Barrett

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.

Displaying 1 - 3 of 3

Implementation of Machine Learning on Low Power Microcontrollers

Description
Machine learning has been increasingly integrated into several new areas, namely those related to vision processing and language learning models. These implementations of these processes in new products have demanded increasingly more expensive memory usage and computational requirements. Microcontrollers can lower this increasing cost. However, implementation of such a system…

Machine learning has been increasingly integrated into several new areas, namely those related to vision processing and language learning models. These implementations of these processes in new products have demanded increasingly more expensive memory usage and computational requirements. Microcontrollers can lower this increasing cost. However, implementation of such a system on a microcontroller is difficult and has to be culled appropriately in order to find the right balance between optimization of the system and allocation of resources present in the system. A proof of concept that these algorithms can be implemented on such as system will be attempted in order to find points of contention of the construction of such a system on such limited hardware, as well as the steps taken to enable the usage of machine learning onto a limited system such as the general purpose MSP430 from Texas Instruments.
ContributorsMalcolm, Ian (Author) / Allee, David (Thesis director) / Spanias, Andreas (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2024-05

Electricity & the Arts: Creative Thesis Projects

Description
Engineering, and more specifically, electrical engineering can be a difficult topic to explain through spoken communication. Along with taking years of education to learn and understand necessary topics, the field is riddled with jargon and items that may take lectures to explain. However, this type of education may not be…

Engineering, and more specifically, electrical engineering can be a difficult topic to explain through spoken communication. Along with taking years of education to learn and understand necessary topics, the field is riddled with jargon and items that may take lectures to explain. However, this type of education may not be feasible for a younger or inexperienced audience. Therefore, engineers must find new ways to explain such difficult topics, especially in an attempt to garner interest in children, for example, through art.
ContributorsHedges, Madison (Author) / Aukes, Daniel (Thesis director) / Weeks, Eric (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor) / School of Earth and Space Exploration (Contributor)
Created2023-12

Using Microwaves to Detect Various Substances in a Sample of Water

Description
This research explores the potential use of microwave energy to detect various substances in water, with a focus on water quality assessment and pathogen detection applications. There are many non-thermal effects of microwaves on microorganisms and their resonant frequencies could be used to identify and possibly destroy harmful pathogens, such…

This research explores the potential use of microwave energy to detect various substances in water, with a focus on water quality assessment and pathogen detection applications. There are many non-thermal effects of microwaves on microorganisms and their resonant frequencies could be used to identify and possibly destroy harmful pathogens, such as bacteria and viruses, without heating the water. A wide range of materials, including living organisms like Daphnia and Moina, plants, sand, plastic, and salt, were subjected to microwave measurements to assess their influence on the transmission (S21) measurements. The measurements of the living organisms did not display distinctive resonant frequencies and variations in water volume may be the source of the small measurement differences. Conversely, sand and plastic pellets affected the measurements differently, with their arrangement within the test tube emerging as a significant factor. This study also explores the impact of salinity on measurements, revealing a clear pattern that can be modeled as a series RLC resonator. Although unique resonant frequencies for the tested organisms were not identified, the presented system demonstrates the potential for detecting contaminants based on variations in measurements. Future research may extend this work to include a broader array of organisms and enhance measurement precision.
ContributorsChild, Carson (Author) / Aberle, James (Thesis director) / Blain Christen, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2023-12