Engineering Commons^™

Simulation Of Silicon Neurons With Memristive Synapses For Ai Accelerators, Marcus Ivey, Kelvin Shi

Electrical Engineering

This project seeks to design and simulate a neuromorphic spiking neural network (SNN) that implements the logical AND and logical OR operation through the interaction of a Leaky Integrate-and-Fire (LIF) output neuron and memristive synapses modeled using the Biolek formulation. Two pulsed inputs are transmitted through memristive devices whose conductance serves as the synaptic weights. A supervised Hebbian training strategy, implemented in MATLAB, is employed to adjust the synaptic conductance according to the Hebbian delta rule. The proposed framework demonstrates how elementary logical computation may arise from biologically motivated learning processes embedded in hardware-realistic neuromorphic circuits. The study provides a …

Wildlife Tracking Via Uav&Rf, Nam Ah Nguyen

Electrical Engineering

Animal tracking collars transmit very-high-frequency (VHF) beacon signals so researchers can locate tagged wildlife in terrain where direct visual tracking is difficult. This project develops a radio-frequency (RF) wildlife tracking prototype in which a UAV carries a receiving antenna and receiver over the search area to detect the collar signal and send measurements to a ground station. A transmitter test device was built to emulate a tracking collar. An STM32 microcontroller reads keypad input, controls a digital-to-analog converter (DAC), tunes a voltage-controlled oscillator (VCO) to the selected VHF frequency, and sends the RF signal through an amplifier and antenna. The …

Uav Trio Formations For Aerial Pest Deterrence With Vision-Based Bird Monitoring, Benjamin Andrew Ly, Chris Kwon, Christian Joseph Macaranas

Electrical Engineering

No abstract provided.

Portable Food Pasteurization Using Pulsed Electric Fields (Pef), Thomas E. Mcmillan Iii

Electrical Engineering

Foodborne illnesses remain a significant public health concern, motivating continued development of alternative food pasteurization technologies. Pulsed electric field (PEF) treatment is a non-thermal pasteurization method that inactivates microorganisms through electroporation while minimizing thermal degradation of food products. The long-term objective of this project was development of a portable PEF food pasteurization system.

An iterative design approach was used to investigate generation of the high-voltage pulses required for PEF treatment. Multiple pulse forming network topologies were evaluated through simulation, leading to selection of a solid-state Marx generator architecture. A low-voltage five-stage prototype was designed, constructed, and tested to validate the …

Pv Performance Evaluation Study At Cal Poly Solar Farm, Eva Paola D. Calderon

Electrical Engineering

This photovoltaic (PV) system performance evaluation study aims to assess the performance of Cal Poly’s Gold Tree Solar Farm, which produces 4.5MW of solar energy. The evaluation concerns itself with the reliability of the PV system that can be affected by weather conditions, component malfunctions, and degradation of the PV modules. Under the International Energy Agency Photovoltaic Power Systems (IEA-PVPS) Task 13 objectives of reliability and maintenance, this study is necessary to contribute towards improvements in analysis and mitigation strategies for long term usage. Existing operational monitoring data from 2018 to 2025 is the focus timespan, providing real world data …

A Broadband, Dual Polarized Antenna For The Radio Neutrino Observatory In Greenland, Laken Baker

Electrical Engineering

Neutrinos contain information necessary to determine the origins of the universe and cosmic events because they can travel long distances with minimal interaction, preserving information about their cosmic origins. Since neutrinos interact with ice sheets resulting in RF radiation, antennas have been developed to detect RF transmissions.

A compact 'vane structure' (see Fig. 1a) dual-polarized broadband antenna model has been developed, constructed, and characterized according to input reflection coefficient, and co and cross-pol E and H plane radiation patterns using HFSS and Cal Poly San Luis Obispo’s anechoic chamber for the Radio Neutrino Observatory in Greenland (RNO-G) [1]. Its design …

Wireless Communication In Autonomous Vehicles, Kaylie Bao, Nicholas Andrews, Mark Negus

Electrical Engineering

This project focuses on developing and testing a vehicle-to-everything (V2X) communication system using Dedicated Short Range Communications (DSRC) based on the IEEE 802.11p standard. The system uses the NXP i.MX 8XLite V2X Evaluation Kit, which includes the SAF5400 modem for wireless communication in the 5.9 GHz band.

The main goal of this project was to establish reliable communication between two V2X evaluation boards and to verify that custom, user-defined data could be transmitted between them. Through iterative testing, we were able to successfully send and receive custom 802.11 frames using the provided command-line tools and achieve consistent communication between nodes. …

Vlsi Spike Encoder For Spiking Neural Networks With 4-Bit Sar Adc, Jack Marshall, Wyatt Tack, Cameron Young, Ryken Thompson

Electrical Engineering

A spike encoder forms the interface between sampled data, such as image data or a sensor signal, and a spiking neural network by converting numerical input samples into discrete spike events. Unlike conventional artificial neural networks, spiking neural networks use spare, even-driven computation instead of continuous-valued activations. This makes them attractive for low-power embedded systems, biomedical electronics, and other edge applications where energy consumption, physical area, and thermal limits are important design constraints.

This project develops a modular spike encoder architecture for spiking neural networks with selectable support for temporal, rate, multi-spike, and delta encoding. Prior work has shown that …

Lora Radio Propagation & Antenna Design For Freight Trains, Cesar Chavez, Marlon Jennson Hernandez

Electrical Engineering

Freight-train environments present significant challenges for wireless communication due to large metallic structures, varying cargo types, and changing antenna orientations that can degrade radio-frequency propagation. This project evaluated the performance of LoRa-based communication links intended for End-of-Train (EOT) and Head-of-Train (HOT) systems operating at 915 MHz. Field testing was conducted to characterize antenna performance using metrics including received signal strength indicator (RSSI), signal-to-noise ratio (SNR), and communication range. Experimental results showed that antenna polarization and directivity significantly affect communication performance in freight-train environments. Directional antennas provided improved signal strength when properly aligned but experienced performance degradation as antenna orientation changed. …

Cal Poly Mars Rover Battery Management System, Lawrence Nichols, Caleb Michael King, Thomas Anh Khoa To, Angel Soto

Electrical Engineering

The exploration of space has consistently been one of the most expensive endeavors humanities has undertaken in its journey to expand ever further. The PolyRover project aims to not only cheapen that expense through student-based research but also provide a better bang for buck as more unmanned ground vehicles (UGVs) can be utilized on planets in concert. In order to do so, the rovers need a robust, yet compact battery management system that can fit within the wheel well. Our system will consist of six commercially-available 18650 batteries in series, organized in a hexagonal fashion around the motor. The BMS …

Lora Networking Hardware Reference Designs For Terrestrial And Low-Earth-Orbit Communications, Kevin Nottberg

Master's Theses

The work presented here demonstrates a highly robust and tested LoRa networking hardware reference design to meet the needs of the embedded networking company OWL Integrations. The hardware presented integrated a unique combination of features and design choices. The detailing of its unique design is potentially of use to others for use in fielded battery powered terrestrial sensor networking hardware utilizing LoRa. Also, the terrestrial hardware presented is shown to have the capability to support command and control (C2) LoRa links in low-earth orbit beyond terrestrial systems. The design presented has a more U.S. centric component bill-of-materials (BOM), with the …

A Workflow For Automating Geospatial And Data Visualizations For Post-Earthquake Building Damage Data, Alejandra Bravo

Architectural Engineering: Graduate Reports

After major seismic events, reconnaissance efforts of various types are made to gather data. Coarse data can be collected with satellite imagery, mid-scale data can be recorded by capturing thousands of images, and granular data is typically documented manually by humans. Post-earthquake reconnaissance teams can be deployed by universities, research organizations, professional associations, and private firms. Academics, engineers, and students with varying degrees of expertise are tasked with collecting building metadata and damage data, typically in a short period of time. This data can be of various types including numerical (i.e. number of stories, height, etc.), categorical (i.e. damage level, …

Operation Bite Block, Jennifer Aline Robles, Laura Marie Strobbe, William Pearce Graham, Annabelle Katherine Thalken

Mechanical Engineering

Current dental bite blocks, or mouth props, are typically manufactured in fixed sizes, and often result in patient discomfort, reduced procedural efficiency, and the need for dental offices to maintain multiple product sizes. This project sought to design, prototype, and validate an adjustable dental bite block capable of accommodating a wide range of patient mouth openings while maintaining comfort, structural integrity, sterilizability, and operator usability. Working in collaboration with Dr. Alan Latta, a practicing dentist in San Luis Obispo, the design process incorporated stakeholder feedback, patent and market research, engineering analysis, and iterative prototyping to develop a solution that addresses …

Mars Rover Wheels And Drive, Presley S. Sacavitch, Ryan W. Trevena, Dylan A. Mack, Daniel Hudak

Mechanical Engineering

Cal Poly’s Poly1Rover team, advised by Professor Rich Murray, aims to deploy four student-designed mini-Mars rovers, each equipped with a sample-tube retrieval claw, before 2030. However, the wheels of Poly1Rover’s current 6th generation rover are not ready for deployment to Mars, as they do not utilize space-grade materials, are not optimized for manufacturability, and lack sufficient spoke compliance to absorb landing and high-impact loads. This project will be developed by a team of Mechanical Engineering students at California Polytechnic State University, San Luis Obispo (Cal Poly): Daniel Hudak, Dylan Mack, Presley Sacavitch, and Ryan Trevena. Next Intent is providing funding …

Formula Sae Planetary Gearbox Characterization Dynamometer, Trevor Marco Toma, Thomas Welden Pierce, Ethan Liu

Mechanical Engineering

This report outlines a custom hub motor dynamometer requested by the Cal Poly Racing FSAE team. The need for this testing platform is to characterize an existing Formula SAE planetary gearbox for a proposed 4WD powertrain. Hub motors, compact electric machines integrated directly into each outboard wheel, offer significant advantages in efficiency, traction, and chassis packaging compared to conventional RWD drivetrains. By mapping torque capacity, efficiency, lubrication method effectiveness, and fatigue life, the team can validate gearbox design and performance.

This senior project group designed and built a dynamometer according to these specifications which will allow for successful testing to …

Dot Product Engine Based Neuromorphic Hardware For Continuous-Time Biomedical Signal Classification, Sanjeev Srinivasan

Master's Theses

Accurate diagnosis of pathological conditions from biomedical signals, such as electrocardiograms (ECGs) is often performed offline, making it time-consuming, costly, and inefficient, especially when abnormal patterns are rare and long-term monitoring generates large amounts of data. To address this, this work proposes a compact, scalable, and programmable neuromorphic system designed for real-time preliminary arrhythmia detection and classification using ECG signals, that can be extended to other biomedical signals. The proposed design processes ECG signals using a delta modulation-based spike encoder, followed by classification with a dot-product engine (DPE) based spiking neural network (SNN) processor and winner-take-all (WTA) circuit. The architecture …

Effects Of Atomic Oxygen Exposure On Stressed Drag Sail Materials For Low Earth Orbit Applications, Nazanin Sadeghian Dezaki

Master's Theses

As low Earth orbit (LEO) has become an increasingly valuable region for satellite operations, it has grown increasingly congested. The Federal Communications Commission (FCC) deorbit regulations require satellites to be deorbited within 5 years of launch, and drag sails represent a practical means of meeting this requirement. An important consideration for drag sail design is the effect of atomic oxygen (AO) on sail materials. To address the gap in the literature regarding the behavior of stressed drag sail materials under AO exposure, a new test plate was manufactured for the California Polytechnic State University minimum atmospheric experimentation (MAX) AO chamber. …

A Higher Order Panel Method With Vortex Particle Wake, Luca Flick-Kaiser

Master's Theses

Panel codes were some of the earliest methods for computing the flow around aircraft. Despite the availability of higher fidelity CFD methods, panel methods remain an essential tool for the development of modern aircraft, allowing engineers to quickly iterate during the conceptual design phase.

This work develops and implements a high order panel method using Python. The wake is modeled using vortex particles, resulting in an accurate wake representation with minimal user input. The integration of the higher order singularity distributions has been extended to include the calculation of the velocity gradients necessary for the vortex particle implementation. The use …

Development Of A Free-Floating Space Robotic Simulator, Truman: Terrestrial Robotic Unit For Multibody Analysis And Navigation, Jackson W. Cordova

Master's Theses

This work describes the development of a 3 Degree-of-Freedom (DOF) robotic manipulator for use on a free-floating planar air-bearing vehicle. The system developed aims to serve as a foundation for future space robotics research at the California Polytechnic State University (Cal Poly)’s Space Robotics Laboratory. Systems doc- umentation describes conceptual operation and architecture of the proposed system: Terrestrial Robotic Unit for Multibody Analysis and Navigation (TRUMAN). The key operation of TRUMAN is to study a self launch maneuver of a free-floating ve- hicle including 4 distinct phases: launch off a fixed rail, coast, reorientation using manipulator motion, and capture of …

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 …

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 …

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. …

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 …

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 …