Electrical and Computer Engineering Commons^™

Robotic Arm Extrusion End Effector, Nicholas Viamin, David Blouin, Savannah Hunt, Nico Figueroa

Interdisciplinary Design Senior Theses

This senior design project aims to enhance the capabilities of the Rotrics AIO Desktop Arm (Dexarm) by designing and implementing an extrusion device capable of smooth and consistent extrusion for 3D printing applications. The project focused on ensuring safety, affordability, and ease-of-use for users, while achieving precise control over the extrusion process. Various mechanical and electrical components were carefully selected to ensure compatibility with the Dexarm and to provide optimal performance. To maintain safety, extensive testing and risk assessments were conducted to minimize any potential hazards associated with the extrusion process. To achieve smooth and consistent extrusion, precise control mechanisms …

Neurogen: Eeg And Near-Infrared Light Stimulation Control System, Arnold Nieto, Jaylinn Solis, Matthew Tamanaha

Interdisciplinary Design Senior Theses

Light stimulation or transcranial photobiomodulation (tPBM) therapy has been shown to be effective when treating patients suffering neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. While there is currently no cure, light stimulation can help alleviate symptoms for those patient’s suffering from these diseases. With this in mind, the senior design team from last year began a prototype hybrid electroencephalography (EEG) and tPBM device. They implemented a specific wavelength of 810 nanometer (nm) near-infrared (NIR) light emitting diodes (LEDs), with a 16 channel EEG headset from OpenBCI. The device was intended to serve as a potential research tool, with a …

Deep Learning For Power Flow Estimation And High Impedance Fault Detection, Kun Yang

Electronic Theses and Dissertations

My thesis is divided into two parts.

The first part is: “Optimal Power Flow Estimation Using One-Dimensional Convolutional Neural Network [1]“. Optimal power flow (OPF) is an important research topic in power system operation and control decisions. Traditional OPF problems are solved through dynamic optimization with nonlinear programming techniques. For a large power system with large amounts of variables and constraints, the solving process would take a long time. This paper presents a new method to quickly estimate the OPF results using a one-dimensional convolutional neural network (1D-CNN). The OPF problem is treated as a high-dimensional mapping between the load …

Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi

Electronic Theses and Dissertations

Smart and intelligent devices are being integrated more and more into day-to-day life to perform a multitude of tasks. These tasks include, but are not limited to, job automation, smart utility management, etc., with the aim to improve quality of life and to make normal day-to-day chores as effortless as possible. These smart devices may or may not be connected to the internet to accomplish tasks. Additionally, human-machine interaction with such devices may be touch-screen based or based on voice commands. To understand and act upon received voice commands, these devices require to enhance and distinguish the (clean) speech signal …

Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning, Wei Gao

Electronic Theses and Dissertations

This dissertation investigates the feasibility and effectiveness of using Reinforcement Learning (RL) techniques for power system dynamic control, particularly voltage and frequency control. The conventional control strategies used in power systems are complex and time-consuming due to the complicated high-order nonlinearities of the system. RL, which is a type of neural network-based technique, has shown promise in solving these complex problems by fitting any nonlinear system with the proper network structure.

The proposed RL algorithm, called Guided Surrogate Gradient-based Evolution Strategy (GSES) determines the weights of the policy (which generates the action for our control reference signal) without back-propagation process …

Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi

Electronic Theses and Dissertations

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …

Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner

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Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, …

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

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In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

Investigating The Application And Sustained Effects Of Stochastic Resonance On Haptic Feedback Sensitivity In A Laparoscopic Task, Kara Liane Wilcox

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Stochastic resonance (SR) is a phenomenon that can enhance the detection or transmission of weak signals by adding random noise to a non-linear system. SR introduced into the human motor control system as a subthreshold mechanical vibration has shown promise to improve sensitivity to haptic feedback. SR can be valuable in a laparoscopic surgery application, where haptic feedback is critical. This research sought to find if applying SR to the human motor control system improves performance in a laparoscopic probing task, if the performance differs based on the location of stochastic resonance application, and if there are sustained effects from …

Optimal Management And Sizing For Battery Energy Storage Systems For Grid Applications, Abdullah Muslih Alharbi

Electronic Theses and Dissertations

Battery energy storage systems (BESSs) play a dominant role in the reliability, resiliency, economics, and operational flexibility of the power grid. As such, the BESS is a promising and reliable green technology for supporting power grid facilities. However, the integration of BESS technology into power projects can be expensive and challenging, both technologically and in terms of regulation compliance. Thus, it is necessary to examine best practices for fully optimizing BESS sizing, operation, and scheduling in the context of benefiting BESS operators and investors by fully exploiting the valuable economic and technical benefits of BESSs. In this research, we identify …

Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando

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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …

Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball

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A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated …

Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green

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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …

Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung

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Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …

Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal

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Since their invention in 1958, Integrated Circuits (ICs) have become increasingly more complex, sophisticated, and useful. As a result, they have worked their way into every aspect of our lives, for example: personal electronic devices, wearable electronics, biomedical sensors, autonomous driving cars, military and defense applications, and artificial intelligence, to name some areas of applications. These examples represent both collectively, and sometimes individually, multi-trillion-dollar markets. However, further development of ICs has been predicted to encounter a performance bottleneck as the mainstream silicon industry, approaches its physical limits. The state-of-the-art of today’s ICs technology will be soon below 3nm. At such …

Behavior, Switching Losses, And Efficiency Enhancement Potentials Of 1200 V Sic Power Devices For Hard-Switched Power Converters, Ali Mahmoud Salman Al-Bayati, Mohammad Abdul Matin

Electrical and Computer Engineering: Faculty Scholarship

Semiconductor power devices are the major constituents of any power conversion system. These systems are faced by many circumscriptions due to the operating constraints of silicon (Si) based semiconductors under certain conditions. The emergence and persistence evolution of wide bandgap technology pledge to transcend the restrictions imposed by Si based semiconductors. This paper presents a thorough experimental study and assessment of the performance of three power devices: 1200 V SiC cascode, 1200 V SiC MOSFET, and 1200 V Si IGBT under the same hardware setup. The study aims to capture the major attributes for each power device toward determining their …

A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong

Interdisciplinary Design Senior Theses

The project objective is to create a low-cost, long-range, and solar-based IoT soil quality monitoring system. The system must transmit packages of data gathered from separate nodes, consisting of two dierent types of sensors, to a centralized gateway receiver to be displayed to the user in an elegant and readable manner. The end goal of the project is to supplement produce grown by large agricultural bodies around the United States without the misuse of water resources. This report presents the need for this system, details the components of the system, and the rationale behind design choices. It serves as a …

Neurogen: Eeg And Near-Infrared Light Stimulation Control System, Karina Sanchez, Sruthi Sakthivel, Michael Bose, Evan Jennings

Interdisciplinary Design Senior Theses

Neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease are widespread, affecting millions of people worldwide. These diseases occur when neurons in the brain or peripheral nervous system progressively lose function and deteriorate. Current pharmacological treatments manage some of the neurological symptoms, but there is no cure yet. Interventions that mitigate or restore loss of function can fill the void until that goal is met. Light stimulation, or transcranial photobiomodulation (tPBM) therapy, can help treat people with neurodegenerative diseases, as it has been shown to improve sleep, attention, memory, and cognitive function.

The objective of this project is to develop …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Data-Enabled Distribution Grid Management, Zohreh Sadat Hosseini

Electronic Theses and Dissertations

In 2020, U.S. electric utilities installed more than 94 million advanced meters, which brought the percentage of residential customers equipped with smart meters to 75%. This significant investment allows collecting extensive customer data at the distribution level, however, the data are not currently leveraged effectively to help with system operations. This dissertation aims to use the smart meters’ data to improve the grid’s reliability, stability, and controllability by solving two of the most challenging problems at the distribution level, namely distribution network phase identification and outage identification.

Distribution networks have typically been the least observable and most dynamic and locally …

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu

Electronic Theses and Dissertations

Efficiently computing an (approximate) orthonormal basis and low-rank approximation for the input data X plays a crucial role in data analysis. One of the most efficient algorithms for such tasks is the randomized algorithm, which proceeds by computing a projection XA with a random projection matrix A of much smaller size, and then computing the orthonormal basis as well as low-rank factorizations of the tall matrix XA. While a random matrix A is the de facto choice, in this work, we improve upon its performance by utilizing a learning approach to find an adaptive projection matrix A from a set …

Crossroad - Avoid Crowd Intelligence, Xukun Zhang, Yuzheng Wu, Haochen Zhang

Interdisciplinary Design Senior Theses

Nowadays, waiting takes big chunks of daily-life activity. People may always find themselves facing long queues, waiting in a crowded facility, even when they have tried to avoid peak hours. Heading to a highly populated public area may have felt like heading to a battlefield. Without access to the real-time information of the facility, people start to discover that waiting starts to become an unpredictable event that can sometimes delay their schedule or even worse. This project serves as a solution to tackle this lack of transparency. Crossroad aims to combine facilities’ cameras with micro-controller to see the engagement of …

Jamming Attack Workaround Study, Soren Madsen, Jack Schoen

Interdisciplinary Design Senior Theses

The Internet of Things (IoT) is a fast growing industry with strong footholds in the smart home market featuring devices such as the Amazon Echo, Ring security cameras, smart TVs, and much more. However, it doesn’t stop there; the industrial sector has begun using smart devices for measurement, automated tasks, and time sensitive communication. Many of these devices have become reliant on WiFi technology and are vulnerable to attacks on the security of the protocols involved.

In this paper, we discuss the details of the deauthentication attack on WPA and WPA2 systems and propose a solution for detection and recovery …

Mobile Nanogrid, Daniel Mendoza, Ben Mahony, Charles Ju, Michael Batshon

Interdisciplinary Design Senior Theses

The mobile nanogrid is a standalone mobile power solution which uses a combination of automatic and manual tracking mechanisms to maintain a solar panel's perpendicularity to the sun over the course of the day in order to maximize energy generation. The power can then be consumed by a user or stored. It is designed to be placed on the roof of a vehicle for the recreational camping market to meet the need for mobile power generation. A scaled-down functional prototype was designed in SolidWorks, modeled in MATLAB Simulink, fabricated in the machine shop using a combination of off-the-shelf and custom …

Distributed Control, Optimization, And State Estimation For Renewable Power System, Qiao Li

Electronic Theses and Dissertations

The traditional power systems are usually centralized systems, in which the control, operation and monitoring are performed by the centralized control center, e.g., SCADA. However, with the development of renewable energy, power systems are getting more and more distributed. So, it becomes necessary to establish the distributed power system operation methods for these power systems. In this research, the distributed techniques for the renewable power systems are proposed based on the consensus protocol technique from graph theory. These techniques cover the three important problems in power systems, i.e., economic dispatch, state estimation, and optimal power flow. First, the Distributed Economic …

Design, Manufacture, And Test Of A Hybrid Aerial-Ground Robotic Platform, William Garrett Willmon

Electronic Theses and Dissertations

A hybrid aerial-ground robotic platform allows for enhanced functionality combining most of the operational profiles of an aerial and ground vehicle with applications to intelligence, surveillance, reconnaissance (ISR), infrastructure inspection, emergency response, photography, etc. Motivated by this challenge, we designed, developed, and tested a prototype hybrid aerial-ground robotic vehicle capable of guidance, navigation, and control in the air and on the ground. The thesis focus is on the system design. As such, at first, we designed and analyzed the mechanical component to ensure durability. We then designed the electrical component to reduce overall weight and maximize battery life. We developed …

Mechanisms Of Sensory Adaptation In The Primate Visual System, Boris Isaac Peñaloza Rojas

Electronic Theses and Dissertations

Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms …

Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani

Electronic Theses and Dissertations

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold:

First, a Convolutional Neural Network (CNN)-based method for …

Optimal Sizing And Operation Of A Pumped Thermal Energy Storage System, Matthew Perez

Electronic Theses and Dissertations

Current trends in the modern grid are leading to the integration of energy storage technologies (ESSs), such as pumped thermal energy storage to help incorporate more variable renewable energy sources into the grid. This paper analyzes the operation of a pumped thermal energy storage (PTES) system under the grid services of energy arbitrage, regulation services, spinning and non-spinning reserve, resource adequacy, and a combination of them all. Each revenue stream is setup into an optimization problem and solved to find which revenue generating technique would generate the most revenue. The combined revenue stream was found to produce the most revenue …