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Integration Of Robotic Arm And Conveyor With Programmable Logic Controller, Drake A. Small 2026 California Polytechnic State University, San Luis Obispo

Integration Of Robotic Arm And Conveyor With Programmable Logic Controller, Drake A. Small

Master's Theses

To meet new curriculum demands brought on by Cal Poly's upcoming switch to semesters, a new, cross-disciplinary lab module was developed for EE 435 (Industrial Power Control and Automation). The module emphasizes career-applicable skills, preparing students for the field of controls engineering within the manufacturing industry. These skills include robotic control, computer networking and configuration, and embedded systems. The work focused on integrating a collaborative robot arm to pick-and-place boxes on a conveyor. A myCobot 320 Pi and an Ultimation Powered Roller MDR Conveyor were integrated with the existing PLC system using Modbus RTU and EtherNet/IP communication protocols, respectively. A …


A Performance-Weighted Environmental Assessment Of Ultra-High-Volume Fly Ash Substitution In Portland Cement Concrete, Youngguk Seo, M.A. Karim, Teddy Tzvetkov, Joshua Hardy 2026 Kennesaw State University

A Performance-Weighted Environmental Assessment Of Ultra-High-Volume Fly Ash Substitution In Portland Cement Concrete, Youngguk Seo, M.A. Karim, Teddy Tzvetkov, Joshua Hardy

Faculty Articles

Fly ash substitution for cement in Portland cement concrete (PCC) has been regarded as a sustainable solution, but its widespread application remains constrained by concerns over mechanical performance and durability of PCC, especially at higher replacement rates. This study evaluates PCC mixes incorporating fly ash Type C (FA-C) or Type F (FA-F) across cement replacement rates from 10% to 90%, tracking fresh-state workability, compressive strength, and surface electrical resistivity at 7, 14, and 28 curing days. A process-based life cycle assessment (LCA) with the TRACI 2.1 method quantified global warming potential (GWP, kg CO2/m3) under a …


Evaluation Of Laser Doppler Flowmetry And Transillumination Laser Speckle Contrast Imaging To Measure Blood Flow Change In Ischemia Mouse Hindlimb Models, Simon Park 2026 California Polytechnic State University, San Luis Obispo

Evaluation Of Laser Doppler Flowmetry And Transillumination Laser Speckle Contrast Imaging To Measure Blood Flow Change In Ischemia Mouse Hindlimb Models, Simon Park

Master's Theses

Peripheral Artery Disease (PAD), caused by plaque buildup and narrowing of the arteries, reduces blood flow to the extremities. Promoting collateral arteriogenesis can help redirect blood flow. However, simple growth of collaterals may not be enough to reverse PAD. Instead, the ability for the collaterals to vasodilate and control blood flow is important, meaning assessing collateral function is important for the arteriogenesis assesment. Although microscopy techniques can measure vasodilation, contrast limitations in larger vessels such as collaterals make blood flow measurements difficult. Techniques such as ultrasound or magnetic resonance imaging (MRI) can measure blood flow but have limitations with cost …


Polysaber: A Custom Reactive Lightsaber Soundboard, Pedro B. Medeiros 2026 California Polytechnic State University, San Luis Obispo

Polysaber: A Custom Reactive Lightsaber Soundboard, Pedro B. Medeiros

Computer Engineering

The PolySaber project was developed as a custom reactive lightsaber control system built as a fully custom PCB design. The purpose of the project was to create a lower-cost and more customizable alternative to commercially available lightsaber soundboards while simultaneously providing hands-on experience in PCB design, embedded systems development, and hardware integration. Commercial lightsaber soundboards are expensive, proprietary, and difficult for hobbyists to customize. The PolySaber project addresses this by creating a modifiable hardware platform built around the ESP32 microcontroller. The system supports programmable firmware, RGB NeoPixel blade control, motion sensing, reactive swing and clash effects, onboard audio amplification, and …


Multiplexed Fabry-Pérot High-Temperature Sensing Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Bohong Zhang, Koustav Dey, Jie Huang 2026 Missouri University of Science and Technology

Multiplexed Fabry-Pérot High-Temperature Sensing Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Bohong Zhang, Koustav Dey, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We propose and experimentally demonstrate a multiplexed high-temperature Fabry-Pérot (FP) fiber sensing system interrogated by dispersive microwave-photonic frequency-time domain analysis (DM-FTDA). In the proposed architecture, incoherent broadband probing light is modulated by radio-frequency (RF) signals and then reflected by a parallel network of hollow-core photonic crystal fiber FP (HCPCF-FP) sensors. A chirped fiber Bragg grating provides strong dispersion to map the composite FP spectral response into a well-defined microwave transfer function. Unlike conventional optical Fourier-domain multiplexing that requires deliberate cavity-length allocation, the proposed approach achieves multiplexing via delay-dominated discrimination. Distinct delay fibers are assigned to each sensor branch, and an …


Foundation For A Digital Beamforming System Using Software Defined Radio, Daniel Cruz Guerrero, Shiron Bendrihem, Benjamin Tucker 2026 California Polytechnic State University, San Luis Obispo

Foundation For A Digital Beamforming System Using Software Defined Radio, Daniel Cruz Guerrero, Shiron Bendrihem, Benjamin Tucker

Electrical Engineering

This report demonstrates a basis for the foundation of a software-defined radio (SDR)-based digital beam forming system. Specifically, a discussion of time, frequency, and phase synchronization is had in the absence of costly hardware like an OctoClock. Furthermore, this report digs deep into the design process and device characterization of a 4-way Wilkinson Power Divider, which is a necessary hardware component for phase calibration. SDR synchronization and calibration are critical in any digital beamforming system.


Design And Characterization Of A Pulsed Electric Field Chamber For Microalgae Lysis, Connor Strutin 2026 California Polytechnic State University, San Luis Obispo

Design And Characterization Of A Pulsed Electric Field Chamber For Microalgae Lysis, Connor Strutin

Electrical Engineering

Microalgae are a promising renewable source of biofuel due to their high lipid content and rapid growth rates; however, algae cells must be electroporated (lysed) to release these lipids. The system developed in this project applies short (40 μs–10 ms), high-intensity (up to 33 kV/cm) pulsed electric fields (PEF) across cell membranes to enable electroporation.

Our lab-scale PEF chamber generates uniform, high-intensity electric fields using parallel-plate electrodes with sub-millimeter spacing. The system is designed to efficiently lyse microalgae cells for lipid extraction and biofuel production.


Maximum Power Point Tracking For Photovoltaic Cells, Rodrigo Menchaca-Ramirez, Jesus Martinez, Steven Rodriguez 2026 California Polytechnic State University, San Luis Obispo

Maximum Power Point Tracking For Photovoltaic Cells, Rodrigo Menchaca-Ramirez, Jesus Martinez, Steven Rodriguez

Electrical Engineering

Unlike an ideal DC Power Supply, a solar panel does not operate with linear I-V Characteristics. The voltage and current characteristics of a solar panel change based on irradiance, temperature, weather conditions, and load demand. Because of these factors, solar panels do not always operate at their Maximum Power Point, which can lead to significant power losses. Maximum Power Point Tracking is used to adjust the panel operating point so that more usable power can be delivered to the load.This project developed a Maximum Power Point Tracking system using an STM32 Nucleo-L4A6ZG microcontroller and an LT8705A DC-DC converter stage. The …


A Novel Multi−Agent Deep Reinforcement Learning Framework For Fast Frequency Response In Inverter−Based Hybrid Power Plants, Muhammad Ikram, Asma Aziz, Daryoush Habibi 2026 Edith Cowan University

A Novel Multi−Agent Deep Reinforcement Learning Framework For Fast Frequency Response In Inverter−Based Hybrid Power Plants, Muhammad Ikram, Asma Aziz, Daryoush Habibi

Research outputs 2022 to 2026

The increasing penetration of inverter−based resources (IBR) in power grids necessitates novel control techniques to deliver advanced ancillary services such as fast frequency response (FFR), crucial for ensuring power system stability. Existing schemes−droop control, virtual synchronous generator (VSG), and hybrid approaches−require full observability, and centralized control, which are unsuitable for utility−scale hybrid power plant (HPP) with a distributed grid−forming inverter (GFMI). In addition, it lacks adaptive control capabilities in response to real−time disturbances according to the IEEE 2800−2022 standard. To address these challenges, this paper proposes a design of a novel multi−agent deep reinforcement learning (MADRL) framework for utility−scale IBR−dominated …


Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie ZHOU, Bin ZHU, Jiarui YANG, Xiangyu ZHAO, Jingjing CHEN, Yu-Gang JIANG 2026 Singapore Management University

Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie Zhou, Bin Zhu, Jiarui Yang, Xiangyu Zhao, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Recent advances in Vision-Language-Action (VLA) models have enabled robots to execute increasingly complex tasks. However, VLA models trained through imitation learning struggle to operate reliably in dynamic environments and often fail under Out-of-Distribution (OOD) conditions. To address this issue, we propose Robot-Conditioned Normalizing Flow(RC-NF), a real-time monitoring model for robotic anomaly detection and intervention that ensures the robot's state and the object's motion trajectory align with the task. RC-NF decouples the processing of task-aware robot and object states within the normalizing flow. It requires only positive samples for unsupervised training and calculates accurate robotic anomaly scores during inference through the …


Design And Parametric Study Of A Mems-Based Reservoir Computer For Reinforcement Learning, Andrew P. Carr 2026 California Polytechnic State University, San Luis Obispo

Design And Parametric Study Of A Mems-Based Reservoir Computer For Reinforcement Learning, Andrew P. Carr

Master's Theses

Single-node reservoir computing (RC) is a hardware-efficient approach to machine learning, leveraging the dynamics of physical systems. In this work, two reinforcement learning algorithms, Q-learning and Proximal Policy Optimization (PPO), are applied to a simulated micro-electro-mechanical system (MEMS)-based reservoir computer to solve both discrete and continuous control tasks. MEMS-based reservoirs are low-power, compact, and their natural frequencies (kHz to MHz) pair well with real-time control loops. To explore the relationship between reservoir dynamics and learning performance, a parametric study is conducted on two reservoir hyperparameters, reservoir size and neuron separation, using CartPole-v1 and MountainCar-v0. The RC successfully learns multiple tasks …


Alford Loop Antennas For Ultra-High Energy Neutrino Detection, John K. Kimura 2026 California Polytechnic State University, San Luis Obispo

Alford Loop Antennas For Ultra-High Energy Neutrino Detection, John K. Kimura

Master's Theses

The neutrino is a fundamental particle of matter emitted by high energy phenomena, such as supernovae and black holes. Detecting neutrinos can give scientists information regarding the frequency of high-energy cosmic events, as well as point them towards specific high-energy events. Ultra-high energy (UHE) neutrino interactions in Greenland ice result in electromagnetic pulses between 200MHz and 800MHz. The Radio Neutrino Observatory - Greenland (RNO-G) seeks to observe the resultant electromagnetic waves. The Alford Loop antenna is proposed to detect these emissions, because of its dipole-like radiation pattern, horizontal polarization, and adequate dimensions to fit in a 10" diameter ice borehole. …


Practical Multimodal Wearable Sensing For Functional Upper Extremity Primitive Classification With Application To Stroke Rehabilitation, Nicholas Weiss 2026 California Polytechnic State University, San Luis Obispo

Practical Multimodal Wearable Sensing For Functional Upper Extremity Primitive Classification With Application To Stroke Rehabilitation, Nicholas Weiss

Master's Theses

Stroke often causes long-term weakness and impaired motor control in the upper extremity (UE), making everyday tasks such as reaching, grasping, and moving objects more difficult. Restoring functional arm use is therefore a central goal of post-stroke rehabilitation. Measuring affected arm use continuously and objectively is important because isolated clinical assessments may not fully capture how the affected arm is used during therapy or daily life. Wearable sensors offer a promising approach for monitoring, but raw sensor signals are difficult to interpret directly. Functional movement primitives address this issue by describing UE behavior as smaller, task-agnostic movement units.

This thesis …


Rf Fingerprinting: Neural Networks For Device Identification, Pranav Chainani, Maxwell Gertner, Genevieve Patmore 2026 Santa Clara University

Rf Fingerprinting: Neural Networks For Device Identification, Pranav Chainani, Maxwell Gertner, Genevieve Patmore

Electrical and Computer Engineering Senior Theses

Conventional cybersecurity protocols authenticate devices using digital credentials that can be stolen, copied, or extracted from compromised hardware. Radio frequency (RF) fingerprinting offers a complementary physical-layer authentication mechanism that binds device identity to the unforgeable manufacturing variations present in every transmitter’s analog hardware. This thesis explores the application of convolutional neural networks (CNNs) to RF fingerprinting, focusing on the identification of nominally identical IoT transmitters from raw I/Q samples of the LoRa preamble’s turn-on transient.

We developed an end-to-end system consisting of a modular data collection testbench using a USRP B210 software-defined radio, a 1D CNN trained directly on raw …


Rf Target Identification With Custom Radar Systems, Francis Chau, Alfred Galindez, Austin Petersen 2026 Santa Clara University

Rf Target Identification With Custom Radar Systems, Francis Chau, Alfred Galindez, Austin Petersen

Electrical and Computer Engineering Senior Theses

This project presents the design, construction, and testing of a low-cost Frequency- Modulated Continuous Wave (FMCW) radar system inspired by the MIT Coffee-Can Radar. The system was developed as a modular educational radar platform intended to demonstrate fundamental radar concepts while incorporating updated RF components, custom printed circuit board designs, and improved system-level testing. The radar architecture includes a triangle-wave modulator, voltage-controlled oscillator, attenuator, power amplifier, RF splitter, transmit and receive antennas, low-noise amplifier, mixer, SMA interconnects, and video amplifier.

The project focused on validating individual subsystems, characterizing the chirped RF output, tuning the antennas near the 2.4 GHz operating …


Santa Clara Radio Astronomy Project (Scrap) V, Alejandro Hernandez, Agustin Garcia 2026 Santa Clara University

Santa Clara Radio Astronomy Project (Scrap) V, Alejandro Hernandez, Agustin Garcia

Electrical and Computer Engineering Senior Theses

Santa Clara Radio Astronomy Project (SCRAP) V aims to develop an entirely operational, real-time platform software for an affordable radio telescope that can operate autonomously. This thesis describes the design and implementation process of the fifth generation project through concentrating on the following three key areas: the creation of the live data acquisition and visualization dashboard, thorough verification of the hardware chain received by us, and outdoor system protection from weather factors. The live data dashboard that was created in the MATLAB App Designer completely solved the architecture issues faced with its predecessor being the Python version of the system, …


Skinclusive Ai: Towards Equitable Skin Cancer Detection For Deployment On Edge Devices, Joseph Galicinao 2026 California Polytechnic State University, San Luis Obispo

Skinclusive Ai: Towards Equitable Skin Cancer Detection For Deployment On Edge Devices, Joseph Galicinao

Master's Theses

Skin cancer is one of the most prevalent cancers worldwide, yet existing deep-learning models exhibit significant racial disparities because many widely used datasets are heavily skewed toward lighter skin tones. In addition, many approaches are not designed for deployment on resource-constrained devices, which limits accessibility. This work presents a comprehensive evaluation of classical machine learning and deep-learning based models for binary skin lesion classification, identifying the Swin-Tiny transformer architecture as the most effective backbone. To address bias, we curate a skin-tone balanced dataset, and introduce fairness-aware training through adversarial training, and joint distribution oversampling, to improve performance across protected attributes. …


Dot Product Engine Based Neuromorphic Hardware For Continuous-Time Biomedical Signal Classification, Sanjeev Srinivasan 2026 California Polytechnic State University, San Luis Obispo

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 …


Development Of A Multi-Mode Switching-Inverter Laboratory Module For An Introductory Power Electronics Course, Darcy Eliasi 2026 California Polytechnic State University, San Luis Obispo

Development Of A Multi-Mode Switching-Inverter Laboratory Module For An Introductory Power Electronics Course, Darcy Eliasi

Master's Theses

DC–AC converters, or inverters, are essential power‑electronic interfaces widely used in photovoltaic systems, microgrids, energy‑storage installations, and numerous other modern electrical applications. This thesis presents the design, construction, and testing of an improved laboratory module developed as a student learning tool for demonstrating four fundamental inverter switching techniques: simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. Building upon the previous module, the improved design centers on three key enhancements. These include the selection of a more suitable wave‑generation solution, a multiplexer‑based mode‑selection architecture that reduces user complexity and eliminates conflicting signal configurations, and the integration …


Computer Vision Methods For Detecting Counterfeit Usd Bills, Tyler W. Jones 2026 California Polytechnic State University, San Luis Obispo

Computer Vision Methods For Detecting Counterfeit Usd Bills, Tyler W. Jones

Master's Theses

This thesis addresses the global challenge of counterfeit paper currency by proposing a classical computer vision framework for distinguishing genuine United States Dollar (USD) bills from counterfeit ones using image data. In contrast to existing approaches that rely on a large number of easily reproducible visual features, this work prioritizes the detection of a single, robust security feature: the ultraviolet (UV) reactive security strip embedded in genuine USD bills of denominations $5 and above. By focusing on a feature that is inherently difficult to replicate, the proposed method reduces the likelihood of counterfeit bills being misclassified as genuine.

The system …


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