Digital Commons Network^™

An Analysis Of The Power Consumption Of Various Computer Vision Machine Learning Techniques On A Microcontroller Utilizing The Clusterduck Protocol, Kaveh Shafiei

Electrical Engineering

Constant data processing is essential for effective data collection, particularly in remote and hard-to-reach areas. The need for efficient, autonomous data acquisition and transmission is increasingly addressed by integrating machine learning within larger communication networks. This paper explores the application of machine learning techniques with Internet of Things (IoT) mesh networks. Utilizing the LoRa communication protocol, data is captured and analyzed on an edge device and transmitted to a larger communication network. The ClusterDuck Protocol (CDP), developed by OWL Integrations, serves as an IoT mesh network designed to allow for communication in areas lacking traditional static infrastructure such as WiFi …

Leader-Follower Platooning With Turtlebot3: A Low-Cost Ros Test-Bed Using Vision-Lidar Fusion, Patrick Kelly Crandall, Kalon Ma Bienz

Electrical Engineering

This report presents the design, implementation, and indoor validation of a two-robot leader–follower platoon built on low-cost Turtlebot3 platforms. Each robot runs ROS Noetic on an on-board Raspberry Pi 4, fusing a fisheye camera for HSV-based lane detection with an LDS-02 LiDAR for clustering-based leader identification. A dual-loop architecture (PD steering for lateral control and PID for longitudinal gap regulation) maintains a 0.40m headway and keeps the follower centered within +/- 5 cm of the lane midline, without any inter-vehicle communication or external localization. Track experiments at speeds up to 0.18m/s achieved mean gap error of +/- 3 cm and …

Advanced Light Dimming Power Converter, Jaden Nguyen, Edwin Lin, Alan Thai

Electrical Engineering

This senior project discusses and follows the development of the Advanced Light Dimming Power Converter meant to modernize the power electronics curriculum and improve student safety for a lab. The power converter attempts to replace the original experiment which includes a traditional TRIAC-based dimmer and focuses on demonstrating phase angle control for incandescent light bulbs. However, several drawbacks including high-voltage exposure and outdated technology warranted a revamp. The redesigned module includes a dual-experiment setup with an updated TRIAC-based dimmer circuit and a new AC-DC LED driver circuit with constant current control and PWM dimming capability. Both systems have been fabricated …

A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat

Dissertations

Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.

This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …

Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha

Theses and Dissertations

Wireless communication networks are advancing at a rapid pace, driven by various challenges and ambitious goals. This rapid growth is driven by a range of applications, including technologies like the Internet of Things (IoT), as well as innovations in smart cities, autonomous vehicles, and more. Different applications demand specific performance criteria such as high data throughput, low latency, robust reliability, and efficient energy usage. In this thesis, we investigate two enhancements that can be adopted in wireless networks to tackle the challenges of resource optimization and network management. The motivation behind this is the fact that future networks will face …

Robust Adaptive Fractional-Order Pid Controller Design For High-Power Dc-Dc Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm For Electric Vehicles, Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The Dual Active Bridge converter (DABC), known for its bidirectional power transfer capability and high efficiency, plays a crucial role in various applications, particularly in electric vehicles (EVs), where it facilitates energy storage, battery charging, and grid integration. The Dual Active Bridge Converter (DABC), when paired with a high-performance CLLC filter, is well-regarded for its ability to transfer power bidirectionally with high efficiency, making it valuable across a range of energy applications. While these features make the DABC highly efficient, they also complicate controller design due to nonlinear behavior, fast switching, and sensitivity to component variations. We have used a …

Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo

Engineering Faculty Articles and Research

Monitoring children’s handwriting, such as avoiding writing assignments, displaying uneven letter formation, or showing slow writing speed, can help identify developmental and academic issues early. Poor handwriting affects up to 34% of children, leading to academic and self-esteem challenges. Handwriting assessments, typically conducted by teachers, are often delayed due to workload and could be subjective and inconsistent. This paper explores the potential of Optical Character Recognition (OCR) technology to augment and ease handwriting assessments. Based on an evaluation of 10 OCR algorithms using 33 handwriting samples assessed by two experts, the research indicates that Pen to Print and Google are …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Distributed Formation Control Of Nonholonomic Mobile Robots: Safety-Critical Leader-Follower Approach With Obstacle Avoidance And Dynamic Reconfiguration, Kelvin C. Villago

Master's Theses

Networked control systems for multi-agent robotics have emerged as a critical paradigm for executing complex coordinated tasks in diverse environments. While formation control serves as the backbone of such systems, real-world deployment introduces significant challenges including communication constraints, environmental obstacles, and the need for adaptive reconfiguration. This research addresses these challenges by developing a novel unified framework that seamlessly integrates obstacle avoidance algorithms with dynamic formation reconfiguration capabilities, specifically designed for communication-limited networked control architectures. The proposed framework represents a significant advancement over existing approaches by simultaneously handling both static and dynamic obstacles while maintaining system cohesion under communication constraints. …

Leveraging Machine-Learning Algorithms In Two Car Crash Detection Systems On A Custom Dataset, Addison Jacob Sandvik

Master's Theses

Traffic accidents pose a significant threat to public safety, causing millions of deaths and injuries worldwide each year. While efforts to reduce accidents have seen limited progress in recent years, improving emergency response times through automated detection systems is a promising avenue for saving lives. This thesis describes the development of machine learning-based traffic accident detection systems, exploring both video classification and image detection models. The models are trained on a new dataset deemed the Cal Poly Traffic Accident Dataset, an extension of the existing Car Accident Detection and Prediction (CADP) dataset with a precise collision annotations. Two systems were …

Nonlinear Integral Control Schemes For A Cadence-Heartrate Process: A Matlab Exploration, Alexander G. Elliott

Master's Theses

Keeping one’s heart-rate within a specific range during a cardiovascular workout can be difficult due to many factors including variations in the exercise environment and changes in energy level. One’s heart-rate can be controlled by tuning the intensity level of the activity over time. This study focuses on the relationship between a runner’s cadence and their heart-rate and explores ways to control the heart-rate by adjusting the cadence. Previous work in this area modeled the cadence-heartrate plant as a first-order linear system, but this has been shown to be insufficient. This work improves upon previous research in this area by …

Study On The Application Of Smart Electric Meters For Secondary Voltage Protection, Jayaditya Sisodia

Master's Theses

The purpose of our research is to utilize PG&E’s Smart Meters installed across California to protect the Secondary Voltage delivered to the meter. This means detecting electrical faults between the utility’s distribution transformer and the installed Smart Meter. Our goal is to propose and implement various solutions through additional devices and protocols to detect and prevent these faults, communicate them with the meter, and forward fault information to the utility. A device will be designed to be installed on the transformer, detect faults, shut off power transmission, and communicate to the meter via fiber optic cable. Research will then be …

Open Source Asic Design Curriculum, Francisco Wilken

Master's Theses

The ever-growing importance of Application-Specific Integrated Circuits (ASICs) in a high-compute world necessitates that college graduates entering the workforce are well prepared to design them. This thesis details the design of novel ASIC curriculum, using open source tools to teach at the undergraduate level. By moving to a higher level of abstraction than classical transistor-focused coursework, chip design material can be made accessible earlier in an undergraduate degree. Additionally, open source tools provide a powerful, free, and portable platform for students to create their own designs, solving assignments focused on industry readiness. Finally, this thesis studies the results and challenges …

Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman

Master's Theses

The purpose of this study is to explore the ability of a programmable logic controller (PLC) to wirelessly monitor and control power protection relays. The technologies surrounding power protection and industrial automation are ever evolving and have developed significantly in recent history. Industrial power applications call for consistent condition monitoring and status updates for various high-importance components. The high-importance components have power protection schemes that are managed by digital relays to trip circuit breakers in fault or unsafe operating conditions. The smart relays have a wide range of capabilities, including communications. Cal Poly assembled a collection of relays from Schweitzer …

Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk

Master's Theses

Advancements in power electronics require high switching frequencies which the digital control routines of the systems cannot keep up with. Analog computing is added to digital control systems to prevent bottlenecks and allow real-time implementation. This paper proposes a hybrid computing model predictive control system for a buck converter. The control system implements the gradient dynamics of the optimization function using digital computing, and the gradient dynamics for the penalty function and integrator using analog computing. For the full simulations of the entire system, the PLECS RT Box is used to simulate the controller in real time with a 1 …

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling

Theses and Dissertations

Gravimeters are devices that measure gravitational acceleration which can be used by the United States Air Force (USAF) in the areas of navigation and remote sensing. Fused-silica microelectromechanical systems (MEMS) devices offer capabilities to make inexpensive relative gravimeters with higher thermal stability than common silicon devices while maintaining good gravitational sensitivity. The fused-silica devices in this research were designed, simulated, fabricated, and tested to observe their performance as gravimeters. The devices exhibit properties of highly sensitive accelerometers but the current designs do not qualify as gravimeters. This study provides information to improve the sensitivity and stability of these fused-silica MEMS …

Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan

Dissertations

This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.

The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang

Dissertations and Theses

Deep learning (DL)-based angle-of-arrival (AoA) estimation offers significant advantages over traditional signal processing methods, especially in complex and high-noise environments. However, situational complexity and differences in hardware can significantly impact the estimator's performance. It is therefore of interest to investigate the relationship between the performance of deep learning models and the variation of physical parameters such as the number of signal sources, the number of receiving antennas, and the signal-to-noise ratio (SNR). In this study, we investigate the impact of these variations on deep learning-based AoA estimation by systematically analyzing how the variations in the characteristics of the received signal …

Strongly Confined Bi2se3 Quantum Dots Via Pulsed Laser Ablation In Liquids, Gregory Guisbiers, Rajendra Subedi, Burningham Burningham, Francisco Francisco Ruiz-Zepeda, Qiaohui Zhou, Xin Lu

Faculty Scholarship

Bismuth selenide (Bi2Se3) is a binary compound displaying a strong spin−orbit coupling, resulting in a narrow bulk bandgap material with a gapless metallic surface. By shrinking the size of Bi2Se3 within the strong confinement regime, its optoelectronic properties changed drastically. To achieve this goal, strongly confined Bi2Se3 quantum dots (QDs) were produced by pulsed laser ablation in liquids (PLAL). The laser used for the synthesis was a nanosecond Nd/YAG laser emitting at 1064 nm and pulsing at ∼13 mJ/pulse. The irradiation of the bulk target was performed at 1 kHz in acetone and lasted 5 min. Finally, the Bi2Se3 QDs …

Preparation And Modification Of Mxene Composites For Application In Electrochemical Energy Storage, Zhang-Hai You, Ding-Ze Lu, Kiran Kumar Kondamareddy, Wen-Ju Gu, Peng-Fei Cheng, Jing-Xuan Yang, Rui Zheng, Hong-Mei Wang

Journal of Electrochemistry

With the acceleration of advanced industrialization and urbanization, the environment is deteriorating rapidly, and non-renewable energy resources are depleted. The gradual advent of potential clean energy storage technologies is particularly urgent. Electrochemical energy storage technologies have been widely used in multiple fields, especially supercapacitors and rechargeable batteries, as vital elements of storing renewable energy. In recent years, two-dimensional material MXene has shown great potential in energy and multiple application fields thanks to its excellent electrical properties, large specific surface area, and tunability. Based on the layered materials of MXene, researchers have successfully achieved the dual functions of energy storage and …

Theoretical Insights Into The Atomic And Electronic Structures Of Polyperyleneimide: On The Origin Of Photocatalytic Oxygen Evolution Activity, Yi-Qing Wang, Zhi Lin, Ming-Tao Li, Shao-Hua Shen

Journal of Electrochemistry

Polymeric perylene diimide (PDI) has been evidenced as a good candidate for photocatalytic water oxidation, yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration. Herein, with crystal and atomic structures of the self-assembled PDI revealed from the X-ray diffraction pattern, the electronic structure is theoretically illustrated by the first-principles density functional theory calculations, suggesting the suitable band structure and the direct electronic transition for efficient photocatalytic oxygen evolution over PDI. It is confirmed that the carbonyl O atoms on the conjugation structure serve as the active sites for oxygen evolution reaction by the crystal …

Three-Dimensional Melamine Carbon Sponge/Nai As Cathode Materials For Sodium-Ion Batteries, Qian-Ying Huang, Yue Liu, Zi-Xin Lin, Shu-Yi Zheng, Ting-Ting Mei, Yu-Ting Tang, Ying-He Zhang, Jun Liu

Journal of Electrochemistry

The sodium-iodine (Na-I) battery exhibits significant potential as an alternative energy storage device to the lithium-ion battery. However, its development is hindered by inadequate electrical and thermal stability, as well as the dissolution and shuttling of polyiodide. In this study, we report a preparation method for melamine carbon sponge (MC) via carbonizing a commercially available kitchen sponge. It was revealed that the as-prepared MC, composed of unique self-growing carbon nanotubes, could provide both physical and chemical adsorption capabilities for intermediate polyiodides to improve the electrochemical performance of NaI. Consequently, the NaI/MC electrode effectively minimized polyiodide dissolution and reduced the electrochemical …

Comprehensive Risk Assessment Of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis, Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. Mccann

Electrical Engineering and Computer Science Faculty Publications and Presentations

Power grid infrastructures, essential to modern societies for electricity distribution, are prone to vulnerabilities due to their numerous sensitive components, necessitating a comprehensive risk assessment. Uncertainty in historical failure data often compromises accurate risk quantification, leading to the integration of expert elicitation as a solution. This study develops a Bayesian network (BN) risk assessment model integrated with fuzzy set theory (FST), referred to as the fuzzy Bayesian network (FBN). By incorporating expert insights, this model quantifies internal and external risk variables more comprehensively. Crisp probabilities (CPr), derived from regional transmission operator (RTO) failure incident data, are complemented by fuzzy probabilities …

Understanding The Morphology And Mass Transport Resistance Of Mesoporous Carbon-Supported Pemfc Based On Modeling Analysis, Hao Deng, Jia Liu, Zhong-Jun Hou

Journal of Electrochemistry

Mesoporous carbon supports mitigate Pt sulfonic poisoning through nanopore-confined Pt deposition, yet their morphological impacts on oxygen transport remain unclear. This study integrates carbon support morphology simulation with an enhanced agglomerate model to establish a mathematical framework elucidating pore evolution, Pt utilization, and oxygen transport in catalyst layers. Results demonstrate dominant local mass transport resistance governed by three factors: (1) active site density dictating oxygen flux; (2) ionomer film thickness defining shortest transport path; (3) ionomer-to-Pt surface area ratio modulating practical pathway length. At low ionomer-to-carbon (I/C) ratios, limited active sites elevate resistance (Factor 1 dominant). Higher I/C ratios improve …

Optimization Of Renewable Energy Systems: Comparative Analysis Of Advanced Algorithms And Photovoltaic-Electrolyzer Performance For Cost Reduction And Efficiency Enhancement, Mohamed-Amine Babay, Mustapha Adar, Ahmed Chebak, Mustapha Mabroukia

Journal of Electrochemistry

The increasing demand for cost-effective and efficient renewable energy solutions presents significant optimization challenges in hybrid energy systems. This paper addresses these challenges by conducting a comparative analysis of three advanced optimization algorithms—Lévy Flight Optimization (LFO), Archimedean Optimization (AO), and Quantum Gorilla Optimization (QGO)—to minimize the Total Net Present Cost (TNPC) and Levelized Cost of Energy (LCOE) in hybrid renewable energy systems. The study integrates critical cost parameters such as Capital Expenditure (CAPEX), Operational Expenditure (OPEX), replacement costs, and salvage values into an advanced optimization framework. Three system configurations are evaluated: Wind Turbines and Fuel Cells (WT/FC), Photovoltaic Systems and …

Design And Performance Evaluation Of Pv-Powered Ev Charging Stations With Grid Integration And Comparative Analysis Of Dc-Dc Converters For Offboard Chargers, Mohammad Abidur Rahman

Theses and Dissertations

Grid-integrated photovoltaic (PV)-powered electric vehicle (EV) charging stations offer a sustainable solution for reducing grid dependency and fossil fuel consumption in workplace environments. This study proposes a PV-powered EV charging system with an AC bus configuration and grid support to ensure stable and efficient operation. A comparative analysis of four DC-DC converter topologies—Dual Active Bridge (DAB), LLC Resonant, Interleaved Buck-Boost, and Interleaved Buck—is conducted for offboard charging applications. Performance evaluation is carried out using MATLAB/Simulink, considering voltage and current ripple, power density, stress levels, bidirectional capability, and control complexity. Component-level reliability is assessed using MIL-HDBK-217 standards to estimate failure rates …

Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed

Turkish Journal of Electrical Engineering and Computer Sciences

This work describes a microstrip log-periodic dipole array (MLPDA) antenna that uses metamaterials and operates across the whole Ka-band. The suggested MLPDA antenna layout provides a wide bandwidth with fewer dipole elements than traditional MLPDA antennas while maintaining the same resonance frequencies. To reduce size while covering a wide operational spectrum, the antenna design includes bending dipoles as radiating elements, as well as an incomplete ground plane. Furthermore, the proposed MLPDA antenna’s energy loss has been reduced while boosting its signal strength (gain) by inserting a metamaterial-based structure in front of it at a certain distance and on the same …

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif

Electrical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure …