Digital Commons Network^™

Exploring Denitrification In Wetland Nitrogen Cycling And Biostimulant-Based Agricultural Strategies To Improve Ecosystem Health, Alexander Bechtel

Theses

The overuse of fertilizers has doubled the amount of reactive nitrogen in the environment. Agricultural runoff then carries these pollutants into the waterways eventually causing severe ecological damage such as the Gulf of Mexico dead zone. Nitrogen plays an important role in all life on this planet, here we describe two complementary projects that investigate ways to mitigate nitrogen pollution. The first project investigates denitrification rates in soil after the Len Small Levee breached in 2016 which reconnected the Dogtooth Bend Floodplain with the Mississippi briefly. The denitrification process that began in the hydrologically activated soils was hypothesized to be …

Embedded Sensor Design For Non-Robust Delay Testing, Presh Jayawardana Manannaidelage

Theses

Current delay testing methodologies for integrated circuits face critical limitations, asrobust tests remain unachievable for most paths, forcing reliance on Non-Robust (NR) tests that suffer from unrealistic single-fault assumption, the path under test non being sensitized, and vulnerability to hazard-induced errors. This thesis propose a built-in sen- sor to detect delayed hazards and a sensor to diagnose circuits in the presence of those hazards resulting reliable detection. This thesis intends to propose 2 sensors for non-robust test-based monitoring and test- ing. The first sensor discussed is for IC testing with NR tests. This sensor is capable of detecting any full-swing …

Relationship Between Semi-Aquatic Mammal Occupancy And Particulate Carbon, Nitrogen, And Phosphorus Dynamics In Freshwater Ecosystems, Madison H. Stokoski

Theses

Semi-aquatic mammals such as beavers (Castor canadensis) and muskrats (Ondatra zibethicus) can influence carbon (C), nitrogen (N) and phosphorus (P) dynamics in freshwater systems. While the effect of beavers, in particular, are typically attributed to their dam and lodge building behaviors, these animals do not always build these structures. It’s possible that other, non-damming behaviors (e.g. foraging and burrowing) may influence the availability of nutrients as well. To assess this possibility, we surveyed 54 lentic and lotic waterbodies across Southern Illinois and investigated the possibility that beaver and muskrat occupancy improved our ability to explain variation in nutrient availability across …

A Comprehensive Digital Marketing Strategy Guide For Independent Musicians, William Elree Hilburn

Theses

Creating and implementing a sound digital marketing strategy is a crucial element to consider as an independent musician. In this thesis report and the strategy guide that follows, a number of current digital marketing strategies are discussed at length. The strategies that are discussed in this report and within the strategy guide have been gleaned through semi-structured qualitative interviews with two separate up-and-coming music artists. The information shared by these case studies has been documented and synthesised into this report, as well as, into a comprehensive strategy guide that has been written to aid fledgling music artists in their digital …

Identity And Representation In Contemporary Art: An Inclusive 400/500-Level Art History Seminar Course, Laura E. Franz

Theses

This project is an upper-level art history seminar addressing identity and representation – specifically related to race, ethnicity, gender, and sexuality – in contemporary art. Primarily a discussion-based course, the course is focused on inclusivity and is highly structured, with weekly low-stakes assignments that provide students with ample opportunities to practice engaging with academic texts. Designed for students with varying levels of academic skills, it is built around current non-academic articles that students select via an online survey. Students then “unpack” the “big ideas” in each of the four chosen non-academic articles via a cluster of academic readings and videos …

Frameworks Of Genius: Fresco, Labor, Scaffolding, And Patronage In The Making Of Michelangelo's Sistine Chapel Ceiling, Jackelyn Eileen Adkins

Theses

This thesis examines how the materiality of production and the patronage of Pope Julius II influenced the visual and conceptual outcome of Michelangelo’s ceiling frescoes in the Sistine Chapel. It argues the physical demands of the fresco medium, the architectural constraints of the chapel, and the material infrastructure, such as the pigments, scaffolding, and spatial dynamics related to the political, theological, and ideological imperatives of papal authority. The materials served as a symbolic extension of Pope Julius II’s ambitions, embedding his message directly into the frescoes. By foregrounding the complex web of labor and materials that supported the project, this …

Echo’S Repertoire: Performing Science Fiction And Trans Care Models, Juniper Blue

Theses

Echo’s Repertoire is a mixture of a passion piece and a call for more work with performing science fiction. It focuses on interpersonal communication within trans studies and the experiences of transgender individuals and myself. Echo’s Repertoire is also an example of the Lyrical Model proposed by Awkward-Rich as a new model for trans affirming speech. The show is laid out non-linearly and follows along with Echo as he starts to build new relationships with the advice of his spaceship ai, Eep, who is a previous version of himself prior to transformation (transition).

Surface Water And Groundwater Interactions Within The Riparian Wetlands Of The Mississippi River Dogtooth Bend Southern Illinois, Adeola Jacob Fagorola

Theses

Riparian wetlands serve as transition areas connecting terrestrial and aquatic ecosystems, providing vital functions in maintaining water quality and habitat for diverse array of organisms. A comprehensive understanding of the interaction between surface water (SW) and groundwater (GW) in riparian wetlands is crucial for the management of these ecologically significant habitats. However, the interactions between SW and GW are often only partially constrained particularly with respect to their effects on water chemistry and nutrient cycling.In this study I utilized geochemical and hydrological approaches to examine the dynamics of surface water and groundwater interactions within the riparian wetlands of the Dogtooth …

Comprehensive Drought Analysis: Machine Learning-Based Meterological Drought Forecasting And Pca-Driven Agricultural Drought Monitoring., Bishal Poudel

Theses

Drought is a long-term natural disaster that affects many aspects of human life from health, water supply to ecosystems and agriculture. Drought’s occurrence and intensity has increased in recent years because of global warming, which urges for proper and accurate monitoring and forecasting of drought. For better understanding of droughts, this study uses two approaches. In first part, the study uses the historical temperature and precipitation data from period of 1960 to 2021 as input features for three different machine learning models – Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest (RF). The research focuses on calculating …

Prediction Of Geometric Deviation In Additively Manufactured Tpms Lattice Structures Using Non-Destructive Evaluation And Conditional Generative Adversarial Networks, Prateek Neupane

Theses

Metal 3D printing has emerged as a widely used additive manufacturing method, finding applications across numerous industries and research areas. However, its application is often hindered by geometric inaccuracies and surface quality issues resulting from the complex interplay of laser power, melt pool behavior, and cooling characteristics. These inconsistencies have a significant impact on the design and functionality of printed parts, affecting structural integrity and dimensional accuracy. Thus, an effective data-driven approach is crucial to predict these deviations before manufacturing. This study proposes a methodology that incorporates Non-destructive evaluation techniques, like in-situ monitoring and X-ray CT scan, with Conditional Generative …

Effect Of Water-Deficit Stress On Cannabis Sativa Production And Secondary Metabolite Levels, Shiksha Sharma

Theses

Cannabis (Cannabis sativa L.) is an emerging high-value crop that belongs to the Cannabaceae family and the genus Cannabis, which is known to produce more than 200 cannabinoids. Although genetic variation is the main factor in cannabinoid production, water-deficit stress is believed to induce its production. The objective of this master’s thesis was to determine the effects of water-deficit stress frequencies and timing on growth, physiology, yield, and cannabinoid concentration in cannabis. Heidi cultivars were planted in a controlled environmental growth unit. One period of water-deficit stress was found to produce the lowest concentration of total CBD and THC. In …

Flood Susceptibility Assessment Through Gis Integrated Analytical Hierarchy Process And Machine Learning Models, Sujan Shrestha

Theses

Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both natural environments and human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, and changes in land use. Flood susceptibility maps help identify at-risk areas, supporting informed decisions in disaster preparedness, risk management, and mitigation. This study aims to generate a flood susceptibility map for two regions: Davidson County of Tennessee using an integrated geographic information system (GIS) and analytical hierarchical process (AHP), and the Briar Creek watershed of Mecklenburg County, North Carolina using an integrated GIS and machine …

Accelerating The Degradation Of Biodegradable Mulch Films In Soil And Compost Environments, Harshal Jayesh Kansara

Theses

The incomplete degradation of biodegradable mulch films (BMFs) in agricultural soils poses environmental challenges, with persistent plastic residues impacting soil health. This dissertation investigates the use of bioaugmentation with P. guariconensis to enhance BMF degradation under laboratory, raised bed, and field conditions. The research focuses on optimizing microbial delivery methods, evaluating the efficacy of drip and spray bioaugmentation techniques, and assessing mass loss as a primary metric for degradation. Laboratory experiments established proof-of-concept by demonstrating enhanced carbon mineralization, weight loss, and fragmentation of BMFs under bioaugmented conditions. These findings were translated to field-scale trials, where bioaugmentation treatments consistently outperformed untreated …

Meshed Trees: A Framework For Resilient Network Algorithms And Protocols, Peter Willis

Theses

The continued growth of computer networks in both size and complexity presents challenges for the control protocols that are tasked with maintaining optimal data-forwarding paths. These protocols commonly rely on shortest-path algorithms to determine where network data should be propagated and how it should be analyzed for inclusion in forwarding tables. However, problems arise during reconvergence, the process in which devices rediscover optimal paths following a network failure. Because control protocols were built decades ago for the networks of that era, the existing shortest-path algorithms utilized were designed for problems before the advent of modern computer networks. This resulted in …

Exploring Human Perception And Cognition In Expressing And Understanding Mechanical Designs, Yan-Ting Chen

Theses

Effective communication of mechanical designs through technical drawings requires geometric accuracy, efficiency, and an understanding of human perception and cognition. Although advances in computer-aided design (CAD) software have improved drawing precision and automation, current tools often overlook the spatial reasoning processes that users employ to interpret these representations. This study seeks to improve the accuracy and efficiency of human-computer interaction in CAD environments by examining how individuals perceive and interpret three-dimensional mechanical components within the context of technical drawings. A key focus is the identification of canonical and optimal views that align with intuitive human understanding. Through a series of …

Playa Sediment Bioaccessibility Presents Previously Unknown Risks To Population Health In A Water-Stressed Region Undergoing Lake Desiccation: Salton Sea, Usa, Jordan Jaeger

Theses

Globally, drylands are expanding, and endorheic basins are in rapid decline. Saline lake desiccation exposes lakebed playa likely to become dust, posing potential health risks to surrounding communities. Studies investigating health risks from playa dust exposure often focus on health effects associated with the presence of airborne particulates, but fewer studies investigate health risks associated with dust source chemistry. This study examines dust source particle composition in a desiccating inland sea in a water-stressed agricultural region of California. Specifically, chemical bioaccessibility of bound trace elements uncovers risks to children, adults, and agricultural worker health. Arsenic exposure via sediment ingestion poses …

The World Is Beautiful, Chelsea Demott Wildey

Theses

My thesis, The World is Beautiful is a short, digitally animated film that follows the journey of a jaded employee working at a dystopian fishery. The intention of this piece was to tell a well-paced, coherent story that also served as an allegory to spark verbal discourse in an audience. As a surface level story, the film portrays a working protagonist who has been forced to remain seated at her desk by a mechanical chair. She, presumably, has been monotonously pressing icons on a screen for her entire life until something catches her eye and prompts her to break free …

Advancing Applications Of Deep Learning On Network Traffic Analysis And Fingerprinting, Nate Mathews

Theses

The growing reliance on encrypted communication networks and privacy-preserving technologies, such as Tor, has intensified the demand for advanced defenses against traffic analysis attacks. Although encryption conceals content, the exposure of metadata—such as timing, packet size, and traffic volume—remains a significant vulnerability, allowing adversaries to infer private user behavior and visited websites. This dissertation addresses the limitations of existing analysis by advancing the application of deep learning techniques across multiple domains of traffic analysis and fingerprinting. The first major contribution is a comprehensive evaluation of current website fingerprinting defenses, revealing critical weaknesses against sophisticated modern attacks. Building on this foundation, …

Three-Dimensional Cfd Analyses Of Natural Circulation In A Pressurized Water Reactor During A Loss Of Coolant Accident, Arad Dehestany

Theses

In this research, ANSYS FLUENT simulations will be performed on natural circulation cooling performance during loss of coolant accident on the semi-scale Mod-2A geometry. Natural circulation experiments were performed in the semi-scale Mod-2A test facility which is a small-scale model of the primary system of a four-loop PWR nuclear power generating plant. The CFD results are validated using the tests done in the facility. The scope of the research is to understand the flow, temperature distribution, inventory coolant losses, and pressure drop in the system. These findings can provide insights into the performance of such systems and identify potential improvements …

Experimental Investigation: Performance Of Ranque–Hilsch Vortex Tubes Under Various Surface Boundary Conditions, Ahmad Al-Najjar

Theses

The Ranque–Hilsch vortex tube (RHVT) is a passive thermofluid device that splits compressed gas into simultaneous cold and hot streams through strong swirling flow inside a slender tube, without moving parts. This study experimentally examines how external boundary conditions applied to the tube wall influence RHVT performance. Three wall conditions were imposed: (i) externally cooled (cooling), (ii) externally heated (heating), and (iii) adiabatic (insulated). Tests were conducted with air over an inlet pressure range of 2–6 bar. The primary objective was to understand the extent to which wall thermal condition modifies temperature separation and energy efficiency. Performance was quantified using …

Evaluating Large Language Models For Automated Cv Ranking: A Hybrid Embedding Approach For Enhanced Recruitment, Sarah Mohamed Alhindaassi

Theses

Increasing numbers of applications have revealed limitations in legacy keyword-filtering-based Applicant Tracking Systems (ATS), which commonly overlook candidate potential and ignore contextual or transferable skills. Advances in Natural Language Processing (NLP) and Large Language Models (LLMs) offer an exhilarating alternative, supporting context-sensitive and human-crafted reasoning in candidate evaluation. This thesis systematically evaluates four classes of approaches, lexical models, embedding-based methods, Large Language Models (LLMs), and hybrid ensembles, for automation of Curriculum Vitae (CV) to Job Description (JD) matching without exploiting prior annotations or annotations at match time. Using a combination of publicly available datasets and real-world sample data covering three …

Detecting Data Poisoning Attacks In Medical Imaging: A Study On Chest X-Ray Classification Tasks, Akhila Abdulla Asgar

Theses

This thesis examines the vulnerability of AI medical imaging models to adversarial threats, with a specific focus on data poisoning attacks in chest X-ray classification. The study begins with a Systematic Literature Review (SLR) to assess the existing adversarial attacks and defenses in medical imaging, revealing a significant research gap in studies exploring data poisoning attacks in the medical domain. Based on our literature search, an efficient and lightweight defense, namely friendly noise defense, against data poisoning has not been investigated in medical imaging classification tasks. Hence, in this work, we investigated its effectiveness on the chest X-ray dataset, and …

Graphic Design For Visual Narratives: The Semiotics Of Diegetic Retrofuturism, Brooke Luke Ballard

Theses

While semiotics, diegesis, and retrofuturism have all been discussed at length in academia, it is uncommon to find the synthesis of all three. When these concepts are combined, it forms what I argue is a new genre of graphic design now prevalent enough in contemporary media to warrant definition and analysis. This thesis first explores the theories of visual semiotics, narrative diegesis, and retrofuturistic aesthetics individually before uniting them as a new design genre. Several candidates for this design classification will then be examined in case studies that meet the criteria of 1) containing a visual language that a modern …

Enhanced Air Hockey Robot Performance Through Adaptive Control Algorithim Using Ai-Based Hierarechal Decicion Archeticture, Ayham Majed Salim

Theses

This thesis presents the development of an intelligent air hockey robot that combines precise mechanical design, computer vision, and adaptive control within an AI-based hierarchical decision architecture. The system integrates synchronized stepper motors, high-speed image processing, and a real-time decision framework to achieve competitive gameplay performance. The robot detects the puck using adaptive HSV color segmentation, supported by dynamic calibration that maintains accuracy under different lighting conditions. A two-stage trajectory prediction model, based on exponential decay velocity estimation, enables anticipation of puck motion and improves response time during fast gameplay.

At the decision level, a fuzzy-logic supervisor governs the robot’s …

Enhanced Privacy Preserving Healthcare Data Management With Federated Learning Using Homomorphic Encryption, Omar Abdulla Ali

Theses

Federated Learning (FL) is a decentralized approach of machine learning on multiple clients jointly training models without sharing their raw data, which drastically improves privacy and enhance protection against security breach. This is particularly critical in the healthcare sector, where hospitals and medical institutions are often unable to exchange patient records due to strict privacy regulations and data-management policies. However, there is still a risk of privacy breach when clients send their model updates to the central server, because if a model update is intercepted or analyzed by a malicious entity, it could be used to recover sensitive data using …

Determination Of Variations In Orbital Parameters Of Sample Of Satellites Through Spacecraft Tracking, Asma Ali Alasmari

Theses

The continues increasing density of Resident Space Objects (RSOs) in Earth’s orbit highlights the crucial need for Space Situational Awareness (SSA). This thesis studies the orbital changes in two regions, active low Earth orbit (LEO) satellites and inactive geostationary Earth orbit (GEO) satellites. For LEO satellites we used publicly available data (two line element TLE from Space-Track) and ASTRIAGraph. We verified the orbital elements series and time ordered them, applied a Hampel (median+MAD) mask to semi-major axis, eccentricity vector and inclination to find outliers and exclude them from event detection. The events are then detected using time normalized slopes and …

Enhancing It Security Management With An Advanced Intrusion Detection System Based On Machine Learning And Explainable Ai, Hanan Aslam Al Zubaidi

Theses

The fast changing landscape of cyber threats continues to challenge the development of strong and reliable security frameworks for IT management systems. Traditional defense tools, such as Intrusion Detection Systems (IDS), often struggle to keep up with today's advanced and constantly evolving attack methods. This thesis explores these ongoing challenges and looks into how machine learning (ML) and explainable artificial intelligence (XAI) can be used to boost IDS performance.

The research outlines a smart, adaptive system that combines supervised learning for real-time threat detection, unsupervised models for anomaly analysis, and proactive defense strategies. The goal is to improve detection accuracy, …

Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi

Theses

Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). While commercial electromagnetic (EM) solvers offer robust optimization capabilities, they often operate as "black boxes" without providing physical insights into parameter interdependencies. Furthermore, this thesis focuses on the specific scenario where the antenna input impedance is purely real. To address the lack of explicit design relationships for these specific conditions, this thesis develops and comparatively evaluates artificial intelligence (AI) models for QWT width …

Microstructural And Mechanical Characterization Of Aa6082 /Sic/Al2o3 Hybrid Nano Composite Fabricated By Ultrasonic Assisted Stir Casting, Anasmon Koderi Valappil

Theses

The utilization of aluminium alloys has increased rapidly in past decades due to the increasing demand for lightweight and high-performance materials. Among the popular aluminium alloys, AA6082 is widely favoured for its excellent combination of strength, corrosion resistance, and machinability. Most previous work, however, has concentrated on either on micro scale reinforcement or on single ceramic particles, leaving very few experimental studies on the use of hybrid nano reinforcement in AA6082. Therefore, to further enhance its mechanical properties without compromising its inherent advantages, hybrid metal matrix composites were developed using various nano particulates as reinforcements. In this current study, AA6082-based …

Advancing Security Safeguards In Large Language Models Through Multi-Agent Systems, Mohammed Rashed Alnuaimi

Theses

This thesis focused on enhancing the safe use of Large Language Model (LLM) through the innovative use of a Multi-Agent System (MAS). As LLMs like ChatGPT became essential to our everyday interactions, the need to maintain the safe use of these systems increased. This research thoroughly assessed the current security measures in place for LLM, pointed out their limitations and developed new and more effective security strategies. The core of the proposed solution was a MAS designed to ensure that all data processed by LLM met guidelines including Privacy, Confidentiality, and Ethical standards before reaching the user. The system involved …