Digital Commons Network^™

Indigenous Community Research Opportunities, Sharon Hausam, Aaron M. Canter

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Opportunities For Leadership In Indigenous And Tribally Engaged Research At The University Of New Mexico, Sharon Hausam

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Criticality In A Heterogeneous Neutron Transport Rod Model, Samuel Kaleb Crowford

All Graduate Reports and Creative Projects, Fall 2023 to Present

This work studies the stochastic behavior of neutron populations in a one-dimensional rod model using Monte Carlo simulation. The first part of this project reproduces the computational results of Dumonteil, Horton, Kyprianou, and Zoia (2025) by independently implementing the Monte Carlo algorithm described in their article, with the asymptotic behavior of the first moment analyzed in relation to the dominant eigenvalue and adjoint eigenfunction of the neutron transport operator. The model is then extended to a heterogeneous setting by introducing a central region where fission is suppressed. A global expectation over initial positions and directions is used to estimate the …

Advancements In Modern Seismic Monitoring: Integrating Novel And Traditional Methods For Earthquake Detection, Characterization, And Structural Imaging, Marc Adrian Garcia

Open Access Theses & Dissertations

Modern seismic monitoring has been transformed by machine-learning methods that detect and locate earthquakes at scales manual analysis cannot reach. This dissertation develops, validates, and applies such workflows across three settings that span the range of modern monitoring problems: a major subduction-zone aftershock sequence, the tectonic questions that sequence can answer, and an urban region without any local monitoring at all. First, I construct a high-resolution catalog for the aftershock sequence of the September 8, 2017, Mw 8.2 Tehuantepec, Mexico earthquake, by integrating deep-learning phase detection with established location and relocation methods. The resulting catalog of 11,374 relocated earthquakes is …

A Patch-Level Framework For Urban Vegetation Water Demand Estimation Using Remote Sensing And Deep Learning, Jesus Daniel Pereyra Manriquez

Open Access Theses & Dissertations

Urban water management in semi-arid regions requires an improved understanding of how vegetation and climatic conditions influence landscape water demand. Existing approaches often lack an integrated, spatially consistent framework to quantify this relationship at fine scales. This study proposes a patch-level framework to estimate relative landscape water demand by integrating vegetation coverage, vegetation condition, and atmospheric demand. Vegetation coverage is derived from high-resolution imagery obtained from the National Agriculture Imagery Program (NAIP) using a U-Net segmentation model with a MobileNetV2 backbone. A patch-based representation is used to ensure spatial consistency across the study area. Seasonal vegetation dynamics are captured using …

Domain Adaptation Of Facial Age Estimation For Law Enforcement Mugshot Repositories, Jorge Alejandro Pacheco Roque

Open Access Theses & Dissertations

Facial age estimation supports law enforcement via image-based, age-filtered queries, age-progressive re-identification, and bulk record labeling, where prediction accuracy determines if the resulting decisions can be trusted. State-of-the-art models excel on web imagery but incur higher error on mugshots due to domain shift between the professionally lit, filtered, and posed web photographs used during pre-training and the uniform backgrounds, uncooperative expressions, and decades of evolving capture technology found in mugshot collections. We address this gap by adapting SwinFace - a state-of-the-art multi-task Swin Transformer with public code and pretrained weights, trained on color face imagery for face recognition, facial expression …

Dlc Thin Films For Semiconductor Applications, Balam Arturo Sotelo

Open Access Theses & Dissertations

The growing need for resilient semiconductor supply chains has increased the interest in developing local and accessible materials fabrication strategies. Since large-scale semiconductor manufacturing is complex to establish quickly, simpler deposition techniques may provide a practical route to start developing semiconductors materials. Diamond-like carbon (DLC) is a promising candidate in this context because its properties can be tailored through substrate selection and processing parameters.

This thesis establishes an initial framework for the study and fabrication of diamond-like carbon (DLC) materials in the Department of Physics at The University of Texas at El Paso. DLC thin films were deposited by magnetron …

Stabilized Continuous Galerkin Methods For Heat Transport In Fully Coupled Nonlinear Thermo-Poroelasticity In Heterogeneous Porous Media, Payel Dey

Open Access Theses & Dissertations

This thesis focuses on the numerical approximation of a coupled Thermo-Hydro-Mechanical (THM) model with advective heat transport in heterogeneous media. The governing equations consist of three coupled equations: the momentum balance, the fluid mass balance, and the energy balance. The primary unknowns are displacement, pressure, and temperature. In this system, the fluid pressure determines the Darcy flux, and this flux transports heat through the advective term in the energy equation. Since the Darcy flux is computed numerically from the flow equation, the conservation properties of the flow approximation can affect the temperature solution. This effect is especially important when thermal …

A Hybrid Machine Learning-Based Feasibility Prediction Of 3d Mechanical Designs Using Scalar And Geometric Features, Md Mohsin Uddin Fahim

Open Access Theses & Dissertations

The computational bottleneck of structural feasibility screening frequently hinders the transition from a digital 3D model to a physically manufactured component. Traditionally, engineers have relied on either overly rigid heuristic constraint checks or computationally exhaustive finite element simulations. To address this inefficiency, this thesis proposes and validates a hybrid machine-learning framework to predict the structural manufacturability of 3D mechanical designs. Moving beyond the conventional reliance on isolated scalar parameters, the proposed methodology extracts and integrates both scalar manufacturing constraints (e.g., tolerance, minimum feature thickness) and spatial geometric descriptors (e.g., bounding volume, aspect ratio) directly from STL mesh data. Utilizing a …

Where Electrons Localize And Bonds Vibrate: Computational Insights Into Lanthanides And Octanoic Acid., Sonam Choki Lhamo

Open Access Theses & Dissertations

Density Functional Theory (DFT) is a widely used approach for studying the electronic and vibrational properties of atomic and molecular systems. It provides a practical balance between accuracy and computational cost, making it suitable for a broad range of applications in quantum chemistry and materials science. The primary focus of this thesis is the electronic structure of lanthanide atoms, where strongly localized 4f electrons give rise to significant self-interaction errors in conventional density functional approximations. The performance of the Perdew-Zunger self-interaction correction (PZSIC) and the locally scaled self-interaction correction (LSIC) approach developed by Zope et al. is investigated using both …

Optimizing Urban Forestry Through Green Infrastructure: Tree Health And Water Retention In Ciudad Juarez Rain Gardens, Tomas Rogelio Lizarraga Ruiz

Open Access Theses & Dissertations

Urban green spaces (UGS) in arid regions face significant challenges due to water scarcity and extreme thermal demand. This study evaluates the efficacy of Nature Based Solutions (NBS), rain gardens and median strips, in enhancing the physiological resilience of urban trees in Ciudad Juárez, Mexico. Using a comparative framework, the research monitored a native evergreen (Dermatophyllum secundiflorum) and an introduced deciduous species (Morus sp.) across six planting treatments. Statistical analysis reveals that green infrastructure (GI) acts as a critical physiological accelerant. Trees situated within rain gardens and medians significantly outperformed those in restricted pot and sidewalk settings, maintaining higher stomatal …

A Computational Approach To Electronic Coupling In Molecular Dyads, Irving Alejandro Lopez Ruiz

Open Access Theses & Dissertations

Excitation energy transfer (EET) is a fundamental process in photosynthetic systems and molecular photonic devices, where the efficient transport of electronic excitation between donor and acceptor chromophores determines the overall performance of the system. The electronic coupling V_DA between the transition densities of the two fragments is the central quantity governing this process in the weak-coupling (Förster) regime, and its accurate numerical evaluation is the main objective of this work. Two independent computational implementations of the Coulomb interaction between transition densities were developed and applied to a set of five anthracene-BODIPY donor-acceptor dyads, studied under two geometric configurations: one preserving …

Hfir Antineutrino Flux Mapping With Scale Mesh Tallies, Jacob Adam Mireles

Open Access Theses & Dissertations

This thesis develops and demonstrates a workflow for mapping the spatial distribution of reactor electron antineutrino flux around the High Flux Isotope Reactor (HFIR) using three-dimensional mesh tallies from the SCALE 6.3.1 Monte Carlo transport suite. A detailed HFIR model is executed with KENO, and the mesh-tally output is post-processed to construct a voxelized antineutrino source term. The source field is normalized to reactor power and propagated to sampled spatial points surrounding the reactor to generate three-dimensional source-side flux maps. The main analysis focuses on how the mesh-based HFIR antineutrino flux differs from an ideal point-source approximation. In the point-source …

Physics Model Calibration Via Functional Kernel Regression, Kwesi Appau Ohene-Obeng

Open Access Theses & Dissertations

Physics based computational simulators encode the governing equations of complex physical phenomena through parameters that must be inferred from empirical observations, and the observational record in modern experimental campaigns is increasingly a high dimensional functional response rather than a scalar summary. The canonical treatment of this calibration problem through the additive discrepancy decomposition of Kennedy and O'Hagan incurs O(N^3obs) Gaussian process inversion costs at functional resolution, sensitivity to discrepancy prior specification, and the confounding identifiability between the calibration parameter and the discrepancy function; scalar reduction strategies bypass the cost but discard the morphological information that the functional response carries about …

Towards A Multi-Framework Approach To Explainable Artificial Intelligence, Henry Salgado

Open Access Theses & Dissertations

Artificial Intelligence (AI) and machine learning (ML) models are increasingly being deployed to support decision-making in high-stakes domains such as healthcare, criminal justice, and education, where trust, accountability, and transparency are critical. However, increasing model complexity has made many modern systems insufficiently transparent. Existing approaches to explainable AI (XAI) typically emphasize either intrinsic model simplicity or post-hoc attribution methods that estimate feature importance for predictions. While these approaches provide valuable insights into model behavior, they do not necessarily establish whether the identified importance is grounded in the underlying data patterns or in the structural relationships that generate model behavior. Many …

Behavioral And Dietary Associations Of Vitamin D Deficiency Among Landscaping Workers: An Analytical Cross-Sectional Study In El Paso, Texas., Cristela Anahi Avila

Open Access Theses & Dissertations

Background: Vitamin D deficiency is a persistent public health concern, even among outdoor workers who receive substantial sunlight exposure. Landscaping workers may still be at risk because sun-protective clothing, early work hours, behavioral practices, and low dietary intake can reduce effective vitamin D synthesis. Purpose: This pilot study examined dietary vitamin D intake, sun exposure behaviors, and serum 25-hydroxyvitamin D status among male landscaping workers in El Paso, Texas, to identify behavioral and nutritional factors associated with deficiency. Methods: Twenty participants completed a culturally adapted food frequency questionnaire and behavioral assessment and underwent capillary point-of-care testing for serum 25(OH)D. Descriptive …

The Information Content Of The Implied Volatility Term Structure Slope For Forecasting Commodity Market Volatility, Lawrence E. Mckenzie

Doctoral Dissertations (DBA)

This study evaluates the implied volatility term structure (IVTS) slope (𝜅) for forecasting 21-day realized volatility against traditional time-series benchmarks and a 3-month continuous futures baseline. Using a matched sample of eight energy and agricultural commodities spanning 2007 to 2019, the study explicitly tests whether the option-implied slope contains unique predictive information beyond deferred price histories. The empirical findings yield three primary insights. First, redundancy testing indicates that the slope parameter delivers a statistically significant, independent risk signal even when controlling for deferred continuous futures paths. Second, an integrated joint encompassing framework that combines near-term historical volatility, generalized autoregressive conditional …

The Effect Of Childcare On Female Labor Supply And Child Development In Low And Middle Income Countries, Serena Goldberg, Costas Meghir

Discussion Papers

Childcare services can offer an opportunity for women to develop their careers and increase household income. At the same time, it can affect the development of children, depending on the quality of care. We first develop a collective model of the household as a conceptual framework to show how improving the availability of childcare can affect mothers’ labor market opportunities and earnings and how it can affect child development. We then review the literature on the effects of childcare on the employment and earnings of women and on child development. Childcare can increase mothers’ employment. However, limited work opportunities or …

Edge-Native Multi-Agent System For Latency-Critical Anomaly Detection And Qos Optimization In 6g Smart Manufacturing, Ndidi Nzeako Anyakora

All Dissertations

The increasing reliance on wireless connectivity in smart manufacturing places stringent demands on network latency, reliability, and adaptability that exceed the capabilities of static or threshold-based quality-of-service (QoS) control mechanisms. While 5G standalone networks support industrial deployments, emerging 6G environments are expected to introduce greater variability, tighter latency constraints, and increased performance degradation, necessitating autonomous, learning-driven control strategies.

This dissertation proposed an intelligent multi-agent framework for real-time anomaly detection and QoS optimization in industrial wireless networks by integrating edge-based monitoring, unsupervised anomaly detection, and reinforcement learning-driven control. Network telemetry collected from a Firecell 5G standalone testbed served as an empirical …

Quantifying Dust Structure In An Elliptical Galaxy Via Optical–Near-Infrared Color Mapping: A Detailed Study Of Ngc 6251, Luke Reed

Theses and Dissertations

The giant elliptical galaxy NGC 6251 is a well-studied active radio galaxy that hosts one of the largest known relativistic jet systems, with a projected size of approximately 3 Mpc. In addition to its large-scale radio structure, the galaxy hosts a prominent circumnuclear dust feature surrounding the active nucleus, previously interpreted as a warped dust disk. This thesis focuses on the inner morphology and dust structure of NGC 6251 using archival Hubble Space Telescope observations obtained with the WFPC2 and NICMOS instruments.

The central structure of the galaxy was investigated across multiple wavelengths through image calibration, PSF modeling and subtraction, …

Purdue University General Institutional Description, Purdue University Office Of Research

University General Facility Boilerplate Descriptions

Overview of Purdue University mission, statistics, and key cross-campus infrastructure.

Sludge-To-Sod: Sustainability In Action At Bull Creek Water Treatment Plant, Ava Baker

Goal 6: Clean Water and Sanitation

No abstract provided.

Protecting Wetlands In Georgetown County, Sophia Harrison

Goal 6: Clean Water and Sanitation

No abstract provided.

Pseudo-Riesz Bases, Deborpita Biswas

All Dissertations

In this dissertation, we will introduce the concept of pseudo-Riesz bases, extending the influential notion of near-Riesz bases first proposed by J. Holub in the 1990s. Our goal is to develop an analogous theory for pseudo-Riesz bases, obtaining results parallel to those known for near-Riesz bases, with suitable modifications.

We will develop the foundational theory of pseudo-Riesz bases. Unlike classical Riesz bases, these sequences need not be complete or independent; however, they still retain meaningful expansion properties. We will investigate the conditions under which a Bessel sequence can be transformed into a Riesz basis through finite modifications. In particular, we …

Student Motivation In Social Studies Classes At The Public Museum High School: A Dissertation, Benjamin Kruid

All Dissertations

Students tend to behave differently in different classroom settings. Many factors contribute to the change in behavior, including motivation. Research suggests a tendency for student motivation to decrease as students move from elementary to middle to high school. However, motivation in students is not uniform and is dependent on factors like the subject, and time of day, for example. This dissertation examines student motivation in social studies classes at a public high school in Michigan using Situated Expectancy-Value Theory (SEVT) as a framework for understanding motivation, and student impulsiveness as understood through the lens of Delay Discounting (DD). This research …

Distributed Coordination And Optimization Of Utility-Scale Battery Energy Storage Systems Via Multi-Agent Reinforcement Learning, Parthiv Debnath

All Theses

The increasing integration of renewable energies into modern power systems has created significant operational challenges, including transmission congestion, renewable energy curtailment, and increased real-time supply-demand variability, which makes effective coordination and optimization of multiple distributed Battery Energy Storage Systems (BESS) across power systems a critical problem, a useful solution, yet an unresolved challenge. Existing centralized optimization methods require perfect future information and are incompatible with the confidentiality constraints of deregulated electricity markets, while rule-based approaches fail to capture the multi-objective complexity of real-world power grid operations. This thesis proposed a Multi-Agent Proximal Policy Optimization (MAPPO) framework with Centralized Training and …

Scope: Deep Learning-Based Side-Channel Evaluation Across Classical And Post-Quantum Cryptographic Implementations, Nouf Nur Nabilah

All Theses

A cryptographic algorithm that is mathematically secure can still be broken since its hardware implementation leaks secret information through power consumption or electromagnetic emissions. These vulnerabilities are applicable to widely deployed classical encryption schemes as well as emerging post-quantum schemes which are standardized to provide quantum resistance. This thesis evaluated how deep learning changes such side-channel attacks across both through a unified study of four attacks, spanning a classical block cipher and two protected post-quantum schemes, and tested learned methods against the conditions that separated a laboratory result from a practical attack. Profiled deep-learning attacks recovered keys efficiently under favorable …

Llm-Assisted Task-Adaptive Semantic Communication Over Non-Ideal Channels For Vision–Language Systems, Oluwagbenga Oluwapelumi Orimoogunje

All Theses

The growth of intelligent wireless systems and bandwidth-limited edge devices has created a need for communication methods that move beyond bit-level data transmission. Semantic communication addresses this by transmitting task-relevant meaning, which reduces bandwidth usage while preserving task performance. However, existing approaches often rely on frozen encoders without task feedback and are trained under fixed or ideal signal-to-noise ratio (SNR) conditions. These limitations lead to poor generalization in realistic noisy channels.

This thesis proposed a task-adaptive semantic communication framework for Visual Question Answering (VQA) over bandwidth-constrained Additive White Gaussian Noise (AWGN) channels. The system transmits a compact 16,384-dimensional semantic feature …

2026-08-11 Executive Council Minutes, Susie Salazar

Executive Council Minutes

No abstract provided.

Optimizing Few-Shot Learning In Pruned Large Language Models With Task-Specific Prompts, Danyal Aftab

Dissertations

Few-shot learning enables large language models to efficiently perform tasks given only a limited number of labeled examples. However, training these models entirely from scratch requires substantial computational resources, making it challenging for many organizations to fully leverage their potential. This thesis explores how structured pruning, task-specific prompting, and parameter-efficient fine-tuning can be combined to preserve few-shot learning capabilities in compressed LLMs, while also extending their utility to real-world recommendation systems.

In this research, we propose the Tailored LLM framework, which first reduces model size through structured pruning and then enhances few-shot learning performance using carefully designed prompts. We experiment …