Digital Commons Network^™

Intelligent Predictive Frameworks Under Data Scarcity And Uncertainty, Solayman Hossain Emon

Open Access Theses & Dissertations

Modern predictive systems frequently operate under conditions of limited annotated data, high uncertainty, and the need for reliable decision-making. When the predictive models expand across heterogeneous data types (e.g., spatial, temporal streams), the challenge lies not only in accurate prediction but also in adapting in data distributions shifts or label scarcity. To address these issues, this thesis explores an Intelligent Predictive Framework that operates robustly under data scarcity and uncertainty across two distinct domains: medical imaging (spatial) and time-series forecasting (temporal). In the first part of this work, a semi-supervised mean teacher (MT) paradigm is tailored for medical image segmentation …

Development Of Oxide And Oxynitride Thin Films For Advanced Optical Applications, Nathan Christopher Episcopo

Open Access Theses & Dissertations

To develop Ga2O3 and TiOₓNᵧ thin films for optical applications, the process–structure–properties relationship was investigated using a comprehensive set of characterization techniques to establish the atomic structure and composition of the films in relation to the deposition conditions. The results provide critical insights into how deposition parameters influence the atomic structure and composition during magnetron sputtering. Furthermore, the correlation between atomic structure and composition with the optical and electrical properties of the films was examined to determine how variations in these factors affect functional performance. Collectively, these findings offer the necessary information to target desirable optical properties for Ga2O3 and …

From Morphology To Machine Learning And Genomics: Understanding Phenotypic Variation In Wild Ducks, Sara Gonzalez

Open Access Theses & Dissertations

Understanding the genetic underpinning and distribution of phenotypic variation within and between divergent groups is core towards shedding light into how populations diverge and adapt, as well as how hybridization breaks or builds on these scenarios; and thus, central to evolutionary biology. In wild organisms, however, quantifying and linking phenotypic traits to underlying genetic processes, like mutation, gene expression, epigenetics and allele interactions, remains challenging. This difficulty arises from the complex interplay between morphology, environment, and gene regulation, as well as the logistical barriers of collecting and standardizing large-scale data across individuals and populations. As a result, researchers are increasingly …

Facilitating Deep Learning Performance Analysis Through Automated Roofline Model Generation, Irvin Lopez-Audetat

Open Access Theses & Dissertations

This thesis presents a tool to profile deep learning (DL) and machine learning (ML) models by collecting FLOPs, memory movement, and timing data through cyPAPI to generate roofline performance models. The tool is containerized for portability and reproducibility, integrates directly with PyTorch workflows, and provides fine grained insights into computational bottlenecks across model components. Unlike prior system-level or benchmarking-centric tools, this project empowers developers and researchers with an accessible, modular framework for performance analysis and optimization.

A Half Century Of Biophysical Change In Polygonized Tundra On The Coastal Plain Of Northern Alaska, Mariana Mora

Open Access Theses & Dissertations

Climate change is amplified in the Arctic. As a result, Arctic tundra landscapes are undergoing physical changes through accelerated thaw and ice-wedge degradation. Understanding the magnitude and direction of these changes in the Arctic is a necessary step toward understanding the response of the Arctic to climate change and feedbacks to the Climate System. Through repeat measurements collected from 1973 through 2018, we were able to assess decadal time scale changes in polygon geomorphology, thaw depth, land surface compression and expansion, and vertical elevation within a highly polygonized tundra system, and their implications when scaled to a regional level. This …

What Limits Dryland Ecosystems? Patterns Of Soil Fertility And Resource Limitation In The Chihuahuan Desert, Dylan Stover

Open Access Theses & Dissertations

Human activities are substantially altering global resource cycles with widespread implications for biogeochemistry and ecosystem functioning globally. Drylands, regions where precipitation is outweighed by water losses, are especially sensitive to these large shifts in resource cycles due to their inherently low and variable resource availability. In these regions, resource availability and biological activity are often concentrated around plants – or fertile islands – and predominantly driven by pulses of water. However, our knowledge of the processes influencing biological productivity in drylands – patterns of soil fertility and resource limitation – remains lacking, and their unique biogeochemical and biological processes create …

A Unified Framework For Embedding-Based Synthetic Data Generation With High Cardinality Categorical Features, Cesar Iram Vazquez

Open Access Theses & Dissertations

High-cardinality categorical variables remain difficult to model in tabular data, where classical encoders encounter sparsity, susceptibility to leakage, and the loss of meaningful relational structure. This dissertation develops a unified framework for learning, evaluating, and synthesizing representations of such variables using both traditional encoders and modern embedding methods, including Word2Vec, FastText, Node2Vec, TF–IDF/SVD, and supervised entity embeddings. The framework is applied across three benchmark datasets (Adult, PetFinder, Breast Cancer) and a hierarchical educational case study (IPEDS/CIP). Embedding quality is examined through both downstream predictive performance and structure-focused diagnostics that quantify neighborhood behavior and geometric coherence. To assess whether synthetic data …

Hubert-Based Models And Evaluation Strategies For Pragmatically-Faithful Speech To Speech Translation, Javier Vazquez

Open Access Theses & Dissertations

Pragmatic fidelity in speech-to-speech translation (S2ST) has largely been understudied, leading to communication tools inadequate to support non-superficial dialog. We aim to improve pragmatic faithfulness in English-Spanish translation through the development of machine learning models that are able to predict a corresponding pragmatic representation in the other language. To evaluate performance, we developed a pipeline that utilizes a recently-developed pragmatic similarity evaluation metric to compare models. Further, we developed models that exploit HuBERT features as these have been found suitable for various prosody and pragmatics related tasks. Our models outperformed human and state-of-the-art predictions, albeit the methodology being limited to …

Metal Zonation And Evolution Of The Bronson Slope Porphyry Cu-Au-Mo Deposit In The Iskut Region Of British Columbia, Canada, Luis Jacobo Yagual

Open Access Theses & Dissertations

Bronson Slope is a Cu-Au-Mo porphyry deposit located within the Stikine Terrane in the Golden Triangle District of northwestern British Columbia, Canada. This deposit represents a complex, multistage magmatic-hydrothermal system emplaced into sedimentary and volcanoclastic rocks of the Triassic Stuhini Group. Bronson has an inferred resource of 517.3 Mt at 0.33 g/t Au, and 0.09% Cu. This study integrates detailed and quick logging from 20 drill holes, totaling 20,296m, SWIR spectral analysis, ICP-MS geochemistry, XRF analysis, magnetic susceptibility measurements, geochronology, and 3D models developed in Leapfrog Geo which define the stratigraphy, intrusive geometry, extension, alteration footprint assemblage, metal zonation, and …

Physics-Guided Strategies For Enhancing Neural Networks Trained With Limited Data, Jose Guadalupe Perez Zamora

Open Access Theses & Dissertations

Deep neural networks excel at a wide range of processing tasks across various disciplines. However, the quantity and quality of data significantly impact network performance. In specialized domains, high-quality datasets are often difficult to gather, interpret, and curate for effective learning. Few-shot learning techniques, including transfer learning, data augmentation, and meta-learning, have emerged to address these constraints.

We propose three physics-guided strategies for enhancing neural networks trained with limited data: (1) combining existing models like LSTMs with Physics-Informed Neural Networks through two-branch architectures that merge their outputs, (2) deriving custom physics-informed data augmentation algorithms to expand limited datasets, and (3) …

Benthic Infaunal Responses To Shoreline Restoration, Jessica Lauren Cline

Theses and Dissertations

In the age of increasing urban coastal sprawl, natural shorelines are being replaced by hard armoring structures, which result in the loss of valuable ecosystem services. Hybrid living shorelines, areas that include limited and less intensive armoring strategies paired with the integration of plants and other natural materials, present an opportunity to marry the need for more aggressive stabilization with the continued preservation of ecosystem functions and biological communities. This project uses benthic infauna to evaluate the success of a living shoreline installation in Palm Bay, Florida. The deployment features experimental treatments of breakwaters and red mangroves to explore how …

Qualitative Stereo Vision Using Distributed Extended Waltz Filtering, Ben Mathew

Theses and Dissertations

Stereo vision is a fundamental problem in computer vision, aimed at reconstructing three-dimensional scene structure from two or more two-dimensional images. Traditional stereo algorithms rely on quantitative disparity estimation, often constrained by calibration precision, lighting variations, and surface texture. In contrast, our proposed Qualitative Stereo Vision seeks to understand depth relationships and spatial configurations from multiple planar views through symbolic reasoning and constraint satisfaction, offering a more flexible and cognitively plausible approach to scene interpretation.

This dissertation presents a novel framework called Distributed Extended Waltz Filtering, designed to provide qualitative stereo vision, particularly in the presence of occlusions—a persistent challenge …

Earthquake Relocation, Fault Complexity, And Nucleation Patterns In Interior Alaska, Nealey Sims

Geosciences

Interior Alaska is one of the most seismically active intraplate regions in North America, yet its faults remain poorly defined due to diffuse seismicity and limited surface expression. Bounded by the Denali and Tintina fault systems, the region hosts the Minto Flats, Fairbanks, and Salcha fault zones, which produce large earthquakes, as evidenced from the 1937 Ms 7.3 Salcha and 1995 Mw 6.0 Minto Flats events. Despite their hazard potential, these structures have historically been represented as broad seismic zones rather than mapped faults. This dissertation applies mod­ern seismological approaches—network matched filtering, waveform cross-correlation, and rela­tive relocation—to build high-resolution earthquake …

Review Of Resonance: A Sociology Of Our Relationship To The World By Hartmut Rosa, Ryan Derby-Talbot

Turning Toward Being: The Journal of Ontological Inquiry in Education

No abstract provided.

A New Goodness-Of-Fit Test For Azzalini’S Skew-T Distribution Based On The Energy Distance Framework With Applications, Joseph Njuki, Abeer M. Hasan

Mathematics and Statistics

In response to the growing need for flexible parametric models for skewed and heavy-tailed data, this paper introduces a novel goodness-of-fit test for the Skew-t distribution, a widely used flexible parametric probability distribution. Traditional methods often fail to capture the complex behavior of data in fields such as engineering, public health, and the social sciences. Our proposed test, based on energy statistics, provides practitioners with a robust and powerful tool for assessing the suitability of the Skew-t distribution for their data. We present a comprehensive methodological evaluation, including a comparative study that highlights the advantages of our approach over traditional …

Is Complexity Virtuous?, Ryan Elmore, Jack Strauss

Business Information and Analytics: Faculty Scholarship

(Kelly et al., 2024) show that increasing complexity in linear models, with potentially thousands of predictors, is "virtuous". Their work contradicts the dogma of model selection, including the Principles of Parsimony and Occam's Razor. They find that when the number of predictors far exceeds the number of observations, the bias-variance trade-off breaks down, the variance declines, and the Sharpe ratio increases. In the context of ridge regression, we find that very high complexity coupled with large penalty terms (excessive shrinkage) generate forecasts that converge to a rolling window of past returns. For example, we show the past twelve-month moving average …

Climate Change Has Increased Global Evaporative Demand Except In South Asia, Saeed Karimzadeh, Arman Ahmadi, Dennis Baldocchi, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change alters how strongly the atmosphere draws water from the land, yet a consistent global assessment of this evaporative demand has been lacking. Here, we analyze 45 years of climate data and global models to quantify trends in the key drivers—air temperature, humidity, radiation, wind speed, and cloud cover—that determine the atmosphere’s drying power. We find that evaporative demand has increased worldwide, indicating a stronger atmospheric thirst, except in South Asia, where it has declined. There, widespread irrigation has increased soil and air moisture, enhanced cloud formation, and reduced sunlight reaching the surface, counteracting the global signal. These contrasting …

From Digital Divide To Equity-Enhancing Diffusion: Generative Ai And Writing Quality, Rebecca Tukachinsky Forster, Kerk Kee, Gabriel Miao Li

Communication Faculty Articles and Research

This study investigates whether generative AI can narrow the gap between stronger and developing writers and explores the mechanisms underlying these effects. In a within-subject experiment, students wrote two essays, with and without AI assistance. Computer-aided analysis of the writing quality confirmed that while all students benefited from AI, that less skillful writers gained more. There was also no evidence of skillful writers using AI in more sophisticated and beneficial ways. The study contributes to theorizing the digital divide and offers insights into maximizing the benefits of AI tools. Theoretically, we situate generative-AI use within Diffusion of Innovations, treating ChatGPT …

Benchmarking Dna Foundation Models For Genomic And Genetic Tasks, Haonan Feng, Lang Wu, Bingxin Zhao, Chad Huff, Jianjun Zhang, Jia Wu, Lifeng Lin, Peng Wei, Chong Wu

School of Medicine Faculty Publications

The rapid evolution of DNA foundation models promises to revolutionize genomics, yet comprehensive evaluations are lacking. Here, we present a comprehensive, unbiased benchmark of five models (DNABERT-2, Nucleotide Transformer V2, HyenaDNA, Caduceus-Ph, and GROVER) across diverse genomic and genetic tasks including sequence classification, gene expression prediction, variant effect quantification, and topologically associating domain (TAD) region recognition, using zero-shot embeddings. Our analysis reveals that mean token embedding consistently and significantly improves sequence classification performance, outperforming other pooling strategies. Model performance varies among tasks and datasets; while general purpose DNA foundation models showed competitive performance in pathogenic variant identification, they were less …

Development Of A Digestion Procedure Using Fe2+ Ions For Electrochemical Detection Of Mno2 Particles In Drinking Water, Kayla Elliott, Sarah Jane Payne, Zhe She

Journal of Electrochemistry

Developing methods for detection contaminants in drinking water is essential to ensuring that safe and acceptable quality drinking water is delivered to consumers. While manganese (Mn) was previously known only as a mere aesthetic issue, recent epidemiological data has shown to have negative neurological effects on humans, especially on children, prompting new health-based guidelines by Health Canada and the World Health Organization. In drinking water, Mn exists predominantly as Mn(II) and Mn(IV), and is regulated based on total Mn levels. Interestingly, measurement of Mn particulate using electroanalytical methods has not yet been reported in the literature. Herein, a digestion procedure …

High Variability In Flood Discharge And Stage Accelerates River Mobility, Chenliang Wu, Wonsuck Kim, Shuo Yang, Frank Tsai, Jeffrey A. Nittrouer, Tian Y. Dong, Duhwan Keum, Kyle M. Straub

School of Earth, Environmental, & Marine Sciences Faculty Publications

Lateral channel migration is a fundamental process in natural alluvial rivers; however, the factors that control the rate of migration remain unclear. Despite its importance in shaping river morphology, the impact of water discharge on river mobility is still largely unexplored. Here, we leverage a dataset of 64 rivers across the globe to show that higher variability in river discharge and stage promotes higher rates of river migration. To reveal the physical processes behind this relationship, we focused analyses on the lowermost 500 kilometers of the Mississippi River, where a pronounced gradient in water stage variability and migration rate exists. …

Improving Glycemic Control Among Indonesian Urban Adults: A Digital And Behavioral Extension Of The Information–Motivation–Behavioral Skills Model, Imelda Appulembang

Kesmas

Management of type 2 diabetes mellitus (T2DM) in Indonesia continues to face challenges due to behavioral, informational, and technological gaps among patients. This study analyzed the influence of self-regulatory competence and information, motivation, family support, and digital health literacy on glycemic control behavior. A cross-sectional survey was conducted from February to April 2025 among 587 adults aged >30 years with T2DM enrolled in the Chronic Disease Management Program at primary health care in six major cities: Jakarta, Surabaya, Yogyakarta, Medan, Makassar, and Banjarmasin. Data were collected through structured questionnaires and analyzed using partial least squares structural equation modeling. The findings …

Regulating Lithium Metal Nucleation And Growth For Dendrite Suppression: From Liquid-Electrolyte To Solid-State Batteries, Ao Du, Juan Zhang, Pan Xu, Ya-Jie Li, Kang-Yu Yi, Zhen-Zhen Shen, Hui-Lin Ge, Guang-Wen Zhang, Chao-Hui Zhang, Yu-Hao Wang, Chen-Zi Zhao, Meng-Yang Xu, Yu-Lin Jie, Rui Wen, Shu-Hong Jiao, Si-Qi Shi, Qiang Zhang, Chun-Peng Yang, Yu-Guo Guo

Journal of Electrochemistry

Lithium metal anodes, with a theoretical capacity of up to 3860 mAh·g⁻¹, are regarded as the cornerstone for developing next-generation high-energy-density batteries. However, several key challenges hinder their practical applications, including dendrite formation, unstable solid electrolyte interphase (SEI), side reactions with electrolytes, and associated safety risks. This review systematically explores the mechanisms of lithium nucleation, growth, and stripping in both liquid and solid-state battery systems, analyzing critical theoretical concepts like heterogeneous nucleation thermodynamics, surface diffusion kinetics, space charge effects, and SEI-induced nucleation, which are crucial for understanding the genesis of dendrite growth. Additionally, the review discusses the electrochemical-mechanical …

Biocompatible And Antibacterial Pcl-Tio2@Ag/Γ-Cd Mof Nanocomposite Coating For Corrosion Resistance Of Magnesium Alloy In Simulated Body Fluid, Sara Dehghan-Chenar, Hamid R. Zare, Zahra Mohammadpour, Maryam Sadat Mirbagheri-Firoozabad

Journal of Electrochemistry

Magnesium alloys are promising candidates for bio-implant applications due to their biodegradability and biocompatibility. However, their rapid corrosion remains a critical limitation. This study presents the development of a multifunctional nanocomposite coating designed to enhance the corrosion resistance and antibacterial properties of magnesium alloy implants. The coating comprised γ-cyclodextrin metal-organic frameworks (γ-CD MOFs) decorated with TiO₂@Ag core-shell nanoparticles, embedded in a polycaprolactone (PCL) matrix. Immersion tests in a simulated body fluid (SBF) revealed an initially higher corrosion rate for the PCL-TiO₂@Ag/γ-CD MOF coating compared to the coating without TiO₂@Ag nanoparticles; however, it demonstrated significant …

Ai-Based Mapping Of Offshore Wind Energy Around The Korean Peninsula Using Sentinel-1 Sar And Numerical Weather Prediction Data, Jason Sung-Uk Joh, Son V. Nghiem, Menas Kafatos, Jay Liu, Jinsoo Kim, Seung Hee Kim

Institute for ECHO Articles and Research

Offshore wind farm projects are being promoted in the seas surrounding the Korean Peninsula to secure renewable energy. To support site selection, offshore wind resource maps were generated using deep neural networks trained on Sentinel-1 SAR imagery, numerical weather prediction data, offshore wind observations, sea surface temperature, and bathymetry. The deep neural network (DNN) framework consisted of six sub-models targeting eastward and northward wind components across three regions—the Yellow Sea, Korea Strait, and East Sea—to account for spatial heterogeneity. The proposed models outperformed existing approaches, achieving mean absolute errors (MAE) ranging from 1.31 to 1.69 m/s and correlation coefficients (CC) …

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

Thesis/ Dissertation Defenses

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 …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

Sign Patterns Of Certain Infinite Products, Zeyu Huang, Timothy J. Huber, James Mclaughlin, Pengjun Wang, Yan Xu, Dongxi Ye

School of Mathematical & Statistical Sciences Faculty Publications

The signs of Fourier coefficients of certain eta quotients are determined by dissecting expansions for theta functions and by applying a general dissection formula for certain classes of quintuple products. A characterization is given for the coefficient sign patterns for

(qi;qi)∞(qp;qp)∞

for integers i>1 and primes p>3. The sign analysis for this quotient addresses and extends a conjecture of Bringmann et al. for the coefficients of (q2;q2)∞(q5;q5)−1∞. The sign distribution for additional classes of eta quotients is considered. This addresses multiple conjectures posed by Bringmann et al.

A Practical Framework For Integrating Basic Separation Techniques With Molecular Quantification To Extract And Monitor Antibiotic Resistance Genes In Water Samples, Amani Jereb, Celestene Adrianne Sebag, Asmaa Sadoon, Diksha Shrestha, Mary Savin, Wen Zhang, Yong Wang

Physics Faculty Publications and Presentations

Antibiotic resistance of harmful microorganisms is recognized as a serious threat to human and animal health, which is worsened by the dissemination of antibiotic resistance genes (ARGs). However, it remains challenging to identify ARGs in water samples and to distinguish intracellular (iARGs) and extracellular ARGs (eARGs). In this work, we present a feasibility study to use simple, practical methodologies to extract and distinguish ARGs in water samples using both filtration and centrifugation, followed by quantification using qPCR. Using both synthetic water samples and lake water samples, we demonstrated that the workflow reliably detected and quantified ARGs in synthetic samples. In …

Tannin Supplementation Alters Foraging Behavior And Spatial Distribution In Beef Cattle, Bashiri Iddy Muzzo, R. Douglas Ramsey, Kelvyn Bladen, Juan J. Villalba

Wildland Resources Student Research

Beef production on chemically uniform grass monocultures can limit nutrient synchrony and contribute to uneven pasture use. We evaluated whether supplementing tannins with bioactive plant secondary compounds improves foraging dynamics and landscape use by beef cattle grazing a meadow bromegrass monoculture in ways aligned with rangeland sustainability. Twenty-four Angus cow–calf pairs were allocated to six 3.6-ha paddocks (four pairs/paddock), randomly assigned to Control (Ctrl; n = 3) or Tannin treatment (TT; n = 3). Animals received 1 kg/cow/day of DDGs, with TT receiving an added 0.4% tannins (2:1 condensed:hydrolyzable). Grazing occurred during four 15-day periods (July– September) across two years. …