Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Description
The NASA Psyche Iron Meteorite Imaging System (IMIS) is a standalone system created to image metal meteorites from ASU’s Center for Meteorite Studies’ collection that have an etched surface. Meteorite scientists have difficulty obtaining true-to-life images of meteorites through traditional photography methods due to the meteorites’ shiny, irregular surfaces, which

The NASA Psyche Iron Meteorite Imaging System (IMIS) is a standalone system created to image metal meteorites from ASU’s Center for Meteorite Studies’ collection that have an etched surface. Meteorite scientists have difficulty obtaining true-to-life images of meteorites through traditional photography methods due to the meteorites’ shiny, irregular surfaces, which interferes with their ability to identify meteorites’ component materials through image analysis. Using the IMIS, scientists can easily and consistently obtain glare-free photographs of meteorite surface that are suitable for future use in an artificial intelligence-based meteorite component analysis system. The IMIS integrates a lighting system, a mounted camera, a sample positioning area, a meteorite leveling/positioning system, and a touch screen control panel featuring an interface that allows the user to see a preview of the image to be taken as well as an edge detection view, a glare detection view, a button that allows the user to remotely take the picture, and feedback if very high levels of glare are detected that may indicate a camera or positioning error. Initial research and design work were completed by the end of Fall semester, and Spring semester consisted of building and testing the system. The current system is fully functional, and photos taken by the current system have been approved by a meteorite expert and an AI expert. The funding for this project was tentatively capped at $1000 for miscellaneous expenses, not including a camera to be supplied by the School of Earth and Space Exploration. When SESE was unable to provide a camera, an additional $4000 were allotted for camera expenses. So far, $1935 of the total $5000 budget has been spent on the project, putting the project $3065 under budget. While this system is a functional prototype, future capstone projects may involve the help of industrial designers to improve the technician’s experience through automating the sample positioning process.
ContributorsBaerwaldt, Morgan Kathleen (Author) / Bowman, Cassie (Thesis director) / Kozicki, Michael (Committee member) / School of Art (Contributor) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Power spectral analysis is a fundamental aspect of signal processing used in the detection and \\estimation of various signal features. Signals spaced closely in frequency are problematic and lead analysts to miss crucial details surrounding the data. The Capon and Bartlett methods are non-parametric filterbank approaches to power spectrum estimation.

Power spectral analysis is a fundamental aspect of signal processing used in the detection and \\estimation of various signal features. Signals spaced closely in frequency are problematic and lead analysts to miss crucial details surrounding the data. The Capon and Bartlett methods are non-parametric filterbank approaches to power spectrum estimation. The Capon algorithm is known as the "adaptive" approach to power spectrum estimation because its filter impulse responses are adapted to fit the characteristics of the data. The Bartlett method is known as the "conventional" approach to power spectrum estimation (PSE) and has a fixed deterministic filter. Both techniques rely on the Sample Covariance Matrix (SCM). The first objective of this project is to analyze the origins and characteristics of the Capon and Bartlett methods to understand their abilities to resolve signals closely spaced in frequency. Taking into consideration the Capon and Bartlett's reliance on the SCM, there is a novelty in combining these two algorithms using their cross-coherence. The second objective of this project is to analyze the performance of the Capon-Bartlett Cross Spectra. This study will involve Matlab simulations of known test cases and comparisons with approximate theoretical predictions.
ContributorsYoshiyama, Cassidy (Author) / Richmond, Christ (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
The objective of this paper is to find and describe trends in the fast Fourier transformed accelerometer data that can be used to predict the mechanical failure of large vacuum pumps used in industrial settings, such as providing drinking water. Using three-dimensional plots of the data, this paper suggests how

The objective of this paper is to find and describe trends in the fast Fourier transformed accelerometer data that can be used to predict the mechanical failure of large vacuum pumps used in industrial settings, such as providing drinking water. Using three-dimensional plots of the data, this paper suggests how a model can be developed to predict the mechanical failure of vacuum pumps.
ContributorsHalver, Grant (Author) / Taylor, Tom (Thesis director) / Konstantinos, Tsakalis (Committee member) / Fricks, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the

This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the Terahertz Imaging system. The GUI was developed in response to a need for synchronization, ease of operation, easy parameter modification, and data management. Along the way, many design decisions were made ranging from choosing a software platform to determining how variables should be passed. These decisions and considerations are discussed in this document. The resulting GUI has measured up to the design criteria and will be able to be used by anyone wishing to use the Terahertz Imaging System for further research in the field of Around the Corner or NLoS Imaging.
ContributorsWood, Jacob Cannon (Author) / Trichopoulos, Georgios (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Analog to Digital Converters (ADCs) are a critical component in modern circuit applications. ADCs are used in virtually every application in which a digital circuit is interacting with data from the real world, ranging from commercial applications to crucial military and aerospace applications, and are especially important when interacting with

Analog to Digital Converters (ADCs) are a critical component in modern circuit applications. ADCs are used in virtually every application in which a digital circuit is interacting with data from the real world, ranging from commercial applications to crucial military and aerospace applications, and are especially important when interacting with sensors that observe environmental factors. Due to the critical nature of these converters, as well as the vast range of environments in which they are used, it is important that they accurately sample data regardless of environmental factors. These environmental factors range from input noise and power supply variations to temperature and radiation, and it is important to know how each may affect the accuracy of the resulting data when designing circuits that depend upon the data from these ADCs. These environmental factors are considered hostile environments, as they each generally have a negative effect on the operation of an ADC. This thesis seeks to investigate the effects of several of these hostile environmental variables on the performance of analog to digital converters. Three different analog to digital converters with similar specifications were selected and analyzed under common hostile environments. Data was collected on multiple copies of an ADC and averaged together to analyze the results using multiple characteristics of converter performance. Performance metrics were obtained across a range of frequencies, input noise, input signal offsets, power supply voltages, and temperatures. The obtained results showed a clear decrease in performance farther from a room temperature environment, but the results for several other environmental variables showed either no significant correlation or resulted in inconclusive data.
ContributorsSwanson, Taylor Catherine (Co-author) / Millman, Hershel (Co-author) / Barnaby, Hugh (Thesis director) / Garrity, Douglas (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05