Digital Commons Network^™

Harmonic Rescue Lantern (Hrl), Michael Victor Caldwell Mr.

Defensive Publications Series

The Harmonic Rescue Lantern (HRL) is a grapefruit‑sized, passive, quasicrystalline survival device designed to increase human survivability in aquatic and terrestrial emergencies without requiring power, electronics, fuel, or moving parts. The HRL integrates a hollow icosahedrally derived quasicrystalline shell, a tension‑balanced internal lattice, a passive acoustic resonator, and a thermal boundary‑layer geometry to provide four simultaneous life‑supportive functions: omnidirectional optical scattering, enhanced acoustic signaling, buoyant high‑visibility flotation, and localized thermal stabilization.

The HRL is optimized for oceans, lakes, rivers, streams, and floodwaters, where conventional signaling tools often fail due to battery loss, corrosion, or mechanical damage. Any available light source—sunlight, …

Hardware-Enclaved Isolation Interface With Dynamic Visual Obfuscation And Asynchronous Keyboard Hid Emulation Valve, Daitona Carter

Defensive Publications Series

This disclosure defines a system and framework for establishing an out-of-band hardware trust boundary between user input peripherals and an untrusted host computing environment. By routing user keyboard hardware directly to the isolated internal memory architecture of a dedicated, non-networked processing unit, alphanumeric keystrokes are completely decoupled from the host operating system's kernel. The dedicated processing architecture localizes and isolates text processing from Ring 0 exploits, keyloggers, and system-level compromises present on the primary machine. The system subsequently utilizes native human interface device (HID) emulation classes to relay the processed string to the host system via a physical, hardware-isolated link.

Icosahedral Quasicrystalline Monolith (Iqm), Michael Victor Caldwell Mr.

Defensive Publications Series

The Icosahedral Quasicrystalline Monolith (IQM) is a macro‑scale, icosahedrally symmetric, aperiodic quasicrystalline metamaterial designed to exhibit topological resonance, scale‑invariant behavior, field stabilization, and analog physical computation.

The IQM is released freely as a conceptual online invention, intended for global scientific study, fabrication, and experimentation.

This document provides complete build specifications, materials, CAD constraints, ASCII blueprint diagrams, fabrication steps, safety guidelines, laboratory testing protocols, validation criteria, and performance comparisons enabling any qualified research group to fabricate and study the IQM immediately using commercially available tools.

The IQM is intended for open exploration in acoustic metamaterials, topological physics, electromagnetic field control, analog …

Vectorized Pipeline For Real‑Time Lock‑In Amplification On Microcontrollers, Gary Cheng

Defensive Publications Series

Lock‑in amplification involves extracting weak signals from background noise, a process that traditionally utilizes computationally intensive floating‑point operations. Performing these operations on standard microcontrollers frequently causes central processing unit (CPU) saturation. The disclosed system provides a vectorized data pipeline that structures digital signal processing tasks to natively utilize internal hardware multiply‑accumulate instructions within a microcontroller. To bypass runtime floating‑point trigonometry, a pre‑computed integer look‑up table and a phase accumulator generate reference waveforms. Further, a scaling recovery algorithm mathematically restores absolute physical units following high‑speed hardware vector bit‑shifts. Consequently, the disclosed system facilitates real‑time, phase‑sensitive signal extraction on resource‑constrained microcontrollers, decreasing …

Dynamic Programming For Post‑Route Power Delivery Network Augmentation, Prateek Pendyala, Vishant Gotra

Defensive Publications Series

Modern high‑performance integrated circuits frequently experience localized dynamic voltage drop hotspots due to accumulated peak currents in congested layout regions. Traditional post‑route power grid augmentation approaches may encounter limitations due to routing blockages and a lack of available placement sites. The disclosed method provides a track‑aware standard cell repositioning technique that treats a post‑route layout database as a primary constraint and standard cell locations as adjustable variables. A computing device executing a dynamic programming algorithm scans lower‑level metal tracks to identify continuous vertical routing corridors. It then calculates localized standard cell displacements to accommodate the insertion of new power grid …

Rapid Ir Hotspot Identification Via Hybrid Machine Learning, Praphulla Pandey, Vaibhav Gupta

Defensive Publications Series

Traditional dynamic voltage drop (IR drop) analysis in integrated circuit design might be computationally expensive and oftentimes relies on late‑stage routing data. These traditional methods can lead to delays in design closure and may increase infrastructure costs due to high resource needs. This document discloses a two‑stage hybrid machine learning method for rapid IR hotspot identification. As a part of the method, an algorithm utilizes a gradient boosting model to capture a bulk IR drop distribution and triggers a neural network for high‑risk instances to predict peak hotspot values. The method incorporates physics‑grounded features (e.g., power switch density for gated …

Predictive Workload Modeling And Voltage Scaling Using Event‑Driven Workload Queue Telemetry, Girish Vv

Defensive Publications Series

Conventional power management methods for processors may be reactive, adjusting frequency only after a computing device exceeds utilization thresholds. This reactive lag may result in increased latency for sudden workload bursts and allow low‑priority background tasks to trigger voltage increases. This publication describes a predictive frequency scaling method based on real‑time introspection of operating system workqueues. Implementing the method, a computing device may extract internal statistics (e.g., queue depth, task wait times) through event‑driven kernel tracepoints. The computing device can identify task priorities by resolving function pointers and incorporating application‑level telemetry. The computing device then generates a predictive workload index …

Generating Structured Responses From Large Language Models For Client-Side Updates, Duc-Hieu Tran, Florian Hartmann

Defensive Publications Series

Interactive systems using large language models (LLMs) may experience inefficiencies where a user edit to a query can trigger a re-inference process, consuming resources and increasing latency. A backend system can predict potentially editable components in a user's query. An LLM may then generate a structured response containing static text and executable client-side functions or tool calls corresponding to these predicted components. A client device, such as a smartphone or personal computer, can parse this response to render an interactive interface. This can allow user modifications to interactive components to be processed locally on the client device, which may reduce …

Defensive Publication Concerning Electrical Machines, Optionally With Externally Pressurized Fluid Bearings, For Wind Power Generation And Marine Propulsion, Per Lenberg

Defensive Publications Series

This disclosure relates to application systems comprising an electrical machine having a rotor, a stator, one or more windings, and optionally one or more externally pressurized fluid bearings configured to maintain a fluid film between movable and stationary machine parts. In particular, the disclosure describes use of such electrical machines as motors, motor- generators or generators in wind turbines and wind power plants, and as motors, motor- generators or generators in marine propulsion systems, including pod propulsion systems, azimuthing thrusters, tunnel thrusters, rim-driven propulsors, shaft-line propulsion systems, pump jets, and water jets. The electrical machine may comprise an axial flux, …

The Impact Of Artificial Intelligence On Strengthening Democracy, Lect. Dr. Majid Hamed Faraj, Lect. Dr. Mahmood Noori Matlab

Imam Ja'afar Al-Sadiq University Journal of Legal Studies

The research aims to examine the impact of artificial intelligence on promoting democracy and the associated challenges. Using an analytical approach, the findings suggest that AI can improve the accuracy and objectivity of information, contribute to strengthening the rule of law and public opinion analysis, and play a role in the legitimacy of elections by ensuring their integrity. However, the findings indicate that overreliance on technology may weaken direct interaction between government and citizens and negatively impact individual rights. There are also risks related to the collection of voters’ personal data and the unethical exploitation of AI. The study suggests …

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 Of Transfer Student Policies And Practices At Four-Year Public Regional Universities In Louisiana, Mickey Diez

Doctoral Dissertations

This research study presented a qualitative, multiple case study that examined the extent to which universities within the University of Louisiana System (ULS) align their transfer policies and practices with national best practices for transfer student success, as outlined in the American Association of Collegiate Registrars and Admissions Officers’ A Guide to Best Practices: Awarding Transfer and Prior Learning Credit (AACRAO, 2017). Through a document analysis of institutional transfer policies and practices, the study aimed to identify common themes, similarities, differences, strengths, and gaps in institutional support for students transferring from two-year community colleges to four-year universities. The study was …

An Oral History Study: The Relationship Between Curriculum And Social And Cultural Capital In The New Orleans School System, Alaina Gaugis Carter

Doctoral Dissertations

This oral history study examines how high school academic experiences in New Orleans public and charter schools have shaped graduates’ preparedness for adulthood, active citizenship, and participation as productive members of society. This study explores the relationship between curriculum, particularly scripted curriculum, and the development of social and cultural capital. The research critiques neoliberal education reforms that prioritize accountability, standardization, and market-based outcomes over relational and community-centered learning. Using oral history methodology and the currere method, semi-structured interviews were conducted with twelve New Orleans high school alumni who graduated both before and after Hurricane Katrina from public, charter, and parochial …

An Exploration Of Variables Related To Gender Role Differences And Social Relationships Among Nontraditional Bachelor's Degree Recipients, Cynthia Bourgeois Bergeron

Doctoral Dissertations

The goal of this study was to examine variables that speak to gender role differences among nontraditional bachelor’s degree recipients aged 30 to 49. These issues are particularly relevant given enrollment trends showing that the diversification of bachelor’s degree seekers has outpaced the policies and norms of traditional undergraduate education. A nonexperimental, correlational research design was employed using chi-square tests and Cramer’s V as post-hoc measures on categorical data from the 2012, 2014, and 2016 General Social Survey. Shaped by Gilligan’s moral development theory, several social variables were included in the analysis. Two statistically significant associations emerged: women earning bachelor’s …

A Cross-Sectional Study Of First-Generation College Students' Sense Of Belonging Across Diverse Institutional Contexts, Nirmal Chandra Gope

Doctoral Dissertations

First-generation college students comprise a significant growth demographic in U.S. higher education. Even with lower enrollment rates, more than one-third of U.S. postsecondary school students are first-generation students (Cataldi et al., 2018; Redford & Mulvaney Hoyer, 2017; Ward et al., 2012; Whitley et al., 2018). However, their retention and graduation rates are significantly lower than those of their continuing peers (Choy, 2001; Engle, 2007, 2008; Ishitani, 2006; Longwell-Grice & Longwell-Grice, 2021). Various factors play a significant role in creating this disparity (Longwell-Grice & Longwell-Grice, 2021; Tinto, 1993). Research identifies belonging as a crucial factor influencing student persistence, academic achievement, mental …

The Pie Thief (And Friends): Ethnographic Microanalysis Of Peer Interactions Involving Children With Highly Unintelligible Speech: A Descriptive Study, Katherine Anne Mcquitty Hays

Doctoral Dissertations

This dissertation is an ethnographic microanalysis investigating how children with highly unintelligible speech accomplish a range of social actions when interacting with their peers. Detailed transcription of multimodal communications of peers interacting in the context of a 9-day summer therapy camp yield profiles of two participants of interest, each with approximately 30-40% speech intelligibility. Domain analysis and taxonomy organize data for the purposes of comparative analysis across transcribed durations of peer conversation and peer play. Findings indicate pervasive pragmatic impacts as well as effective uses of multimodal means within interactional frames and schemas. Clinical implications include consideration of AAC optimization …

Uncovering Hidden Potential: A Multiple Case Study Of Best Practices To Identify Giftedness In Underserved Student Populations, Kevin Hislop

Doctoral Dissertations

This study investigates district-level practices that promote equitable identification of giftedness among underserved student populations, particularly those who are culturally, linguistically, and ethnically/economically diverse (CLED) (Briggs et al., 2008; Briggs & Renzulli, 2009; Lewis & Novak, 2019). Grounded in Renzulli’s Schoolwide Enrichment Model, the research addresses persistent disproportionality in gifted education by examining how universal screening, teacher education, and alternative opportunities for talent development—such as student academic portfolios, teacher referrals, and nonverbal ability tests—can expand access or limit barriers to gifted services. Drawing from a solid literature base, the study emphasizes systemic barriers rooted in traditional IQ-based identification and subjective …

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 …

Fairness-Aware And Efficient Federated Learning Frameworks For Heterogeneous Systems, Simin Javaherian

Doctoral Dissertations

Federated Learning (FL) enables decentralized clients to collaboratively train machine learning models without sharing raw data, making it a promising paradigm for privacy-preserving intelligence across large-scale, heterogeneous systems. However, practical FL environments face significant challenges arising from variations in client resources, participation patterns, client behavior, and data distributions. These challenges often lead to inefficiency, unbalanced contributions, and unfairness, ultimately degrading model performance and discouraging long-term client participation. This dissertation advances the state of FL by developing a unified suite of fairness-aware and efficiency-driven frameworks tailored for heterogeneous environments. We investigate fairness from multiple perspectives, including client selection, contribution weighting, and …

Out There: Notes And Stories A Hybrid Collection With Critical Introduction, Ben Porter

Doctoral Dissertations

This dissertation is composed of two parts: literary criticism and a collection of fiction and lyric essays. Across both sections, it examines the problem of description: how persons make experience, action, and suffering intelligible in language, and what happens when that intelligibility breaks down under historical, social, and familial pressure. The critical essay, “Failed Descriptions and Neoliberal Talk in Don DeLillo’s The Body Artist,” argues that DeLillo represents a crisis of intentional speech under neoliberal modernity, in which public language is narrowed to private affect and meaningful social description becomes increasingly difficult. Reading the novel through philosophers of language and …

Investigations Of Carbon Dioxide Storage In Low-Temperature Reservoirs For Non-Leaking Storage, Md Nahin Mahmood

Doctoral Dissertations

Carbon dioxide (CO₂) injection into subsea or low-temperature water zones has emerged as a promising strategy for long-term, non-leaking CO₂ storage through the formation of solid hydrates. This research investigates CO₂ injection into Berea sandstone cores saturated with water under simulated subsea conditions, focusing on hydrate formation behavior across varying temperatures, pressures, and injection flow rates. Experimental results demonstrate that CO₂ hydrate formation under dynamic (flowing) conditions occurs at significantly higher pressure compared to static conditions reported previously. At temperatures ranging from 0 °C to 5 °C, dynamic hydrate formation pressures were observed to be approximately double. This can be …

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 …

A Qualitative Study Examining Teachers' Knowledge And Awareness In Recognizing The Characteristics Of Twice Exceptional Learners: An Underrepresented And Underserved Population, Adrianne Monique Williams

Doctoral Dissertations

Over the past 30 years, research on twice exceptional learners has been gradually increasing, however, knowledge and awareness of the information in the educational community have been slowly evolving (Bailey & Rose, 2011; Baum, 2004). Outwardly, twice exceptional students may present as typical. Still, they face many unique challenges that include academic achievement, social awkwardness, executive functioning deficits, social communication challenges, and teachers who are not aware and trained to meet the atypical needs of these students. Researchers and practitioners are becoming increasingly aware of the underrepresentation that plagues gifted and talented programs, especially concerning twice exceptional students, and students …

Diversity, Systematics, And Phylogenomics Of The Neotropical Glass And Longtail Knifefishes (Gymnotiformes: Sternopygidae), Kevin Thomas Torgersen

Doctoral Dissertations

This dissertation provides a comprehensive systematic and phylogenetic study of the electric knifefish family Sternopygidae, integrating morphological, molecular, osteological, and phylogenomic data to clarify species diversity, evolutionary relationships, and biogeographic patterns in this Neotropical group. Across six studies, the work reveals that Sternopygidae diversity has been significantly underestimated due to morphological conservatism that obscures species boundaries. Chapter 1 revises the genus Sternopygus in the Guiana Shield, identifying nine species (five new) using osteology, morphometrics, and µCT imaging. Distinct anatomical traits and distribution patterns show strong regional structuring, highlighting the Guiana Shield as a diversification center. Chapter 2 describes a new …

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 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, …