Digital Commons Network^™

Internet Of Things And Modern Digital Evidence Collection, Muhammad T. Haider

Student Theses

The ever-evolving landscape of technology and its innovations are populating our houses, streets and all kinds of industries. The use of smart devices is booming from most developed nations to underdeveloped countries. The complications which come with the use of the Internet of Things has been an active discussion for the past many years. If we look around in a room of 30 people, we will most likely find double the amount of IoT devices than the people in that room. All of those devices are connected to the Internet, and are communicating with data servers across the world. The …

A Study On The Propagation And Exploitation Of Structured Light In Underwater Turbulence, Jaxon P. Wiley

All Dissertations

The development and optimization of optical systems will play a pivotal role in the continued exploration and exploitation of the world’s underwater environments. These systems offer advantages in many sectors, and includes applications in areas such as high-speed communication, advanced sensing and imaging, and environmental characterization and monitoring. Underwater environments offer a plethora of challenges, however, and mitigating these obstacles remains an arduous task. In this work, the inherent advantages of structured light are leveraged to optimize optical system performance through non-ideal underwater conditions. Additionally, fundamental relationships between the generation of specified structured modes and their interactions with complex environments …

Multiple View Neural Regression Of A Facial Shape Model, Xiang Li

All Dissertations

Creating re-topologized 3D facial meshes is a critical step in high-quality facial animation pipelines, yet it remains a labor-intensive and time-consuming task. Traditional approaches typically rely on multiview stereo reconstruction and specialized photometric environments to acquire accurate geometric and reflectance data under controlled conditions. This dissertation presents work toward more efficient capture of production-ready meshes including (1) developmental aspects of VarIS, a custom-designed light sphere capable of capturing high-resolution stereo geometry and reflectance maps—including diffuse, specular, and normal components under programmable illumination; (2) a study of the effects of camera parameters on automatic 2D and 3D landmarking methods, (3) methods …

Studies On The Effects Of Operator Fatigue On Performance, Trust, And Workload Demand In Human-In-The-Loop Ai-Enabled Drone Systems, Snowil Lopes

All Dissertations

Civil infrastructure must be regularly inspected to ensure its safety and reliability. Traditionally, risk engineers performed these inspections manually and in person. However, with the introduction of drones equipped with artificial intelligence (AI), inspections of civil infrastructure can now be conducted remotely. These AI-enabled drones capture and analyze images, helping engineers monitor large and complex structures from a distance. However, working with integrated systems consisting of multiple drones, especially those with varying levels of reliability, can be challenging. Operators must divide their attention, determine how much to trust each drone, and manage mental workload, which can affect their performance. Another …

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Digital Twin For Real-Time Monitoring And Control Of Conveyor Systems Using Flexsim, Ai And Plc Integration, Jose Francisco Arvizu Astorga

Open Access Theses & Dissertations

Modern manufacturing is making significant advancements by innovating and automating most processes. However, a major challenge remains: systems are constantly evolving and becoming more complex to analyze. Fortunately, a powerful tool can help, Digital Twin (DT) technology. This technology enables the analysis and optimization of processes like never before. A Digital Twin is a real-time virtual model of a physical system that continuously up dates with live data. One of its greatest features is the ability to create infinite scenarios, allowing hundreds of configurations to be tested virtually, risk-free, and without making any real-world changes that could disrupt ongoing operations. …

Application Of Distributed Fiber Optic Sensing (Dfos) For Monitoring Asphalt Pavement Strains Under Accelerated Loading Conditions, Sebastian Morales

Open Access Theses & Dissertations

This thesis presents a study on the application of Distributed Fiber Optic Sensing (DFOS) technology for detecting pavement's strain response with high spatial resolution. Using a Rayleigh-based optical frequency domain reflectometry (OFDR) system, DFOS sensors were calibrated and embedded in full-scale asphalt slabs subjected to accelerated loading using a Model Mobile Load Simulator 3 (MMLS3). Calibration of the DFOS sensors was conducted using a three-point bending flexural test with known load conditions and reference strain gauges to validate theoretical and numerical models. The results demonstrate DFOS's capability to detect pavement response under static and dynamic loading, as well as changes …

Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw

Open Access Theses & Dissertations

The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …

Line Outage Impact Factors: A New Approach To Line Outage Detection With Machine Learning, Daniel Flores

Open Access Theses & Dissertations

Electric power systems have become one of our most critical infrastructures as we've grown dependent on electricity for everyday tasks. Ensuring power systems provide reliable service is a priority that can be affected by disturbance events. A common event is transmission line outages, where a line in the system becomes disconnected due to varying forms of physical damage. If an outage isn't detected in time, other lines in the system may overload, causing cascading failures that leave many customers without power. Therefore, having a power system that can automatically detect outages is crucial for reliability, as it promotes real-time response …

Design And Validation Of A High-Frequency Multi-Output Dc-Dc Converter For Radar Power Applications, Tory Sutton

Graduate Theses and Dissertations

Modern radar systems and advanced electronics demand compact, efficient, and reliable power solutions capable of delivering multiple tightly regulated voltage rails under strict size, weight, power, and reliability (SWaP-R) constraints. This thesis presents the design, implementation, and validation of a high-frequency (460 kHz – 1 MHz), multi-output DC-DC converter for a mission?critical radar platform, addressing both integration and performance requirements. The first implementation, an isolated modular converter (IMC), utilizes isolated silicon?based DC-DC modules to deliver twelve isolated voltage outputs from a single input. This approach provided robust electrical isolation, simplified system integration, and minimized design risk, making it well-suited for …

Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon

Theses and Dissertations

This dissertation advances the real-world implementation of the Well Optimized Linear Finder (WOLF) method for high-speed Atmospheric Turbulence Compensation (ATC). Atmospheric turbulence introduces phase aberrations into optical wavefronts and degrades image quality in terrestrial imaging systems. Traditional phase diversity methods are computationally intensive and poorly suited to real-time operation. The WOLF method addresses these limitations through a novel, point-wise formulation of the optical transfer function (OTF) as a structured autocorrelation of the generalized pupil function (GPF). This formulation enables the estimation of phase aberrations at individual spatial coordinates with distributed computational complexity.

The research begins by developing a MATLAB-based simulation …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

All Dissertations

The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Advancing Smart And Adaptive Living Spaces Through Design And Development Of Reconfigurable Multifunctional Robot Rooms, Nithesh Kumar

All Dissertations

This work explores and introduces prototype hardware for a new category of robots: ‘Robot Rooms’, in an effort to refine the concept of traditional smart spaces and human-robot interaction. Unlike traditional robots that tend to be compact and exist within a space, this new category of robots is designed to be expansive: they do not exist within a space but rather shape space around them. We present several design concepts for potential robotic elements of a Robot Room. We then develop and demonstrate, at full scale, a new and novel concept: a ‘slice’ of a Robot Room. This slice changes …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Designing Self-Healable Aromatic Copolymers And Olefinic Composites, Samruddhi Yashwant Gaikwad

All Dissertations

Self-healing polymers capable of recovering from mechanical damage are promising materials for advanced applications, especially those involving mechanical and/or physical fatigue. In these studies, we have developed techniques to achieve autonomous self-healing in commodity Styrene/n-butyl acrylate copolymers. The mechanism of self-healing in the designed polymers involves inter-and/or intrachain non-covalent interactions between π-cloud and polar linkages of acrylic nBA in random/preferentially alternating copolymers. A combination of spectroscopic tools, thermo-mechanical analysis, and molecular dynamics (MD) simulations has been used to elucidate the mechanism of self-healing. These studies further show the incorporation of dipolar C-F groups to understand the effect of having fluorinated …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

An Investigation Into The Impact Of Inverter Based Resources On Critical Clearing Time, Trupal Patel

All Dissertations

Renewable energy sources, mainly inverter-based resources (IBRs) such as solar and wind plants are being connected in large numbers to the bulk power grid in the United States and around the world. Additionally, generation using fossil fuels are being phased out, which results in the loss of rotor inertia, a key contributor to the transient stability of power systems. Therefore, the large-signal behavior of IBRs and its impact on transient stability must be studied.

This work studies this impact through the metric of critical clearing time (CCT). Impact of grid topology, generation mix and control modes of IBRs on CCT …

Design And Testing Method For Quality Control Of Chill Haze In Bourbon Production., Molly J. Wilburn

Electronic Theses and Dissertations

Chill haze is a quality issue in which white wisps and haze become visible in spirits when reaching sub 0℃ temperatures. Common quality control test methods rely on subjective visual tests and ambient temperature turbidity measurements. Currently there is limited access to commercial devices capable of reaching the sub 0 ℃ temperatures that are required for the formation of chill haze. This thesis focuses on the design, assembly and calibration of a custom-built turbidity meter capable of sub 0 ℃ temperatures and humidity control. The system uses an optical sensor at 90 ° to a light source to detect light …

A Methodology For Model-Based Certification, Jay Albert Silverman

Engineering Management & Systems Engineering Theses & Dissertations

A need for a single source of knowledge for design decisions has led to the development of a new field of systems engineering, model-based systems engineering (MBSE) (Delligati, 2014). System certification is defined as affirming that regulatory requirements for a system have been met (Goodwin & Juzaitis, 2006). System certification is a specific application of system validation. System verification can be defined as ensuring that the system of interest (SOI), as designed, is in accordance with the design inputs/requirements. System validation can be defined as ensuring that the SOI, as designed, meets the defined system needs (Wolfgand, Katz, & Wheatcraft, …

Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou

Electrical & Computer Engineering Theses & Dissertations

As Artificial Intelligence (AI) systems become increasingly integrated into critical domains, ensuring privacy-preserving model design and system deployment has become a pressing priority. Safeguarding both sensitive user data and proprietary model parameters is critical throughout the AI model and system, from data acquisition and pre-processing to model inference and deployment. However, existing privacy-preserving frameworks face several limitations, including fragmented data ownership, incomplete protection across system stages, substantial computational overhead, and poor scalability to modern architectures such as large language models. This dissertation explores a unifying optimization strategy centered on input structure design to address these challenges. The core idea is …

Human Activity Recognition And Identification Driven Automated Deep Learning For Time-Series Classification, Justin Alan Gamble

Engineering Management & Systems Engineering Theses & Dissertations

The growing emphasis on Digital Engineering (DE) within the U.S. Department of Defense (DoD) demands advanced methods for leveraging vast time-series data generated by sensor-rich environments. Deep learning models offer promising solutions for complex timeseries classification tasks, however their design and optimization remain highly resource intensive, requiring specialized expertise. This dissertation addresses this challenge by developing and evaluating an Automated Machine Learning (AutoML) framework specifically tailored for the time-series classification task of Human Activity Recognition and Identification (HARI).

A systematic investigation was conducted using the Design Science Research Methodology (DSRM) comparing traditional search strategies of grid search and random search …

Mantle Flow And Crustal Deformation Revealed By Seismic Anisotropy In The Subduction Zone Beneath Myanmar, Enbo Fan, Mingming Jiang, Yinshuang Ai, Stephen S. Gao, Kelly H. Liu, Yumei He, Yiming Bai, Guangbing Hou, Yuan Ling, Chit Thet Mon, Myo Thant, Kyaing Sein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The oblique convergence of the Indian and Eurasian plates drives significant deformation in the crust and mantle beneath Myanmar. However, the crustal deformation in the Indo-Burman Ranges (IBR) and mantle flow beneath Myanmar and adjacent areas remain unclear due to limited studies. We utilized data from the newly deployed second phase of the China-Myanmar Geophysical Survey of the Myanmar Orogen array to perform shear wave splitting analysis of PKS, SKKS, and SKS (XKS) phases. Our results, together with previous findings, provide new insights into mantle flow and crustal deformation across central Myanmar. In the IBR, we observed a transition from …

Validation Of A Methodology For Predicting Yield Acceleration Of Rock Blocks, Madison Haydn-Myer

Graduate Theses & Non-Theses

Rock slope stability is a critical concern in seismically active regions, where earthquakes can trigger sudden and hazardous failures. Predicting these failures is challenging due to the complex interactions between seismic loading and geological characteristics. This study proposes a simplified analytical model to predict yield acceleration based on the forces acting upon a block just before sliding initiates. A key parameter in this equation is the friction acting on the bottom surface of the block. As rock blocks are commonly formed by the intersection of sets of subparallel fractures known as joints, and the roughness and other features of those …

Genwriter: Reducing Gender Cues In Biographies Through Text Rewriting, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Gendered language is the use of words that indicate an individual’s gender. Though useful in certain context, it can reinforce gender stereotypes and introduce bias, particularly in machine learning models used for tasks like occupation classification. When textual content such as biographies contains gender cues, it can influence model predictions, leading to unfair outcomes such as reduced hiring opportunities for women. To address this issue, we propose GenWriter, an approach that integrates Case-Based Reasoning (CBR) with Large Language Models (LLMs) to rewrite biographies in a way that obfuscates gender while preserving semantic content. We evaluate GenWriter by measuring gender bias …

Supporting Programmers Answering The Hard-To-Answer Questions Through The Use Of Large Language Models, Haixin Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Programmers often face hard-to-answer questions when working on large-scale projects. Not only during team collaborations, but also during interruptions such as meetings, having to suddenly work on another project, or even just taking a break are major reasons these questions arise, as programmers have to regain the context, knowledge, and mental state to resume the work. Traditional text editors such as GitHub do provide a built-in history system, but they lack historical context behind the editing to answer such questions.

To address this issue, we developed an experimental extension, Code History, on Visual Studio Code (VS Code) in the hope …

Designing A User-Centered Bias System To Enhance Media Literacy And Factual Accuracy, Anjali Majan

Theses and Dissertations

In an era of rapid news consumption, readers often struggle to detect bias and misinformation. This study examined whether interface design can support more critical engagement with news. We developed a progressive disclosure interface that encouraged users to reflect as they read by gradually revealing bias and factual cues. Participants were assigned to either Progressive Disclosure or Ground News. The experiment involved two phases. In the intervention phase, participants used an interface with support features. In the assessment phase, they completed tasks without the tool. We evaluated their performance using five measures: bias recognition accuracy, bias shift, factuality judgment, overlap …

Building A Sustainable Home On The Central Coast: An Owner’S Perspective, Austin Chase Anderson

Construction Management

As awareness and technology increase, sustainability as a focus in home construction is also increasing. This case study based research project seeks to understand the process of building a home on California’s Central Coast with sustainability in mind. An interview was conducted with an owner who built their home in Templeton in 2019. The interview was in a semi-structured format which included specific qualitative questions but mostly focused on an open-ended discussion which allowed the owner to share their own experience. The key challenges learned from this interview were that the owner believed price to be the main factor that …

The Significance Of Snow In Hydrometeorological Extremes, Sinan Rasiya Koya

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

Snow is the largest natural reservoir on Earth. It accumulates water during the cold and dry months and releases it during warm and dry months. Societies, especially in the extratropical zone, heavily depend on snow as their freshwater resources, resulting in the massive economic value of snow. The recent changes in snowpacks and associated processes are concerning. We are susceptible to disruptions in snow processes, which can have disastrous implications. Yet the importance of snow is often not realized by a wider population. There are limited studies quantifying snow-related extremes, partly stemming from the limitations of existing methodologies.

This dissertation …

Mass Effects On Energy Transfer Paths In Nonlinear Vibrating Systems, Manal Mustafa

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

This dissertation examines the role of mass in nonlinear systems, uncovering its role in enabling passive energy redistribution and robust vibration control in both idealized and real-world structures. Focusing on a strongly nonlinear two-degree-of-freedom system, it investigates how changes in mass ratio influence the dynamics of energy transfer, nonlinear normal modes (NNMs), and dissipation behavior.

A number of significant contributions are introduced in this work beginning with the introduction of the frequency-energy-peaks (FE-pks) plot, a novel tool that visualizes how energy flows through the system, revealing transient resonance orbits, internal resonance effects, and effectively capturing the different nonlinear phenomena with …

Study Of Ai Applications In Biomedical Data Acquisition, Communication, And Analysis: Cest Mri Acceleration And Ecg Transmissions, Adarsha Bhattarai

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

This dissertation investigates the application of artificial intelligence in biomedical data acquisition, communication, and analysis to advance neurological research and to enable the early detection of cardiovascular conditions. Despite significant advances in imaging and physiological modalities, challenges persist. Imaging modalities, such as the chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) technique are challenged by a prolonged data acquisition time and high operational costs. In addition, physiological modalities such as electrocardiogram (ECG) sensors face constraints in providing uninterrupted signal monitoring which is crucial for the timely detection of premature cardiac abnormalities. The primary goal of this work is to …