Barrett, The Honors College Thesis/Creative Project Collection
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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- Creators: Computer Science and Engineering Program
Description
Energy poverty is a pressing issue in agricultural areas that affects the livelihoods of millions of people worldwide. The lack of access to modern energy services in rural communities hinders the development of the agricultural sector and limits economic opportunities. To address this issue, this thesis aims to develop a predictive modeling framework using machine learning techniques to identify feasible interventions that can improve energy access in specific rural agricultural regions.
Machine learning plays a pivotal role in addressing energy poverty in rural agricultural regions. By leveraging the power of advanced data analytics and predictive modeling, machine learning algorithms can analyze vast datasets related to energy usage, agricultural practices, geographic factors, and socioeconomic conditions. These algorithms can uncover valuable insights and patterns that are not readily apparent through traditional analytical methods. Moreover, machine learning enables the development of predictive models that can forecast energy demand and identify optimal strategies for improving energy access in rural areas. These models can take into account various variables, such as crop cycles, weather conditions, and community needs, to recommend interventions that are tailored to the specific requirements of each region.
ContributorsKonatam, Saisumana (Author) / Osburn, Steven (Thesis director) / Kerner, Hanah (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-12
Description
MAT 117 is ASU’s remedial math course that introduces basic topics in algebra. Its students and instructors alike have suggested improvements in their Aleks-based instructional materials (consisting of short videos and text explanations). The latter note that the explanations provided by Aleks sometimes leave students with an incomplete or superficial understanding of the course’s concepts, especially those, like function composition or quadratics, that prove critical to subsequent math courses like Precalculus (MAT 170). We remedy those issues by creating instructional videos covering relevant material and soliciting student feedback on them.
ContributorsRen, Eric (Author) / Inozemtseva, Iuliia (Thesis director) / Rodic, Tamara (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2023-12
ContributorsMathews, Michael (Author) / Millman, Steven (Thesis director) / Xiao, Xusheng (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-12
ContributorsMathews, Michael (Author) / Millman, Steven (Thesis director) / Xiao, Xusheng (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-12
ContributorsMathews, Michael (Author) / Millman, Steven (Thesis director) / Xiao, Xusheng (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-12
Description
As a Creative Project, there are two goals: learn and leave documentation on a version control system called Git; develop a regression test suite through different testing strategies. Through researching various sources, a set of 62 test cases were developed to accurately verify that a program's logic is correct. As a result, a few defects were found in the source code and effectively notified to the developer.
ContributorsMathews, Michael (Author) / Millman, Steven (Thesis director) / Xiao, Xusheng (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-12
Description
This thesis provides an analysis of the potential issues of using ChatGPT, as despite its benefits it does have its concerns that may deter societal progress. The thesis first provides insight into how ChatGPT generates text and provides insight into how the process of generating its outputs can lead to a variety of issues in the output such as hallucinated and biased output. After explaining how these issues occur, the thesis focuses on the impact of these issues in important industries such as medicine, education, and security, comparing them to popular open-source models such as Llama and Falcon.
ContributorsTsai, Brandon (Author) / Martin, Thomas (Thesis director) / Shakarian, Paulo (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05
Description
Phishing is one of most common and effective attack vectors in modern cybercrime. Rather than targeting a technical vulnerability in a computer system, phishing attacks target human behavioral or emotional tendencies through manipulative emails, text messages, or phone calls. Through PyAntiPhish, I attempt to create my own version of an anti-phishing solution, through a series of experiments testing different machine learning classifiers and URL features. With an end-goal implementation as a Chromium browser extension utilizing Python-based machine learning classifiers (those available via the scikit-learn library), my project uses a combination of Python, TypeScript, Node.js, as well as AWS Lambda and API Gateway to act as a solution capable of blocking phishing attacks from the web browser.
ContributorsYang, Branden (Author) / Osburn, Steven (Thesis director) / Malpe, Adwith (Committee member) / Ahn, Gail-Joon (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05
Description
Victim advocacy is a free and confidential service provided to individuals who have experienced sexual violence. Due to the intense expectations associated with this role, victim advocates often suffer from mental health issues, including compassion fatigue. Compassion fatigue occurs when individuals in helping professions become overly exposed to clients’ traumatic experiences and suffer from debilitating symptoms that impact their daily lives. Through this project, I identified aspects of the role that put victim advocates at a high risk for developing compassion fatigue. I then explored methods for mitigating the negative effects of compassion fatigue including The Accelerated Recovery Program for compassion fatigue, humor as a coping technique, Eye Movement Desensitizing and Reprocessing therapy, comprehensive training efforts, personal and organizational self-care, and social support. With an emphasis on the benefits provided by social support, I developed a resource guide about the prevalence of violence in our community, aimed to help create more open dialogue surrounding sexual violence.
ContributorsSagarin, Rosa (Author) / Sturgess, Jessica (Thesis director) / Soares, Rebecca (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2024-05
ContributorsPalmer, Rock (Author) / Osburn, Steven (Thesis director) / Platt, Dane (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05