Digital Commons Network^™

Synchronized Multi-Modal Verification For Point-Of-Sale Transactions, Gulmohar Khan, Ved Patil

Defensive Publications Series

This disclosure describes systems and methods for multi-modal transaction verification. The technology can involve generating a synchronized sequence of dynamic, single-use validation tokens, such as a numeric code, a visual shape, or a specific color, across a customer's computing device (e.g., a smartphone, smart watch, wearable device, or augmented reality glasses) and a merchant's confirmation device. Visual matching of these tokens, which can be manual or automated, may be used for verification. Additionally, sensory synchronization methods, such as coordinated audio jingles or light patterns between the devices, can be employed. These techniques can aid in creating a verifiable link between …

Scalable Per-Scene Media Signal Generation Using Configurable Signal Extraction Algorithms, Pooja Verlani, Balu Adsumilli, Shruti Kanetkar

Defensive Publications Series

This document describes a distributed computing platform for automatically performing feature extraction, signal extraction, and/or metadata extraction from large collections of media files, including videos, audio recordings, and multimedia content. A cloud-based processing system is described that uses a “Bring-Your-Own-Signal” framework to enable developers to submit custom extraction programs, algorithms, machine learning models, or processing graphs directly into the central management system. The system automatically validates and sets up submitted extraction algorithms for use. The system may support resource sharing and improve scalability by dispatching extraction tasks to execute on client-provided hardware, and receiving, from the client-provided hardware, only the …

Student Perceptions Of Artificial Intelligence: A Freelisting Study, Gary Kaplan, Mslis, Ahip, Jessica G. Hamilton, Mls, Rebecca Miller, Mlis, Rosemary Frasso, Phd, Cph

Thomas Jefferson University Faculty Days

Background

Librarians typically provide guest lectures on topics in information literacy, connecting students to the scholarly literature. Hervieux & Wheatley’s Six Frames for AI Literacy emphasize the need to engage in AI discourse. As artificial intelligence changes the way students often interact with information, librarians must adjust their approach, whether changing the framing while retaining the traditional content, or changing the content. In the 2025-26 academic year, we experimented with various approaches. Here we describe a brief freelisting exercise we conducted before the lessons to surface students’ perceptions of artificial intelligence.

Testing The Christian University Belonging Scale: Revision From Target Population Feedback., Jasmine Bowles

Honors Projects

This study explored whether feedback from a scale’s target population can improve its psychometric qualities. We developed a psychological scale of Christian university belonging, defined as feelings of being accepted, valued, engaged and connected in direct association with the faith-integration at a Christian university. Three studies were executed. First, we collected and analyzed quantitative data (n=55) on the 14-item scale and reduced the number of items to six. Second, we collected and analyzed qualitative data from students attending a Christian university in the Pacific Northwestern United States (n=7) on the 6-item version to revise the scale. After revision, the scale …

Olaf: Towards Robust Llm-Based Annotation Framework In Empirical Software Engineering, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the Operationalization for LLM-based Annotation Framework (OLAF), a conceptual framework that organizes key constructs: reliability, calibration, drift, consensus, aggregation, and transparency. The paper …

A Comparative Examination Of Early Reading Literacy Policies In Louisiana And Mississippi, Joyrance Neveu Cormier

Doctoral Dissertations

Controversies over the best practices for teaching children to read have persisted for decades (Thomas, 2022). Researchers and practitioners continue to identify best practices, curricula, and assessment tools to produce young readers who are ready to "read to learn" by the end of third grade. Since the 1990s, accountability has primarily focused on reading, particularly on students' challenges with reading comprehension. To address these challenges, the National Reading Panel was established in 1997. The panel was charged with synthesizing research findings on the most effective methods for teaching children to read (Shanahan, 2005). More recently, the concerning reading performance of …

The Evolutionary Response Of HawaiʻI ʻAmakihi (Chlorodrepanis Virens) To The Introduction Of Avian Malaria (Plasmodium Relictum), Gabrielle Atkinson

Doctoral Dissertations

The emergence of novel pathogens can impose intense selective pressures on natural populations, driving rapid evolutionary change or precipitating population collapse. In Hawaiʻi, the introduction of avian malaria (Plasmodium relictum) and its mosquito vector (Culex quinquefasciatus) have caused severe declines and extinctions among native forest birds. Yet some populations of Hawaiʻi ʻamakihi (Chlorodrepanis virens) persist across a broad elevational and disease gradient, providing a powerful natural system for examining the genomic basis of rapid adaptation, the role of gene flow in adaptive response, and the potential for parallel evolutionary responses. This dissertation integrates genomic, population genetic, and transcriptomic approaches to …

A Qualitative Study: Understanding The Effects Of Acceleration Programs On The Motivation And Burnout Of Students With Gifts And Talents, Destini Duhon Manuel

Doctoral Dissertations

A student that has an advanced gift or talent which encompasses their peers is often raftered to as gifted (National Association of Gifted Children, 2018) and need differentiated instruction and accommodations to reach their full potential (Clevenger, 2022) Research shows high levels of expectations could lead to underachievement (Garn & Jolly 2019; Hornstra et al., 2003), motivation issues (Hornstra et al., 2023), and burnout (May et al., 2020) of students with gifts and talents. Acceleration programs are often used to accommodate students with gifts and talents, but evaluators must proceed with caution and place students in the correct program to …

The Interplay Of Seasonality, Evolution, And Density-Dependence In Discrete-Time Predator-Prey Dynamics, Narendra Pant

Doctoral Dissertations

We extend the discrete-time mathematical models developed in (Ackleh et al., 2019) and (Ackleh et al., 2024) to account for seasonal prey reproduction and build a class of discrete-time predator-prey seasonal models. Each model distinguishes between breeding and non-breeding seasons, representing prey reproduction as a periodic function of period 2. Altogether, three different models are analyzed. In the first part, we extend the predator-prey model from (Ackleh et al., 2019) to incorporate seasonality. We study the resulting dynamics and show that when the inherent reproduction number of the prey and the invasion reproduction number of the predator are larger than …

Building And Restoring Trust In Deep Learning: From Multimodal Sensing To Generative Synthesis And Model Integrity, Liqun Shan

Doctoral Dissertations

Deep learning has become a foundational technology for modern intelligent systems used in sensing, authentication, media generation, and automated decision-making. As these systems are increasingly deployed in security- and privacy-sensitive settings, ensuring their trustworthiness has become a critical challenge. Yet deep learning models remain vulnerable to spoofed sensory inputs, synthetic media, and malicious behaviors hidden within trained networks. These vulnerabilities undermine reliability and raise serious concerns about whether such systems can be trusted under adversarial and deceptive scenarios. This dissertation investigates how to build and restore trust in deep learning across three tightly connected dimensions: multimodal sensing, generative authenticity, and …

The Promise And The Punishment: A Critical Analysis Of Pbis At The Intersection Of State Discipline Policies In Louisiana, Ashley D. Willis-Brooks

Doctoral Dissertations

Positive Behavioral Interventions and Supports (PBIS) emerged as a preventative instructional alternative to exclusionary and punitive school discipline practices emphasizing tiered systems of support, data-based decision making, and proactive behavioral instruction. Despite its strong theoretical foundation and widespread adoption, PBIS implementation has produced uneven outcomes, particularly in policy contexts where state discipline statutes continue to authorize exclusionary practices. In Louisiana, PBIS is promoted through state guidance as an evidence-based framework; however, governing discipline policies simultaneously permit suspension, expulsion, and zero-tolerance provisions. This coexistence raises critical questions regarding alignment, coherence, and equity within the state’s discipline system. The purpose of this …

Learning And Predicting The Performance Of Gradual Type System, Mohammad Wahiduzzaman Khan

Doctoral Dissertations

Gradual typing reconciles the complementary strengths of static and dynamic typing by allowing programmers to incrementally introduce type annotations while preserving the flexibility of dynamically typed code. This approach improves reliability, documentation, and tooling support without sacrificing rapid prototyping. To ensure soundness, gradual type systems enforce annotations through runtime checks, typically implemented via cast insertion. Although these checks guarantee correctness, they can introduce substantial and highly variable runtime overhead, making performance prediction and optimization a central challenge for practical adoption. Prior work has largely focused on coarse-grained (macro-level) configurations, where entire modules are either fully typed or untyped. While such …

Learning From Extremes: A Copula-Based Feature Selection Framework For Machine Learning-Driven Risk Prediction, Agnideep Aich

Doctoral Dissertations

Reliable feature selection is crucial for building interpretable and practical risk models, particularly when decisions depend on identifying the highest-risk groups rather than relying on average trends. This dissertation presents and tests a supervised filter that ranks predictors by their upper-tail concordance with the outcome, using a Gumbel-implied upper-tail concordance score $\lambda_U$. The score is calculated from pseudo-observations and Kendall’s $\tau$ (via the Gumbel $\tau\mapsto\lambda_U$ mapping), does not require model fitting during selection, and focuses directly on joint extreme events, such as when both a predictor and the positive class are high. The method is compared to Mutual Information, mRMR, …

Fashioning The Self: Trauma, Disability, And Autofiction In Contemporary Quebecois Literature, John Ashburn

Doctoral Dissertations

This dissertation brings into dialogue trauma studies, disability studies, queer theory, and scholarship on autofiction and self-portraiture to examine representations of the self in contemporary Quebecois literature. Focusing on La fille d’elle-même (2021) by Gabrielle Boulianne-Tremblay, Tu aimeras ce que tu as tué (2017) by Kev Lambert, Grosse (2018) by Lynda Dion, Désormais, ma demeure (2020) by Nicholas Dawson, Chienne (2019) by Marie-Pier Lafontaine, and Ouvrir son cœur (2018) by Alexie Morin, this study argues that the literary self emerges as fundamentally unstable, shaped by trauma, embodiment, cognitive variation, and shifting configurations of gender and sexuality. Across this corpus, fragmentation …

Molecular And Histologic Studies Of The Amygdala And Reward Circuits In Rhesus Macaques (Macaca Mulatta) With Self-Injurious Behavior (Sib), Jackie Barua

Doctoral Dissertations

Self-injurious behavior (SIB), also known as non-suicidal self-injury (NSSI), is characterized by deliberate infliction of harming one’s own body tissues without committing suicide, and persists in a group of captive rhesus macaques despite an enhanced enrichment program and pharmacological intervention with diazepam. The aim of this dissertation was to identify the neurobiological underpinnings of SIB by combining RNA-seq guided transcriptomic discovery and targeted candidate gene validation with unbiased histological and imaging analysis. The secondary aim was to employ a complementary mouse model to investigate the endogenous opioid system in response to diazepam. The amygdala transcriptome of primates with SIB (n …

Investigating The Distribution And Origin Of Pitted Mounds On Mars Using Machine Learning-Based Mapping And Integrated Geological Analysis: Application To Isidis Planitia, Precious Batubo

Doctoral Dissertations

Pitted mounds are widespread landforms across the northern plains of Mars, yet their origin remains uncertain. These features have been interpreted as possible expressions of subsurface fluid activity, including sedimentary volcanism, magmatic processes, or other fluid-assisted mechanisms. Determining their distribution, morphology, and geology is therefore important for understanding the evolution of subsurface hydrological processes and the planet’s potential for habitability. However, the large spatial extent of mound-bearing terrains makes comprehensive manual mapping impractical. This dissertation presents an automated approach to mound detection using Faster Region-Based Convolutional Neural Network (Faster R-CNN) from high-resolution Context Camera (CTX) images including morphometric and mineralogical …

Enhancing Hiv Prevention: Implementation And Evaluation Of A Standardized Hiv Risk Assessment Screening In A Primary Care Setting, William Duckworth

Doctoral Dissertations

Background: HIV remains a persistent public health concern, with 1.3 million people affected worldwide. Although advances in treatment have improved long-term management, early prevention still relies on identifying individuals at elevated risk. In many primary care settings, routine HIV risk assessment is inconsistent or absent, resulting in missed opportunities to screen, educate and initiate prevention strategies such as pre-exposure prophylaxis (PrEP). This gap underscores the need for structured, evidence-based tools to improve early risk identification and strengthen HIV prevention efforts. Purpose: Implement and evaluate an evidence-based standardized screening process for HIV risk assessment to achieve early identification and enhance appropriate …

Enhancing Hpv Vaccination Engagement And Uptake Among Young Adults Aged 17 To 26 Through A Multilevel, Multicomponent Intervention, Sarah Dianne Girlinghouse

Doctoral Dissertations

Background: Human papillomavirus (HPV) remains one of the most common vaccine-preventable infections, with vaccination rates among young adults aged 17 to 26 remaining below Healthy People 2030 targets. University health settings represent a critical opportunity to improve vaccine uptake. Prior to this quality improvement (QI) initiative, student health services (SHS) at a public university in the southern United States did not routinely offer HPV vaccination, resulting in missed opportunities for prevention. Evidence supports provider recommendation, clinical decision support, and improved access as key drivers of HPV vaccination uptake. Purpose: The purpose of this QI project was to increase HPV vaccination …

Optimizing Well-Being In Post-Stroke Aphasia: Improving Access And Participation In Mental Health Care, Ashley H. Kidd

Doctoral Dissertations

This dissertation is focused on improving the well-being of people with aphasia. The overall aim of this research agenda is to move the healthcare system forward in its understanding of managing people with aphasia’s well-being after diagnosis. This focus is addressed through a compilation of three separate academic articles that are published or submitted to journals for the peer review process in speech-language pathology. All three works are focused on aphasia, a language disorder resulting from acquired brain injury, and the well-being of the person with aphasia. The first article focuses on managing the communication breakdowns that occur during group …

A Dft Study Of Mg/Ti Fluorites-Structure Materials: Optoelectronic, Photocatalysis, And Hydrogen Storage Applications, Kingsley Etim, Favour Azogor N, Moses Edim, Edet A. Thompson

Polytechnic Journal

This study employs density functional theory (DFT) to investigate the fluorite-derived tetragonal hydride MgTiH₄, highlighting its multifunctionality for energy-related applications. Structural optimization reveals lattice constants of a = b = 3.15 Å and c = 4.70 Å, with a unit cell volume of 46.59 ų and a high bulk modulus of 114.21 GPa, indicating mechanical robustness. Compared to its MgTiH₄ and CaTiH₄ analogs, SrTiH₄ exhibits the highest phonon frequency (1355.19 cm^-1). Superior thermodynamic stability (formation enthalpy: –3.35 eV) is seen in MgTiH₄. Electronic band structure analysis reveals a narrow indirect …

Exploration Of Maryland African American Veterans’ Experiences Utilizing Information On Federal Benefits And Services, Shontrea Bazemore

Walden Dissertations and Doctoral Studies

No abstract provided.

Law Enforcement Officers' Perception Of Human Trafficking And The Efficacy Of The Training They Receive, Christian Jones

Walden Dissertations and Doctoral Studies

No abstract provided.

6tisch Based Sensing Network For Smart Agriculture, Riley Heike, Griffin Jones, Justin Odo, Jalen Paige, Rosalie Wessels

Computer Science and Engineering Senior Theses

This project investigates 6TiSCH (IPv6 over Time-Slotted Channel Hopping), a relatively recent IETF networking standard introduced in 2013 that combines deterministic TSCH scheduling, 6LoWPAN header compression, and RPL mesh routing to enable low-power, reliable, multi-hop wireless communication for IoT deployments. Despite its strong theoretical properties, 6TiSCH remains underexplored in practice, and real-world questions around configuration, scalability, power behavior, and end-to-end integration are not well documented. Our primary goal was to build and operate a working 6TiSCH network, characterize its performance through iterative testing, and understand what it takes to go from raw packet delivery to a complete data pipeline.

To …

The Impact Of Student Choice On Reading Engagement And Comprehension In First Grade, Gia Stella Nardi

Theses and Dissertations

The purpose of this study was to (a) examine the effect of student choice on first-grade students’ reading engagement and (b) determine how student choice impacted their reading comprehension during instruction. Throughout the study, students utilized a choice board following each read-aloud to express their understanding of what they perceived as important in the text. Findings indicated that students demonstrated high levels of engagement during the 12 read-alouds, which were intentionally selected based on their interests, as well as during the choice-based activities that followed. Additionally, students showed growth in their ability to apply key comprehension skills, including summarizing, identifying …

Seeing Through Similar Eyes: How Social Identity Shapes Reinterpretation Of Ambiguous Stimuli, Eli Bailit

Cognitive Science Senior Theses

Identical sensory input can lead to a variety of subjective experiences and interpretations. In the face of such ambiguity, we often turn to our social context. Does the identity of the person providing an alternative interpretation to an ambiguous stimulus impact someone’s likelihood to adopt it? This study examined whether perceived interpersonal similarity modulates reinterpretation of ambiguous visual stimuli. Thirty Dartmouth undergraduates completed a modified “MadLibs” paradigm in which they generated initial interpretations of ambiguous photographs, indicated their confidence in their interpretations, then decided how much to update those interpretations upon viewing an alternative sourced from an individual of varying …

Category Learning Under Verbal Interference, Yawen Xue

Cognitive Science Senior Theses

What happens to cognition when you disrupt language? What does language actually do as a representational medium for cognition? Much literature shows a facilitative role of language on categorical thinking. This work specifically examines the role of language in category learning using a verbal interference paradigm. I ran two experiments where participants learned to distinguish between two novel categories of bugs while under conditions of verbal or visuospatial interference. In Experiment 1, category membership was determined by an XOR rule; in Experiment 2, category membership was determined by an AND rule.

In Experiment 1, participants on average did not succeed …

Identifying Preferred Toothpaste And Improving Toothbrushing Participation In Autistic Individuals, Taylor Bakalar

Doctoral Dissertations - College of Arts and Sciences

Research that assessed the prevalence of oral health disorders among those with autism spectrum disorder (ASD) found that behavior and environmental variables played a role in deteriorated dental hygiene in some patients with ASD. Behavior analytic interventions have been used to increase participation with dental exams and daily toothbrushing skills (Duhanyan et al., 2019). The current study seeks to extend Duhanyan et al. (2019) through the implementation of a modified single-stimulus preference assessment to identify a preferred toothpaste by evaluating increased percentage of participation with experimenter-implemented toothbrushing. For all participants, the SSPA identified at least one toothpaste flavor that increased …

Samuel Johnson Dictionary, 1773 Edition, Beth Rapp Young

Research Data and Datasets

This dataset contains digitized page images from the 1773 fourth edition of A Dictionary of the English Language, contributed by the University of Florida and Indiana University as part of a digital humanities project led by Beth Rapp Young. The collection provides foundational primary source material for the study of 18th-century English lexicography and supports research in textual analysis, transcription, and historical linguistics.

Analyzing Speeding-Related Crash Severity On Louisiana’S Highways, Nelly Akweley Ankrah

Masters Theses

Speeding is a major contributing factor to roadway crashes and remains a significant safety concern. Understanding the factors influencing speeding crash severity and how they vary across roadway environments is essential for developing effective safety countermeasures. A total of 22,151 speeding-related crashes recorded in Louisiana between 2015 and 2024 were analyzed. Crashes were categorized by FHWA functional classification into three roadway groups: Interstates and Principal Arterials, Minor Arterials and Collectors, and Local Roads. Four spatial machine learning models, GXGBoost, SDT, GRF, and GeoKNN, were evaluated to classify crash severity outcomes, as traditional models do not account for the spatial dependence …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …