Online Archive of University of Virginia Scholarship
Detection of Questionable Research Practices in Metaheuristic Optimization Literature Using LLM Based Algorithmic Similarity Analysis; The Evolution of Trust in Automotive Drive by Wire Systems: From Infiniti's 2014 Rejection to Lexus's 2023 Acceptance8 views
Author
Nguyen, Halbert, School of Engineering and Applied Science, University of Virginia
Advisors
Bolton, Matthew, EN-SIE, University of Virginia
Earle, Joshua, EN-Engineering and Society, University of Virginia
Abstract
This portfolio presents two undergraduate capstone projects completed in the
Department of Systems Engineering at the University of Virginia. The technical project
develops a computational tool to detect fraudulent and low quality papers in the field of
metaheuristic optimization, and the STS research paper examines how consumer trust in
automotive drive by wire steering evolved between 2014 and 2023. Although the two projects
sit in different domains, they share a common question: how do people come to trust
computational systems whose internal workings they cannot inspect, and what conditions
must be in place before such trust is granted?
Degree
BS (Bachelor of Science)
Keywords
car; automotive; Metaheuristic
Notes
School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Matthew Bolton
STS Advisor: Joshua Earle
Technical Team Members: Hayden Cook, Colin Heffern, Gunna Kamran, Halbert Nguyen
Language
English
Rights
All rights reserved by the author (no additional license for public reuse)
Nguyen, Halbert. Detection of Questionable Research Practices in Metaheuristic Optimization Literature Using LLM Based Algorithmic Similarity Analysis; The Evolution of Trust in Automotive Drive by Wire Systems: From Infiniti's 2014 Rejection to Lexus's 2023 Acceptance. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2026-05-05, https://doi.org/10.18130/nn10-7198.
