Digital Commons Network^™

Harnessing Bioscaffold-Coupled Stimulation Through Electroactive Graphene Foam For Enhanced Cellular And Mechanical Responses: Applications In Cartilage Tissue Engineering, Mone't Sawyer

Boise State University Theses and Dissertations

Osteoarthritis is a leading cause of joint degeneration, with limited treatment options that fail to restore native cartilage. Tissue engineering offers a promising strategy by combining cells, scaffolds, and bioactive cues to regenerate functional tissue, though challenges remain in developing systems that integrate and precisely control these signals in three-dimensional environments. This work establishes a scaffold-coupled electrical stimulation (ES) platform using electroactive graphene foam (GF) to modulate cellular and mechanical responses relevant to cartilage tissue engineering. Custom stereolithography-printed bioreactors were developed to deliver low-voltage biphasic square waves (20–60 mVpp, 1 kHz) directly to GF scaffolds under submerged culture, maintaining waveform …

Stimulation And Recording Interfaces For Data Transmission To And From A Micro Neural Stimulation Device, Morgan Riley

Boise State University Theses and Dissertations

Advancements in neuromodulation for treating neurological disorders increasingly rely on selective peripheral nerve stimulation rather than whole-nerve activation. Traditional approaches engage all fascicles, causing off-target effects such as involuntary muscle contractions and pain. To address these challenges, this research proposes a minimally invasive microdevice that integrates wireless galvanic impulse communication with an epineural multi-contact nerve cuff. This design facilitates high-throughput, low-power stimulation, recording, and data transfer. Development efforts include optimizing neural stimulation protocols, validating deep tissue galvanic transmission, and fabricating a multi-channel nerve cuff for stable electrode–tissue interfacing. In parallel, custom depth-controlled intramuscular arrays enable high-density electromyography (EMG) recording during …

The Road To Regulation: A Literature Review Of The Influences On The Updated Silica Standards, Skye M. Medcraft

Capstone Experience: Master of Public Health

Silica is a hazardous compound that poses a risk to human health resulting from dust creating activities across various industries. Several agencies, including OSHA (Occupational Health and Safety Administration) and MSHA (Mine Safety and Health Administration) have adopted regulatory oversight of silica exposure in the workplace. As more research has been conducted on silica exposure, the health effects are becoming better described, which has led to the creation and updating of exposure regulations to protect worker health. The objective of this literature study is to review the data presented to the Department of Labor and discuss how the factors that …

User Evaluation Of A Virtual Patient For Philippine Medical Education, Ma. Mercedes T. Rodrigo, Samantha Castaneda, James Alvir Maclin V. Alaan, Paolo Santino P. Caoile

Department of Information Systems & Computer Science Faculty Publications

Caladrius is a virtual patient system designed for use in Philippine medical schools. It responds to the need for medical interview training, for greater variety in teaching-learning strategies, and for culturally appropriate technologies. It has two versions: a text-only version whose interface is similar to a chat interface, and an audio version that accepts speech input and responds with speech output. In a prior test of Caladrius, users requested improved audio response time and the inclusion of different patient personalities. A subsequent version of Caladrius was created to comply with these requests. As much of the lag was attributable to …

Ai-Driven Electromagnetic Design And Performance Prediction Of Microstrip Antennas, Eduardo Javier Vazquez

Theses and Dissertations

This thesis investigates the application of Deep Learning to automate and accelerate microstrip antenna inverse design. The initial investigation was to predict microstrip antenna performance from its geometry parametric input, and found out that forward prediction with adopted geometric representation results in ill-posed scenario, high ambiguity and unstable mapping. The study later mostly focuses on the inverse prediction by machine learning from S11 parameter input to predict antenna patch geometry parameters instead.

A dataset of 5,000 ANSYS HFSS simulated antennas (later filtered to 4,136 valid samples) was generated using cubic spine -described geometry profiles. Multiple neural architectures were adopted for …

Development And Testing Of A Prototype Erbium-Doped Lithium Tantalate Based Sensor For Infrastructure Crack Detection And Measurement, Alejandro Barrera

Theses and Dissertations

Ensuring the safety and longevity of infrastructure is crucial to safeguarding communities and preserving economic stability. In this study, the development of a novel sensor for detecting and characterizing cracks in infrastructure, particularly suited for deployment on Unmanned Aerial Vehicles (UAVs), is presented. The device utilizes a laser (operating at 980 nm) for excitation of erbium-doped lithium tantalate nanoparticles that emit 1550 nm wavelength, which stimulates a photodiode for data collection. The data was utilized to collect, process, and reconstruct topological information. The synthesized lithium tantalate nanoparticle samples vary in erbium doping percentages of 0.5%, 3%, and 10%. Experimental evaluation …

Building Services Engineering November/December 2025

Building Services Engineering

No abstract provided.

Property Management System, Abbas Kurnool

Electronic Theses, Projects, and Dissertations

The real estate industry generates and manages large amounts of data, including tenant information, lease agreements, property maintenance schedules, and financial transactions. Reliance on traditional manual methods often results in inefficiencies, fragmented data, and delays in decision-making. To overcome these challenges, this project presents the design and implementation of a Real Estate Property Management System (REMS) for Future Properties, a company aiming to optimize its operations through digital transformation.

The proposed system is developed on Microsoft Dynamics 365 as the core platform, integrated with the Microsoft Power Platform tools (Power Apps, Power Automate, and Power Pages). This integrated framework provides …

Digital Solutions For Bridging Language Barriers: Designing And Testing An App For Construction Spanish Safety Communication On Construction Jobsites, Adrian Cappella

All Theses

Language barriers between English-speaking supervisors and Spanish-speaking workers create safety risks on U.S. construction jobsites. Hispanic workers face higher injury and fatality rates, with miscommunication being a major contributing factor. Existing translation tools lack the accuracy, cultural context, and jobsite relevance needed for effective safety communication.

In this study a mobile application with construction-specific safety phrases in English and Spanish was designed and field tested. The research included a literature review, phrase collection and validation with industry experts, application development and design with a computer science collaborator, and usability testing with supervisors and workers. Surveys and field trials measured navigation, …

Study On The Knock Resistance Offered By Thermally Stratifying Water Injections In A Single Cylinder Spark Ignition Engine, Aditya Datar

All Theses

Stochastic end-gas autoignition in SI engines, commonly called ‘knock’, limits attainable engine efficiencies. Multiple pathways to extend SI engine operation into knock-limited regions have been studied, including direct water injection (DWI). This study employs single-cylinder engine experiments and modeling to investigate the knock resistance offered by compression stroke water injections, which have shown to thermally stratify the cylinder in HCCI. In SI, thermally stratifying injections are expected to forcibly widen the cylinder temperature distribution by preferentially cooling the cylinder periphery. The end-gas is in the cylinder periphery; therefore, a cooler end-gas would result in longer ignition delays, thus providing knock …

Tradespace Exploration For Multiple Collaborative Vehicles, Mrunal Deshmukh

All Theses

Modern military operations demand systems that adapt to uncertain, rapidly changing missions across diverse terrains. Traditional single-platform vehicle design is insufficient for such complexity. This research introduces a hierarchical tradespace exploration framework for designing and evaluating families of heterogeneous ground vehicles under a System-of-Systems (SoS) architecture. The framework treats vehicle design as a co-optimization problem, where a “parent” vehicle (e.g., a Squad Multipurpose Equipment Transport) coordinates specialized “child” vehicles for reconnaissance, amphibious tasks, terrain traversal, and stealth missions. Unlike conventional approaches that optimize vehicles individually, this study emphasizes collaborative performance, resource sharing, and adaptability at the family level. Central to …

Comparison Of The Recent Icrp Occupational Intakes Of Rradionuclides Series To Annual Limits On Intake (Ali) In The United States For Select Radionuclides, Aidan B. Barker

All Theses

Dose coefficients (DCs) and secondary limit values (such as the annual limit on intake [ALI] and derived air concentration [DAC]) are useful and convenient quantities in radiation protection (RP) for estimation of radiological dose and the practical application of dose limits. DCs link radioactivity intake to dose while secondary limit values express a dose limit in terms of the type and extent of exposure. The International Commission on Radiological Protection (ICRP), an international organization which provides guidance and recommendations for RP, calculates, tabulates, and updates DCs following new findings and updated knowledge relevant to dose determination (e.g. improved human biokinetics, …

Understanding Policy Transfer Under Decomposition And Coordination: Sequential Reinforcement Learning With Relaxation-Based Feasibility Control, Aannand Lal

All Theses

This thesis investigates how decomposition and coordination (D&C) choices influence exploration, learning, and transfer in reinforcement learning (RL) based design frameworks. A unified methodology is developed to evaluate generality under decomposition and to demonstrate sequential coordination on a representative physical task. The generality study holds the underlying physics constant while varying problem presentation - specifically scalarization weights, objective orientations, and feasibility handling. A train-evaluate matrix is constructed in which each trained policy is assessed across all alternative decompositions. Set-based diagnostics quantify generality through exact-match identity, Jaccard similarity of distinct feasible states, total feasible coverage, and Pareto-front quality. Results show that …

Real Time Markerless 3d Hand Tracking For Intuitive Robotic Arm Control, Dylan G. Featherson

Master's Theses

This thesis presents a real-time, markerless motion-capture system for intuitive control of a multi-degree-of-freedom robotic arm. Using two synchronized RGB cameras and stereo-vision triangulation, the system reconstructs the three-dimensional position of a user’s hand without the need for physical markers or wearable sensors. The reconstructed 3D coordinates are mapped directly to the end-effector position of the Quanser QArm, a four-degree-of-freedom educational manipulator. Developed entirely in Python, the system integrates stereo camera calibration, 3D hand tracking with MediaPipe, coordinate transformation, and inverse kinematics into a unified real-time control pipeline operating at approximately 200 Hz. Calibration is performed through a checkerboard-based stereo …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Hallucination Techniques For Self-Supervised Synthetic Datasets For Mobile Robots, Wyatt D. Colburn

Master's Theses

Classical techniques in autonomous navigation struggle in tightly constrained spaces. Machine learning has been shown to perform better in these difficult environments but most techniques require large amounts of navigation experience for training. Using a new machine learning paradigm learning from hallucination (LfH), training data can be collected in a safe environment and not require supervision. Data is collected in real time while an agent performs a random walk in free space, supervision is not required as there are no obstacles for the robot to run into. After a random walk a post processing pipeline will hallucinate a safety corridor …

Bridging The Gap Between Network Science And Network Systems To Identify And Mitigate Cyber Risk: Identify And Mitigate Backdoor Attacks On Graph Neural Networks And On Complex Systems, Sabah Ettahri

Electrical & Computer Engineering Projects for D. Eng. Degree

This doctoral project aims to bridge the gap between graph theory and network science to identify and mitigate cyber risk, represented as a CY-Triangular Network that connects different networks. The CY-Triangular Framework is a cybersecurity system that integrates graph theory and network science through an interoperable learning approach. The objective of this project is to bridge the gap between two domains: network science and network systems. Accordingly, it examines one representative network from each field, focuses on a complex system network, and explores Graph Neural Networks (GNNs). The connection between these domains lies in graph theory. This research demonstrates that …

Advancing Life Cycle Assessment Of Mass Timber: Environmental Performance, Circular Design And End-Of-Life Strategies, Muzan Williams Ijeoma

All Dissertations

Mass timber has emerged as a leading candidate for low-carbon construction, offering the dual benefits of reduced embodied emissions and biogenic carbon storage. Yet, fully realizing its sustainability potential requires a comprehensive and context-specific understanding of its environmental performance across the entire life cycle, from raw material production to building operation and beyond end-of-life (EoL). This dissertation advances life cycle assessment (LCA) practices for mass timber by addressing critical challenges across multiple phases of its life cycle. This dissertation is comprised of three published papers, and two submitted manuscripts. First, I conducted a critical review and meta-analysis of mass …

Towards Trustworthy Federated Learning, Alina Basharat

Theses and Dissertations

Federated learning is a collaborative training model in which multiple clients optimize aglobal model by transmitting updates to a coordinating server while keeping raw data on-device, thereby reducing direct data exposure and enabling iterative global improvement. However, the iterative communication process is vulnerable to malicious attackers that either deliberately destroy the model or curious to infer raw data. Moreover, learning from multiple agents may result in unfair results. To enhance trustworthiness within this setting, we employ two-sided norm-based screening (TNBS) that removes both abnormally large and abnormally small updates, pair it with a q-fair objective to emphasize high-loss (disadvantaged) clients, …

Modeling Flood Risks For Small-Scale Coastal Watershed Across Shared Socioeconomic Pathway Scenarios, Sebastian Loschner

Graduate Theses and Dissertations (2019 - present)

Coastal flooding, driven by the mixture of natural processes and human activities such as precipitation, waves, sea level rise, and urbanization, remains a growing concern. While recent flood-risk studies use IPCC's Shared Socioeconomic Pathways with climate projections to assess future flood exposure, smaller coastal watersheds, < 120,000 acres, remain insufficiently studied. Projected sea level rise is expected to intensify these impacts in smaller systems, potentially causing more severe flooding than reported for larger watersheds. To address this gap, this study used the SRH-2D model integrated with Aquaveo's Surface-water Modeling System to simulate flooding in the lower Fish River basin, Alabama. A coastal watershed sensitive to both riverine and tidal influences. Simulations tested different sea levels based on SSP scenarios corresponding to low, moderate, and high emissions for the years 2050 and 2100. Results indicate that the midcentury scenarios remained even in inundation extent and volume, between 9.9-10.4% compared to the 2020 baseline, the latter scenarios had a wider range in results of between 25.9-50.3% compared to the same baseline. Across scenarios, the most vulnerable and inundated areas of the smaller coastal watershed were the narrow points where upstream flow convene with downstream backwater. These findings highlight the need for futuristic location-specific flood mitigation strategies.

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …

Efficient Adaptive Spline-Based Path Planning For In-Space Servicing, Assembly, And Manufacturing Applications, Christian Lozoya

Open Access Theses & Dissertations

Autonomous robotic systems operating in cluttered and partially observed environments require trajectory generation methods that produce smooth and dynamically feasible motion while reacting to locally sensed obstacles. This requirement is especially pronounced for free-flyer and in-space servicing, assembly, and manufacturing (ISAM) platforms, where onboard sensing is sparse, global environmental information is unavailable, and communication or computational resources are constrained. In such settings, motion plans must be updated online using incomplete and rapidly changing local observations, while avoiding excessive replanning that can lead to oscillatory or unstable behavior. Many existing approaches either rely on dense optimization over extended horizons, which is …

Further Insights Into The Network Link Outlier Factor's (Nlof) Light-Load Penalty, Sunday Oluwaleke Ogundele

Open Access Theses & Dissertations

This research investigates the performance of the Network Link Outlier Factor with Most Likely Links (NLOF:MLL), under varying network load conditions. Earlier studies reported that the NLOF:MLL algorithm experienced a noticeable drop in fault-localization accuracy when operating in lightly loaded networks. To further examine this limitation, 240 experiments were carried out to observe how the algorithm responds as overall network load increases. The evaluation focused on the classification performance metrics: precision, recall, and F1-score. The results show that NLOF:MLL’s effectiveness improves as network load increases but that the rate of improvement slows progressively, eventually stabilizing in a pattern consistent with …

Gpu-Based Electromagnetic Microwave Tomography For Brain Imaging And Stroke Detection, Pablo Sotelo Torres

Open Access Theses & Dissertations

Each year, an estimated 795,000 people in the U.S. suffer a stroke, with approximately 610,000 being first-time cases. Of these, 87% are ischemic strokes, while the remaining 13% are hemorrhagic. Current imaging methods, such as Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI), provide useful information into brain tissue properties; while each technique has its advantages, they remain expensive, non-portable, and often too slow for emergency bedside or in-ambulance use. Electromagnetic Microwave Tomography (EMT) offers a promising alternative: an affordable, portable, rapid, and safe method for stroke detection. By contrasting dielectric properties between healthy and affected …

Advancing Aerospace Materials: 3d Printing Of Fiber Reinforced Cyanate Ester Ipns And Uhtcmcs, Saqlain Zaman

Open Access Theses & Dissertations

Additive manufacturing (AM) is rapidly reshaping the landscape of advanced materials for aerospace, hypersonic, and extreme-environment systems. However, AM of high-temperature polymer and ceramic composites, especially those reinforced with continuous or aligned fibers, remains limited by challenges in rheological control, in situ fiber impregnation, curing compatibility, densification, and achieving directional multifunctional properties. This dissertation advances a unified Direct Ink Writing (DIW) framework enabling the processing of architected, high-performance composite materials across polymer and ceramic systems. Three research thrusts collectively establish scalable pathways for fabricating fiber-reinforced cyanate ester interpenetrating polymer networks (IPNs) and ultra-high-temperature ceramic matrix composites (UHTCMCs). First, a dual-curable …

Qualitative Stereo Vision Using Distributed Extended Waltz Filtering, Ben Mathew

Theses and Dissertations

Stereo vision is a fundamental problem in computer vision, aimed at reconstructing three-dimensional scene structure from two or more two-dimensional images. Traditional stereo algorithms rely on quantitative disparity estimation, often constrained by calibration precision, lighting variations, and surface texture. In contrast, our proposed Qualitative Stereo Vision seeks to understand depth relationships and spatial configurations from multiple planar views through symbolic reasoning and constraint satisfaction, offering a more flexible and cognitively plausible approach to scene interpretation.

This dissertation presents a novel framework called Distributed Extended Waltz Filtering, designed to provide qualitative stereo vision, particularly in the presence of occlusions—a persistent challenge …

Establishing Procedures For Primary Human Myoblast Cell Culture, Erica Duffy

Biomedical Engineering

Peripheral Artery Disease (PAD) affects an estimated 200 million people worldwide and is the leading cause of amputation in the United States. PAD is characterized by atherosclerotic narrowing of arteries, resulting in ischemia from reduced blood flow to distal tissues. Although surgical and percutaneous interventions can restore perfusion, fewer than 50% of patients experience sustained benefit, highlighting the need for alternative therapeutic strategies. One promising approach is promoting arteriogenesis, the growth and outward remodeling of pre-existing collateral vessels that improve blood flow around the occluded arteries. Arteriogenesis is regulated by regenerative, M2-polarized macrophages, making macrophage polarization a key therapeutic target. …

Securing Connected And Autonomous Vehicles, Owana Marzia Moushi

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

A vehicular network is susceptible to various security flaws and attacks. Cryptographic techniques are used in vehicular networks but these alone cannot provide proper security to the network. Identifying various types of attacks is necessary to secure vehicular communication networks. In this dissertation, we focused on detecting various insider attacks in vehicular networks to enhance the security of the network.

Our first contribution in this dissertation is the detection of both binary and multi-class data replay and data replay Sybil attacks in vehicular networks. A publicly available dataset, VeReMi-Extension is used to detect these attacks. This dataset has been reformulated …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Accident Data Analytics And Ai-Based Auditory Enhancement For Highway Construction Safety, Thinh Nguyen

All Dissertations

This research develops data-driven and AI-enhanced approaches to improve worker safety in highway construction environments. The study integrates advanced analytics and auditory signal enhancement to identify high-risk worker behaviors and improve real-time safety warnings. The work consists of three core studies. The first study applies Sequential Pattern Mining and Social Network Analysis to more than 1,000 construction accident reports to identify high-risk worker actions and their hidden sequential relationships with accident types and consequences. These insights reveal sector-specific risk patterns, supporting the creation of targeted, data-informed safety interventions. The second study introduces an AI-based auditory enhancement model built on a …