Digital Commons Network^™

Identifying Opportunities For Nature-Based Solutions With Geospatialized Life Cycle Assessments And Fine-Scale Socioecological Data, Gabriela Shirkey, Annick Anctil, Ranjeet John, Venkatesh Kolluru, Leah Mungai, Herve Kashongwe, Lauren T. Cooper, Ilke Celik, Joshua B. Fisher, Jiquan Chen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) …

Ready, Set, Woes: A Narrative Inquiry Into Special Education Teacher Attrition By Transfer To General Education, Brent G. Collom

Teacher Education, Educational Leadership & Policy ETDs

Despite the prevalence of unfilled special education teaching positions nationwide, it is fair to ask whether there is truly a shortage of special education teachers (SETs). While SETs leave education at high rates, they are almost twice as likely to transfer to general education positions. Many former SETs are employed in schools yet outside of special education.

This narrative inquiry examined the stories of 10 former SETs who transferred to general education. This study found that former SETs continue to identify as teaching special education. Former SETs want general education teachers (GETs) and administrators to have training in special education …

Training Machine Learning Algorithms For The Transient Startup Of A Long-Life Modular Microreactor, Ahmad N. Shaheen

Nuclear Engineering ETDs

There is an increasing interest in developing and deploying small modular nuclear reactors (SMRs) and micro modular reactors (MMRs). They could be operated with minimal on-site personnel or remotely with a high degree of autonomy. This can be enabled through the use and application of Artificial Intelligence (AL) and Machine Learning (ML) algorithms and methods. The objective of the present work is to train machine learning algorithms for remote control mimicking the transient startup of the Very-Small, Long-LIfe, Modular (VSLLIM) microreactor. This walk-away safe microreactor design and a fully integrated transient model have been developed at the University of New …

Mapping Invasive Aquatic Plants Using Deep Learning Classification And Segmentation Models, Ruchitha Yadav Prakash

Theses and Dissertations

High-resolution imagery from Uncrewed Aerial Systems (UAS) equipped with multispec tral(MSI) and RGB sensors can be used for mapping invasive aquatic species. This research employs classification models like CNN, AlexNet, VGG16, ResNet, and DenseNet, alongside segmentation models such as FCN, U-Net, SegNet, DeepLabV3+, and Mask R-CNN, to analyze and visualize four invasive aquatic species including Cuban Bulrush (Oxycaryum cubense), Water Hyacinth (Eichhornia crassipes), Juncus (Juncus effusus), and Cattail (Typha latifolia). Among the tested models, ResNet (97.44% for RGB)andDenseNet(96.20%forMSI)exhibitedthehighest classification accuracies. For segmentation tasks, FCN (75.5% for RGB) and SegNet (79.6% for MSI) excelled. The study also examines the computational complexity …

A Comprehensive Performance Evaluation Of Proprietary And Open-Source Language Models In Closed And Open-Domain Tasks, Abhilash Kanduri

Theses and Dissertations

As the field of Natural Language Processing (NLP) continues to evolve, evaluating the performance of both proprietary and open-source language models has become increasingly critical. This research provides a comprehensive analysis of proprietary models like GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo, alongside open-source models such as FLAN-T5, GPT-Neo, and GPT-2. By leveraging traditional metrics like ROUGE and BLEU, as well as custom metrics including ReGrAde, Contextual Precision, and Faithfulness, the study evaluates these models across closed-domain tasks (e.g., factual question-answering) and open-domain tasks (e.g., creative writing and brainstorming). The proprietary models excelled in structured, fact-based tasks, while the open-source models …

The Impact Of Diversity, Equity, And Inclusion Trainings And Study/Work Abroad Experiences On The Ability Of Staff And Faculty To Build Systems Of Support For International Students, Alina Fasirovna Nigmatullina

Theses and Dissertations

The issue of effective communication with the international students and their comfortable adaptation play an important role in developing the U.S. higher educational system in the field of competition of educational services. The international student population benefits from higher education just as much as higher education benefits from them. If universities are willing to recruit and retain more international students, they must be sensitive to the perceptions, needs, and concerns of prospective and enrolled international students. In order to sustain this, staff and faculty have to be exposed to certain trainings and experiences that will allow them to gain basic …

Multi-Temporal Uav Remote Sensing Combined With Machine Learning For Estimating Cotton Yield, Amrit Shrestha

Theses and Dissertations

Accurate crop yield estimation early in season can help in identifying specific areas within a field that may require different management practices, thus enhancing overall efficiency and productivity. However, early estimation has been a challenging task mainly due to integrated complex association between genetic × environment × management factors. Over the decades, machine learning techniques, especially artificial neural network, has been widely adopted in conjunction with uncrewed aerial system (UAS) for high-throughput plant phenotyping and crop yield estimation. This study introduces the plus neural network (pNN) to incorporate temporal dynamics across different crop growth stages. Cotton field data from 2020-2023 …

Assembly And Analysis Of A Mobile Reactor System For The Continuous Conversion Of Landfill Gas To Sustainable Aviation Fuels, Benjamin Eston Gibens

Theses and Dissertations

Recent policy changes have shifted research and development to pursue technology that promotes a circular economy and net zero emissions by 2050. Current research is actively developing “drop-in” sustainable aviation fuels (SAF) that reduce emissions and are compatible with modern-day jet engines, mimicking conventional jet fuel's physical and chemical properties. While ensuring sustainable engine performance and operability using drop-in SAF is critical, several challenges remain in the economic outlook of SAF production. Biogas reforming and Fischer-Tropsch synthesis (FTS) can be used in series to convert landfill gas to SAF; however, novel design approaches must be considered to alleviate capital and …

Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing In Metal-Based Additive Manufacturing, Durant Hayes Fullington

Theses and Dissertations

This dissertation aims to develop effective methodologies towards enhanced intellectual property protections for data sharing frameworks in metal-based additive manufacturing (AM). Currently, many small-to-medium sized manufacturers face data availability challenges due to the prohibitive high cost to collect, process, and analyze large amounts of process-related data for AM. Because these manufactures rely heavily on small-scale data, it can be difficult for them to effectively train complex machine learning (ML) algorithms, which are commonly used for AM process monitoring. One popular solution is to develop collaborative data sharing frameworks, where multiple independent AM users can share their data to increase the …

Understanding Stream Litter Loading Through Watershed Characteristics, Elinor Reed Mallon

Theses and Dissertations

Litter, whether river-based, marine, or terrestrial, is an ever-increasing environmental and economic issue. However, litter in freshwater environments is studied less than in marine environments. To better understand factors impacting stream-transported floating litter, seven watershed characteristics were assessed across a network of thirty litter collection devices. The research objective for this study was to quantify litter loading and assess watershed characteristics relative to litter loading. Of the various watershed characteristics in this study, land cover classification had the greatest impact on the amount of litter collected from the Litter Gitters followed by median household income. Results from this study can …

Projecting Land Cover Changes And Impacts On Bird Conservation Using Geographic Information System, Remote Sensing And A Cellular Automata – Artificial Neural Network Model In Nairobi National Park, Kenya., Frank Juma Ong'ondo

Theses and Dissertations

This study examines land cover changes and their projected future impacts on bird species conservation in and around Nairobi National Park, Kenya. 2016 and 2023 Satellite imagery, analyzed through Google Earth Engine and the MOLUSCE plugin were used to assess changes in five land cover types: grassland, shrubland, forest, urban, and water. Bird population data from the Kenya Bird Map were used to evaluate birds' responses to land cover changes. Birds were categorized into five habitat guilds—grassland-dependent, shrubland-dependent, forest-dependent, water-dependent, and urban-dependent bird species. Between 2016 and 2023, grassland and shrubland decreased by 14.21% and 5.54%, respectively, and urban increased …

Exploring Single Particles Through Optical Trapping And Advanced Laser Spectroscopy Techniques, Haifa Hassan Alali

Theses and Dissertations

This dissertation explores the innovative integration of optical trapping (OT) with advanced laser spectroscopy techniques to investigate the physicochemical properties of single particles from a variety of atmospheric aerosols, such as bioaerosols, terrestrial dust, and extraterrestrial dust. Each technique offers unique insights, significantly enhancing our understanding of these critical atmospheric components. The first work focuses on employing OT in conjunction with cavity ringdown spectroscopy (OT-CRDS) to measure the single-particle extinction of interplanetary dust particles at ultraviolet wavelengths (~308 nm). This method allows for the stable trapping of individual dust particles in air, facilitating precise characterization with minimal external interference. Our …

Mass Timber Utilization In Architecture: Carbon Sequestration, Building Materials And Construction Practices, Jacob Alan Gines

Theses and Dissertations

The built environment must innovate and adopt new materials and construction practices in order to meet current and forecasted environmental challenges, economic uncertainties and construction pressures. The specification of mass timber materials and building assemblies will play a major role in addressing these issues. The objectives of this research are fourfold: 1) Develop a deeper understanding among construction professionals of the role mass timber buildings can have in greatly reducing CO2 emissions through the use of renewable forest products and the storage of carbon in buildings; 2) Provide insights into the utilization of mass timber products for architectural application that …

Evaluating The Emergent Wetland Plant Juncus Effusus As A Tool In Phytoremediation Of Nitrogen And Copper, Jacob Aaron Hockensmith

Theses and Dissertations

Eutrophication is an increasing issue around the globe, including the Lower Mississippi Alluvial Valley where excess nitrogen runs into the Mississippi River and subsequently the Gulf of Mexico. The restoration of wetlands is one method that has been developed to help reduce nitrogen runoff, however, species selection should be done carefully as species selected must not only remove nitrogen but be able to compete with established species. Chapter II of this thesis investigates whether J. effusus is a viable candidate for use in this role. Additionally, copper contamination around the globe is increasing due to a variety of anthropogenic sources. …

Assessing Plate Load Testing And Modulus Of Subgrade Reaction Determination For Pavements, Jami Lynn Rushing

Theses and Dissertations

This thesis aims to: 1) determine the effect of plate size on the modulus of subgrade reaction (k), 2) investigate the differences between the ASTM D1196-21 and CRD-C 655-95 plate load test methods, and 3) develop new effective k curves. 150 plate load tests were executed on three subgrade materials under varying base course thicknesses. Plate load testing was designed to evaluate various plate sizes and testing standards (e.g., the military standard – CRD-C 655-96 and the ASTM standard – ASTM D1196-21). By performing plate load tests on varying base course thicknesses, newly developed effective k curves were developed from …

Beyond Clear Paths: Training With Neural Style Transfer And Auto-Augmentation For Domain-Generalized Segmentation Of Soiled Images, Jacob Randall Kutch

Theses and Dissertations

The use of image segmentation within mission-critical autonomous vehicle applications is contingent on reliability of visual sensors, which may become significantly compromised by environmental occlusions such as mud, water, dust, or ice. This thesis explores semantic segmentation techniques tailored for identifying occluded regions, addressing the limitations of conventional methods under unpredictable real-world conditions. Given the scarcity of training datasets with realistic occlusions and the resulting reliance on synthetic data, this research leverages style transfer augmentations and a novel augmentation policy optimization framework to diversify training datasets and improve model generalization. A newly-curated dataset of naturally occurring occlusions evaluates the efficacy …

The Plastics Crisis: Responsible Recycling In Civil Engineering And Infrastructure, Jason Howell Stewart

Theses and Dissertations

A global plastics crisis exists with around 400 million metric tons (MMT) of plastics production and 350 MMT of plastics waste generated annually around the globe. Plastics are durable and essentially non-biodegradable, so they accumulate in both terrestrial and marine environments as pollution and within landfills without breaking down over time. Plastics are ubiquitous in 21st-century society and culture, comprising essential elements in most industries including packaging, transportation, electrical/electronics, and building/construction. The role of civil engineering and infrastructure in addressing the plastics crisis was specifically explored. Responsible plastics recycling yields products with improved engineering properties, performance characteristics, marketability, and/or manufacturing …

Factors Influencing Quality Of Citizen Science-Collected Litter Data And The Retention Of Recruited Citizen Scientists, Jessi Alexandria James-Barry

Theses and Dissertations

There are many benefits to using citizen science in scientific research, however, there are several perceived limitations. One being that citizen science data are often viewed as inferior or unusable by the broader science community. A primary concern to the usability and accuracy of this data depends on the level of training a participant receives. Another limitation is the recruitment and retention of volunteers participating in the data collection process. To further understand how training level affects the accuracy of citizen science and how demographics may influence participation, this study evaluated 73 volunteers trained in two different marine debris data …

Plastic Contaminants Detection And Classification In Seed Cotton Using Customed Design Feeder Separator Unit And Convolutional Neural Network, Jonathan Harjono

Theses and Dissertations

The thesis presents an application of a convolutional neural network (CNN) to detect and classify plastic contaminants in seed cotton in real-time, in a ginning environment. A multi-layered CNN was developed and used to detect plastic contaminants from images captured by a universal serial bus (USB) camera, in a flowing cotton stream, with an artificial lighting system. The CNN was trained using a collection of images captured in the dynamic setting that simulated real-time cotton flow using a custom design feeder system. The CNN was trained in Google Colaboratory (Colab) environment. After the training was completed, it was then converted …

A Case Against Exclusive Reliance On Volumetric Mixture Characterization For Future Asphalt Pavements And The Advancement Of A Viable Alternative, Jonathan Randy Easterling

Theses and Dissertations

Volumetric properties have been the cornerstone of asphalt mixture design and control dating back to the early 20th century. However, social and economic drivers have caused the asphalt industry to make changes in materials and processes used to produce mixtures that have stretched the limits of volumetric centric methodologies. The primary objectives of this dissertation were to present an extensive case on how volumetrics is limited in their ability to characterize asphalt mixtures and to advance the body of knowledge of a viable alternative. State agency specifications were examined and found that Departments of Transportation (DOTs) were using asphalt volumetric …

An Open-Source, Student-Centric Approach To The Cyber Kill Chain, Justin Lane Wooten

Theses and Dissertations

The cybersecurity landscape demands professionals with practical skills and a deep understanding of attack methodologies. However, many institutions face significant challenges in providing comprehensive cybersecurity education due to the high costs associated with commercial tools and platforms. This thesis presents a student-centric, open-source curriculum for teaching the Cyber Kill Chain, designed to bridge the gap between theoretical knowledge and real-world application while addressing the financial constraints faced by many educational institutions. Our approach leverages freely available tools and hands-on exercises to cover each phase of the Cyber Kill Chain, emphasizing ethical considerations and collaborative learning. We detail the curriculum development …

Bridging Scales Integrating Satellite Derived With Airborne And Uas-Collected Bathymetry For Coastal And Inland Water Management, Md Salman Bashit

Theses and Dissertations

This study makes important scientific contributions by improving remote sensing methods for collecting bathymetric data. It demonstrates an improved and novel approach to utilizing Sentinel-2 reflectance data to extract satellite-derived bathymetry (SDB), validated against data from airborne LiDAR bathymetry (ALB). The study looks at how well SDB works in several coastal areas of the United States. It uses the Normalized Difference Turbidity Index (NDTI) and Total Suspended Solids (TSS) to see how water quality affects the accuracy of SDB. The study also analyzes how unoccupied aerial systems (UAS) can be combined with echo sounder systems to derive bathymetric maps with …

Invasive Bigheaded Carp Distribution Patterns In Oxbow Lakes Of The Lower Mississippi Alluvial Valley, Michaela Ann Palmieri

Theses and Dissertations

Large populations of Silver Carp (Hypophthalmichthys molitrix) and Bighead Carp (H. nobilis), collectively called bigheaded carps, may have significant impacts where they are invasive. In the Lower Mississippi Alluvial Valley (LMAV), bigheaded carps have been documented in major rivers; however, knowledge of their distribution in oxbow lakes is lacking. Species distribution models are tools that can be used to estimate species distribution with presence data and environmental variables. As a cost-effective alternative to onsite sampling, I administered a questionnaire to biologists to inventory bigheaded carp presence and obtained environmental data from existing datasets. I used Maximum Entropy (Maxent) to illustrate …

Effects Of Turbulence On Scramjet Engines Combustion, Mohamed En-Nali

Theses and Dissertations

In the present work, we aim to investigate the predictive capabilities of low and high-fidelity turbulence models and understand how they perform in complex conditions in a scramjet engine. In this study, we use the DLR experiments to present a comparative performance assessment of low to high fidelity turbulence models. The DLR case is interesting since it exhibits turbulence due to wall effects as well as due to shear layer. Results show relatively good agreement when compared against the validation data set from the experiment. DHRL was able to resolve more turbulence structures compared to all other models. HRL showed …

Physics-Based And Data-Driven Constitutive Modeling Of Unsaturated Soils Under Multi-Physics Loading Conditions, Mohsen Ajdari

Theses and Dissertations

Understanding the behavior of unsaturated soils under multi-physics loading is crucial for addressing several challenges related to emerging geo-energy technologies, climate change, and geohazard mitigation. The main objective of this research is to enhance the state of the art for modeling unsaturated soils under multi-physics loading conditions through physics-based and data-driven approaches. Toward this objective, this dissertation is divided into two distinct yet interrelated parts. In the first part (Chapters 2, 3, and 4), thermodynamic principles are employed to develop new constitutive functions to describe soil suction and stress-dilatancy of unsaturated soils under temperature-dependent conditions. Building upon the insights gained …

Numerical Predictions Of Turbulent Heat Transfer In Liquid Metal Flows, Mohammed Elmellouki

Theses and Dissertations

Fast breeder nuclear reactors use liquid metals such as Sodium (Na), Sodium-Potassium (Na-K), and Lead (Pb) as coolants since these liquids have high thermal conductivity, high thermal diffusivity, and lower heat capacity compared to water and air, thus involving low Prandtl numbers (Pr). However, liquid metals solidify at room temperature which poses challenges for experimental studies, making computational fluid dynamics (CFD) is considered a valuable analysis and design tool. Furthermore, the accurate modeling of turbulent heat transfer in low Pr flows remains one of the main challenges due to the gap between momentum and turbulent thermal diffusion. The study aims …

Examining Special Education Programming Through The Lens Of Upper Elementary And High School General Education Teachers In Select Black Rural Schools In Mississippi - Do They Feel Prepared To Serve?, Natasha Michelle Porter

Theses and Dissertations

The present study investigated the perceptions of upper elementary and high school general education teachers towards special education programming and whether they felt prepared to meet the needs of students with Individualized Education Plans. The literature review provided a comprehensive synthesis of existing research on the topic researched, offering an in-depth exploration of key themes, trends, and findings in the relevant academic literature. It critically examined assorted studies, theories, and methodologies researchers employ, identifying gaps and areas of consensus. The purpose of this study was to build from the foundation set by existing bodies of related literature, to gain formal …

Multi-Cloud Identity Security Utilizing Self-Sovereign Identity, Morgan Lee Reece

Theses and Dissertations

With the increasing use of multi-cloud environments, security professionals face challenges in configuration, management, and integration due to uneven security capabilities and features among providers. As a result, a fragmented approach toward security has been observed, leading to new attack vectors and potential vulnerabilities. Other research has focused on single-cloud platforms or specific applications of multi-cloud environments. Therefore, there is a need for a holistic security and vulnerability assessment and defense strategy that applies to multi-cloud platforms. This dissertation explores risk and vulnerability analysis to identify attack vectors from software, hardware, and the network, as well as interoperability security issues …

Impact Of Cascading Optical Processes On Spectroscopic Quantification Of Absorption And Scattering Properties Of Samples, Pathum Dilshan De Silva Wathudura

Theses and Dissertations

Light absorption and scattering are fundamental properties of matter, particularly significant in nanoscale materials. This study explores how cascading optical processes affect the experimental measurement of absorption and scattering intensities, along with scattering depolarization, in samples containing absorbers and scatterers. The experimental UV–vis spectrum results from the combination of absorption and scattering extinction spectra. However, the maximum measurable extinction may be limited by forward scattered light. Light absorption decreases the intensity of scattered light and influences scattering depolarization. While scattering can reduce absorption along the optical path to the detector, sufficient absorption of the scattered light may counterbalance this effect, …

Analysis Of Cortical Evoked Auditory Response Detection In Adults Using Machine Learning, Pranavi Beerelli

Theses and Dissertations

This study focuses on the use of machine learning (ML) techniques to automate the detection of Cortical Evoked Auditory Responses (CEARs), which are key in understanding how the auditory cortex processes sound stimuli. Traditionally, analyzing these auditory responses has relied on manual interpretation by audiologists, a process that can introduce variability and human error, particularly in complex cases. To address this challenge, the research utilizes advanced deep learning models, including Convolutional Neural Networks (CNNs), Long Short Term Memory (LSTM) networks, and Bidirectional LSTM (BiLSTM) architectures, to analyze Electroencephalography (EEG) data and classify the presence or absence of auditory responses automatically. …