Matching Items (379)
Description
The rapid growth of published research has increased the time and energy researchers invest in
literature review to stay updated in their field. While existing research tools assist with organizing papers, providing basic summaries, and improving search, there is a need for an assistant that copilots researchers to drive innovation. In response, we introduce buff, a research assistant framework employing large language models to summarize papers, identify research gaps and trends, and recommend future directions based on semantic analysis of the literature landscape, Wikipedia, and the broader internet. We demo buff through a user-friendly chat interface, powered by a citation network encompassing over 5600 research papers, amounting to over 133 million tokens of textual information. buff utilizes a network structure to fetch and analyze factual scientific information semantically. By streamlining the literature review and scientific knowledge discovery process, buff empowers researchers to concentrate their efforts on pushing the boundaries of their fields, driving innovation, and optimizing the scientific research landscape.
ContributorsBalamurugan, Neha (Author) / Arani, Punit (Co-author) / LiKamWa, Robert (Thesis director) / Bhattacharjee, Amrita (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / Economics Program in CLAS (Contributor)
Created2024-05
DescriptionThis project tracks the history of fiscal stimulus in the United States as it relates to defense and economic projects. This is done in order to place the Biden administration's fiscal agenda into a historical context of fiscal spending.
ContributorsMiller, Jordan (Author) / Calhoun, Craig (Thesis director) / Kirkpatrick, Jennet (Committee member) / Fong, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / Economics Program in CLAS (Contributor)
Created2024-05
Description
For decades, society has held an innate fascination with serial murder and serial killers. The fascination lies in the motivations behind the actions and the way in which investigators apprehend them. The psychological field of investigative and behavioral psychology emerged to attempt to answer some of these questions and the investigative tool of behavioral profiling soon followed. Researchers have conducted comparison studies of male and female serial killers many times to understand what differentiates them. This research aims to answer another question: Are female serial killers more homogenous based on their profiles than male serial killers? The media portrays female serial killers in a very specific light, poisoners who kill due to revenge or money, but how well does this portrayal actually hold up when analytically examined? This research compiled case studies of fifteen male and fifteen female serial killers based on twenty-six characteristics and profiled each according to three different typologies to determine how homogenous these groups actually are. This research can help assist investigators and the public to better understand the diversity of these types of offenders and be able to determine who these offenders are.
ContributorsRotenberg, Taylor (Author) / Guyll, Max (Thesis director) / Madon, Stephanie (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor)
Created2024-05
Description
Milk has long played an important role in American society and remains a popular staple of many Americans’ diets. Yet, despite its long standing popularity, the role of milk within American society has begun to develop new meaning in recent years. This paper aims to understand the symbolism that today’s Americans ascribe to milk. Academic journal articles, advertising campaigns, online articles, and government policy pertaining to milk were researched in order to identify the themes that characterize consumers’ perceptions of milk. In recognition of the diverse types of milk that are now accessible to many Americans, this paper uses the word “milk” to refer to cow-derived, fluid (liquid) dairy unless otherwise specified. This research reveals eleven principal themes that describe consumers’ perceptions of milk: milk symbolizes health, American values, is associated with athleticism, is unhealthy, is not preferable to plant-based alternatives, is bad for the environment, is animal cruelty, represents white supremacy, is anti-feminist, is reflective of consumer lifestyles, and there is a general trend of consumers being uninformed about the milk that they consume. This research helps to understand consumers; therefore, this research can be used to help dairy-related industries shape their business strategies and target their customer segment and to help policymakers design effective dairy-related policies. Furthermore, this paper invites further research to identify the consumers that hold the beliefs this research describes, and the extent to which these consumers share said beliefs.
ContributorsHladik, Jessica (Author) / Hughner, Renee (Thesis director) / Voorhees, Matthew (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Economics Program in CLAS (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of International Letters and Cultures (Contributor)
Created2024-05
Description
This study presents a comparative analysis of machine learning models on their ability to determine match outcomes in the English Premier League (EPL), focusing on optimizing prediction accuracy. The research leverages a variety of models, including logistic regression, decision trees, random forests, gradient boosting machines, support vector machines, k-nearest neighbors, and extreme gradient boosting, to predict the outcomes of soccer matches in the EPL. Utilizing a comprehensive dataset from Kaggle, the study uses the Sport Result Prediction CRISP-DM framework for data preparation and model evaluation, comparing the accuracy, precision, recall, F1-score, ROC-AUC score, and confusion matrices of each model used in the study. The findings reveal that ensemble methods, notably Random Forest and Extreme Gradient Boosting, outperform other models in accuracy, highlighting their potential in sports analytics. This research contributes to the field of sports analytics by demonstrating the effectiveness of machine learning in sports outcome prediction, while also identifying the challenges and complexities inherent in predicting the outcomes of EPL matches. This research not only highlights the significance of ensemble learning techniques in handling sports data complexities but also opens avenues for future exploration into advanced machine learning and deep learning approaches for enhancing predictive accuracy in sports analytics.
ContributorsTashildar, Ninad (Author) / Osburn, Steven (Thesis director) / Simari, Gerardo (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05
Description
This duo thesis is an autoethnography of what it means to be Filipino-American in the United States. Being raised in varying backgrounds yet with the similarity of being Filipino, there are aspects of our lives that are simultaneously similar and different. The goal of this project is the exploration of one’s cultural, familial and personal identities and how they intersect with their individuality and sense of belonging. Through this project, we documented our experience as Filipinos in the United States and our travel back to the Philippines and showcased it through videos. It is a means to document our reflections on this project to share with the Filipino community and individuals who share the same sentiments.
ContributorsTamayo, Rianne Daisy (Author) / Onayan, Youla Tricia (Co-author) / O'Flaherty, Katherine (Thesis director) / Fedock, Rachel (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2024-05
Description
This duo thesis is an autoethnography of what it means to be Filipino-American in the United States. Being raised in varying backgrounds yet with the similarity of being Filipino, there are aspects of our lives that are simultaneously similar and different. The goal of this project is the exploration of one’s cultural, familial and personal identities and how they intersect with their individuality and sense of belonging. Through this project, we documented our experience as Filipinos in the United States and our travel back to the Philippines and showcased it through videos. It is a means to document our reflections on this project to share with the Filipino community and individuals who share the same sentiments.
ContributorsOnayan, Youla Tricia (Author) / Tamayo, Rianne Daisy (Co-author) / O'Flaherty, Katherine (Thesis director) / Fedock, Rachel (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2024-05
Description
Anelloviruses are small, negative-sense, single-stranded DNA viruses that have are found to be present in over 90% of adult humans. Despite being highly prevalent, little is known about the biology or pathogenic potentials of the anelloviruses. Initially, the family Anelloviridae, contained 14 genera. However, in the last few years, there have been an abundant number of diverse anelloviruses that were identified in various organisms. Thus, a new criterion for anelloviruses classification was necessary to establish new genera and species to accommodate unclassified anelloviruses. As part of an ongoing effort to characterize the human virome of female genital tract (FGT), we performed virome metagenomic sequencing of Peruvian women living with HIV, and we have identified 7 novel anellovirus genome sequences found in cervicovaginal clinical specimens. Through phylogenetic and sequence analyses of the new characterization criteria, we classified the genome sequences as three novel anellovirus genera, provisionally named, Petorquevirus, Sadetorquevirus, and Quoptorquevirus.
ContributorsDo, Eric (Author) / Lim, Efrem (Thesis director) / Kaelin, Emily (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor)
Created2024-05
Description
This paper details the process of implementing a schedule change for the Orbit Saturn, a neighborhood circulator bus in Tempe with poor on-time performance. It describes the methods used to estimate the true runtimes for the Saturn between timepoints, and measures the effectiveness of a schedule change that allows operators more time to traverse between timepoints. Changes were implemented on October 23, 2023, upon which there was a statistically significant decrease in average deviation from schedule, as well as a significant increase in the proportion of trips classified as “on-time” by Valley Metro. Increased on-time performance does not appear to be due to outside factors, such as seasonal changes in traffic.
ContributorsMalzewski, Trevor (Author) / Kuby, Michael (Thesis director) / Tong, Daoqin (Committee member) / Stevenson, Sam (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor)
Created2024-05