (AR) environments to foster user interaction and storytelling. By situating AI personas within real-world contexts, the project examines how design principles, storytelling techniques, and user-centric technology can create engaging and intuitive experiences. Through iterative prototyping and design refinement, the project addressed challenges in aesthetic design, interface usability, and AR integration. The resulting low-poly aesthetic and customized visual filters enhance spatial storytelling while maintaining a balance between user focus and environmental immersion. This research highlights the potential of AI-driven narratives to reshape AR experiences, emphasizing user …

Leveraging Machine Learning For Advanced Malware Detection, Khalifa Al Habtoor

Theses

The detection of malware is an important challenge in the field of cybersecurity, which is demanding efficient and accurate solutions for making threats easier. This study is focused on the detection of malware by integrating a framework that uses a Mamdani fuzzy interference system (FIS) and diffusion techniques based on three different deep learning algorithms, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) for malware detection by using recent dataset. This was done by using their outputs through a voting and routing mechanism. The results of the study show that the fuzzy logic …

Selling The City: A Qualitative Study On The Image Construction Of Times Square Through Its Media Environment, Sheetal Pandey

Theses

As a globally recognized symbol of indulgent consumerism and urban spectacle, the media environment of New York City’s Times Square plays a pivotal role in constructing its iconic image. This qualitative study uses a media ecology framework to analyze how Times Square’s digital displays, interactive installations, and live performances create an immersive experience that informs one’s image of it. Through participant observation and visual content analysis, this study examines how visitors interact with Times Square’s media landscape and identifies recurring media-driven themes. Observations reveal that Times Square’s media ecosystem invites constant public interaction, actively engaging visitors in a feedback loop …

Social Media Intelligence: Responding To Crime And Violence In The Digital World, Chloe Lynn Sitton

Theses

The integration of social media into everyday life has transformed how crime is committed, communicated, and investigated. This capstone project examines the emerging field of social media intelligence and its growing influence on modern policing, surveillance, and the community. Drawing from sociological theory, law enforcement practice, legal analysis, and community-based research, this project offers a far-reaching interdisciplinary view of how social media is shaping crime and justice in the United States.

Rêvê La Drame, Pranjal Yogendra Sawai

Theses

Rêvê La Drame envisions the future of luxury branding by merging Audrey Hepburn's timeless elegance with the transformative capabilities of augmented reality (AR). This thesis addresses the growing demand for immersive and personalized consumer experiences, proposing a pioneering model that integrates traditional design principles with advanced technology to redefine engagement in the fashion industry. The project includes an innovative identity system featuring cinematic storytelling and AR interactions, such as a giant virtual shopping bag installation showcased at flagship locations like the MET. This thesis presents Rêve La Drame as a transformative approach to branding in the evolving luxury fashion landscape …

Rental Property Demand And Supply Analysis Using Machine Learning, Ahmed Amiri

Theses

The real estate market in Dubai is famous for its activity and stimulating potential due to the geographical position of the emirate, well-developed transport and legal framework. Timely determination and prediction of rental price is crucial for investors, property owners and managers, tenants and authorities in their decision making to maximize returns and ensure market stability. Traditional approaches are insufficient for the analysis of the temporal and spatial relations between property characteristics and market processes, which require the use of sophisticated machine learning algorithms. This paper aims to predict the rental prices of properties in Dubai using machine learning models …