Digital Commons Network^™

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 …

Report On The Ethical Use Of Ai For Participatory Planning, Sahana Kotha, Blythe Wilson

City and Regional Planning

This report provides an overview of key considerations for using artificial intelligence for community engagement in urban planning. As interest in AI adoption in the public sector increases, an understanding of ethical issues is needed to guide responsible AI implementation. Informed by a literature review and interviews with urban planning practitioners and academics, this report describes and analyzes different AI-supported community engagement methods, explores case studies, and outlines key concerns and opportunities for using AI. We recommend that AI use for community engagement prioritizes transparency, human oversight and accountability, intentional AI implementation, and community involvement.

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 …

Electrical Resistivity Tomography Investigation Of Hard Rock Aquifers In The Salinian Block, Roxanne C. Chambers

Physics

Identifying a productive groundwater source in hard rock terrain is often a challenge. Conventional hard rock aquifer models commonly describe a weathering derived layered system consisting of a laminated layer, an underlying fractured zone, and a competent granitic basement. This study investigates the applicability of this conceptual model at Lockshaw Ranch, a granitic site within the Salinian Block of central California located near the Rinconada Fault.

Previous electrical resistivity tomography (ERT) surveys and time domain electromagnetic (TDEM) data were integrated with a newly acquired ERT profile (ERT-06) are used to characterize the subsurface structure and identify potential groundwater bearing zones. …

Bowl-O-Matic, Nathan Lin, Luis Torres, Jill Worthington, Aiden Foote

Mechanical Engineering

Adaptive physical education presents the unique challenge of accommodating individuals with diverse physical and cognitive abilities. Instructors and program designers must often integrate specialized equipment, fixtures, or features to ensure activities remain safe, inclusive, and user-friendly. Beyond accessibility, adaptive physical education highlights the importance of empowerment— enabling every participant to experience personal growth, confidence, and connection through movement. Friday Club, a local San Luis Obispo program supported by Cal Poly’s Kinesiology Department, embodies these values by providing adaptive physical activities that promote health and well-being for individuals with varying abilities. One of the most popular and regularly held activities is …

Cosmetic Clamper, Daniel Peter Gates, Bruno Roberto Martinez, Samantha Remy, Zachary Joseph Roeber

Mechanical Engineering

Cosmetic Clamper Mechanical Engineering Senior Project was a senior project at California Polytechnic State University, San Luis Obispo in the College of Engineering, Mechanical Engineering Department. The project ran from September 2025 to June 2026. The project developed the Cosmetic Clamper device, an accessibility product designed to help individuals with unilateral upper extremity motor deficits open, use, and close cosmetic containers independently.

Me3329 Modular Phonograph Gearbox, Garrett Andrik Leighton, Preston Robert Hupe, Gavin Carter Ebner, Andrew Renato Reyes

Mechanical Engineering

The Mechanical Engineering Department at California Polytechnic State University, San Luis Obispo (Cal Poly), seeks to develop a laboratory tool allowing students to reinforce concepts of gears for Mechanical Systems Design (ME329). Some current laboratories do not provide students with hands-on interaction, and the department lacks equipment and documentation to support a standardized lab. With ME329 expanding from ten to fifteen weeks, there is an opportunity to create a physical gearbox design lab allowing students to reinforce lecture material in engaging ways, while standardizing student learning. This senior project is presented and sponsored by Professor Alan Zhang. It will be …

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 …

Experimental Methods For Cryogenic Rare Event Detection: Cuore And Cupid, Alessandro Libenson

Physics

This senior project was written with the primary purpose of serving as a introductory guide for undergraduate students learning about the experimental methods used in the CUORE and CUPID Collaborations. In particular, this project is geared towards getting students in Dr. Gutierrez's research group at Cal Poly up to speed on what CUORE and CUPID actually do. I wrote this as an undergraduate aiming to help future undergraduates. For Cal Poly students, I would suggest the following prerequisites before reading this paper: Electronics and Instrumentation, Quantum Laboratory 1, and the equivalent of the coding/analysis class. It is also important to …

Kinetic Sculpture For The San Luis Obispo Botanical Garden, Yotam Barr, Reynaldo Farias, Natalie Krueger, Priscilla Puei Ci Lam

General Engineering

Flower Power designed, fabricated, tested, and installed a wind-driven metal lavender and bee sculpture for the San Luis Obispo Botanical Garden Children's Garden. The project provides a colorful kinetic installation that complements the existing poppy sculpture while remaining child-safe, durable outdoors, manufacturable with campus resources, and low cost to the sponsor. The final sculpture consists of a steel main stem installed in a sleeve-style concrete foundation, three green branch clusters, independently rotating purple lavender bud assemblies, decorative leaves, and a bee. The sculpture was fabricated from steel tube, sheet metal, bearings, printed ASA components, paint, and foundation materials. The installed …

25₵ Per Minute, Tashi Manchip

Intertidal

No abstract provided.

The Temple In Me, Luca Shahar

Intertidal

No abstract provided.

Chasing Mavericks, Hannah Hochheiser

Intertidal

No abstract provided.