Engineering Commons^™

Systematic Co-Culture Of Ipsc-Cm And Ipsc-An Promote Co-Maturation In Vitro, William Gregory Terrell Jr.

Graduate Dissertations and Theses

The cardiac microenvironment is a complex system of multicellular interactions that enables proper heart function. In native heart muscle, sympathetic neurons (SN) and parasympathetic neurons (PSN) modulate the beat rate of cardiomyocytes (CM) to maintain homeostasis. Pluripotent stem cells can differentiate into CM, but differentiated CMs are fetal-like, with a high beat rate, and lack organized sarcomeric structure. Recent reports of co-cultured pluripotent CM/SN pairs have reported electrophysiological changes in the SN (increased upstroke velocity). However, interpretation of these results are obscured by the differences in co-culture parameters between studies (stage of development, co-culture duration, etc.). The goal of this …

Design And Manufacturing Of Multifunctional Piezoelectric Composites, Huan Zhao

Dartmouth College Ph.D Dissertations

Piezoelectric materials possess a unique ability to convert mechanical energy into electrical signals and have broad industrial applications. However, monolithic piezoelectric materials such as piezoceramics and piezopolymers often suffer from inherent trade-offs among mechanical strength, elasticity, and durability. Piezoelectric composites, typically consisting of a polymer matrix with ceramic reinforcements, offer a solution by combining the advantages of each constituent. Nevertheless, maintaining stable mechanical performance in high-temperature environments remains a significant challenge as conventional polymer matrices usually experience structural degradation.

In this thesis, a novel piezoelectric composite is developed using a preceramic polymer (PCP) matrix with barium titanate (BTO) inclusions. PCPs …

Long-Term Assessment Of The Morphological Behavior Of The Beaches North Of Sebastian Inlet, Florida, Aidan O'Gorman

UNF Graduate Theses and Dissertations

The morphological behavior of the beaches north of Sebastian Inlet, Florida is investigated by applying Empirical Orthogonal Function (EOF) analyses to a series of beach surveys conducted semi-annually (winter and summer) over a period of fifteen years (2005-2019), with the primary objectives being to 1) determine the extent to which the inlet’s influence to the north typically fluctuates on a short-term basis (e.g. annually), and 2) identify any long-term trends of accretion or erosion that might exist. Each survey is comprised of thirty-one cross-shore profiles that are referenced to permanently installed range monuments (“R-monuments”) that are spaced nominally 305 …

Fault Box Modeling Of Dip Slip Faults: A Framework For Fault Box Design And Future Studies, Hailey Pressnell

Master's Theses

The behavior of soils during surface fault rupture is a serious concern in the planning and design of infrastructure that may be located within or near a fault zone. Challenges associated with developing mitigation measures for surface fault rupture include the uncertainty of fault rupture and the variability of fault behavior. Current analytical procedures define surface fault rupture according to the type of fault movement (strike slip, normal or reverse), the amount of displacement on the fault, and the mechanics of the material overlying the fault. The purpose of this thesis is to reconfirm analytical solutions and gain a better …

Analyzing The Safety Effects Of Edge Lane Roads For Motor Vehicle Users, John Yang

Master's Theses

This thesis builds upon a prior study that analyzed the safety effects of Edge Lane Roads (ELRs) within the U.S. context, addressing gaps related to collision, traffic volume, and speed data. An ELR is a roadway configuration that accommodates two-way automobile traffic within a single center lane while providing edge lanes for vulnerable road users (VRUs), i.e., bicyclists or pedestrians. Although the concept of a single shared lane for opposing traffic often raises safety concerns among the public, ELRs have demonstrated potential to control speeds, optimize roadway space, and improve traffic operations on low-volume roads.

To evaluate safety outcomes, this …

Designing An Affordable Motion Capture System For Multi-Robot Research And Education, Hojune Kim , '25

Senior Theses, Projects, and Awards

In this work, we propose a low-cost motion capture system for real-time tracking of multiple robots’ positions and orientations in indoor environments, specifically tailored for research and educational applications. Precise localization is essential for evaluating robotics algorithms such as decentralized multi-agent control, cooperative path planning, and collision avoidance. [1-3] However, commercial motion capture systems like Vicon and OptiTrack cost between $50,000 and $150,000, making them inaccessible for many smaller institutions, student clubs, and low-resource labs. To address this challenge, we developed an affordable alternative based on three ceiling-mounted 1080p USB cameras and AprilTags. Our system operates at 30 Hz and …

Analysis Of Port Traffic Growth For Optimization Of Traffic Flow: A Microscopic Traffic Simulation Study Of Jaxport's Blount Island Marine Terminal, Amy A. Aida

UNF Graduate Theses and Dissertations

To accommodate increasing cargo volumes and remain competitive, ports worldwide are facing growing pressure to expand and modernize their facilities. However, these expansions can place additional strain on land transportation networks, leading to congestion, delays and operational inefficiencies. This study used VISSIM, a microscopic traffic simulation tool, to model and analyze the complex traffic dynamics at the Blount Island Marine Terminal in Jacksonville, Florida, which is currently undergoing expansion.

To account for future traffic conditions, time series analysis was employed to project growth in traffic demand, taking into consideration anticipated expansions in tenant yard facilities, as well as increases in …

Toward Strategy Identification And Subtask Decomposition In Task Exploration, Tom Odem

Master's Projects

This research builds on work in anticipatory human-machine interaction, a subfield of human-machine interaction where machines can facilitate advantageous interactions by anticipating a user’s future state. The aim of this research is to further a machine’s understanding of user knowledge, skill, and behavior in pursuit of implicit coordination. A task explorer pipeline was developed that uses clustering techniques, paired with factor analysis and string edit distance, to automatically identify key global and local strategies that are used to complete tasks. Global strategies identify generalized sets of actions used to complete tasks, while local strategies identify sequences that used those sets …

Improving Contextual Retrieval For Long Documents In Q & A Systems, Sakshi Garg

Master's Projects

With the vast amount of information available on the internet distributed across several lengthy documents, finding relevant information has become more important and challenging. The goal of this project is to develop advanced techniques to retrieve information from long texts in order to deliver accurate and relevant results while ensuring speed and efficiency. As part of this work, we employ techniques to address unique difficulties posed by large and complex documents. This paper presents a custom Retrieval-Augmented Generation (RAG) framework designed to improve contextual retrieval in long and multi-document settings. In this paper, we employ several techniques like summarization, semantic …

Comparative Analysis Of Embedding Techniques With Clustering Algorithms For Malware Opcodes, Ayush Koul

Master's Projects

Malware detection and classification remain critical challenges in cybersecurity, especially as malicious software becomes increasingly sophisticated and prevalent. While much of the work involving embeddings has traditionally relied on supervised learning approaches, there is significant potential in leveraging unsupervised learning techniques to discern hidden structures in malware data. By employing embedding techniques to convert malware samples into high-dimensional vector representations, we can capture the subtle and complex patterns inherent in malicious code without relying on pre-labeled data. This unsupervised approach helps categorize malware into predefined malware families, greatly aiding in developing cybersecurity solutions. In contrast to traditional supervised models that …

Gen Ai For Malicious Network Data, Aneesh Maturu

Master's Projects

Though botnet attacks are on the rise, they also have become sophisticated and difficult to detect. Such a rising threat demands more and more sophisticated cybersecurity that leverages machine learning technology. Nevertheless, one of the biggest bottlenecks remains the unavailability of large and well-balanced datasets, particularly for malicious traffic, which hampers the efficacy of detection models. In an attempt to address this issue, our research utilizes Generative Adversarial Networks (GANs) to produce synthetic samples of botnet traffic from the CTU-13 dataset. While the majority of generative models have been targeting image data, we use GANs for a new application: generating …

Development, Characterization And Testing Of Traditonal And Advanced Nuclear Fuel Cladding Materials, Joshua Eddy Rittenhouse

Doctoral Dissertations

Kanthal D and FeCrAl alloys in general, are prospective candidates as accident tolerant nuclear fuel cladding materials. The work presented herein focuses on applying two techniques of severe plastic deformation, equal channel angular pressing (ECAP) and high-pressure torsion (HPT), as means of grain refinement to improve irradiation resistance. Samples of as-received, ECAP, and HPT processed Kanthal D were exposed to neutron irradiation to a dose of 2 DPA at two different temperatures, 300 °C and 500 °C. Detailed characterization was performed including mechanical and microstructural, and several positive improvements with regards to irradiation resistance were identified in the ECAP and …

Machine Learning For Automated Classification Of Tree Species Based On Color-Texture Fusion, Brandon C. Jones

College of Graduate Studies: Theses & Dissertations

This study aimed to develop robust machine learning tools for the classification of southeastern United States tree species based on bark images, addressing challenges posed by significant intraspecies variation in bark texture and color. The primary objectives included constructing specialized machine learning libraries and classification models, identifying optimal algorithms and parameters to maximize accuracy, and integrating the best-performing texture and color classifiers into a unified system to enhance the overall classification performance. The methodology involved collecting a dataset of 360 field images, extracting hue and saturation histograms for color features, and employing Histogram of Gradients (HOG) and Histogram of Binary …

Nmr Relaxometry Approach For The Detection Of Asphalt Binder Performance Properties, Rebecca Herndon

Doctoral Dissertations

"Asphalt is a necessary material for transportation infrastructure. Understanding the material properties of asphalt binders is critical for improving infrastructure and enhancing the lifetime of pavements. While the physical properties of asphalt binders are well-defined by standard procedures and parameters, the chemical environment lacks definition. Physical parameters like viscosity and stiffness are traditionally used to differentiate asphalt binders, describe aging, and indicate the impact of additives. However, these tests have limited insight into the material's chemical environment. Therefore, a nondestructive analytical technique, nuclear magnetic resonance (NMR) relaxometry, was employed to investigate the chemical environment of asphalt binders. Although NMR relaxometry …

Characterization And Modeling Of Properties Of Unsaturated And Partially Damaged Cement-Based Materials, Rezwana Binte Hafiz

Doctoral Dissertations

"Transport properties, governing the resistance of cement-based materials to harmful substances are essential considerations for long-term performance. This study addressed the often-overlooked dimension of transport properties in unsaturated cement-based materials, crucial as most concrete structures face variable environmental conditions, leading to partial saturation. A two-scale model was introduced, enhancing our comprehension of transport properties in conditions reflecting real-world scenarios. Empirical correlation representing bulk paste characteristics was established, facilitating the upscaling of properties to mortar and concrete. The model was extended to predict the transport properties of mortar as well.

Environmental factors can contribute to the degradation of cement-based materials, with …

Ranking Of Non-Destructive Testing Methods For Ductile Iron Castings For Industry 4.0, Michael W. Jones

College of Graduate Studies: Theses & Dissertations

Non-destructive testing techniques provide a unique solution to provide quality assurance of parts rapidly and efficiently without altering the functional properties of the workpiece. The metal casting industry requires an elevated level of quality assurance, as castings are critical components to several industries. The wrong selection of non-destructive testing methods could increase production costs, quality costs, and potentially permit non-conforming castings to enter the market. The aim of this research is to develop a ranking model for non-destructive testing techniques for ductile iron castings within the context of the fourth industrial revolution. The ranking model analyzes the effectiveness of the …

Intelligent Tutoring Systems In The Age Of Llm-Based Agentic Frameworks - Adapting Small On-Device Language Models For Fact-Checking And Student Compliance Detection, Evan Vahid Naderi

Honors Undergraduate Theses

As large language models (LLMs) demonstrate increasingly sophisticated language understanding capabilities, they offer transformative potential for educational technology, particularly in developing more responsive intelligent tutoring systems (ITS). To develop these systems, a synthesis that balances theoretical frameworks with practical, cutting-edge, and deployable technology would be useful. This thesis aims to advance the field of ITSs theoretically by viewing the modern advancements in natural language processing within the context of the foundational frameworks important to the fields of self-regulated learning, ITSs, and cognitive agents. Then, building on prior research on the ITS MetaTutor \citep{Azevedo2022}, this research focuses on how functions of …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia

Open Access Theses & Dissertations

In the past decade, Additive Manufacturing (AM) has proven to be groundbreaking yet reliable technology. Not only has it revolutionized the way we approach problems in research, design, and production but it has enabled burgeoning discoveries and methods due to the technologyâ??s efficiency, speed, and low manufacturing cost. One area that benefits greatly from this includes radio frequency (RF) devices like horn antennas. At the moment, most horn antennas produced by conventional manufacturing are expensive, heavy, and limited in customization, yet they are necessary for various systems like satellite communication, radar, radio astronomy, and more. 3D printing technology would alleviate …

Navigating Big Data In Cyber Archaeology: An Updated Four-Field Approach Applied To San Miceli, Jared Wilson

Dissertations

Problem

This dissertation examines the evolving role of digital technologies in archaeological research, focusing on the management and interpretation of extensive digital datasets generated by modern excavations. Drawing on six years of comprehensive fieldwork at San Miceli, Sicily, this study critically evaluates and updates the established four-field methodology proposed by Levy et al. (2012), encompassing acquisition, analysis, dissemination, and curation. While traditional archaeological documentation methods rely heavily on analog techniques, these approaches increasingly fall short due to the rapid expansion and complexity of digital data.

Method

To address this gap, the dissertation refines and expands the current methodological framework by …

Novel Redox Oxygen Active Materials For Solid Oxide Cells And Thermochemical Hydrogen Production, Jiaxin Lu

Theses and Dissertations

This dissertation investigates novel materials designed to significantly enhance the performance and durability of oxygen electrodes for solid oxide cells and redox active materials for thermochemical hydrogen production. The first part of this work evaluates Ta-doped BaCoO₃₋δ (BCT) and its structural analog SrCoO₃₋δ (SCT), focusing on their catalytic performance in oxygen reduction and evolution reactions. Among BCT compositions (x = 0.1, 0.3, 0.5), the BCT10 (x = 0.1) composition exhibited the highest oxygen vacancy concentration, electronic conductivity, and lowest polarization resistance. However, SCT10 surpassed BCT10 in these critical performance parameters and also demonstrated greater stability over extended operational periods. Notably, …

Flame Boundary Effects Of Hydrogen-Air Premixing, Alecson L. De Lima Junior

Honors Undergraduate Theses

The objective of this research was to investigate the reaction of hydrogen and heated air premixing when injected into a combusting ethylene-air crossflow, and to study the flame stabilization location with varying premixing levels. The main parameter of this investigation was the flame stabilization diagnosed through chemiluminescence, based on recorded equivalence ratio, temperature, and flame boundaries, and maintaining a constant air temperature, hydrogen and air mass flow, and momentum flux ratios. Testing was conducted at different ratios of hydrogen and air premixing achieved through alternating the distance between the point where hydrogen and air are mixed and the combusting crossflow. …

Your Foot Is Not A Brick: Using A Multi-Segment Foot Model To Explore The Actions Of The Ankle-Foot Complex During Uneven Terrain Gait., Tayler Jon Hoekstra

Dissertations and Theses

The field of biomechanics has seen continued development of models to be used and circumstances to be considered. An increasing number of more complex models for the foot known as multi-segment foot models (MSFMs) have created opportunities to better understand the compensatory motion of this vital portion of human anatomy. This research seeks to utilize one such MSFM model to increase understanding in how human ambulation changes in uneven terrain environments. Unique inner-foot joints defined by the Rizzoli foot model (RFM) were measured for and compared for subjects traversing both even and uneven terrain to quantify joints that experienced significant …

The Effect Of Need For Cognition & Need For Affect On Human Reliance And Artificial Intelligence Interactions, Aliyah Mcgowan

Doctoral Dissertations and Master's Theses

Abstract

With the increased use of Artificial Intelligence (AI) automations in fields like medical diagnoses and mental health queries, there are concerns regarding an individual’s trust and reliance on the technology. Reliance on AI output may lead an individual to accept inaccurate or incorrect information without further analysis. Trust may influence reliance and trust formation may be a product of affective processing. This study investigated the relationship between Need for Affect (NFA), Need for Cognition (NFC), and trust and reliance on AI interactions. Participants were assessed on the NFA scale for willingness to approach or avoid emotional stimuli, the NFC …

Dielectric Performance Of Fused Filament Fabricated Ultem 9085 For Naval Radome Application, Carson Rogers

UNF Graduate Theses and Dissertations

ULTEM 9085 is a high-performance thermoplastic used in the fused filament fabrication (FFF) additive manufacturing process. It has found use in applications where mechanical strength, chemical integrity, and thermal stability are of paramount importance. In this thesis, the effects of process parameters, annealing, and weathering on the mechanical and dielectric properties of FFF ULTEM 9085 have been investigated.

The first part reviews existing research on how printing parameters such as nozzle temperature, chamber temperature, print speed, infill, and layer height affect the mechanical performance of FFF ULTEM 9085. Data from the manufacturer of commonly used ULTEM 9085 filament, Stratasys, has …

Digital Twins For Flexible Manufacturing, Drew Brandon Sander

Theses and Dissertations

With the establishment of Digital Twins as an enabling technology for Industry 4.0, it is time to transition from the previous foundations to works that implement and highlight the capabilities Digital Twins present. The Industry 4.0 paradigm has recentered the focus on customizability, leading to reemerging goals of flexibility within manufacturing. Empowered through new cyber-physical systems, new enabling technologies are driving the revolution. To identify how Digital Twins as an enabling technology contribute to flexibility within manufacturing, a comprehensive investigation is conducted along with a detailed case study. A systematic literature review is conducted to analyze quality Digital Twin implementations …

Molecular Simulation Studies Of Protein Interactions Associated With Aging, Charlotte Jenna Thomas

Honors Theses and Capstones

No abstract provided.

Biological Computing From Microscopic To Macroscopic Evolution, Xiaofeng Ding

Masters Theses

A unified theory from microscopic to macroscopic DNA-based biological systems is explained in terms of the rule components used when the system size is increased. Even though the eight female rules in each ruleset are provided with an equal probability of the computation-state outcomes, the initial ensemble of the computation states will exponentially settle into one dominant rule that supports the nutrition needed for growth. The remaining seven rules form into two minority groups to provide the biological characteristics of the system's growth from a micro to macroscopic evolution. The object of this study is to prove that such a …

Impact Of Automated Controlled Tile Drainage On Field Discharge Water, Soil Moisture, And Crop Yield In Southeastern South Dakota, Joshua Becker

Electronic Theses and Dissertations

Automated controlled tile drainage is an innovative approach to water management, using dynamic weir settings programmed to drain water out of the tile system if it encroaches into the root zone at pre-programmed depths and duration. While past studies have indicated potential yield and water quality benefits of controlled drainage, there has been very little research into the performance of automated controlled drainage. In addition to overall performance, there is a gap in knowledge of management settings to optimize yield and water quality benefits. Two experiments, one plot-scale and one modeling, were conducted to assess the impact of automated controlled …

Evolution Of Bed Shear Stress In Open Channel Flow Over A Rough-To-Smooth Transition, Monika Kafle

Electronic Theses and Dissertations

The study of flow over roughness transition in an open channel is very important in the field of hydraulic engineering. Bed shear stress is the key factor in predicting sediment transport and determining the stability of hydraulic structures while flow depth, flow velocity, surface roughness are some hydraulic parameters that can affect the bed shear stress in an open channel flow. In this thesis, a detailed investigation into the development of bed shear stress in a rough-to-smooth transition is performed. Experiments were conducted on flow over a rough-to-smooth transition in an open channel flume with an M2 to S2 composite …