Electrical and Computer Engineering Commons^™

Range-Doppler Map Processing Chain For Marine Radar On Fpga Of An Rfsoc, Nickolas W. Ogilvie

Master's Theses

To improve the accuracy and resolution of the measurements, radar systems employ increasingly complex, resource-intensive signal processing, larger bandwidths, and higher carrier frequencies. However, implementing these improvements requires more expensive, complex electronics that are larger and use more power. Using RFSoC (Radio Frequency System on Chips) in radars can address these challenges. By combining processors, an FPGA (Field Programmable Gate Array), and RF data converters into a single integrated circuit, RFSoCs allow for radar electronics that are physically smaller, use less power, and are simpler to design. As using RFSoCs to perform RF data conversion for radars has been already …

Neural Compression Inference Accelerator: A Cost And Energy-Effective Alternative To Conventional Machine Learning Inference Methods, Matthew Wallace

Master's Theses

Recent developments in machine learning and artificial intelligence have sparked an influx of workloads that require specialized computer hardware for cloud services. The hardware running machine learning models predominantly consists of graphics processing units (GPUs) and tensor processing units (TPUs). However, these com- ponents are expensive for cloud services to purchase, costly for customers to rent, prone to price spikes, and energy-intensive. In this research we show that both cloud services and customers would benefit from utilizing field programmable gate arrays (FPGAs) to alleviate the aforementioned challenges. An FPGA can be configured as a machine learning accelerator, operating similarly to …

Parameter Measurement Of 0.33 Hp Synchronous Machine Using Itech Digital Power Supply, Andrew Kargol

Master's Theses

The classical methodologies for synchronous machine modeling provide a solid estimation for synchronous machine behavior but are limited in terms of accuracy due to the assumptions made in the modeling process. The equivalent circuit model developed by the classical approach breaks down the entire machine into a singular impedance component. This allows the model to be generated more quickly but limits its accuracy. In the pursuit of developing a more realistic model, this thesis outlines the parameter measurement of a Hampden SM-100 synchronous machine. In determining the SM-100’s experimental parameters, this thesis executes and analyzes new experimental approaches to synchronous …

Class F Power Amplifier And Doherty Power Amplifier Design, Shreyansh Suman

Master's Theses

The main goal of this thesis is to design and fabricate a power amplifier suitable for entry in IMS 2023 High Efficiency Power Amplifier Student Design Competition. Power amplifier design requires multiple design tradeoffs, for example, efficiency and linearity are the two main conflicting design parameters that require careful tradeoff to ensure optimum performance. Two prototypes are designed and fabricated for the competition: Class F operating at 1.5 GHz and Doherty Power Amplifier designed for an operating frequency of 3 GHz. Both prototypes meet the minimum requirement for qualifying in the IMS 2023 HEPA SDC. Class F power amplifier designed …

Enhancing Telecom Churn Prediction: Adaboost With Oversampling And Recursive Feature Elimination Approach, Long Dinh Tran

Master's Theses

Churn prediction is a critical task for businesses to retain their valuable customers. This paper presents a comprehensive study of churn prediction in the telecom sector using 15 approaches, including popular algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, and AdaBoost.

The study is segmented into three sets of experiments, each focusing on a different approach to building the churn prediction model. The model is constructed using the original training set in the first set of experiments. The second set involves oversampling the training set to address the issue of imbalanced data. Lastly, the third set …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Solar Farm Utilizing A Battery Energy Storage System, Hannah Nicole Bonderov

Master's Theses

According to the US Energy and Information Administration, between 2022-2023 60% of planned new electricity generation consists of solar farms with a battery energy storage system [1]. The demand for these paired systems has increased since batteries can be charged during the day with the energy captured from the solar farm then released to the customer in the evening during peak energy demand. This achieves peak load shaving which reduces the cost of electricity for the customer and is ecologically friendly.

This thesis aims to create an efficient solar farm with a battery energy storage system for a farmer in …

Simple Open-Source Formal Verification Of Industrial Programs, Christopher Disney Peterson

Master's Theses

Industrial programs written on Programmable Logic Controllers (PLCs) have become an essential component of many modern industries, including automotive, aerospace, manufacturing, infrastructure, and even amusement parks. As these safety-critical systems become larger and more complex, ensuring their continuous error-free operation has become a significant and important challenge. Formal methods are a potential solution to this issue but have traditionally required substantial time and expertise to deploy. This usability issue is compounded by the fact that PLCs are highly proprietary and have substantial licensing costs, making it difficult to learn about or deploy formal methods on them.

This thesis presents the …

Time-Domain Evaluation Of Atmospheric Ducting Effects On X-Band Propagation Over Water, Jack A. Gallegos

Master's Theses

The marine atmospheric boundary layer (MABL) is the region of atmosphere that interacts with the ocean surface. The atmospheric variability (i.e. temperature and relative humidity) in this region can result in rapid changes in the refractive index with increasing height from the sea surface. The complex region can result in non-standard propagation of electromagnetic (EM) waves beyond the horizon under atmospheric ducting conditions. However, when ducting layers are not present, EM waves are limited to line-of-sight transmission. Atmospheric ducting research is typically conducted using radio frequencies in the X-band (around 8-12 GHz) due to its impact on performance of marine …

Identifying And Minimizing Underspecification In Breast Cancer Subtyping, Jonathan Cheuk-Kiu Tang

Master's Theses

In the realm of biomedical technology, both accuracy and consistency are crucial to the development and deployment of these tools. While accuracy is easy to measure, consistency metrics are not so simple to measure, especially in the scope of biomedicine where prediction consistency can be difficult to achieve. Typically, biomedical datasets contain a significantly larger amount of features compared to the amount of samples, which goes against ordinary data mining practices. As a result, predictive models may fail to find valid pathways for prediction during training on such datasets. This concept is known as underspecification.

Underspecification has been more accepted …

The Rise Of Terrorism In Africa And What It Means For U.S. Policymakers, Bridget Mary Hughes

Master's Theses

This thesis utilizes three case studies to measure the rise of terrorism in Africa. This qualitative data leads the reader to one ultimate question: what does the rise in terrorism in Africa mean for the United States (U.S.) and U.S. policymakers, National Security academia, students in National Security, if anything at all? The answer is: if civilian and military compounds are being targeted by these violent extremists, as these three case studies demonstrate, it is my recommendation that U.S. policymakers cease sending troops to the African theater and, instead, allocate funding to the citizens and nonprofits of the countries whom …

Hypoxic Incubation Chamber, Simone Lisette Helfrich, Makenzie Nicole Jones

Master's Theses

This paper describes the design, manufacturing, and testing of a novel controllable hypoxic incubator with fully functional oxygen gas control and temperature control in a humid environment. On the current market, a majority of the few hypoxic incubators use pre-mixed gas that does not offer precise control over gas concentration. The objective for this project was to create a chamber that allows the user to set the O2 concentration to varying set points of % O2 while maintaining the chamber at a constant body temperature, CO2 level, humidity, and sterility. To start the project, multiple concepts were developed for the …

Design And Analysis Of A Discrete, Pcb-Level Low-Power, Microwave Cross-Coupled Differential Lc Voltage-Controlled Oscillator, Pavin Singh Virdee

Master's Theses

Radio Frequency (RF) and Microwave devices are typically implemented in Integrated Circuit (IC) form to minimize parasitics, increase precision and tolerances, and minimize size. Although IC fabrication for students and independent engineers is cost-prohibitive, an abundance of low-cost, easily accessible printed circuit board (PCB) and electronic component manufacturers allows affordable PCB fabrication.

While nearly all microwave voltage-controlled oscillator (VCO) designs are IC-based, this study presents a discrete PCB-level cross-coupled, differential LC VCO to demonstrate this more affordable and accessible approach. This thesis presents a 65 mW, discrete component VCO PCB with industry-comparable RF performance. A phase noise of -103.7 dBc/Hz …

Current-Source Dc-Dc Converter For Fiber-Optic Communication Systems, Jissell C. Jose

Master's Theses

In this thesis, a proof of concept for a current-source DC-DC converter for powering sensors used in an underwater communications system is presented. The proposed converter steps down an input current of 0.9 A to 0.625 A, while maintaining an output voltage of 24 V and output power of 15 W. The complete steady-state analysis and design of the proposed converter in its single-stage form is also explained in detail. Performance evaluation of the proposed converter was carried out using LTspice. Results of the simulation demonstrate that the design was able to produce average output current of 0.639 A at …

Reliability Study Of Electrical Distribution System With Local And Interregional Bidirectional Centralized Electric Vehicle Charging Stations, Janine Gian Christii C. Darato

Master's Theses

In this thesis, a method was developed to evaluate the impact of bidirectional electric vehicle (EV) charging on power system reliability using Synergi Electric software. Load profiles, EV availability, EV state-of-charge (SOC) were important factors considered in this study. The analysis in this study is based on local and interregional vehicle-to-grid (V2G) implementation at different load points in the system. In general, local V2G implementation is observed to be more effective in improving system reliability over interregional V2G power flow. System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) improvements were observed to increase with increasing …

Music Visualization Using Source Separated Stereophonic Music, Hannah Eileen Chookaszian

Master's Theses

This thesis introduces a music visualization system for stereophonic source separated music. Music visualization systems are a popular way to represent information from audio signals through computer graphics. Visualization can help people better understand music and its complex and interacting elements. This music visualization system extracts pitch, panning, and loudness features from source separated audio files to create the visual. Most state-of-the art visualization systems develop their visual representation of the music from either the fully mixed final song recording, where all of the instruments and vocals are combined into one file, or from the digital audio workstation (DAW) data …

A Nano-Drone Safety Architecture, Connor J. Sexton

Master's Theses

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a …

Neural Network Based Diagnosis Of Breast Cancer Using The Breakhis Dataset, Ross E. Dalke

Master's Theses

Breast cancer is the most common type of cancer in the world, and it is the second deadliest cancer for females. In the fight against breast cancer, early detection plays a large role in saving people’s lives. In this work, an image classifier is designed to diagnose breast tumors as benign or malignant. The classifier is designed with a neural network and trained on the BreakHis dataset. After creating the initial design, a variety of methods are used to try to improve the performance of the classifier. These methods include preprocessing, increasing the number of training epochs, changing network architecture, …

Bearing Fault Detection And Classification Using Artificial Neural Networks, Harnak Singh

Master's Theses

Bearings are the essential components of modern rotating machines. Bearing faults can cause severe machine damages or even breakdowns.

In recent years, artificial intelligence and deep learning have been successfully applied to fault detection. In this thesis, convolutional neural networks (CNN) are employed for bearing fault detection and classification. Computer simulations results demonstrate that the CNN based approach is advantageous over the conventional regression model, with an overall accuracy of 99.5%.

Design And Analysis Of N-Path Filter For Radio Frequencies, Nathan M. Bergen

Master's Theses

Due to the growth of wireless communication many communication frequencies have grown increasingly dense. This density requires higher Q-factor to receive only the signal of interest. With the rise of smaller integrated circuits previous solutions used for filtering have become viable again. This paper explores whether the N-path filter is viable in the modern day for radio frequency receiver purposes. A non-differential N-path filter was created by utilizing Cadence Virtuoso with a working center frequency range of 750MHz to 1GHz while using TSMC technology. The desired quality factor of over 1,000 was reached while maintaining a total area of 800 …

Microgrid Laboratory Wind Energy Integration, Vincent Liang

Master's Theses

Cal Poly San Luis Obispo’s Electrical Engineering Department and the Power Energy Institute have developed a microgrid laboratory with various generators, loads, and protection systems over the past several years. To improve and make the Cal Poly microgrid laboratory more realistic, this thesis outlines the process of improving the EE microgrid setup by adding a wind energy generation system via an induction generator, excitation capacitors, and a protection relay. By adding an induction generator, the microgrid system becomes more resilient to sudden power fluctuations by maintaining a stable voltage and frequency when the microgrid is islanded. To test this, a …

X-Band Rf Transmitter Design For Multi-Purpose Small Satellite Communication Operations, Omer F. Gumus

Master's Theses

This thesis provides a description of the analysis, design, and tests of an X-band RF Transmitter communication system for small satellites. X-band transmitter systems are becoming popular in the upcoming deep space missions. Most of the deep-space ground stations have been using X-band frequencies to receive or transmit signals. The X-band (<10 GHz) can offer lower atmospheric losses and up to a couple of Mbps data rates for multiple satellite operations. Nowadays, many small satellites have been using frequency bands such as VHF, UHF, L, and S-band frequencies for communication. From deep space to the ground station, the low-frequency ranges are inadequate in providing Mbps level data rates and enough bandwidth for deep space missions.

The main focus of this thesis was the development of the subsystems such as gain block amplifier, Mixer, Bandpass Filter, and RF power amplifier. The subsystems were designed separately, then they were connected together to perform an end-to-end system test. One of the thesis aims is to design …

Design Of An Automotive Iot Device To Improve Driver Fault Detection Through Road Class Estimation, Matt Murray

Master's Theses

Unsafe driver habits pose a serious threat to all vehicles on the road. This thesis outlines the development of an automotive IoT device capable of monitoring and reporting adverse driver habits to mitigate the occurrence of unsafe practices. The driver habits targeted are harsh braking, harsh acceleration, harsh cornering, speeding and over revving the vehicle. With the intention of evaluating and expanding upon the industry method of fault detection, a working prototype is designed to handle initialization, data collection, vehicle state tracking, fault detection and communication. A method of decoding the broadcasted messages on the vehicle bus is presented and …

Model-Based Design Of An Optimal Lqg Regulator For A Piezoelectric Actuated Smart Structure Using A High-Precision Laser Interferometry Measurement System, Grant P. Gallagher

Master's Theses

Smart structure control systems commonly use piezoceramic sensors or accelerometers as vibration measurement devices. These measurement devices often produce noisy and/or low-precision signals, which makes it difficult to measure small-amplitude vibrations. Laser interferometry devices pose as an alternative high-precision position measurement method, capable of nanometer-scale resolution. The aim of this research is to utilize a model-based design approach to develop and implement a real-time Linear Quadratic Gaussian (LQG) regulator for a piezoelectric actuated smart structure using a high-precision laser interferometry measurement system to suppress the excitation of vibratory modes.

The analytical model of the smart structure is derived using the …

Investigation Of Green Strawberry Detection Using R-Cnn With Various Architectures, Daniel W. Rivers

Master's Theses

Traditional image processing solutions have been applied in the past to detect and count strawberries. These methods typically involve feature extraction followed by object detection using one or more features. Some object detection problems can be ambiguous as to what features are relevant and the solutions to many problems are only fully realized when the modern approach has been applied and tested, such as deep learning.

In this work, we investigate the use of R-CNN for green strawberry detection. The object detection involves finding regions of interest (ROIs) in field images using the selective segmentation algorithm and inputting these regions …

Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone

Master's Theses

One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any …

Underground Transmission For Renewable Energy: Design, Modeling, And Analysis, Matthew Suen

Master's Theses

A microgrid is a local energy grid that could be disconnected from the larger grid and operate autonomously. This particular segment of the power industry is growing due to its reliability during times of emergency and crisis. Among these benefits are improved efficiency, lower operating costs, renewable generation sources, and improved resiliency of the regional electric grid. Communities can better prepare for unprecedented weather like wildfires, hurricanes, and other natural disasters. Regions that produce renewable energy can export their surplus through high voltage transmission lines to balance power supply and demand needs.

This Underground High-Voltage Transmission Network project aims to …

Integration Of Electrical Impedance Spectroscopy For Multichannel Cell Culture Measurement, Conard Chan

Master's Theses

ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY (EIS) has been widely used to study the electrical properties of biological material due to its non-invasive nature and experimental reliability. However, most of the precision impedance analyzers used in EIS only provide single- or two-channel measurements which are inadequate for larger-scale multiplexed measurements, such as those found in modern microfluidic cell culture experiments. The Biomedical Microsystems Laboratory has developed a 16-channel cell culture platform with integrated electrode arrays for monitoring cell growth and electrical properties (i.e., the so-called “electrical phenotype”). In this paper, a system consisting of a 16-channel solid-state analog multiplexer (MUX)paired with a low-cost, …

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …