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The Interwoven Dynamics Of Climate, Fire, Resilience And Orangutan Survival In Central Kalimantan’S Peat Swamp Forest, Putu Pujiantari
The Interwoven Dynamics Of Climate, Fire, Resilience And Orangutan Survival In Central Kalimantan’S Peat Swamp Forest, Putu Pujiantari
Graduate Theses and Dissertations
Tropical peat swamp forests are globally significant carbon reservoirs and biodiversity strongholds, yet they face escalating threats from climate change, fire, and anthropogenic disturbances. This dissertation investigates the interwoven dynamics of climate, fire, forest resilience, and orangutan survival in Central Kalimantan, Indonesia, a region which was transformed by the failed Mega Rice Project and recurrent catastrophic wildfires for decades. Using a multi-scale approach that integrates remote sensing time-series analysis (2001–2024),nlandscape-scale disturbance mapping (2005–2025), and fine-scale movement ecology, this research tests three core hypotheses: (1) moisture availability is the dominant climatic driver of wildfire activity, operating through non-linear thresholds; (2) post-fire …
Item Response Theory Evaluation Of Mental Health Sentiment Scales, Muhammad Amzad Hossain
Item Response Theory Evaluation Of Mental Health Sentiment Scales, Muhammad Amzad Hossain
Graduate Theses and Dissertations
Mental health is an essential part of overall well-being. Accurate measurement of constructs such as loneliness, anxiety, depression, and life satisfaction is extremely important in research and practice. Traditional approaches based on Classical Test Theory (CTT) are limited. They rely on total test scores and assume constant measurement error across individuals. They may not reflect true variability in measurement precision (Zein & Akhtar, 2025; Marvianto, 2023). In contrast, Item Response Theory (IRT) provides an advanced approach by examining item-level performance. It models the relationship between latent traits and responses (Zein & Akhtar, 2025 ). To address these limitations, this study …
Cosmic Chirps: Studies In The Evolution And Detection Of Gravitational Waves From Compact Binary Systems, Calla Irene Bassett Bigg
Cosmic Chirps: Studies In The Evolution And Detection Of Gravitational Waves From Compact Binary Systems, Calla Irene Bassett Bigg
Graduate Theses and Dissertations
This dissertation will go over three projects that have to do with gravitational wave mechanics and history. The first project is about investigating computationally cheaper approximation methods for modeling EMRI (extreme mass ratio inspiral) orbits using interpolation. Two codes are interpolated together for full coverage of the parameter space. This interpolation has yet to be tested for accuracy but the preliminary outlook is positive. This may well be a useful tool for studying EMRIs. The second project is investigating the origins of the term “chirp mass”, where chirp mass is a combination of the two masses in a binary that …
Beyond Semantic Matching: Integrating Graph Structures, Boolean Logic, And Interactive Aggregation In Modern Retrieval, Quan Mai
Graduate Theses and Dissertations
Modern Natural Language Processing (NLP) and Information Retrieval (IR) systems have achieved remarkable success in semantic understanding; however, they continue to struggle with complex logical reasoning, structural interactions, and dynamic aggregation. This dissertation presents a comprehensive framework to enhance the structural, logical, and interactive capabilities of language models and retrieval systems across four progressive studies. First, we address the challenge of modeling dynamic conversational logic in online debates. We introduce a Sequence Graph Network (SGN) that captures the temporal and interactive exchange of ideas—such as counterarguments and reinforcements—by updating node features sequentially through a novel Sequence Graph Attention (SGA) layer. …
Soil Moisture Regime Effects On Greenhouse Gas Emissions In A Native Tallgrass Prairie In The Ozark Highlands, Thomas William Dockery
Soil Moisture Regime Effects On Greenhouse Gas Emissions In A Native Tallgrass Prairie In The Ozark Highlands, Thomas William Dockery
Graduate Theses and Dissertations
The Ozark Highlands is an ecoregion in the mid-southern portion of the United States that is characterized by a mosaic of tallgrass prairies, oak (Quercus spp.) savannas, and oak-hickory (Carya spp.) forests, which represents a unique biophysical transition zone between the relatively dry grasslands of the west and the humid forests of the southeast. Quantifying greenhouse gas (GHG) emissions, namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), from natural, undisturbed ecosystems is critical to understanding atmospheric warming and climate-change implications. The objective of this study was to simultaneously evaluate CO2, CH4, and N2O emissions in an aquic and …
Potassium Fertilization Timing And Critical Stalk Potassium Concentration As Tools To Improve Corn Production, Gabriela Andrade Leite Mengez
Potassium Fertilization Timing And Critical Stalk Potassium Concentration As Tools To Improve Corn Production, Gabriela Andrade Leite Mengez
Graduate Theses and Dissertations
Potassium (K) is a common yield-limiting nutrient in Mid-Southern U.S. corn (Zea mays L.) production, emphasizing the importance of effective diagnostic tools to support fertilizer decision-making. This study integrated two approaches to improve K management in irrigated corn systems: (i) evaluating K fertilization timing to identify in-season opportunities for correcting K deficiency, and (ii) developing a corn stalk-based diagnostic test to assess end-of-season K and nitrate-nitrogen (NO₃-N) status and fertilizer adequacy. Seven (2024-2025) and eight (2023-2024) field trials were conducted across Arkansas for the K application timing and stalk testing studies, respectively. For the K timing study, fertilizer-K (112 kg …
Benchmarking Current Progress In 3d Content Generation, Vuong Ho
Benchmarking Current Progress In 3d Content Generation, Vuong Ho
Graduate Theses and Dissertations
In recent years, 3D generation has rapidly advanced with the development of powerful generative AI models capable of producing high-quality 3D content from various modalities, including text, images, and multi-view inputs. These advancements have significantly accelerated progress in applications such as gaming, virtual reality, robotics, and digital content creation. Despite this progress, there is still a lack of standardized and fair benchmarking protocols for evaluating 3D generation methods. Existing approaches are often assessed under inconsistent experimental settings, using different datasets, evaluation metrics, and processing pipelines. Such inconsistencies make reliable and objective comparisons difficult, limiting our understanding of the strengths and …
Iterative Generation Of Feature-Based Cad Models Using An Llm With Domain Specific Constraints, Ammon I. Hepworth
Iterative Generation Of Feature-Based Cad Models Using An Llm With Domain Specific Constraints, Ammon I. Hepworth
Graduate Theses and Dissertations
This paper presents a method to generate feature-based parametric mechanical CAD models from text input. The method uses domain-specific constraints (DSCs) to guide a large language model (LLM) in the generation of scripts to build models from the CAD API. It also presents a framework for an iterative text-based system that produces parametric CAD models. The method was implemented by developing DSCs for FreeCAD and Open AI GPT-5.2 and incorporated into a web-based software application which generates models that can be visualized with an interactive viewer after each iteration. Tests were run comparing various models with and without this method. …
Establishing Ferromagnetism In Van Der Waals Antiferromagnets Mps3, Dinesh Upreti
Establishing Ferromagnetism In Van Der Waals Antiferromagnets Mps3, Dinesh Upreti
Graduate Theses and Dissertations
Recent discoveries of magnetism in low dimensions not only have gained fundamental scientific interest but also holds significant potential in numerous technological applications, such as spintronics. This has led to a wide range of efforts in the synthesis of new layered materials or tuning their existing magnetic properties, which has been instrumental in understanding the novel physical concept and development of new technological frontiers. Transition metal thiophosphate, MPS3, is a class of layered antiferromagnet family. The rich magnetic/crystal structure with delicate choice of transition metal (M) together with intriguing optical, electronic, and ferroelectric properties have placed them as a model …
The Gravity Of The Ukraine War: Measuring Conflict Impacts On European Grain Trade, Stefan Bonchis
The Gravity Of The Ukraine War: Measuring Conflict Impacts On European Grain Trade, Stefan Bonchis
Graduate Theses and Dissertations
This thesis investigates the heterogeneous structural disruptions caused by the war in Ukraine on the European Union’s agricultural trade architecture, focusing on three critical commodities: wheat, maize, and sunflower seeds. Employing a structural gravity model framework across all 27 EU Member States, the study evaluates two conflict episodes, the 2014 Crimea annexation and the 2022 full-scale invasion, to identify the net beneficiaries and heavily impacted nations within the EU agricultural trade network. The empirical strategy utilizes a dual-test design to capture the full scope of the disruption. Test A (Ukraine towards the EU trade) reveals a distinct geographic logic in …
Chaotropic And Kosmotropic Effects Of Brines On Protein Structure: Habitability Across The Solar System, Shelby Dawn Osborne
Chaotropic And Kosmotropic Effects Of Brines On Protein Structure: Habitability Across The Solar System, Shelby Dawn Osborne
Graduate Theses and Dissertations
Salts exhibit unique and specific effects on biomolecular structure depending on the physical nature of the salt (ion density, formation of hydration shells, direct binding to protein). This thesis implements biochemical, thermodynamic, and computational methods to investigate how the nature of the salt effects protein structure, which aids in defining the habitability of various brine solutions. By using simple proteins and solar system relevant salts, we inspect the physical reactions of proteins to these saltwater environments to understand which salts stabilize or destabilize protein structure. Several methods of experimentation are utilized to provide an understanding of the interaction relevant to …
Statistical Machine Learning For Calibrating Climate Model Wind Fields., Augustine Ouru
Statistical Machine Learning For Calibrating Climate Model Wind Fields., Augustine Ouru
Graduate Theses and Dissertations
This thesis investigates statistical calibration methods for wind data from Global Climate Models (GCMs), with emphasis on wind speed and wind direction. The analysis uses 30 years of daily observed and GCM wind records from 9 spatial locations in the South East USA. Wind is represented in polar coordinates, but also often modeled in Cartesian coordinates. Four calibration models are compared: a marginal wind speed model, an independent Cartesian model. The calibration models are based on semi-parametric quantile regression, a flexible conditional density estimator fitted using neural networks. The neural network objective functions are optimized using maximum likelihood estimation (MLE) …
Optimizing Escort Strategies For Chokepoint And Littoral Maritime Lanes Using Mixed-Integer Programming, Shantonu Mitra
Optimizing Escort Strategies For Chokepoint And Littoral Maritime Lanes Using Mixed-Integer Programming, Shantonu Mitra
Graduate Theses and Dissertations
Protecting high-value units (HVUs) while traversing maritime chokepoints under threats is a significant challenge that requires effective planning for allocating limited naval assets (escort ships, detection capabilities, and defensive capabilities). Although the weapon-to-target assignment problem has been previously studied in the literature, the problem of allocating limited naval assets under uncertain threat scenarios remains unexplored. This research develops a two-stage stochastic optimization framework with the objective of maximizing the expected weighted survivability of HVUs across all scenarios. The first-stage decisions include assigning available escorts to HVUs, selecting locations for deploying detection capabilities, and allocating defensive capabilities to each escort prior …
Automated Machine Learning And Satellite Image Data Fusion For Monitoring Water Quality In Mosaicked Landscapes, Sahar Rezaei
Automated Machine Learning And Satellite Image Data Fusion For Monitoring Water Quality In Mosaicked Landscapes, Sahar Rezaei
Graduate Theses and Dissertations
Despite the ecological, economic, and social importance of inland water bodies, they are increasingly impacted by human and natural drivers. Harmful algal blooms (HABs) and total suspended solids (TSS) are key indicators of water quality, and elevated concentrations pose significant ecological and public health risks. The spatiotemporal dynamics of these variables remain insufficiently understood in major river systems, including the Upper Mississippi River (UMR) and the Illinois River Basin (IRB). While in situ measurements provide accurate observations, they are costly and offer limited spatial and temporal coverage, restricting basin-scale monitoring. Remote sensing offers a powerful alternative; however, single-sensor approaches are …
Univariate And Bivariate Binary Spatial Regression Models With Application To Plant Abundance Data, Amir Hamza Akash
Univariate And Bivariate Binary Spatial Regression Models With Application To Plant Abundance Data, Amir Hamza Akash
Graduate Theses and Dissertations
Analyzing species distributions is of prime interest in ecological research. Prevalence of a species usually depends on several environmental and topographic features not all of which can be quantified or measured. Spatial random effects play an important role as a surrogate for missing features that can explain similarity in species prevalence patterns between neighboring locations. In this thesis, we focus on a dataset on abundance of plants in the southern part of South Africa. First, we build a hierarchical Bayesian model for binary regression, using the probit link, on presence/ absence of a species based on available covariates. Since the …
Physics-Informed Machine Learning For Predictive Digital Twins In Greenhouses, Hoang Kim Tran
Physics-Informed Machine Learning For Predictive Digital Twins In Greenhouses, Hoang Kim Tran
Graduate Theses and Dissertations
Greenhouses are widely used to create controlled environments for crop production, where indoor climate variables such as air temperature, relative humidity, CO2 concentration, radiation, and soil or substrate conditions directly affect plant growth, yield, energy consumption, and resource use. However, greenhouse climates are highly dynamic because they are influenced by complex interactions among outdoor weather, greenhouse structure, crop transpiration, heating systems, ventilation, screens, fans, irrigation, and other actuators. Building digital twins for greenhouses provides a powerful way to represent, monitor, and predict these climate dynamics. A predictive digital twin can simulate future indoor climate states based on current greenhouse conditions, …
Localizing And Repairing Backdoor-Sensitive Layers In Pre-Trained Language Models For Secure Fine-Tuning, Sunanda Das
Localizing And Repairing Backdoor-Sensitive Layers In Pre-Trained Language Models For Secure Fine-Tuning, Sunanda Das
Graduate Theses and Dissertations
Task-agnostic backdoor attacks can contaminate pre-trained language models (PLMs) in a way that survives downstream adaptation, even under full fine-tuning, making it difficult for practitioners to trust third-party checkpoints. Existing defenses often rely on privileged assumptions (e.g., access to poisoned data or trigger/target knowledge), thereby limiting their applicability in realistic settings. We present DiSec (Disentanglement of potentially adversarial weights for Secure fine-tuning), a robust and label-efficient purification framework that uses only clean auxiliary text and does not rely on downstream supervision or attack signatures. DiSec elicits model-internal signals from this clean data to separate suspicious parameter components that are inconsistent …
From Learner To Leader: Exploring Principals' Perspectives On Professional Learning, Development, And Mentoring, Eric William Kausch
From Learner To Leader: Exploring Principals' Perspectives On Professional Learning, Development, And Mentoring, Eric William Kausch
Graduate Theses and Dissertations
This purpose of this qualitative study was to examine veteran secondary school principals’ engagement in professional learning, development, and mentoring for the improvement of their leadership skills. While previous literature provides insight into administrative preparation programs, mentoring of novice leaders, and succession planning for those advancing their careers, there are fewer studies that discuss enhancing experienced principals’ leadership development. The study was guided by three research questions: (1) How do principals describe their experiences participating in professional learning and development? (2) What types of leadership experiences do principals engage in to improve their leadership skills? and (3) How does engaging …
Investigating And Comparing Special Education Teachers’ Perceptions Of Workload Manageability And The Relationship With Attrition, Kasey Sanders
Investigating And Comparing Special Education Teachers’ Perceptions Of Workload Manageability And The Relationship With Attrition, Kasey Sanders
Graduate Theses and Dissertations
This study investigated special education teachers’ (SETs) perceptions of workload manageability and the relationship between these perceptions and intentions to quit. State-wide data from the Kansas State Department of Education showed a significant increase in the number of special education vacancies from a total of 161, or .03% in the 2019-2020 school year to 557, or 11%, in the 2024-2025 school year. Over the past four years, the number of special education teachers with a non-traditional license has increased from 312, or 6%, in the 2021-2022 school year to 427, or 8%, in the 2024-2025 school year (KSDE, 2025). Using …
Sigesn-Based Lasers On Silicon For Mid-Infrared Optoelectronics, Sudip Acharya
Sigesn-Based Lasers On Silicon For Mid-Infrared Optoelectronics, Sudip Acharya
Graduate Theses and Dissertations
Germanium-tin (GeSn) alloys represent a significant advancement in semiconductor technology, particularly for applications in the short-wave and mid-infrared (SWIR and MIR) spectral ranges. As a group IV material system, these alloys offer a unique combination of tunable optoelectronic properties and full compatibility with established silicon-based manufacturing processes. The controlled incorporation of tin into germanium enables the engineering of a fundamental direct bandgap, a critical feature that distinguishes GeSn from its indirect bandgap materials, silicon and germanium. This direct bandgap behavior which was demonstrated in high-quality single crystalline GeSn alloys around the year 2015 is the foundation for efficient light emission …
The Role Of Speculators In The Agricultural Futures Market And Their Impact On Prices, Clement Asamoah
The Role Of Speculators In The Agricultural Futures Market And Their Impact On Prices, Clement Asamoah
Graduate Theses and Dissertations
The study evaluates the impact of speculative activity on agricultural commodity returns, specifically in the corn, soybeans, rice, and oats markets. The study also analyzed the influence commodity returns have on speculative positions. Weekly data from the Commodity Futures Trading Commission were used as a proxy for speculative activity, and futures data were also retrieved from Barchart. Vector Autoregressive models and the Granger Causality tests were estimated to identify the relationships between returns and speculation. The paper found that speculative positions do not Granger-cause returns over the course of a week except for rice Tuesday results, which recorded a statistically …
Investigation Of Early To Late Cretaceous North American Ecosystems And Paleoclimate Using Geochemical Proxies, Clayton William Forster
Investigation Of Early To Late Cretaceous North American Ecosystems And Paleoclimate Using Geochemical Proxies, Clayton William Forster
Graduate Theses and Dissertations
The relationships between the environment and an organism can be traced through stable isotope and trace element geochemistry. This thesis explores the stable oxygen and carbon isotopic composition of fossil vertebrate assemblages in pursuit of revealing the relationships between dinosaurs and their archosaur relatives with the environment in which they lived during the Cretaceous. The Cretaceous Period of North America experienced some of the hottest intervals in the Phanerozoic Eon and the continental vertebrate taxa that existed during this time recorded these periods within the stable isotopic composition of their skeletal bioapatite. Oxygen isotopes in the bioapatite of vertebrates reflect …
Advancing Social Media Analytics And Personalized Generation Via Transfer Learning, Discourse-Aware Modeling, And Collaborative Modeling, Gibson Nkhata
Graduate Theses and Dissertations
Social media platforms have become central to information exchange, shaping public opinion across social, political, and economic domains. However, the massive volume of user-generated content, combined with its informal, nuanced, and often noisy nature, presents significant challenges for automated analysis and generation. Tasks such as stance detection, rumor verification, and personalized content generation are further complicated by sarcasm, evolving discourse structures, and diverse user preferences. Addressing these challenges requires models that can effectively leverage linguistic nuance, conversational dynamics, and collaborative user signals. Transfer learning has emerged as a powerful paradigm for improving performance in low-resource and complex language understanding tasks. …
Integrated Sensing And Communication For Uavs With Oddm Waveforms, Mohammad Abdul Mobin
Integrated Sensing And Communication For Uavs With Oddm Waveforms, Mohammad Abdul Mobin
Graduate Theses and Dissertations
A new delay-Doppler (DD) integrated sensing and communications (ISAC) framework is proposed for unmanned aerial vehicle (UAV) systems. In the DD-ISAC framework, both sensing and communications are performed by using the orthogonal delay Doppler division multiplexing (ODDM) waveforms, which unify sensing and communication designs through their unique properties, such as local bi-orthogonality and dual-resolution in the DD domain. Specifically, the dual-resolution property enables the generation of delay-Doppler map for accurate and low complexity sensing, and the bi-orthogonality minimizes interference for both sensing and communications. The ODDM waveforms are used in combination with the phase comparison monopulse technique and a scaled …
Towards Audio-Driven Photorealistic Avatars For Teleconsultation: A Development And Evaluation Framework Under Constrained Bandwidth Environments, Fnu Himanshu
Graduate Theses and Dissertations
Telehealth can improve access to healthcare services, especially for patients in rural and underserved areas. Many telehealth services use video communication to provide real-time interaction and a visible connection between patients and healthcare providers. However, video communication requires continuous transmission of audio and video data. When network conditions are limited or unreliable, audio and video interruptions can reduce communication quality. This thesis explores an audio-driven photorealistic avatar as a possible visual communication layer for teleconsultation without requiring continuous webcam video transmission. It develops two connected frameworks: the Audio-Driven Photorealistic Avatar Communication Framework and the Evaluation Framework. The Audio-Driven Photorealistic Avatar …
A Systems Analysis Of Autonomous Uav Swarm Spraying For Precision Agriculture, Ryker Davis
A Systems Analysis Of Autonomous Uav Swarm Spraying For Precision Agriculture, Ryker Davis
Graduate Theses and Dissertations
The application of Unmanned Aerial Vehicles (UAVs) in civilian sectors, particularly for precision agriculture and targeted aerial spraying, has rapidly evolved from passive monitoring to advanced, autonomous, multi-agent coordination. While deploying UAV swarms offers a promising solution to the payload and battery endurance limitations of single drone operations, realizing field-scale coverage introduces significant logistical and safety challenges. To evaluate the trajectory and viability of swarms, this study synthesizes bibliometric trends, operational simulation, and safety reporting analysis. First, because physical testing of complex swarms poses financial and safety risks, we developed an agent-based and discrete event simulation to evaluate autonomous spraying …
Design And Modeling Of A Robotic Manipulator For Agricultural Explorations, Trent Thomas Powell
Design And Modeling Of A Robotic Manipulator For Agricultural Explorations, Trent Thomas Powell
Graduate Theses and Dissertations
This thesis focuses on the modeling, design, and early testing of a spherical revolute revolute prismatic (RRP) robotic manipulator for probe based applications. The system is motivated by agricultural grain probing, where a probe is positioned over a truck bed and inserted into the grain to collect samples as trucks enter storage facilities, ports, hubs, or transfer points. A spherical RRP configuration is useful for this type of task because it provides a large accessible workspace while maintaining a relatively simple mechanical structure. A model based design approach is used to develop the system, beginning with forward and inverse kinematics …
Designing Functional Nanolaminates From Complex Atomic Layer Deposition Reactions, Joseph Joel Muhanga
Designing Functional Nanolaminates From Complex Atomic Layer Deposition Reactions, Joseph Joel Muhanga
Graduate Theses and Dissertations
Atomic layer deposition (ALD) enables precise cycle by cycle control over film thickness and composition. This kind of control is ideal for the engineering of functional nanolaminate coatings with tailored optical properties. Since ALD synthesized composite films are deposited as discrete, stratified layers and not as homogeneously intermixed solids, it is not yet clear when such composites can be be treated with the effective medium approximation (EMA). EMA is simplification that is important to the design of mixed oxide coatings. This dissertation addresses that question using a model system, and then asks whether the same approach can be used to …
Coupled Effects Of Sub-Atmospheric Pressure And Surface Structures On Pool Boiling Performance And Hysteresis Pathways, Mohammad Ishraq Hossain
Coupled Effects Of Sub-Atmospheric Pressure And Surface Structures On Pool Boiling Performance And Hysteresis Pathways, Mohammad Ishraq Hossain
Graduate Theses and Dissertations
The increasing power density of microelectronics has created a need for cooling technologies capable of maintaining low operating temperatures. Sub-atmospheric pool boiling of water is promising because reducing saturation pressure lowers the boiling temperature, enabling two phase cooling within electronics-relevant temperature limits. However, reduced pressure also affects CHF, HTC, and post-CHF recovery. In this work, pool boiling experiments were conducted on flat copper, microchannel copper, and micro-pin-fin copper surfaces over 10–100 kPa to examine the coupled effects of pressure and surface structure. CHF and HTC increased with pressure, while structured surfaces enhanced both relative to flat copper. Surface structure dominated …
Harness: Hybrid Architecture For Resilience In Networked Engineering System Simulations, Daniel Scott
Harness: Hybrid Architecture For Resilience In Networked Engineering System Simulations, Daniel Scott
Graduate Theses and Dissertations
This dissertation presents the development of HARNESS, a unified, domain-agnostic framework for the modeling, optimization, and evaluation of complex systems under conditions of degradation and uncertainty. The research addresses a persistent challenge in systems engineering: the lack of a generalizable, behaviorally grounded approach for quantifying resilience and robustness across diverse domains. HARNESS integrates graph-theoretic dependency modeling, GPU-accelerated evolutionary optimization, and agent-based simulation into a modular architecture that enables both system design and diagnostic analysis. The framework models system interdependencies through user-defined components, parameters, and constraints, allowing architectures to evolve dynamically while maintaining structural validity. A mutation-only genetic algorithm with a …