Digital Commons Network^™

Black Lives Still Matter: Freedom Schools As An Embodiment Of Critical Literacy Through Reflection And Action, Elena M. Venegas, Lakia M. Scott

Bilingual and Literacy Studies Faculty Publications

The continuation of racial inequities in the United States has ignited the recent Black Lives Matter Movement, a protest of police brutality and gun violence. Black lives matter in public school classrooms, too—where students of color face barriers to equitable educational experiences. The Children's Defense Fund Freedom School program is a major component in developing critical literacy skills through critique, inquiry, and transformation through social justice and action. Critical literacy is enacted through identity—mainly as difference, self, consciousness, narrative, and positionality. Historical and contemporary relevance of Freedom Schools connects to the urgency of the Black Lives Matter Movement.

On The Advantages Of Hierarchical Bayesian Regression For Cognitive Control Studies: A Case Study With The Dmcc Task Battery, Thomas Dudey

Arts & Sciences Graduate Student Theses and Dissertations

Arising from the so-called 'replication crisis' in the experimental psychology literature, there has been a growing call to reassess whether specific analytic practices might lead to the improved accuracy and precision of given findings. This issue is explored here, through a case-study examination of two previously collected datasets (Dual Mechanisms of Cognitive Control [DMCC] task battery), used to illustrate some of the unique advantages afforded by Hierarchical Bayesian Regression (HBR) models as a potentially more rigorous analytic approach to statistical inference. The goal is not to provide a definitive argument for the HBR approach relative to other available computational methods, …

Proceedings Of The 2024 Child Language Acquisition Symposium For Indigenous Communities, Tamera C. Yazzie, Bethany G. Lycan, Alec J. Goldberg, Kayleigh L. Russell, Melvatha R. Chee

Indigenous Child Language Research Center

The proceedings of the inaugural Child Language Acquisition Symposium for Indigenous Communities, which took place at the University of New Mexico on May 17-18, 2024.

2024 Indigenous Child Language Research Center Handbook, Tamera C. Yazzie, Bethany G. Lycan, Ryan D. Smith, Cormac League, Melvatha R. Chee

Indigenous Child Language Research Center

This handbook is continuously being developed by the Indigenous Child Language Research Center at UNM to provide Indigenous communities with a description of our organization and our research methodologies to aid in their own child language research endeavors.

Triadic Temporal-Semantic Alignment For Weakly-Supervised Video Moment Retrieval, Jin Liu, Jialong Xie, Fengyu Zhou, Shengfeng He

Research Collection School Of Computing and Information Systems

Video Moment Retrieval (VMR) aims to identify specific event moments within untrimmed videos based on natural language queries. Existing VMR methods have been criticized for relying heavily on moment annotation bias rather than true multi-modal alignment reasoning. Weakly supervised VMR approaches inherently overcome this issue by training without precise temporal location information. However, they struggle with fine-grained semantic alignment and often yield multiple speculative predictions with prolonged video spans. In this paper, we take a step forward in the context of weakly supervised VMR by proposing a triadic temporalsemantic alignment model. Our proposed approach augments weak supervision by comprehensively addressing …

An Aggregate Matching And Pick-Up Model For Mobility-On-Demand Services, Xinwei Li, Jintao Ke, Hai Yang, Hai Wang, Yaqian Zhou

Research Collection School Of Computing and Information Systems

This paper presents an Aggregate Matching and Pick-up (AMP) model to delineate the matching and pick-up processes in mobility-on-demand (MoD) service markets by explicitly considering the matching mechanisms in terms of matching intervals and matching radii. With passenger demand rate, vehicle fleet size and matching strategies as inputs, the AMP model can well approximate drivers’ idle time and passengers’ waiting time for matching and pick-up by considering batch matching in a stationary state. Properties of the AMP model are then analyzed, including the relationship between passengers’ waiting time and drivers’ idle time, and their changes with market thickness, which is …

Unsupervised Modality Adaptation With Text-To-Image Diffusion Models For Semantic Segmentation, Ruihao Xia, Yu Liang, Peng-Tao Jiang, Hao Zhang, Bo Li, Yang Tang, Pan Zhou

Research Collection School Of Computing and Information Systems

Despite their success, unsupervised domain adaptation methods for semantic segmentation primarily focus on adaptation between image domains and do not utilize other abundant visual modalities like depth, infrared and event. This limitation hinders their performance and restricts their application in real-world multimodal scenarios. To address this issue, we propose Modality Adaptation with text-toimage Diffusion Models (MADM) for semantic segmentation task which utilizes text-to-image diffusion models pre-trained on extensive image-text pairs to enhance the model’s cross-modality capabilities. Specifically, MADM comprises two key complementary components to tackle major challenges. First, due to the large modality gap, using one modal data to generate …

3d Snapshot: Invertible Embedding Of 3d Neural Representations In A Single Image, Yuqin Lu, Bailin Deng, Zhixuan Zhong, Tianle Zhang, Yuhui Quan, Hongmin Cai, Shengfeng He

Research Collection School Of Computing and Information Systems

3D neural rendering enables photo-realistic reconstruction of a specific scene by encoding discontinuous inputs into a neural representation. Despite the remarkable rendering results, the storage of network parameters is not transmission-friendly and not extendable to metaverse applications. In this paper, we propose an invertible neural rendering approach that enables generating an interactive 3D model from a single image (i.e., 3D Snapshot). Our idea is to distill a pre-trained neural rendering model (e.g., NeRF) into a visualizable image form that can then be easily inverted back to a neural network. To this end, we first present a neural image distillation method …

Mimicking To Dominate: Imitation Learning Strategies For Success In Multiagent Competitive Games, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

Training agents in multi-agent games presents significant challenges due to their intricate nature. These challenges are exacerbated by dynamics influenced not only by the environment but also by strategies of opponents. Existing methods often struggle with slow convergence and instability. To address these challenges, we harness the potential of imitation learning (IL) to comprehend and anticipate actions of the opponents, aiming to mitigate uncertainties with respect to the game dynamics. Our key contributions include: (i) a new multi-agent IL model for predicting next moves of the opponents --- our model works with hidden actions of opponents and local observations; (ii) …

Sampdetox : Black-Box Backdoor Defense Via Perturbation-Based Sample Detoxification, Yanxin Yang, Chentao Jia, Dengke Yan, Ming Hu, Tianlin Li, Xiaofei Xie, Xian Wei, Mingsong Chen

Research Collection School Of Computing and Information Systems

The advancement of Machine Learning has enabled the widespread deployment of Machine Learning as a Service (MLaaS) applications. However, the untrustworthy nature of third-party ML services poses backdoor threats. Existing defenses in MLaaS are limited by their reliance on training samples or white-box model analysis, highlighting the need for a black-box backdoor purification method. In our paper, we attempt to use diffusion models for purification by introducing noise in a forward diffusion process to destroy backdoors and recover clean samples through a reverse generative process. However, since a higher noise also destroys the semantics of the original samples, it still …

Learning To Handle Complex Constraints For Vehicle Routing Problems, Jieyi Bi, Yining Ma, Jianan Zhou, Wen Song, Zhiguang Cao, Yaoxin Wu, Jie Zhang

Research Collection School Of Computing and Information Systems

Vehicle Routing Problems (VRPs) can model many real-world scenarios and often involve complex constraints. While recent neural methods excel in constructing solutions based on feasibility masking, they struggle with handling complex constraints, especially when obtaining the masking itself is NP-hard. In this paper, we propose a novel Proactive Infeasibility Prevention (PIP) framework to advance the capabilities of neural methods towards more complex VRPs. Our PIP integrates the Lagrangian multiplier as a basis to enhance constraint awareness and introduces preventative infeasibility masking to proactively steer the solution construction process. Moreover, we present PIP-D, which employs an auxiliary decoder and two adaptive …

Self-Supervised Fine-Tuning For Neural Expert Finding, Budhitama Subagdja, Dan Sanchari, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Expert finding systems allow ones to find individuals who have expertise in specific fields or domains. Traditional expert finding are mostly based on topic modeling or keyword search methods that are limited in their capability to encode contextual knowledge from natural language. To address the limitation, this paper presents Neural Expert Finder (NEF), a novel method that takes a transfer learning approach based on transformer encoder networks to leverage the rich seman-tic and syntactic patterns of language encoded in pre-trained language models (PLMs). We propose a self-supervised learning approach utilizing contrastive training using both positive and automatically generated negative samples …

Long-Tailed Out-Of-Distribution Detection Via Normalized Outlier Distribution Adaptation, Wenjun Miao, Guansong Pang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Onekeychallenge in Out-of-Distribution (OOD) detection is the absence of groundtruth OOD samples during training. One principled approach to address this issue is to use samples from external datasets as outliers (i.e., pseudo OOD samples) to train OOD detectors. However, we find empirically that the outlier samples often present a distribution shift compared to the true OOD samples, especially in LongTailed Recognition (LTR) scenarios, where ID classes are heavily imbalanced, i.e., the true OOD samples exhibit very different probability distribution to the head and tailed ID classes from the outliers. In this work, we propose a novel approach, namely normalized outlier …

Determinants Of Child Care Subsidy Policies In The American States: A Mixed-Method Investigation In The Era Of Covid-19, Hailey Heinz

Political Science ETDs

This mixed-method dissertation investigates policy variation in states’ administration of the federal child care subsidy program (CCDF). The quantitative chapters draw on a 50-state, ten-year dataset to examine associations between state characteristics and CCDF policy outcomes. These analyses conclude that state-level drivers of CCDF policy are distinct from drivers identified in the cash welfare literature, and that drivers vary across dimensions of CCDF policy. The qualitative chapters report results from a comparative case study examining CCDF policy in New Mexico and Nevada from 2010 to 2022. These analyses conclude that the departmental placement of the CCDF program within state government …

A Report Summarizing Hsc Faculty Participants: Ithaka S+R Coordinated Study Making Ai Generative For Higher Education, Laura J. Hall, Robyn Gleasner

Publications

This report presents findings from the University of New Mexico Health Sciences Center’s (HSC) participation in the ITHAKA S+R study Making AI Generative for Higher Education. Seven faculty members from HSC disciplines including internal medicine, pathology, psychiatry, nursing, radiology, and population health were interviewed to explore their perspectives on generative AI (GenAI) in teaching and learning, research and scholarship, and institutional support. A unique theme of “practice” emerged, reflecting how GenAI is influencing clinical care, bench-to-bedside translation, and the preparation of students for future professional practice. The report highlights faculty experiences, ethical concerns, and support needs, offering insight into how …

Divlog: Log Parsing With Prompt Enhanced In-Context Learning, Junjielong Xu, Ruichun Yang, Yintong Huo, Chengyu Zhang, Pinjia He

Research Collection School Of Computing and Information Systems

Log parsing, which involves log template extraction from semistructured logs to produce structured logs, is the first and the most critical step in automated log analysis. However, current log parsers suffer from limited effectiveness for two reasons. First, traditional data-driven log parsers solely rely on heuristics or handcrafted features designed by domain experts, which may not consistently perform well on logs from diverse systems. Second, existing supervised log parsers require model tuning, which is often limited to fixed training samples and causes sub-optimal performance across the entire log source. To address this limitation, we propose DivLog, an effective log parsing …

Single Droplet Combustion Of Alternative Fuels, Karah Powell

Masters Theses and Doctoral Dissertations

As the need to reduce greenhouse gas emissions grows, research into alternative fuels is becoming increasingly important. Biofuels, such as biodiesel and ethanol, are already used in the transportation sector. Rising biodiesel production generates byproducts like glycerol and surplus alcohols, which are also candidates for combustion applications. This study explores both conventional and alternative fuels, including butanol and biocrude from Algal. Droplet combustion experiments were performed to analyze the combustion characteristics of the fuels. Using the suspended droplet method, various droplet sizes were tested. The results show that combustion progresses through distinct stages: preheating, swelling, and burning. While hydrocarbon fuels …

Radial, Vortex, And Spiral Solutions To The Nonlinear Schrödinger Equation And Other Reaction--Diffusion Systems, James Redmon Cummins

Masters Theses and Doctoral Dissertations

This dissertation explores various solutions to nonlinear reaction-diffusion systems, focusing primarily on the nonlinear Schrödinger equation. Three types of solutions are investigated: radial solutions (with no angular dependence), vortex solutions (with angular dependence but no radial phase dependence), and spiral solutions (which have radial phase dependence). The study considers free particles without potential and trapped particles inside the cylindrical potential with an impenetrable barrier. We show that spiral solutions to the nonlinear Schrödinger equation only exist for a radially constant phase by considering a related system of nonlinear ordinary differential equations. This system is shown to be a special case …

Before Ministry, Education Is Important (Bmei): A Comprehensive Enquiry About The Impact Of Education On Ministry, Mcclintock Acsmhour

Electronic Theses and Dissertations

Ministry has a variety of fields ranging from churches, social nonprofit organizations, and government ministries in agriculture, health, education, lands, and many more. While this study did not focus on other ministries apart from Christian non profit ministries like church, to some extent, all leaders in these ministries avow that one requires some level of education to be in leading positions in these ministries. In other words, the qualified individual must have been trained in a particular field within the ministry of interest. This indicates the importance of education in ministry. Therefore, this study was conducted to uncover the impact …

Leading The Charge: A Case Study On The Leadership Behaviors Of Education Leaders At Title I Campuses In Texas Prisons, Ashley Mckelvey

Electronic Theses and Dissertations

Each year, eligible schools across the nation receive Title I grant funds through the Elementary and Secondary Act. These funds, justified in pursuit of social justice and educational equity, serve to provide supplemental education services to neglected and delinquent students. While the majority of the awarded schools operate within the traditional school setting, a very small number of schools in the United States operate within the correctional setting. These schools receive Title I Part D Subpart 1 funds. Consequently, most of the guidance pertains to best practices within traditional public schools, which provides no provision on the appropriate use of …

Measuring Palatability Of Pet Food Products: Sensory Components, Evaluations, Challenges, And Opportunities, Natalia Calderon, Brittany L. White, Han-Seok Seo

Food Science Faculty Publications and Presentations

The pet food industry is a growing business launching a variety of new products in the market. The acceptability or preference of pet food samples has traditionally been measured using either one-bowl or two-bowl tests. Academic researchers and professionals in the pet food industry have explored other methods, including the cognitive palatability assessment protocols and the ranking test, to evaluate more than two samples. A variety of approaches and perspectives were also utilized to predict palatability and key sensory attributes of pet foods, including descriptive sensory analysis by human-trained panelists and pet food caregivers’ perceptions of pet food. This review …

A Comparative Analysis Of Early Algebraic Thinking Activities From U.S. And Singapore Primary Textbooks, Christian Joel Hernandez

Theses and Dissertations

Many studies highlight the challenges students face when transitioning to algebra at the secondary level. Introducing algebraic concepts and fostering algebraic thinking at the primary level can help mitigate these difficulties. Prior to formal algebra instruction, early algebra can be cultivated as a mode of thinking known as algebraic thinking. Several international curricula, such as Singapore Math, incorporate early algebraic thinking into the early stages of schooling. Singapore Math, renowned for its high performance in international assessments, has been widely adopted by schools seeking to replicate its success.

This study compares two primary-level mathematics curricula—CCSSM-aligned textbooks and Singapore Math—specifically focusing …

Religious Affiliation And Alcohol Use Amongst The College Population At The University Of Northern Colorado, Cassandra H. A. Higgins

Undergraduate Honors Theses

A rampant problem growing globally is the issue of substance use disorders, especially that of alcohol abuse. As the problem of alcohol abuse spreads, finding tactics to mitigate this issue or discover what aspects are causing this issue is important to decrease the threat of a further problem developing. Prior research on different religious groups has shown that people who identify as highly devout in their religion are often less likely to exhibit signs of alcohol abuse. This study examined students at the University of Northern Colorado with the goal of comparing their levels of religious affiliation with their levels …

Take A Ballot: Can Transnational Theatre Foster Political Efficacy In Women Of Color?, Breanna Marie Bailey

Undergraduate Honors Theses

This research examines whether transnational theatre fosters political efficacy in women of color. Research shows the history of disenfranchisement of women of color; even today, upper-class, white males have the greatest access to civic resources– including access to theatre–which ignite their political efficacy in the United States. The gap in research surrounds how, and if, transnational theatre can affect women of color’s political efficacy. By analyzing theatre’s role in engaging political efficacy, I offer an avenue to build a more equitable and democratic society. Using a case study analysis of two female playwrights from opposite sides of the U.S. border–Sor …

Emergency Room Nurses' Perceptions Of Medication Errors In The Emergency Department, Yasmeen Mustafa

Undergraduate Honors Theses

Medication errors (MEs) remain a pervasive issue in United States emergency departments, where emergency room (ER) nurses play a central role in the medication process. The medication process involves transcribing, prescribing, dispensing, administering, and monitoring. Proper adherence to the process ensures that the right medication is given to the right patient in the correct dose, route, and time. It also allows consideration of potential interactions and side effects, with the goal of achieving safe and efficacious therapeutic outcomes. Given the potential life-altering consequences of MEs, it is imperative to harness the unique insights and experiences of ER nurses who are …

It’S So Liberating To Do The Work: Education In Archives Creates Space For People With Disabilities, Jen Hoyer, Julia Pelaez

Publications and Research

What are the barriers and possibilities archives education presents to the disabilities community? More specifically, how can archives education and teaching with primary sources provide opportunities for disabled students that they might not find in mainstream education settings? What matters when working with students with disabilities in archives, and what does it feel like to be a disabled educator in an archive? How can education in archives provide opportunities for vulnerability, connection, and liberation? Sharing a passion for the possibilities of education work in archives and special collections, Jen Hoyer and Julia Pelaez sat down for a conversation about these …

Preparing Educators To Effectively Engage With Postsecondary Stem Students With Autism, Luzconsuelo Gavaldon

Open Access Theses & Dissertations

Autism spectrum disorder (ASD) is a lifetime mental disability (Boucher, 2009). Because the brains of people with autism work differently than their non-neurodiverse peers (Kuzminskaite et al., 2020), they tend to respond to external stimuli in a hypo- or hyper-sensory fashion. One of the primary considerations that must be accounted for when working with individuals with autism is that the brains of these persons are each neurologically distinct. In other words, there is no "one-size-fits-all" means by which individuals with ASD learn and develop and, consequently, no single way to therefore engage with said individuals (Anderson & Butt, 2017; Kuzminski …

Phosphene Or 233 Reasons Why I Never Listened To Abba, Matt Edwards

Open Access Theses & Dissertations

A hybrid collection about gods and fathers, saviors and sons

*MFA theses don't have abstracts. My critical preface is 20 plus pages.

Examining Key Predictors Of Enrollment At A Regional, Open-Access Research University On The U.S. - Mexico Border, Marcus Gay

Open Access Theses & Dissertations

Each year, approximately 64% of admitted students do not enroll at the University of Texas at El Paso (UTEP). This is particularly concerning given the projected decline in regional high school graduates beginning in the 2025-2026 academic year. The El Paso region is also predominantly composed of groups who have been historically underrepresented in higher education, including Hispanic or Latino students, individuals from low socio-economic backgrounds, and first-generation college students. Using logistic regression analysis, this quantitative study investigates how seven key factors impact the likelihood of enrollment among admitted UTEP applicants. The study utilized admissions data provided by UTEP’s Texas …

Protective And Risk Exposures Of Cancers Disproportionately Affecting Hispanics In A U.S. - Mexico Border Population: A Clinical Informatics Approach, Amir Hernandez

Open Access Theses & Dissertations

BACKGROUND: Cancer is the second leading cause of death in the U.S. with over 8 million new cases between 2016 and 2020. A variety of protective and risk exposures are associated with multiple cancers and disparities and inequalities exist in the health outcomes of minority populations. Hispanic populations in the U.S. and Texas have some of the highest rates of cancer incidence and mortality when compared to other populations. The use of Population and Public Health Informatics approaches to address these issues have shown promise when employed in healthcare institutions METHODS: A case-control study design examined associations between multiple cancers …