Digital Commons Network^™

Diseño Visual, Identidad De Género Y Diversidad Cultural En La Animación Contemporánea: El Caso De Raya And The Last Dragon, Elisabet Fonts González

GDI. Revista de investigación de Género, Diseño e Innovación

En los últimos años, la animación ha evolucionado hacia representaciones más inclusivas de género y diversidad cultural. Raya and the Last Dragon (López Estrada & Hall, 2021) destaca como un caso significativo de esta transformación, integrando elementos visuales, narrativos y simbólicos que reconfiguran los arquetipos femeninos tradicionales. Este estudio adopta un enfoque cualitativo centrado en el análisis visual, narrativo y simbólico de los personajes Raya, Namaari y Sisu. Basándose en fuentes primarias del proceso creativo y marcos teóricos de la animación y los estudios de género (Furniss, 2017; Lauretis, 1987; Wells, 1998), presta especial atención al diseño de personajes, la …

Colaboración, Discurso Y Técnicas: La Resistencia Simbólica En El Sueño De La Sultana (Isabel Herguera, 2023), Nerea Cuenca-Orellana

GDI. Revista de investigación de Género, Diseño e Innovación

La película El sueño de la sultana (Isabel Herguera, 2023) reinterpreta el cuento utópico homónimo de Rokeya Sakhawat Hossain (1905) realizando una exploración visual que combina animación, archivo y testimonio. El presente trabajo propone un análisis de la obra desde cuatro puntos clave e interrelacionados: la autoría colaborativa y femenina, los discursos visuales, los lenguajes y técnicas, y las formas de resistencia simbólica con el objetivo principal de establecerla como un caso práctico de diseño feminista contemporáneo.

En primer lugar, se examina el proceso de creación de la película como práctica colaborativa transnacional, donde la animación se convierte en un …

Enhancing Management Of Transportation Projects: Integration Factors For Using Smart Contracts, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The US Department of Transportation (USDOT) delivers a wide range of infrastructure projects, backed by a fiscal year 2023 budget exceeding $100 billion. These projects face mounting pressures to meet performance, accountability, and delivery standards, driven by their dependence on public funding and their operational complexity. Transportation infrastructure presents sector-specific challenges - such as time-sensitive user disruptions, multiparty coordination, and asset intersection risks - that demand more robust, automated, and transparent project delivery mechanisms. Blockchain-enabled smart contracts have emerged as a promising solution to address these operational pain points through real-time automation, immutable data records, and decentralized transaction processing. However, …

Processing-Driven Crystallization, Morphology, And Mechanics In Pekk Composites, Nicholas Ryan Enos

Dissertations

This dissertation aims to understand how thermoplastic composites can be processed at faster manufacturing rates while identifying how processing variables influence crystallization, morphology, and mechanical properties. Throughout this dissertation, the influence of nano-scale additives, carbon fibers, rapid cooling, shear, and molecular weight on polymer physics, crystallization, morphology, and mechanics is investigated.

The inclusion of carbon nanotubes and graphene nanoplatelets accelerated crystallization, increased nucleation density, reduced lamellar thickness, and shifted governing Hoffman-Lauritzen growth regimes in PEKK. Velisaris-Seferis modelling identified a surface-induced nucleation mechanism in PEKK nanocomposites, and fast scanning calorimetry allowed for the study of rapid cooling rates, helping to identify …

On The Scalability Of Anisotropic Mesh Adaptation On Distributed And Shared Memory Architectures For Numerical Approximations, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Mesh generation is a critical component in numerical approximations of Partial Differential Equations (PDEs). One such example includes Computational Fluid Dynamics (CFD), as CFD simulations in turn are crucial for applications in many industries, such as personalized healthcare and the design of aerospace vehicles. Generating high quality meshes for large-scale CFD problems presents a significant bottleneck in the CFD workflow. This dissertation proposes “fast,” parallel 3D mesh generation methodologies that are designed to leverage the concurrency offered by emerging High-Performance Computing (HPC) architectures. First, a distributed memory method is presented that integrates a sequential state-of-the-art isotropic, advancing front local reconnection-based …

The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden

Milne Open Textbooks

Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.

Demystifying the Machine

This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …

Next-Generation Underwater Localization: Artificial Intelligence-Based And Energy-Aware Approaches, Mainul Islam Chowdhury, Quoc Viet Phung, Iftekhar Ahmed, Walid K. Hasan, Daryoush Habibi

Research outputs 2022 to 2026

Designing accurate, reliable, and energy-efficient localization techniques for underwater acoustic networks is highly challenging due to factors such as large propagation delays, the absence of Global Positioning System (GPS), node mobility, and limited acoustic link capacity. In any underwater sensor network (UWSN) monitoring application, data collected by underwater nodes becomes more meaningful when accompanied by location information. However, traditional localization methods often rely on geometric models and statistical filters that are highly sensitive to sensor noise and communication constraints. Energy consumption is another primary concern in UWSNs, not only because replacing and recharging underwater batteries are challenging, but also due …

Data-Driven Evaluation Of Sustainable Waste-To-Energy Pathways For Intelligent Urban Systems, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The handling of municipal solid waste (MSW) in swiftly urbanizing Philippine cities poses intricate energy and governance challenges. In Baguio City, reliance on landfills has reached critical levels due to diminishing capacity, rising transport costs, and opposition to trash transfers by nearby LGUs. Although shaped by unique topographical and governance constraints, Baguio’s situation reflects issues faced by other rapidly growing Philippine cities; therefore, analyzing it offers insights for national MSW decision-making. This study applies a triple bottom line (TBL) framework to assess three management scenarios: (1) Status Quo, where all MSW is landfilled with no energy recovery; (2) Landfill with …

Machine Learning For Anomaly Detection In Neural Network Security And Srf Cavities, Hal Ferguson

Electrical & Computer Engineering Theses & Dissertations

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications.

First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves …

Private Sand Mining In The Mississippi River: Sediment Budget And Morphology Implications Between Baton Rouge And Belle Chasse, Louisiana, Brett Mcmann

LSU New Orleans Theses and Dissertations

This analysis examined how private sand mining within the Mississippi River between Baton Rouge, LA and Belle Chasse, LA affected its sand budget from 2004-2012.

Records assembled indicated that private mining removed an annual average of 2.8 million cubic yards of sand. A HEC-RAS one-dimensional sediment transport model was utilized to assess this practice. Three scenarios were simulated: a baseline without mining, conditions reflecting documented mining rates, and a hypothetical case with excessive extraction.

Results suggest that private mining constituted approximately 26 percent of the total sand deficit between Baton Rouge and Belle Chasse. Mining appeared to cause localized changes …

Diabetes-Induced Mitral Valve Degeneration: Tissue-Engineered Solutions And Antioxidant Therapy, Samantha Hahn

All Theses

Mitral valve (MV) fibrosis is a progressive pathological condition characterized by leaflet thickening and stiffening, ultimately compromising valve function. This process is accelerated in diabetes, where chronic hyperglycemia elevates reactive oxygen species (ROS) and alters the mechanics of the extracellular matrix (ECM), collectively promoting the activation of valvular interstitial cells (VICs). Under healthy conditions, VICs maintain a quiescent, fibroblast-like phenotype responsible for sustaining ECM homeostasis. However, pathological biochemical cues or mechanical stress drive VICs toward a myofibroblast phenotype. While this transformation is essential for short-term repair, its persistence contributes to maladaptive MV remodeling and fibrosis. Diabetic stressors may be mitigated …

Mitral Annular Calcification In Diabetes: Valvular Interstitial Cells, Antioxidant Therapy, And Tissue Engineering Approaches, Raleigh J. Keenan

All Theses

Mitral annular calcification (MAC) is a chronic, progressive, and degenerative condition that impairs mitral valve function and increases the risk of cardiovascular disease. The mitral annulus is a saddle-shaped, fibrous structure that is primarily composed of collagen and elastin. The annulus also contains interspersed lipids that are involved in cellular metabolism, as well as inflammatory and osteogenic signaling. These lipids increase the annulus’ susceptibility to calcification, under conditions that increase mechanical stress (hypertension) and promote atherosclerosis (diabetes mellitus). These conditions intensify calcification by promoting the activation of valvular interstitial cells (VICs), increasing fibrosis, and inducing osteogenic differentiation. Although it is …

The Iron Pyramid: Expanding The Iron Triangle To Integrate Safety As A Fundamental Dimension Of Construction Success, Laura Cooley

All Theses

For more than fifty years, construction project success has been judged by staying on schedule, remaining within budget, and completing the planned scope of work—an approach commonly known as the “Iron Triangle” (Barnes, Ph.D., 2006). While these measures are important, they do not capture the full range of factors that determine whether a project truly succeeds.

This study introduces the “Iron Pyramid” (Cooley, 2025), a model that expands the traditional framework by adding a fourth dimension: safety. Safety is understood not simply as regulatory compliance or the absence of injuries, but as a holistic construct encompassing project culture, leadership practices, …

Locomotion And Balance Control In A Biped Robot With Continuum Legs And A Kangaroo-Inspired Tail, Gavin A. Platt

All Theses

This thesis work presents the design, testing, and validation of a continuum-legged biped robot equipped with a kangaroo inspired tail for enhanced stability and adaptability. Unlike traditional rigid link robots, this one expands on soft-legged robots and utilizes tendon-driven continuum robots to mimic octopus and kangaroo behavior for locomotion. The robot uses a hierarchical hybrid control framework to implement walking, obstacle avoidance, vaulting, and push recovery behaviors. To test the performance of the robot four sets of experiments were conducted to validate these systems and evaluate how they performed. The results demonstrate stable walking with rhythmic tail load transfer, effective …

Barriers To Modernizing Aviation Maintenance Technician Education To Meet Emerging Industry Needs, Durwa Chavan

All Theses

Modernizing aviation maintenance education is essential to keep pace with emerging technologies, including electric propulsion systems and advanced avionics. As aircraft systems become more digitized and interconnected, there is a growing demand for qualified technicians who can conduct advanced diagnostics and maintenance. However, training programs have not kept pace with these technological shifts, creating a gap between workforce preparation and industry needs.

Using a qualitative research approach, this study conducted semi-structured interviews with industry professionals, educators, and regulatory personnel to identify gaps in existing training programs and Airman Certification Standards (ACS). This study addresses the disconnect between current aviation maintenance …

Examining The Relationship Between Title 14 Code Of Federal Regulations (Cfr) Part 147 Maintenance School Aviation Maintenance Technician (Amt) Instructor Experience And Instructor Pass Rates For Airmen Certification Standards (Acs) Element Subject Areas, Richard Lyman Johnson

Theses and Dissertations

This quantitative, correlational study examined the relationship between Aviation Maintenance Technician (AMT) instructor experience and student pass rates in 14 CFR Part 147 maintenance schools. Data were collected from February to August 2025 using purposive and snowball sampling, which yielded 67 complete responses. Instructor experience, measured in months of A&P-rated maintenance work prior to teaching, ranged from 1 to 684 months (M = 253.54, SD = 197.97). Student pass rates, defined as the proportion of students passing ACS element subject area courses, ranged from .52 to 1.00 (M = .95, SD = .07). Most instructors were male, White, over 50 …

Exploring Transformative Learning Experiences In Engineering Doctoral And Post-Doctoral Education: Developing Non-Technical Competencies For Early-Career Academic Roles, Ibukunoluwa Eunice Salami

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores the transformative learning experiences that early-career engineering faculty recounted from their doctoral and postdoctoral training and how these experiences shaped the development of non-technical competencies essential for academic success. Grounded in Mezirow’s Transformative Learning Theory (TLT) and the Competency-Based Professional Development Framework (CBPDF), the study examines how reflection and shifts in frames of reference supported competency growth and faculty readiness. A qualitative holistic single-case study design was employed. Data sources included semi-structured interviews with early-career engineering faculty and program learning objectives drawn from graduate handbooks. Data analysis was both deductive and inductive guided by Mezirow’s ten phases …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

Real-Time, Co-Regulated Design For Cyber-Physical, Multi-Rotor Uas Swarms, Grant Simon Phillips

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Uncrewed Aerial Systems (UAS) have been integrated into a wide range of research and industrial applications, with growing interest in extending mission duration and spatial coverage through coordinated multi-UAS systems, or swarms. While swarming offers the potential for extended mission endurance and robustness through advanced path-planning, control, and estimation algorithms, significant challenges arise when implementing these methods on decentralized platforms composed of size, weight, and power-constrained (SWaP) vehicles. Limitations in onboard computational capacity and congested communication channels can break critical design-time assumptions, which at best, will degrade application quality of service, and at worst, destabilize the fleet through excessive delays …

Making Deep Neural Networks Trustworthy: Intelligibility And Safety Through Symbolic Methods, Eleanor Catherine Quint

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The rapid adoption of deep learning has come at the cost of properties long valued in artificial intelligence: intelligibility and safety. This dissertation develops methods that restore these properties by coupling neural networks with symbolic structure.

First, for supervised classification, I propose a differentiable decision tree integrated with a supervised variational autoencoder. The resulting model maintains competitive accuracy and generative performance while exposing clear macro-features in its latent space, improving interpretability.

Second, for reinforcement learning, I extend constrained Markov decision processes by specifying constraints in formal languages. This formal language constrained MDP enables the use of automata for state augmentation, …

Building Kit For K-8 Education: An Introduction To Construction Fundamentals, Marc Joynt

Construction Management

Introducing construction concepts to young students requires tools that are both engaging and easy to use, which led to the development of a laser-cut building kit designed for K–8 classrooms. The process began with hand-drawn sketches to establish a simple, age-appropriate structure. The design was then modeled in AutoCAD, where each individual component was drafted for fabrication. After completing the digital model, the files were transferred into Rhino and organized by layer to ensure accurate communication with the laser cutters used to produce the final basswood pieces. Throughout the project, challenges such as material limitations, tolerance adjustments, and simplifying complex …

A Human Factors Analysis And Classification System (Hfacs) Approach To Compare Cardiovascular, Orthopedics, Trauma Care, And Neurosurgery, Asfandyar Khan

Doctoral Dissertations and Master's Theses

Background: Despite significant progress in patient safety, human error continues to occur at high rates in procedural settings. Traditional safety models tend to focus on retrospective incident analysis, often overlooking the systemic conditions that allow errors to occur. The Human Factors Analysis and Classification System (HFACS) offers a proactive lens to understand how and where errors emerge and is useful for identifying active and latent failures.

Objective: To evaluate the utility and reliability of the Human Factors Analysis and Classification System (HFACS) in categorizing and comparing the pattern of frequencies (events) in cardiovascular, orthopedic, trauma care, and neurosurgical procedure.

Design, …

Thermal Management With Supercritical Carbon Dioxide Under Extreme Applications, Devon Hardy

Doctoral Dissertations and Master's Theses

A unique challenge in thermal system design is minimizing the power required to operate cooling systems while maintaining effective heat removal. Traditional cooling systems utilize single-phase fluids where the heat transfer mechanisms are well understood. To meet a variety of cooling demands, a range of technologies are available, including microchannel forced convection, jet impingement, porous media, nanofluids, pin fin arrays, and film cooling, each offering distinct advantages and limitations. While the performance of single- or two-phase cooling systems are generally predictable, in extreme thermal environments, new cooling solutions are needed to improve overall system efficiency and reliability.

Supercritical fluids, particularly …

Propeller Noise Prediction Of An Urban Air Mobility Vehicle In Urban Environment, Jie Hua

Doctoral Dissertations and Master's Theses

Urban Air Mobility (UAM) vehicles operate in complex, unsteady aerodynamic environments where wake interactions, gust and turbulence significantly affect both performance and noise generation. Understanding these mechanisms is critical for developing quieter and more efficient eVTOL systems that meet future community noise and certification requirements. This dissertation focuses on the high-fidelity numerical investigation of propeller noise in three representative unsteady loading scenarios: (i) transition (tilt) flight, (ii) edgewise inflow, and (iii) wake–propeller interaction. Each case emphasizes different physical mechanisms that dominate noise generation in UAM operations. Hybrid turbulence-resolving approaches—Detached Eddy Simulation (DES) and Delayed Detached Eddy Simulation (DDES)—are coupled with …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

From 2d To 3d: Multi-Agent Reinforcement Learning For Spectrum-Constrained Urban Air Mobility., Qingyang Li

Electronic Theses and Dissertations

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) are accelerating a transformation of air transportation but face acute spectrum congestion in dense urban environments. Reliable Control and Non-Payload Communications (CNPC) must be maintained at all times to ensure safe operations, even as fleets of aerial vehicles (AVs) transport passengers and cargo between distributed vertiports. We first develop a 2D formulation that jointly optimizes discrete headings, velocities, and spectrum allocation to minimize total mission time while satisfying quality of service (QoS) and collision-avoidance constraints, and we demonstrate significant gains over non-learning and learning baselines. Building on this 2D framework, we …

Feasibility And Potential Of Electric Air Taxis For Long Distance Airport Access/Egress Trips, Atul Subedi

All Graduate Theses and Dissertations, Fall 2023 to Present

Getting to the airport is often one of the most stressful parts of a trip, especially for people who live far from the airport. In the United States, many travelers live more than an hour’s drive from a major airport, and their choices such as driving, using public transit, or paying for ride-hailing can be time-consuming, expensive, and inconvenient. A new technology, Electric Air Taxis (EATs), is being developed as a potential solution. These small, battery-powered aircraft could offer faster, cleaner, and more direct connections to airports. However, the success of EATs depends not only on the technology itself but …

Enhancing Grid Integration Of High-Power Loads Through Modular Unfolding-Based Power Conversion With Decentralized Control, Sanat R. Poddar

All Graduate Theses and Dissertations, Fall 2023 to Present

The transition to electric vehicles (EVs) is a critical step toward reducing greenhouse gas emissions and creating a cleaner, more sustainable transportation sector. However, many drivers — particularly those operating larger vehicles such as trucks and buses — face significant challenges, including limited driving range and lengthy charging times. High-power, fast-charging stations, which can rapidly replenish EV batteries, are therefore essential for mitigating these barriers and making electric transportation practical across all vehicle classes.

Despite the promise of electric vehicles, deploying high-power fast-charging stations presents significant challenges. They require large amounts of electricity, making them expensive to install, operate, and …

Auction Consensus Algorithm With Loss Mechanism For Decentralized Task Allocation, Jose Rodriguez, Wenjie Dong, Constantine Tarawneh, Qi Lu

Electrical and Computer Engineering Faculty Publications

This paper presents an Auction-Consensus Algorithm with a Loss Mechanism (ACALM), a decentralized task allocation method for multi-robot systems that enhances the existing Consensus-Based Auction Algorithm (CBAA) by incorporating a novel loss propagation mechanism. In contrast to purely greedy bidding strategies, it enables agents to dynamically update task priorities based on the accumulated loss from previously unsuccessful bids. This extended work reduces globally inefficient allocations caused by early suboptimal decisions. The proposed approach is evaluated through large-scale simulations in thousands of randomized scenarios and swarm sizes ranging from 5 to 120 robots. Compared to existing CBAA and GCAA algorithms, ACALM …

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …