Digital Commons Network^™

Development Of A Video-Based Tool To Measure Motor Asymmetry In Infants At Risk For Hemiparesis, Roha Ali

Master's Theses

Congenital hemiparesis is a unilateral motor impairment stemming from brain injury in utero or early postnatally. Hemiparesis can be difficult to detect in early infancy with current clinical tools. Yet, early identification of motor asymmetry could play a key role in the design of effective early intervention and rehabilitation strategies. This thesis presents the development and validation of a video-based tool designed to extract infant limb movement data using DeepLabCut’s (DLC) machine learning network. The pipeline was developed using videos of typically developing (TD) infants and infants with Asymmetric Perinatal Brain Injury (APBI), all at or under 3 months corrected …

A Security Framework For Pacemaker Lead Failure: Anomaly Detection System And Failsafe Policy Considerations, Ethan Wagner

Master's Theses

Embedded system security in implantable medical devices (IMDs) remains an underexplored challenge due to the unique constraints of these systems. Specifically, pacemakers are optimized for ultra-low power consumption to maximize device lifespan, are highly resource constrained, and demand reliable and correct operation to prevent severe health consequences. These systems rely on sensing electrodes, called leads, to detect cardiac activity and stimulate the patient’s heart when appropriate. Therefore, pacemaker lead integrity is a critical issue, as malfunction or compromise can result in device failure jeopardizing patient safety.

The security framework presented in this thesis integrates several works to proactively detect and …

Large Scale Kmer-Based Proteomic Analysis: An Application Towards Evolutionary Constraint Discovery, Matthew Chak

Master's Theses

Large protein databases now make it possible to study short peptides across natural protein sequence space at unprecedented scale, but exhaustively counting k-mers across billions of protein sequences remains computationally difficult. This thesis develops an exact amino-acid k-mer counting method based on direct addressing, in which fixed-length amino-acid strings are encoded as base-20 integers and updated with a sliding-window recurrence. By avoiding key storage and collision resolution, this approach removes overhead inherent to hash-map-based methods when the k-mer space is sufficiently dense. A memory analysis shows when direct addressing is preferable to open-addressing hash tables, and expected-saturation calculations motivate its …

Perception Is Reality: Evaluating Transportation Satisfaction And Utilization In Continuing Student Housing At Cal Poly, Lucas Owens

Master's Theses

As higher education institutions increasingly mandate on-campus living to foster student success, the built environment becomes a critical determinant of daily mobility. California Polytechnic State University (Cal Poly) is transitioning to a two-year residency requirement and tightening vehicle restrictions. This thesis evaluates how the spatial and built-environment realities of peripheral housing complexes in Cerro Vista Apartments and Poly Canyon Village shape student transportation satisfaction and utilization, and emergency evacuation preparedness.

Employing a mixed-methods approach, this research triangulates data from 79 student surveys and 10 semi-structured interviews. The findings indicate that supplementing traditional metrics of proximity with localized spatial data presents …

Structured Dynamic Factor Analysis Of Environmental Time Series With Application To Morro Bay Estuary, Jose Garcia

Master's Theses

This thesis develops a structured dynamic factor analysis (sDFA) framework for decomposing multivariate environmental time series into latent biological and physical components. The methodology is applied to five years of high-resolution passive monitoring data collected from two sites in Morro Bay, California from 2020 through 2024. Relative contribution indices are developed based on the structured DFA that measure how much each latent process contributes to each observed variable at any given time. Structured DFA models fit to the application data suggest site-specific patterns in how biological and physical processes affect water quality variables. At the bay mouth location, physical processes …

A Proof-Of-Concept Design Of A High-Gain Deployable Reflectarray Antenna For A 3u Cubesat, Armin Behbahani

Master's Theses

CubeSats are a class of nanosatellites that have democratized space exploration by greatly reducing cost and complexity. Their small size and limited power generation directly limit the performance of a high-data-rate communication system due to low transmit power and limited gain from small antenna sizes. Transmission losses increase with higher operating frequencies, spurring the need for innovative high-gain antenna solutions. This thesis investigates the design of a deployable 10 GHz reflectorarray, a planar high-gain aperture antenna, for a 3U CubeSat. A simple variable-size square-patch resonant unit cell was designed for implementation on commonly available PCB layer stack-ups. Preliminary reflectarray system …

Trim-Transfer: A Transfer Learning Approach For Cross-Trim Level Can Intrusion Detection, Baylor J. Whitehead

Master's Theses

Modern vehicles contain many Electronic Control Units (ECUs) that communicate through CAN. While CAN enables efficient data communication, it lacks built in authentication and encryption, allowing adversarial actors to inject malicious CAN messages. This limitation has motivated the development of CAN intrusion detection systems (IDS). However, deploying IDS across a vehicle lineup requires collecting large labeled datasets and retraining models, increasing development cost and limiting scalability.

This thesis investigates the use of transfer learning with LSTM-based deep neural networks to reduce retraining cost while maintaining model detection performance. A baseline LSTM model is trained using CAN data from a base …

Exploring Regenerative Vegetable Systems On The Central Coast Of California, Una S. O'Connell

Master's Theses

As climate change and current agricultural practices place pressure on the long term sustainability and resilience of food production systems, there is growing interest in whether existing agricultural systems can adapt to maintain productivity while improving environmental outcomes.

This study evaluated the effects of regenerative versus standard organic vegetable production systems on yield, insect communities, and weed suppression across three field trials conducted on California's Central Coast. In addition, I collected baseline soil health data for all trials. Trials 1 and 2 were carried out at the Cal Poly San Luis Obispo Organic Farm using cabbage and broccoli as cash …

A Comparative Study Of Model Predictive Control And The Stanley Method For Vehicle Path Tracking Applications, Noah S. Fitzgerald

Master's Theses

This thesis compares a model predictive controller (MPC) and a lateral Stanley controller for vehicle path-tracking applications under simulation-based and perception-driven operating conditions. Both controllers were evaluated in simulation using a nonlinear dynamic bicycle model executing single and double lane change maneuvers. Following simulation-based evaluation, both controllers were implemented on hardware within a perception-driven steering-control pipeline. This pipeline utilized recorded sensor data from the MXcarkit 1/8^th-scale autonomous vehicle platform, incorporating lane instance segmentation and homography-based roadway estimation.

Under idealized simulation conditions, the MPC demonstrated improved trajectory-tracking performance during aggressive maneuvers while requiring greater steering activity and computational effort …

Constructing Orthonormal Bases With The Residuals Of Successive Approximations, An Introduction To Multiresolution Analysis, Elijah J. Guptill

Master's Theses

Wavelets and wavelet analysis are used in the study of signal processing, quantum field theory, functional analysis, multifractal analysis, and various other areas of mathematics. Multiresolution analysis provides a framework for building a wavelet basis of $\mathcal{L}^{2}(\mathbb{R})$ from a scaling function $\phi$, whose dyadic dilations and translations, $\{2^{j /2}\phi(2^{j}x-k):j,k\in \mathbb{Z}\}$, approximate $\mathcal{L}^{2}(\mathbb{R})$. One of the key properties of  $\phi$ is that it must satisfy $\phi(x)=\sum_{k\in \mathbb{Z}}{p_{k}2^{j /2}\phi(2^{j}x-k)}$ with respect to the norm on $\mathcal{L}^{2}(\mathbb{R})$. This equation is called a two-scale difference equation. Such equations enforce a regularity on the ordinary generating function $2^{-1 /2}\sum_{k\in \mathbb{Z}}{p_{k}z^{k}}$, known as the quadrature condition. …

Developing A Humpback Whale Vocalization Detector Using Machine Learning Models, Lucas Kantorowski

Master's Theses

Humpback whale songs are notoriously complex. Identification of humpback whale song units requires bioacousticians to tediously listen, analyze, and annotate collected sound data. Even sparse data requires listening to the entirety of the collected acoustic data. In this study, three hours of audio containing over one-thousand humpback whale song units was collected in Monterey Bay, California.

Prior studies have seen success using convolutional neural networks by performing image classification on hundreds of hours worth of spectrograms. Our study uses traditional machine learning models, as they are less computationally demanding, and require less data.

We use time splitting and Mel-frequency cepstrum …

Discovering Differentially Correlated Sets Across Multiple Treatments, Tyler J. Stoen

Master's Theses

When comparing data sampled under several different conditions, we often want to study not only the overall treatment effect but also how treatments influence the relationships among variables. Differential Correlation Mining (DCM) is an existing method for identifying groups of variables whose average pairwise correlation differs significantly between exactly two sampling conditions. We extend this framework to the setting of three or more treatments, where the goal is to identify variable sets whose pairwise correlation structure varies across all conditions simultaneously. Our proposed method, VSAT for three or more treatments, generalizes the DCM search procedure using a multi-treatment hypothesis test …

Discrete S-Band Low-Noise Amplifier Designs For High Data-Rate Cubesat Uplink, Alejandro Martin Cosper, Alejandro Cosper

Master's Theses

In the world of small satellites, there is growing interest in higher-data-rate systems and the technologies that enable them. Due to limitations in the extremely reliable and proven Ultra-High Frequency (UHF) systems, the current CubeSats developed by the Cal Poly CubeSat Laboratory operate at 9600 Baud. However, the low Baud rate is rooted in decades of proven flights and is very resistant to many forms of signal degradation. While a slow but simple system was critical to past successes, future satellite payloads may require higher data rates to drastically reduce the number of passes needed to transfer large amounts of …

How Human Vs. Ai Chatbots Support Psychological Needs Of Students, Tymon T. Vu

Master's Theses

AI auto graders and virtual assistants are increasingly prevalent in educational set- tings. Although current literature demonstrates that AI chatbots can positively im- pact student motivation, there is little definitive evidence exploring whether these systems can replicate the effective motivational methods used by human teachers. Thus, in this experiment, we investigate how the perception of the identity of a tutor (AI versus human) impacts the psychological needs of students. 27 undergraduates taking introductory computer science courses were asked to explain code in plain English (EiPE). Participants received feedback from two tutors in within-subjects fashion: one human and one labeled as …

The Effects Of Maceration And Enzymes On The Chemical Characteristics Of Hard Apple Cider, Manou De Pelsmaeker

Master's Theses

The purpose of this study was to analyze the effects of maceration and pectinase enzymes on the base chemical, polyphenolic, and volatile characteristics of cider. The apples (Fuji) were milled and macerated for 0, 4, 12, 24, or 36 hours, both with and without an enzymatic pectinase addition. While base chemical characteristics such as sugar content and ABV were unaffected, the acidity of cider was influenced maceration and enzymes. Extended maceration time resulted in lower concentrations of malic acid, and enzymes resulted in a lower pH compared to the control. Polyphenols were extracted during maceration time, resulting in higher concentrations …

A Study On Quantization And Hardware Cost Tradeoffs In A 5g Nr Ldpc Decoder On Fpga, Giancarlo Acosta

Master's Theses

The fixed-point implementation of a 5G New Radio LDPC decoder forces a tradeoff between precision and hardware cost, governed by the variable node word length W_L, the check node message width W_R, and the normalized min-sum correction factor α. This thesis characterizes how these three parameters affect both error correction performance and FPGA resource utilization for an LDPC decoder on an established LDPC decoder architecture. A bit-accurate MATLAB core model records bit error rate (BER) and frame error rate (FER) while a verified HDL Coder model generates synthesizable VHDL for Vivado synthesis, and both are swept …

Deep Learning For Affect Recognition: A Comparative Study Of Physiological Sensor-Based And Facial Image-Based Approaches, Ravi Panchal, Ravi Panchal

Master's Theses

This thesis investigates deep learning approaches for affect recognition using wearable physiological signals and facial image data. The sensor-based component evaluates stress and affect recognition on the WESAD dataset using wrist-based physiological windows and examines multiple temporal modeling strategies, including convolutional, recurrent, hybrid CNN-LSTM, attention-based, ensemble, and time-frequency approaches.

The image-based component evaluates hard-label facial expression recognition on AffectNet+ using pre-trained ResNet-50, EfficientNet-B3, and ConvNeXt-Tiny architectures across Easy, Challenging, and Difficult subsets representing different levels of expression ambiguity.

Experimental results show that the proposed Multi-Branch Attention CNN-BiLSTM (MBA-CNN-BiLSTM) model achieves the strongest wearable stress- and affect-recognition performance among the evaluated …

Integrating Sustainability Into Engineering Education, Riley R. Moller

Master's Theses

Engineering decisions shape lasting technology that affects environmental integrity, public safety, economic stability, and social equity. As global challenges such as climate change, infrastructure vulnerability, and rapid technological advancement intensify, the responsibilities placed on engineers continue to expand. Sustainability provides a framework for addressing these interconnected pressures through systems-based design and long-term thinking. Yet, sustainability education within engineering programs remains unevenly integrated, often positioned as elective or peripheral rather than as a foundational component of professional preparation.

Prior research shows that sustainability is most frequently addressed through stand-alone courses rather than embedded across required curricula, reflecting disciplinary structures that prioritize …

Reproducing And Evaluating Charger Surfing: Robustness Of Smartphone Charging-Line Side-Channels, Colby M. Watts

Master's Theses

Smartphones are frequently connected to external, untrusted charging hardware, creating opportunities for side-channel attacks that do not require malware or direct access to device data. Charger Surfing, a recently proposed charging-line power analysis side-channel attack, reported high accuracy in inferring touchscreen input from voltage measurements collected from a smartphone’s charging cable; however, the reproducibility and robustness of these results under different conditions remain unclear. This thesis presents an independent replication and evaluation of Charger Surfing, including the development of an end-to-end data collection pipeline consisting of a modified charging cable, oscilloscope-based recordings, custom Android app, automated trace processing, and convolutional …

Improving The Reliability And Performance Of A Supersonic Indraft Tube Wind Tunnel, Christian J. Kaml

Master's Theses

Access to supersonic testing is increasing in demand, and wind tunnels remain one of the safest and most cost-effective methods for gathering high-speed flow data. Despite being more economical than alternative options, supersonic wind tunnel facilities often require substantial investment to construct, operate, and maintain.

The novel indraft tube tunnel architecture was conceived as a high-speed flow testbed that incorporates features of both Ludwieg tubes and indraft wind tunnels to maintain costs low enough to be accessible even to small universities. This design was first developed and tested in 2018 at California Polytechnic State University, featuring a cost per test …

Preserving Structural Alias Information Across The Mlir-To-Llvm Lowering Boundary, Shravan Sheth

Master's Theses

Machine learning training and inference workloads run at massive scale, where the efficiency of generated machine code directly affects throughput and energy consumption. The compilers that lower model specifications to hardware instructions rely on optimization passes that can only exploit information visible in the representations they operate on. MLIR, the intermediate representation framework underlying production machine learning compilers such as IREE and Triton, is designed so that each abstraction level can encode semantics that lower levels cannot represent. One example is memref.subview, which partitions a buffer into typed regions with explicit offsets and sizes, making structural non-overlap provable from the …

Praxsmith: An Actor-Centric Domain Specific Language For Emergent Narratives In Video Games, Jacob C. Kelleran

Master's Theses

The video game industry is rapidly growing, and interest in game development is growing alongside it. Among this growing interest is a desire to include branching and emergent narratives in games. This subject is understood to be difficult, as every possible trajectory within the story creates exponential complexity. Large studios are sometimes able to create convincing implementations, but that is often with hundreds of developers and writers. Over the years, various solutions have been proposed to create frameworks and languages that aim to tackle this problem, with varying degrees of success. Some frameworks attempt this by placing the focus on …

An Evaluation Of Road Network Structure As A Predictor Of Traffic Volume, Colin M. Mcdonald

Master's Theses

This thesis evaluates the relationships between various graph theory metrics and taxi traffic volume for the cities of San Francisco, California and Porto, Portugal. We also evaluate a modified betweenness centrality metric which incorporates the count of distinct origin-destination pairs from the taxi data as the weight function. This thesis extends a paper by Pengyao Ye, Bo Wu, and Wenbo Fan by reducing circularity through a temporal train-test split and by comparing both line-graph and primal-graph formulations of betweenness centrality.

We found that past traffic volume is almost perfectly correlated with future traffic volume and that the modified betweenness centrality …

Sustainable Management Of Soilborne Pathogens In Strawberry Production Through Host Resistance And Sanitation Practices, Maria G. Alvarez Arredondo

Master's Theses

Strawberry production in California is significantly impacted by soilborne pathogens that reduce plant productivity and increase management costs. This research addressed management of these pathogens through two independent approaches: evaluation of host resistance in strawberry cultivars and assessment of sanitation practices for reducing pathogen movement between fields.

Macrophomina root rot, caused by Macrophomina phaseolina, was evaluated over two growing seasons (2024–2025 and 2025–2026) using field trials at California Polytechnic State University, San Luis Obispo. In Year 1, disease incidence varied widely among genotypes, with mortality ranging from 1.3% to 88.8% and an average mortality of 26.4%. Area under the …

Short Arc Angles-Only Initial Orbit Determination For Reliable Reacquisition Of Low Earth Orbit Objects, Isabella Rackemann

Master's Theses

Low Earth orbit (LEO) is becoming increasingly congested, furthering the need for accurate tracking and catalog maintenance. Initial orbit determination (IOD) is the first step in this process, providing a preliminary estimate of an object’s state given observations. When it comes to LEO optical observations, a large portion of them are inherently short in duration. Angles-only IOD methods struggle with this data, often producing highly inaccurate solutions that limit reacquisition capabilities. This study expands on prior short arc IOD research, testing seven classical and assumed circular orbit (ACO)-modified angles-only IOD algorithms on real LEO observational data spanning 0-4 degrees of …

Evaluation Of Alternative Solvents For Electrospinning Occluded Scaffolds To Model Intracranial Atherosclerotic Disease In Blood Vessel Mimics, Olivia D. Rankin

Master's Theses

Intracranial atherosclerotic disease (ICAD) is characterized by a buildup of fatty plaque within the walls of arteries supplying the brain, resulting in vessel narrowing, restricted blood flow, and increased risk of ischemic stroke. While various treatments exist for ICAD, most are accompanied by high recurrent stroke rates and other adverse events, highlighting the need for further investigation and models for pre-clinical testing. Tissue engineered Blood Vessel Mimics (BVMs), consisting of a polymer scaffold sodded with human vascular cells, serve as physiologically relevant in vitro models for vascular device testing. This thesis focused on the application of alternative solvents to a …

Electrically Evoked Emg Decomposition Using The Perturbative Generalized Series Expansion, William R. Walker

Master's Theses

Electrically evoked electromyography records the muscle's response to nerve stimulation and has been used for clinical assessment of neuromuscular function, as well as treatments such as functional electrical stimulation or stroke rehabilitation. In every muscular contraction, an electrical signal is generated. These signals come from the summation of simultaneously recruited motor units, enabling decomposition techniques to reveal information about motor unit recruitment.  By improving the ability to decompose and analyze these signals, clinical treatments involving neuromuscular electrical stimulation can be optimized and better understood. Much of the research on EMG analysis focuses on voluntary EMG, leaving a gap in the …

Xylem: A Comparative Analysis Of Gpu Dispatch Pipelines For Large-Scale, Procedural Environments, Srinivas Sundararaman

Master's Theses

The real-time rendering of large-scale, procedural scenes presents a significant performance challenge for traditional CPU-bound rendering pipelines. The high volume of draw calls and the need for complex culling and level-of-detail management create bottlenecks that limit scene complexity and visual fidelity. This thesis investigates the evolution of GPU-driven rendering paradigms via the Xylem renderer within NVIDIA’s Donut rendering framework as a solution to these challenges.

A comprehensive benchmarking framework is developed to implement and quantitatively analyze three distinct rendering strategies for a procedurally generated, parameterizable, large-scale forest scene. The evaluated pipelines include: (1) traditional instanced rendering, (2) compute-driven indirect rendering …

Chemical And Sensory Consequences Of Oxidative And Reductive Handling Of White Wines, Amelia Pargellis

Master's Theses

In the 2024 and 2025 vintage four experiments were performed each with a different varietal, namely Albariño, Grenache blanc, Loureiro, and Vermentino. These experiments investigated the effects of hyperoxygenation, reductive winemaking techniques, while monitoring the oxidation-reduction potential.

Albariño grapes were made following two juice protocols, control/reductive (Reductive Control) and oxidative (HyOx). Reductive Control received antioxidants (50 ppm SO₂, 160 mg/L ascorbic acid) and CO₂ blanketing, and HyOx underwent hyperoxygenation at approximately 700 mL/L/h of air for two hours through a stainless-steel sparging stone with 10-µm pores. Juice was cold-settled and racked. Reductive Control juice was split into …

Computational Modeling To Evaluate Bipolar Flexible Electrode Designs For Use In Sciatic Nerve Stimulation, Krystyna S. Allman

Master's Theses

Peripheral nerve stimulation is clinically used to manage pain, rehabilitate motor function, and promote nerve regeneration. The sciatic nerve is often studied for stimulation due to its accessibility and clinical relevance. A conventional nerve cuff electrode is the least invasive method for nerve stimulation, but the mismatch of mechanical properties of the electrode with the nerve tissue can cause damage to the nerve and the electrode itself. This study investigated a novel bipolar, gold nanowire-based cuff electrode design and its ability to selectively activate fibers in the rat sciatic nerve at varying interelectrode spacings. In COMSOL, A finite element model …