Engineering Commons^™

Scalable Real-Time Stream Clustering For Unbounded Text Streams, Nathaniel C. Crossman

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Social media, AI systems, IoT sensors, and other platforms generate vast amounts of streaming data. Given this vast volume of information, techniques that can reduce and aggregate data into meaningful topics are essential. One such technique is the two-phase stream clustering approach. In the first, online micro-clustering phase, the system forms micro-clusters from the incoming data stream, incrementally merges new items into related existing micro-clusters, and prunes or fades micro-clusters as they become inactive, producing a constantly updating yet compact set of micro-clusters representing potential topics and subtopics of the stream. In the second, offline macro-clustering phase, these micro-clusters are …

Patient Subset Classification Using Encoded Embeddings And Knowledge Graph Retrieval-Augmented Generation, Benjamin A. Holmes

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The widespread adoption of electronic medical records has created a vast reservoir of clinical data that can be leveraged to better understand how interventions relate to patient outcomes. Much of this information, however, exists as unstructured free-text, posing significant challenges for traditional statistical and machine-learning methods. Solving these challenges would allow the extraction of specific patient subpopulations (clinically relevant cohorts of individuals who share overlapping symptoms, risk factors, or diagnostic criteria), which could be used in precision medicine. Despite this promise, extracting these subpopulations from unstructured medical notes is an ongoing challenge due to the variability of clinical language and …

Using Unsupervised Machine Learning To Experimentally Categorize Separation On Low-Pressure Turbine Blades, Aaron B. Suter

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Laminar boundary layer separation can significantly degrade the efficiency of Low-Pressure Turbine (LPT) blades. While active flow control (AFC) methods can mitigate these losses, energy-efficient implementation requires activating the system only when performance decreases. This study validates an unsupervised machine learning framework that utilizes sparse, discrete surface-pressure measurements to distinguish between high and low aerodynamic loss states. A fuzzy c-means (FCM) clustering model was trained on limited pressure data obtained in a low-speed linear cascade across Reynolds numbers from 30,000 to 160,000 and used to categorize the flow regime in real time. At Re = 40,000, vortex generator jet (VGJ) …

Vagus Nerve Stimulation Ameliorates Cognitive Impairment Caused By Hypoxia, Birendra Sharma

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Hypoxia disrupts brain function due to the high demand for oxygen, leading to significant cognitive impairments. While vagus nerve stimulation (VNS) has been shown to enhance cognition, its ability to counteract hypoxia-induced deficits remains unclear. In this study, male Sprague–Dawley rats were assigned to sham, hypoxia, or VNS + hypoxia groups, with VNS delivered during hypoxia (8% oxygen) using biphasic pulses (100 μs, 30 Hz, 0.8 mA). Cognitive performance was evaluated using multiple behavioral paradigms, and hippocampal tissue was analyzed for neurotrophin expression through quantitative PCR and immunohistochemistry. Among the behavioral measures, hypoxia specifically impaired performance on the passive avoidance …

Utilizing Optimization Tools For Passive Flow Control Passage Loss Reduction In Low-Pressure Turbines, Bryant Robert Duane Burton

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Low-pressure turbines (LPTs) play a crucial role in fuel efficiency and thrust generation of aero-engines. Traditional LPT designs, however, involve multiple stages and numerous blades, resulting in increased weight and manufacturing costs. The challenge of modern- day researchers is to reduce the weight and cost but maintain the high efficiency of LPTs. To address this, one approach is to increase the aerodynamic loading of individual blades, reducing the blade count. However, this can lead to increased secondary losses caused by flow separation, particularly in the endwall regions. This research focuses on optimizing the blade profile at the junction with the …

Quantification Of Porosity In Hfb2–20%Sic Using Convolutional Neural Networks, Cameron J. Floyd

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Ultra-high-temperature ceramics, commonly used in aerospace applications, operate in high-temperature oxidizing environments where a surface scale forms and regulates oxy gen access. For hafnium diboride–silicon carbide (HfB2–SiC), that scale consists of a borosilicate glass layer over a porous HfO2 skeleton. Oxygen transport through this poros ity governs the kinetics of mechanistic models, requiring reproducible inputs for accurate pore fraction (PF), pore-size distributions, and ultimately tortuosity. This thesis replaces rule-based SEM thresholding with a convolutional neural network that segments pores and predicts the pore-radius distribution for transport models. The resulting calibrated porosity maps and size distributions transfer within the acquisition domain …

Effect Of Build Orientation And Environmental Conditions On Mechanical And Geometric Properties Of Polymeric Parts Fabricated By The Powder Bed Fusion Process, Adedamola O. Adeyemi

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Polyamide-12 (aka PA12) is a synthetic thermoplastic polymer that has been used in various applications, including the electronic and electrical, oil and gas industrial manufacturing and automotive industry. There are several ways to manufacture parts with PA12 and PA12 based composites. Injection molding, a traditional manufacturing process, has been the standard manufacturing route for polymers for a long time. Recently, however, additive manufacturing (AM) processes, such as powder bed fusion (PBF) and material extrusion (ME) have been introduced. PBF is a manufacturing process characterized by the selective sintering of successive layers of powdered material. It is the most effective AM …

Generative Adversarial Networks (Gans) For High-Dimensional Biological Data, Harigovind Harikumar

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This thesis investigates the application of Generative AI models, mainly Generative Adversarial Network (GAN) models to high dimensional and low sample size biological datasets like Motion Sickness, Breast Cancer, Crohn, and Melanoma. We utilized and compared three generative AI frameworks: Vanilla GAN, Wasserstein GAN (WGAN), Locality-Sensitive Hashing GAN (LSH-GAN) and Omics GAN. To address the challenges associated with high-dimensionality and low sample size, which was leading to very poor outputs of biological synthetic samples, we came up with an approach to stop the model when it reaches its saturation level. That is, we printed the loss plots to see where …

The Role Of Trpm7 In Mouse Development And Immune Cell Function, Jananie Rockwood

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Transient receptor melastatin 7 (TRPM7) functions both as an ion channel and a protein kinase. TRPM7 has been implicated in Mg2+ homeostasis, embryogenesis, cardiac automaticity, and immunity. The purpose of this research was to deepen our understanding of TRPM7 channel and kinase functions. To this end, we used two transgenic mouse models: the TRPM7 gain-of-function (GOF) and TRPM7 kinase-dead (KD) mice to address the consequences of increased channel activity and kinase inactivation, respectively. Global deletion of TRPM7 or the kinase domain alone are embryonic lethal, therefore, we used the TRPM7 GOF mouse to investigate germline transmission. We examined embryo development …

Pixmix Attack: Implementation And Evaluation Of A Novel Pixel Injection On Digital Video Port (Dvp) Interface In Embedded Camera Systems With Pcb Hardware Trojan, Sayed Md Tashfi Nowroz

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Image sensors are at the heart of machine vision systems in robotics, industrial automation, and surveillance systems which ideally operate with minimal human supervision and only occasional maintenance. The image sensors convert visible light into electrical signals which are locally decoded to image on the printed circuit board (PCB) by an ordinary embedded processor System on Chip (SoC). This thesis investigates a critical vulnerability in such systems, targeting the communication protocol at the signal level during runtime. Specifically, it focuses on a novel attack in the Digital Video Port (DVP) protocol, possible to exploit with PCB-based hardware Trojans, to craft …

Induced Reduction Of N-Glycosylation Leads To Heart Failure, Anthony M. Young

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Cardiovascular disease is the leading cause of death and contributes to the increasing global prevalence of heart failure (HF). N-glycosylation is a common co-/post-translational modification where branching oligosaccharides are bound to the extracellular domain of membrane proteins. This creates a diverse range of glycan structures and requires the coordination of hundreds of regulated genes. Inherited mutations in glycan synthesis frequently present with cardiomyopathies leading to HF with reduced ejection fraction (HFrEF). Additionally, gene expression studies of HFrEF patients have shown altered expression of glycosylation-related genes, including alpha-1,3-mannosyl-glycoproten 2-beta-N acetlyglucosaminyltransferase (Mgat1). This gene encodes N-acetylglucosaminyl transferase 1 (GlcNAcT1) which is required …

A Secure Ml-Assisted Framework For Resilient And Efficient Prediction Of Physiotherapy Sequence In Bilateral Carpal Tunnel Syndrome, Pratik Pandurang Kharat

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Bilateral idiopathic carpal tunnel syndrome (CTS) is a neuromuscular disorder characterized by compression of the median nerve at both wrists, leading to symptoms such as pain, numbness, tingling, and muscle weakness. Unlike unilateral cases, bilateral idiopathic CTS presents distinct therapeutic challenges due to the simultaneous involvement of both hands and the lack of an identifiable underlying cause. This study explores the application of machine learning techniques to predict the optimal sequence of physiotherapeutic interventions Stretching followed by Myofascial Mobilization (S/M) or the reverse (M/S) in female patients with bilateral idiopathic CTS and right hand dominance. Data were drawn from a …

The Impact Of Ahr And Hs1.2 Enhancer Genetic Variations On Igh Expression And Antibody Production In Human B Cells, Mili Santosh Bhakta-Yadav

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Antibody production is an essential component of the immune response against pathogens. The immunoglobulin heavy chain (IgH) gene codes for the heavy chain of antibodies. The IgH constant regions Cμ, Cδ, Cγ1-4, Cα1-2, and Cε encode the five major classes of antibodies, i.e., IgM, IgD, IgG1-4, IgA1-2, and IgE, respectively. The transcription of the IgH gene and class switch from IgM to other isotypes is regulated by two 3’ IgH regulatory regions (3’IgHRRs), each of which is a cluster of three enhancer regions (hs3, hs1.2 and hs4). The genetic variations in the hs1.2 enhancer have been identified; a ~53 bp …

Learning Under Data Scarcity: Reasoning And Negative Distillation For Texts And Graphs, Calvin T. Greenewald

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Modern machine learning (ML) models rely on large amounts of high-quality labeled data to achieve optimal performance. However, in many real-world domains, such as cyber security, acquiring sufficient labeled data is often infeasible due to cost, privacy concerns, and the rapid evolution of underlying phenomena. This challenge underscores the importance of learning under data scarcity. This thesis addresses this challenge by proposing distinct, modality-specific techniques for text and graph domains, which allow models to generalize effectively with minimal data. For text classification task, we incorporate distilled rationales from large language models and adversarial perturbations into the input space to improve …

Characterization Of Krypton Performance In A Laboratory 300 W Magnetically Shielded Hall-Effect Thruster, Jacob Henry Knott

Dissertations, Master's Theses and Master's Reports

Xenon has long been the propellant of choice in Hall Thrusters; however, significant work has been performed to produce thrusters capable of utilizing alternate propellants due to xenon’s price and scarcity. Krypton is the most similar alternative propellant to xenon. This work examines the performance of a sub-kilowatt magnetically shielded Hall Thruster operating on both xenon and krypton. Krypton produced lower thrust, specific impulse, and was less efficient than xenon. Specifically, the absolute xenon-krypton efficiency gap was 6 to 24 % . Krypton’s inferior efficiency is primarily attributable to differences in mass utilization and beam divergence losses. The impacts of …

Analysis Of Lava Flow Paths Using Remote Sensing And Geomorphological Techniques, Oluwatosin Oluyemisi Ayo

Dissertations, Master's Theses and Master's Reports

Lava flows have severe impacts on the Earth’s surface, communities, and natural habitats. Accurate modeling of lava flow paths is crucial for volcanic hazard assessment and risk mitigation. This research integrated remote sensing, geographic information systems, geomorphological techniques, and hydrologic analysis to numerically determine the optimal ground sample distance (GSD) of digital elevation models (DEMs) for delineating lava flow paths. Two volcanic regions were analyzed: the Afar Region of Ethiopia (Alu, Dalaffilla, and Erta Ale volcanoes) and the Reykjanes Peninsula of Iceland (Fagradalsfjall volcano). Forward and backward modeling methods were used to simulate potential lava flow paths. Remote sensing data, …

Numerical Modelling And Co-Optimization Of Gasoline Fuels For Gasoline Compression Ignition Using Multi Component Approach, Ashwin Karthik Purushothaman

Dissertations, Master's Theses and Master's Reports

Future mobility is expected to rely on a broad spectrum of powertrain technologies, including battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), fuel cell electric vehicles (FCEVs) and traditional internal combustion engine (ICE) vehicles. Despite the shift toward electrification, internal combustion engines are projected to remain a key component of future powertrains, either as the primary power source or as range extenders to generate electricity in hybrid systems. As such, significant research efforts continue to focus on enhancing the efficiency and reducing the emissions of ICEs to meet increasingly stringent regulatory and environmental targets. Gasoline compression ignition (GCI) has been …

Effects Of Invigorating And Relaxing Music On Heart Rate, Blood Pressure, And Heart Rate Variability, Matthew Joshua Faur

Honors Undergraduate Theses

Heart-rate variability (HRV) has been documented to correlate with several health measures, including autonomic nervous system longevity and athletic performance (Zulfiqar, 2010). While increasing age does not affect heart rate, there is a steady decline in HRV, which is a biological marker of aging and the decline of autonomic nervous system function. Furthermore, men who exercise regularly tend to have increased HRV, suggesting a mitigation of the typical age-dependent loss of HRV (Kristal-Boneh et al., 1995). Previous studies have suggested that music may have a physiological effect (e.g., fluctuating vitals, emotional changes) on cardiovascular parameters. However, little is known about …

The Aerodynamics Of Bird Perching: Understanding Wing And Body Interactions In Pigeon Flight, Anirudh Sriram

Honors Undergraduate Theses

During landing, birds often execute a perching maneuver. The perching maneuver refers to the complex series of actions that birds, and pigeons in particular, will perform when landing. They will typically decelerate by pitching their body to a high angle of attack and spreading their wings. It is believed to help achieve better control and reach optimal lift and drag coefficients. This study seeks to better understand the vortex interactions between the main and tail wings during this maneuver. However, it is still an unexplored phenomenon. Thus, two bird models were conceived to analyze it, one with and one without …

Measuring Achilles Tendon Stiffness And Kinetics In-Vivo, Chloe L. Pinkston

Honors Undergraduate Theses

This study aims to measure the gastrocnemii Achilles subtendon passive stiffness and energy storage during walking. Stiffness was first determined using a noninvasive method that combines ultrasound, motion capture, musculoskeletal modeling, and a force transducer. Eight healthy participants were tested using this method to obtain the passive force-displacement relationship of the Achilles tendon at two different knee angles to calculate stiffness of the gastrocnemii subtendon. A gait analysis session was then performed using ultrasound, motion capture, and an instrumented treadmill at self-selected slow, normal, and fast walking speeds, using stiffness to calculate the subtendon’s force and energy storage. Gastrocnemii Achilles …

Effect Of Metal Ions On The Reactive Oxygen Species Scavenging Capabilities Of Cerium Oxide For Biological Applications, Agastya Mittal

Honors Undergraduate Theses

Ceria nanoparticles' capabilities to defend cells against oxidative stress through superoxide dismutase activity are well-documented. Ceria nanoparticles demonstrate a ratio between 3⁺/4⁺ oxidative states on the surface of the particles to exhibit oxygen vacancies, a feature that allows these particles to scavenge Reactive Oxygen Species (ROS) in times of Oxidative Stress. Oxidative stress arises from many wounds in the body, such as wounds in the skin, and can have significant impacts on the health of an individual. Even when receiving treatment for the skin wound, ROS can circulate from around the wound, be generated from an imbalance …

Synthesis And Characterization Of Multifunctional Cerium Oxide Containing Nanoparticles For Biomedical Applications, Ishaan Patel

Honors Undergraduate Theses

This study presents the synthesis and comprehensive characterization of a novel core-shell nanoparticle composed of a maghemite (γ-Fe₂O₃) core and a europium-doped cerium oxide (EuCNP) shell, developed for potential use in cancer theranostics. Using a co-precipitation method, Fe₂O₃–EuCNP core-shell nanoparticles were synthesized and compared against control samples of CNPs, EuCNPs, and Fe₂O₃. A variety of characterization techniques, including UV-Vis spectroscopy, fluorescence spectroscopy, TEM, XRD, XPS, DLS, TGA, and DSC confirmed the successful synthesis of core-shell architecture and europium doping. Moreover, Fe₂O₃–EuCNPs demonstrating strong colloidal …

Utilizing Pneumatic Artificial Muscles To Simulate Wingbeat Kinematics For Morphing Uav Wings, Vireli S. Anbarasu

Honors Undergraduate Theses

The controlling muscles of a bird wing change stiffness and length to provide high efficiency when executing a flight maneuver. This variable stiffness allows the muscles to cycle between increasing energy, transmitting it, and restoring it, allowing an overall increase in mechanical and aerodynamic efficiency. Inspired by this, we have developed a system that uses pneumatic artificial muscles (PAMs) to actuate a morphing wing. The stiffness in the PAMS can be controlled to mimic the changes bird flight muscles undergo when executing a forward flapping maneuver. We will evaluate the performance of the PAMs in actuating a morphing wing through …

Methods Of Variability Reduction In Ramjet Fuel Injection Using Fluid-Structure Interactions, Egan J. Rigney

Honors Undergraduate Theses

The Liquid Jet in Crossflow (LJIC) method of fuel injection in ramjet engines is widely used and well-studied. However, they experience variation in their behavior at different altitudes and flight speeds due to the varied flow conditions following the inlet. This variation becomes more noticeable at high-temperature and high-speed airflow conditions. The optimized and consistent breakup of liquid fuel is a key component in ramjet engine design as there is a minimum surface area requirement of the droplets for combustion to occur. Local equivalence ratios also have a significant influence on the effectiveness of combustion. As such, researchers at the …

Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal

Honors Undergraduate Theses

Multi-agent systems have become more and more prevalent as technology increasingly gets integrated into our daily lives. Some of these technological systems are large in size; for example, the smart grid where multiple devices are used to monitor and control different aspects of the energy grid. Another example is a team of autonomous systems deployed for a specific task. When these systems are spatially distributed, an important component of distributed algorithms is the ability for the agents to reach consensus on the global state of the system. Reaching agreement enables the spatially distributed agent make decisions or determine the next …

A Signal Processing And Mechanical Design Approach To Understanding Triboelectric And Piezoelectric Nanogenerators’ Output, Nicholas Rose

Honors Undergraduate Theses

Scalable energy harvesters—capable of converting motion into electrical output—provide promising solutions to increasing energy demands. This thesis was inspired by the potential biomedical applications of piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG). In theory, these devices could convert mechanical energy from the body into usable electricity for self-powered electronics such as pacemakers or cochlear implants. In line with this goal, this project worked to design a sustainable and biocompatible PENG; however, early devices produced inconsistent voltage. These output inconsistencies motivated an exploration of device reproducibility, but characterizing piezoelectric output signals is a particular challenge in the field. Subtle to significant …

Behavior Analysis Of Simple And Complex Workloads, Davi D. Dantas

Honors Undergraduate Theses

Complex tasks have evolved rapidly in recent times due to tremendous advancements in computational power and data availability. With the ever-increasing presence of complex applications, this paper attempts to distinguish between complex and simple applications. This paper explored side-channel analysis as a method to differentiate complex workloads from simple workloads by monitoring system-level metrics such as power consumption, cache behavior, and memory accesses. By leveraging side-channel effects such as power analysis and memory access, this study seeks to establish unique hardware signatures for complex workloads. Using tools such as Intel Pin, the data will be collected from complex and simple …

Exploring The Dynamics Of Cislunar Space: A Detailed Study Of Periodic Orbits And Their Applications In The Circular Restricted Three-Body Problem, Nicole Weeden

Honors Undergraduate Theses

Ever since NASA announced the Artemis program in 2019, the cislunar space, a region between Earth and the Moon, has attracted substantial research interest. Nonetheless, understanding the complex multipart physics that guides our solar system is not a new area of interest. The ThreeBody Problem was first formulated by Lagrange in ”Essai sur le Probleme des Trois Corps” in 1772 and had additional refinements done by mathematicians like Poincare. However, it was not until NASA’s Apollo program that the cislunar space gained traction, and the Circular Restricted Three-Body Problem (CR3BP) model became more prominent. By deriving and explaining the necessary …

Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock

Theses and Dissertations

This thesis explores an application of reinforcement learning (RL) in maintenance optimization. Recent advances in hardware-accelerated computation and deep learning have made RL a powerful tool for solving optimization problems which are too complex for traditional methods. Maintenance optimization involves improving the efficiency and effectiveness of maintenance activities through data-driven approaches, ultimately reducing costs and increasing asset availability. Making informed maintenance decisions is crucial to long-term sustainability.

A desirable maintenance policy maximizes a utility signal while minimizing the cost of maintenance. Techniques in sequential decision making such as dynamic programming (DP) and RL have found success in optimizing these maintenance …

A First Model Foundation Design Of Wood Pillar In Banjarmasin Swampland, Nursyarif Agusniansyah, Gusti Novi Sarbini, Akbar Rahman, Muhammad Tharziansyah

ASEAN Journal on Science and Technology for Development

Banjarmasin's swampland presents distinct characteristics that make it suitable for constructing homes, but it also requires special attention, especially concerning the foundation. The soil in this area often has extremely low carrying capacity, which poses a significant challenge for construction. Mistakes in choosing construction materials, coupled with mismatched building loads and inadequate foundation functions, often result in foundation failures—a common cause of building collapses. As the complexity and functionality of buildings increase, the need for more thoughtful house design becomes more crucial. The commonly used wooden pile foundation, while popular, has limited load-bearing capacity, necessitating modifications to enhance its strength. …