Engineering Commons^™

Checkerbot, Sean P. Whitty

Electrical Engineering

This product is able to play a game of checkers against the customer at three different preset difficulties. It can process the board on its turn, and displays its next turn to its opponent by updating the board state via the LEDs. It consists of a laptop screen display, and a computer chip with the programmed ability to process the checkers board and decide its next move. It provides the customer with an opponent that can be modified in difficulty so it can provide however much of a challenge as the customer desires, as well as allowing for a 2 …

Distributed Estimation And Inverse Reinforcement Learning For Multi-Agent Systems, Bosen Lian

Electrical Engineering Dissertations - Archive

Consensus-based distributed Kalman filters for estimation with multiple targets have attracted considerable attention. Most of the existing Kalman filters use the average consensus approach, which tends to have a low convergence speed. They also rarely consider the impacts of limited sensing range and target mobility on the information flow topology. The robustness properties, i.e., gain margins and phase margins of distributed Kalman filtering algorithms are still open problems. In the interactions of controlled dynamical agents, it is often assumed that the agents are "rational" in the sense of attempting to act in such a way as to optimize some prescribed …

Fast And Parallelizable Numerical Algorithms For Large Scale Conic Optimization Problems, Muhammad Adil

Electrical Engineering Dissertations - Archive

Many real world problems from various application areas such as engineering, finance and operation research can be cast as optimization problems. Generally, the goal is to optimize an objective function under a set of constraints. Traditionally, convex optimization problems are solved by an interior point method (IPM). Interior point methods proved to achieve high accuracy for moderate size problems. However, the computation cost of iterations of these iterative algorithms grows non-linearly with the dimension of the problem. Although interior-point methods are robust and theoretically sound, they do not scale well for very large conic optimization programs. Computational cost, memory issues, …

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 …

Indoor Positioning Using Synchronized Ultrasonic Ofdma Signals, Julian Bartolone

Master's Theses

This paper proposes a method of short-range indoor localization using differential phase measurements of synchronized two-tone ultrasonic signals in an Orthogonal Frequency Multiple Access (OFDMA) scheme. This indoor positioning system (IPS) operates at an ultrasonic frequency of approximately 40kHz and synchronizes using an infrared signal. The OFDMA scheme allows for a receiver to process the signals from multiple transmitters continuously without the signals interfering with each other. The phases of the signals are measured using Goertzel Filters, allowing for low-complexity frequency content analysis. A MATLAB simulation using the proposed localization method is performed using four transmitter nodes in the corners …

Performance Loss Rate And Temperature Modeling In Predictive Energy Yield Programs For Utility-Scale Solar Power Plants, Katelynn M. Dinius

Master's Theses

The Gold Tree Solar Farm, designed by REC Solar, has a rated output power of 4.5 MW and began operation in 2018 to provide electricity to Cal Poly’s campus. Gold Tree Solar Farm site terrain consists of rolling hills and uneven slopes. The uneven typography results in interrow shading, requiring a modified tracking control algorithm to maximize power production. Predicting a utility solar field’s lifetime energy yield is a critical step in assessing project feasibility and calculating project revenue. The MATLAB-based predictive power model developed for this field overpredicted power in the middle of the day. The purpose of this …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Spectral Dependence Of Deep Subwavelength Metallic Apertures In The Mid-Wave Infrared, Heath Gemar

Electronic Theses and Dissertations, 2020-2023

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength cavities for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns (i.e., mid-wave infrared or MWIR). We explore the trade space of deep subwavelength cavities and its impact on resonant enhancement of the electromagnetic field. The studies provide fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on cavity geometry and material properties. …

Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang

All Dissertations

Material microstructure prediction based on processing conditions is very useful in advanced manufacturing. Trial-and-error experiments are very time-consuming to exhaust numerous combinations of processing parameters and characterize the resulting microstructures. To accelerate process development and optimization, researchers have explored microstructure prediction methods, including physical-based modeling and feature-based machine learning. Nevertheless, they both have limitations. Physical-based modeling consumes too much computational power. And in feature-based machine learning, low-dimensional microstructural features are manually extracted to represent high-dimensional microstructures, which leads to information loss.

In this dissertation, a deep learning-guided microstructure prediction framework is established. It uses a conditional generative adversarial network (CGAN) …

An Analysis Of Camera Configurations And Depth Estimation Algorithms For Triple-Camera Computer Vision Systems, Jared Peter-Contesse

Master's Theses

The ability to accurately map and localize relevant objects surrounding a vehicle is an important task for autonomous vehicle systems. Currently, many of the environmental mapping approaches rely on the expensive LiDAR sensor. Researchers have been attempting to transition to cheaper sensors like the camera, but so far, the mapping accuracy of single-camera and dual-camera systems has not matched the accuracy of LiDAR systems. This thesis examines depth estimation algorithms and camera configurations of a triple-camera system to determine if sensor data from an additional perspective will improve the accuracy of camera-based systems. Using a synthetic dataset, the performance of …

Printed Circuit Board Design And Layout For Hobbyists, Engineers, And Students, Michael A. Derrenbacher

Master's Theses

Printed Circuit Boards (PCBs) are a ubiquitous element of virtually every electronic system manufactured world-wide. It is not a stretch of the imagination to say that if it’s electronic, there is a PCB in it. PCBs are necessary tools for electronics work, and tools need to have instructions. For better or worse, PCB knowledge is a deep and wide ocean. There is much to cover for even a surface level understanding, and there are deep areas rich in technical expertise. Navigating the ocean of knowledge is treacherous; common knowledge of yore can be downright dubious now. PCB manufacturing and electronics …

Adopting Accessibility Guidelines For Videogames To Collectible Card Games, Cooper Biancur

Electrical Engineering Master’s Theses

The development of accessible video games has been discussed through multiple publications in the 21st century; however, little to no attention has been given to non-electronic gaming. Like video games, Collectible Card Games (CCG) have also gained massive popularity, but no accessible guidelines have been created to help the disabled better play them. The need for inclusion in gaming is critical because it can act as a medium for social interaction and a learning tool for teaching. Today offers numerous technologies that can help those with disabilities, such as microcomputers, Artificial Intelligence (AI), Optical Character Recognition (OCR), and Text to …

Using The Inelastic Background In Hard X-Ray Photoelectron Spectroscopy For A Depth-Resolved Analysis Of The Cds / Cu(In,Ga)Se < Inf > 2 < / Inf > Interface, Dirk Hauschild, Ralph Steininger, Dimitrios Hariskos, Wolfram Witte, Sven Tougaard, Clemens Heske, Lothar Weinhardt

Chemistry and Biochemistry Faculty Research

The inelastic background of hard x-ray photoelectron spectroscopy data is analyzed to paint a depth-resolved picture of the CdS/Cu(In,Ga)Se2 (CdS/CIGSe) layer structure. The CdS/CIGSe interface is the central component in next-generation chalcopyrite thin-film photovoltaic devices. By analyzing both, the (unscattered) core-level peaks and the inelastic background, and by varying the excitation photon energy from 2.1 up to 14 keV, we can derive photoemission information over a broad range of electron kinetic energies and, hence, sampling depths. With this complementary information, the CdS film thickness of a CdS/CIGSe interface can be accurately determined as a function of the CdS deposition time. …

The Application Of Deep Learning Algorithms To Pediatric Vascular Anomalies Using A Limited Dataset, Briana I. Robertson

Honors Capstones

No abstract provided.

Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya

Electrical and Computer Engineering Faculty Publications

In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …

Genome Annotation Using Average Mutual Information, Garin P. Newcomb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Advancements in high-throughput DNA sequencing technologies and ambitious goals for their use are resulting in the generation of a deluge of unannotated sequenced genomes. This makes computational tools that can aid in annotation increasingly valuable.

Here, we provide a detailed exploration of the utility as well as the limitations of average mutual information (AMI) in several steps of genome annotation. For a genomic sequence, AMI is a measure of the information a base contains about the base separated by a fixed lag. A profile is constructed by calculating AMI at multiple lags. In addition to traditional AMI, we employ two …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr

Legacy Theses & Dissertations (2009 - 2024)

A key challenge for future wireless networks is to come upon a riveting compromise between spectral efficiency, complexity, and energy efficiency. The challenge is also intensified due to the pace at which the Internet-of-Things (IoT) technology is arriving, causing an upheaval to pre-existing network infrastructures in terms of elevating spectrum scarcity. To keep pace with the exploding data demand forecasts, a circumvention is required. One realization is by utilizing the high-band spectrum and the rich body of knowledge on multiple-input multiple-output (MIMO) technologies. One of the prominent high frequency technologies is visible light communications (VLC). VLC provide a large unregulated …

Multifunctional Programmable Self-Assembled Nanoparticles In Nanomedicine, Yoshie Sakamaki

Graduate Theses and Dissertations

Developing methodologies to control the architecture of nanoparticles (NPs) at the atomic level prevents their inhomogeneity and leads to a variety of expected functions. Rationally designed nanoparticles can either be programmed or crystallized structures into pre-determined structures achieving tunable particle pore size and physiochemistry. In this dissertation, two broad classes of multifunctional nanoparticles are developed, metal-organic frameworks and DNA-NP aggregates.

Metal-organic frameworks are a novel class of highly porous crystalline materials built from organic linkers and metal cluster-based secondary building units. However, applications in bioremediation have not been developed very well especially in applications regarding drug delivery systems (DDS). The …

Study Of Thick Indium Gallium Nitride Graded Structures For Future Solar Cell Applications, Manal Abdullah Aldawsari

Graduate Theses and Dissertations

Indium gallium nitride (InxGa1-xN) materials have held great potential for the optoelectronic industry due to their electrical and optical properties. The tunable band gap that can span the solar spectrum was one of the most significant features that attracted researchers’ attention. The band gap can be varied continuously from 0.77 eV for InN to 3.42 eV for GaN, covering the solar spectrum from near infrared to near ultraviolet. Additionally, it has a high absorption coefficient on the order of ∼105 cm−1, a direct band gap, high radiation resistance, thermal stability, and so on. Nevertheless, the epitaxial growth of high quality …

Automated Flight Controller Adaptive Compensation For Actuator Failures In Transport Type Aircraft, Daniel James Fresella

Graduate Theses and Dissertations

Aircraft operate over a wide range of conditions including atmospheric, weight, and center ofgravity changes. This presents a substantial challenge to automatic control system designers. When these operating conditions are merged with a partial or full control surface failure, automatic flight control is near impossible with conventional controllers. Additionally, when pilots experience control failure emergencies during flight, workload and fatigue increase drastically. The continued research of automatic flight control systems that can seamlessly adapt to unmodelled failures will enable a new generation of robust aircraft control. In this paper a 9th order 6 degree of freedom aircraft model is used …

Design, Extraction, And Optimization Tool Flows And Methodologies For Homogeneous And Heterogeneous Multi-Chip 2.5d Systems, Md Arafat Kabir

Graduate Theses and Dissertations

Chip and packaging industries are making significant progress in 2.5D design as a result of increasing popularity of their application. In advanced high-density 2.5D packages, package redistribution layers become similar to chip Back-End-of-Line routing layers, and the gap between them scales down with pin density improvement. Chiplet-package interactions become significant and severely affect system performance and reliability. Moreover, 2.5D integration offers opportunities to apply novel design techniques. The traditional die-by-die design approach neither carefully considers these interactions nor fully exploits the cross-boundary design opportunities.

This thesis presents chiplet-package cross-boundary design, extraction, analysis, and optimization tool flows and methodologies for high-density …

Acoustoelectric Amplification In Piezoelectric-Silicon Micromachined Lamb Wave Devices, Hakhamanesh Mansoorzare

Electronic Theses and Dissertations, 2020-2023

In this dissertation, heterostructured micro-acoustic devices are explored that leverage the interactions between acoustic phonons and electrons to enable radio frequency (RF) signal amplification or attenuation. Thin films of piezoelectric and semiconductor material are tailored into a heterostructure that allows for a strong acoustoelectric (AE) effect due to the combination of high electromechanical coupling and high electron drift velocity in said films respectively. In such devices, the relative electron drift and acoustic velocities could determine whether the RF signal undergoes AE gain or loss, rendering the device non-reciprocal. This is a highly sought-after property for building isolators and circulators which …

Integrating Degradation Forecasting And Abatement Framework Into Advanced Distribution Management System, Huu Phuong Hoang

All Dissertations

Future distribution grids are expected to face an increasing penetration of heterogeneous distributed energy resources (DERs) and electric vehicles (EVs). This landscape change will pose challenges to the control and management of distribution grids because of the variability of renewable energy resources and EV charging. In addition, multiple DERs dispersed over networks can also challenge the grid operation and maintenance as various DERs at various locations are needed to be monitored and managed. However, customers will not be content with reductions in power quality, reliability, economy, safety, or security. To enhance the effectiveness of grid control and management, future grids …

Chess Piece Detection, Craig Reid Belshe

Electrical Engineering

This project determines the positions of each piece on a physical chessboard, so that a computer can record a game of chess by noting down the piece positions at the end of each turn. It determines each move so that the game can be replayed later without watching actual footage. The project allows for easy viewing of past games. An image of the chessboard is analyzed to detect each square on the board, and each piece's location. This is then done for each turn, so that the system can keep track of an entire game.

Ac/Dc Led Light Bulb Adaptor With Internal Rechargeable Batteries, Esteban A. Rubio, Matthew R. Delaby

Electrical Engineering

To make a sustainable product and provide a temporary source of lights on during emergencies, this project aims to create a small unit that can be attached to a light bulb of any variety and connect it to a socket. Within the device is a rechargeable battery that, when the device is not connected to an 120V AC, 240V AC, or 48V DC power source, will power the light for a short period of time. The battery can be charged during the standard operation of the device and can be powered by the US and EU standard outlet voltages as …

Directional Spectral Solar Energy For Building Performance: From Simulation To Cyber-Physical Prototype, Joseph Del Rocco

Electronic Theses and Dissertations, 2020-2023

The original research and development in this dissertation contributes to the field of building performance by actively harnessing a wider spectrum of directional solar radiation for use in buildings. Solar radiation (energy) is often grouped by wavelength measurement into the spectra ultraviolet (UV), visible (light), and short and long-wave infrared (heat) on the electromagnetic spectrum. While some of this energy is directly absorbed or deflected by our atmosphere, most of it passes through, scatters about, and collides with our planet. Modern building performance simulations, tools, and control systems often oversimplify this energy into scalar values for light and heat, when …

Investigation Of Optical And Structural Properties Of Gesn Heterostructures, Oluwatobi Gabriel Olorunsola

Graduate Theses and Dissertations

Silicon (Si)-based optoelectronics have gained traction due to its primed versatility at developing light-based technologies. Si, however, features indirect bandgap characteristics and suffers relegated optical properties compared to its III-V counterparts. III-Vs have also been hybridized to Si platforms but the resulting technologies are expensive and incompatible with standard complementary-metal-oxide-semiconductor processes. Germanium (Ge), on the other hand, have been engineered to behave like direct bandgap material through tensile strain interventions but are well short of attaining extensive wavelength coverage. To create a competitive material that evades these challenges, transitional amounts of Sn can be incorporated into Ge matrix to form …

Design Of Miniaturized Antipodal Vivaldi Antennas And A Microwave Head Imaging System For The Detection Of Blood Clots In The Brain, Farhana Parveen

Electronic Theses and Dissertations, 2020-2023

Traditional brain imaging modalities, for example, MRI, CT scan, X-ray, etc. can provide precise and high-resolution images of the brain for diagnosing lesions, tumors or clots inside the brain. However, these modalities require bulky and expensive test setups accessible only at specialized diagnostic centers, and hence may not be suitable or affordable to many patients. Furthermore, the inherent health risks limit the usability of these modalities for frequent monitoring. Microwave imaging is deemed a promising alternative due to its being cost-effective, portable, non-ionizing, non-intrusive. Therefore, this work aims to design an effective microwave head imaging system for the detection of …

Study Of Mos2/High-K Interface And Implementation Of Mos2 Based Memristor For Neuromorphic Computing Applications, Durjoy Dev

Electronic Theses and Dissertations, 2020-2023

The scientific world is witnessing an unprecedented triumph of artificial neural network (ANN)- a computing system inspired by the biological neural network. With the enthralling quest for Internet of Everything (IoE), it is expected to have an unparalleled dominance of ANN in our day-to-day life. In recent times, memristor has come as an emerging candidate to realize ANN through emulating biological synapse and neuron behavior. Molybdenum disulfide (MoS2), one well-known two-dimensional (2D) transition metal dichalcogenides (TMDCs), has drawn interest for high speed, flexible, low power electronic devices since it has a tunable bandgap, reasonable carrier mobility, high Young's modulus, and …