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: Meuth, Ryan
Description
Today's prison industrial complex in the United States often dehumanizes inmates simply because they are criminals. Members of the free society are generally too far removed from the inside of prisons that most people do not see the harsh and cruel conditions for and treatment of prisoners. As a Dance and Justice Studies major at Arizona State University, I was curious about how to intertwine my interests in dance and justice. This paper chronicles my exploration of adding a human rights issue to my dance practice through choreographing a solo dance performance based on Cleve Foster's unusual experience on death row. Research on theories of prison and punishment in American society combined with physical research in the dance studio enabled me to create a solo performance that shed light on the inhumane conditions for and treatment of prison inmates in today's society. Through the process, I found that some elements of my dance practice stayed the same, while others changed. This informed me of what continuously remains important to me, while allowing me to expand my personal dance practice. I ultimately discovered a bridge between my two passions, dance and justice, and learned a meaningful way to convey a contemporary social justice issue to the general public.
ContributorsKerr, Elena Marie (Author) / Schupp, Karen (Thesis director) / Vissicaro, Pegge (Committee member) / Barrett, The Honors College (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of Social Transformation (Contributor) / School of Film, Dance and Theatre (Contributor)
Created2015-05
Description
As smart home devices become more common in households across the globe, it is<br/>surprising that companies who specialize in IoT devices have not exploited the world of swimming<br/>pools. As a pool owner and avid IoT user, it has become increasingly obvious to me that such<br/>devices are necessary. Thus, I have developed an embedded system – connected to a web-based<br/>reporting system – that accurately reports common chemical levels of a swimming pool. In<br/>addition, this system includes an autofill function with information about the amount of water<br/>dispensed. This system gives pool owners access to an all-in-one device that can be used on any<br/>pool, new or old. Future implementations include a personalized application to display the pool<br/>levels and user-defined suggestions when certain levels become too high or low.
ContributorsSveom, Jeremy Dale (Author) / Meuth, Ryan (Thesis director) / Vrudhula, Sarma (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This paper examines creative process and performance as a method of research for understanding self-in-context through the lens of my own artistic research for “Dress in Something Plain and Dark,” a project exploring my relationship as a woman to Mennonite religious and cultural identity, spirituality, and dance. Situating my artistic work in relationship to the fields of creative autoethnography, queer and transborder performance art, and somatic dance practice, I discuss the distinctions and commonalities of approach, methods, and practice of artists working in these fields, and the shared challenges of marginalization, translation, and contextualization. In response to these challenges, and the inadequacy of linear, Western, individualistic and mechanistic frameworks to address them, I draw from the ethnographic work of de la Garza, (formerly González, 2000) to seek a “creation-centered” ontological framework that the artist-researcher-performer may use to understand and contextualize their work. I offer the tree as an ontology to understand the organic, emergent nature of creative process, the stages of growth and seasonal cycles, and the structural parts that make up the creative and performative processes, and illustrate this model through a discussion of the growth of “Dress in Something Plain and Dark,” as it has emerged over two cyclical “seasons” of maturation.
Note: This work of creative scholarship is rooted in collaboration between three female artist-scholars: Carly Bates, Raji Ganesan, and Allyson Yoder. Working from a common intersectional, feminist framework, we served as artistic co-directors of each other’s solo pieces and co-producers of Negotiations, in which we share these pieces alongside each other. Negotiations is not a showcase of three individual works, but a conversation among three voices. As collaborators, we have been uncompromising in the pursuit of our own unique inquiries and voices and each of our works of creative scholarship stand alone. However, we believe that all of the parts are best understood in relationship to each other and to the whole. For this reason, we have chosen to cross-reference our thesis documents here, and we encourage readers to view the performance of Negotiations in its entirety.
Thesis documents cross-referenced:
French Vanilla: An Exploration of Biracial Identity Through Narrative Performance, by Carly Bates
Bhairavi: A Performance-Investigation of Belonging and Dis-Belonging in Diaspora Communities, by Raji Ganesan
Deep roots, shared fruits: Emergent creative process and the ecology of solo performance through “Dress in Something Plain and Dark,” by Allyson Yoder
Note: This work of creative scholarship is rooted in collaboration between three female artist-scholars: Carly Bates, Raji Ganesan, and Allyson Yoder. Working from a common intersectional, feminist framework, we served as artistic co-directors of each other’s solo pieces and co-producers of Negotiations, in which we share these pieces alongside each other. Negotiations is not a showcase of three individual works, but a conversation among three voices. As collaborators, we have been uncompromising in the pursuit of our own unique inquiries and voices and each of our works of creative scholarship stand alone. However, we believe that all of the parts are best understood in relationship to each other and to the whole. For this reason, we have chosen to cross-reference our thesis documents here, and we encourage readers to view the performance of Negotiations in its entirety.
Thesis documents cross-referenced:
French Vanilla: An Exploration of Biracial Identity Through Narrative Performance, by Carly Bates
Bhairavi: A Performance-Investigation of Belonging and Dis-Belonging in Diaspora Communities, by Raji Ganesan
Deep roots, shared fruits: Emergent creative process and the ecology of solo performance through “Dress in Something Plain and Dark,” by Allyson Yoder
ContributorsYoder, Allyson Joy (Author) / de la Garza, Sarah Amira (Thesis director) / Ellsworth, Angela (Committee member) / DeWitt, Inertia Q. E. D. (Committee member) / School of Film, Dance and Theatre (Contributor) / Herberger Institute for Design and the Arts (Contributor) / Barrett, The Honors College (Contributor) / Hugh Downs School of Human Communication (Contributor)
Created2016-05
Description
The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and FLAC. Finally, the project is also to be driven by a mobile app running on a smartphone or tablet. To achieve this, a client server design was employed where the Raspberry Pi acts as the server and the mobile app is the client. The server functionality was achieved using a Python script that listens on a socket and calls various executables that handle the different formats of music being played. The client functionality was achieved by programming an Android app in Java that sends encoded commands to the server, which the server decodes and begins playing the music that command dictates. The designs for both the client and server are easily extensible and allow for any future modifications to the project to be easily made.
ContributorsStorto, Michael Olson (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Video games often feature agents that the human player interacts with to overcome.
Designing these agents to cover every case of human interaction is difficult, and usually
imperfect, as human players are capable of learning to overcome these agents in unintended
ways. Artificial intelligence is a growing field that seeks to solve problems by simulating
learning in specific environments. The aim of this paper is to explore the applications that the
self play learning branch of artificial intelligence may pose on game development in the future,
and to attempt to implement a working version of a self play agent learning to play a Pokemon
battle. Originally designed Pokemon battle behavior is often suboptimal, getting stuck making
ineffective or incorrect choices, so training a self play model to learn the strategy and structure of
Pokemon battles from a clean slate would result in an organic agent that would outperform the
original behavior of the computer controlled agents. Though unsuccessful in my implementation,
this paper serves as a record of the exploration of this field, and a log of what worked and what
did not, in order to benefit any future person interested in the same topics.
Designing these agents to cover every case of human interaction is difficult, and usually
imperfect, as human players are capable of learning to overcome these agents in unintended
ways. Artificial intelligence is a growing field that seeks to solve problems by simulating
learning in specific environments. The aim of this paper is to explore the applications that the
self play learning branch of artificial intelligence may pose on game development in the future,
and to attempt to implement a working version of a self play agent learning to play a Pokemon
battle. Originally designed Pokemon battle behavior is often suboptimal, getting stuck making
ineffective or incorrect choices, so training a self play model to learn the strategy and structure of
Pokemon battles from a clean slate would result in an organic agent that would outperform the
original behavior of the computer controlled agents. Though unsuccessful in my implementation,
this paper serves as a record of the exploration of this field, and a log of what worked and what
did not, in order to benefit any future person interested in the same topics.
ContributorsCiudad, Erick Marcel (Author) / Meuth, Ryan (Thesis director) / Kobayashi, Yoshihiro (Committee member) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Behavioral economics suggests that emotions can affect an individual’s decision making. Recent research on this idea’s application on large societies hints that there may exist some correlation or maybe even some causation relationship between public sentiment—at least what can be pulled from Twitter—and the movement of the stock market. One major result of consistent research on whether or not public sentiment can predict the movement of the stock market is that public sentiment, as a feature, is becoming more and more valid as a variable for stock-market-based machine learning models. While raw values typically serve as invaluable points of data, when training a model, many choose to “engineer” new features for their models—deriving rates of change or range values to improve model accuracy.
Since it doesn’t hurt to attempt to utilize feature extracted values to improve a model (if things don’t work out, one can always use their original features), the question may arise: how could the results of feature extraction on values such as sentiment affect a model’s ability to predict the movement of the stock market? This paper attempts to shine some light on to what the answer could be by deriving TextBlob sentiment values from Twitter data, and using Granger Causality Tests and logistic and linear regression to test if there exist a correlation or causation between the stock market and features extracted from public sentiment.
Since it doesn’t hurt to attempt to utilize feature extracted values to improve a model (if things don’t work out, one can always use their original features), the question may arise: how could the results of feature extraction on values such as sentiment affect a model’s ability to predict the movement of the stock market? This paper attempts to shine some light on to what the answer could be by deriving TextBlob sentiment values from Twitter data, and using Granger Causality Tests and logistic and linear regression to test if there exist a correlation or causation between the stock market and features extracted from public sentiment.
ContributorsYu, James (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
As modern advancements in medical technology continue to increase overall life expectancy, hospitals and healthcare systems are finding new and more efficient ways of storing extensive amounts of patient healthcare information. This progression finds people increasingly dependent on hospitals as the primary providers of medical data, ranging from immunization records to surgical history. However, the benefits of carrying a copy of personal health information are becoming increasingly evident. This project aims to create a simple, secure, and cohesive application that stores and retrieves user health information backed by Google’s Firebase cloud infrastructure. Data was collected to both explore the current need for such an application, and to test the usability of the product. The former was done using a multiple-choice survey distributed through social media to understand the necessity for a patient-held health file (PHF). Subsequently, user testing was performed with the intent to track the success of our application in meeting those needs. According to the data, there was a trend that suggested a significant need for a healthcare information storage device. This application, allowing for efficient and simple medical information storage and retrieval, was created for a target audience of those seeking to improve their medical information awareness, with a primary focus on the elderly population. Specific correlations between the frequency of physician visits and app usage were identified to target the potential use cases of our app. The outcome of this project succeeded in meeting the significant need for increased patient medical awareness in the healthcare community.
ContributorsUpponi, Rohan Sachin (Co-author) / Somayaji, Vasishta (Co-author) / McDaniel, Troy (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
A common design of multi-agent robotic systems requires a centralized master node, which coordinates the actions of all the agents. The multi-agent system designed in this project enables coordination between the robots and reduces the dependence on a single node in the system. This design change reduces the complexity of the central node, and makes the system more adaptable to changes in its topology. The final goal of this project was to have a group of robots collaboratively claim positions in pre-defined formations, and navigate to the position using pose data transmitted by a localization server.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
ContributorsThibeault, Quinn (Author) / Meuth, Ryan (Thesis director) / Chen, Yinong (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
For our creative project, we initially wanted to work on a web application that would allow people with busy schedules to easily create and share events while also discovering other events that may interest them. With that in mind, we created the Group Event Planner App, a full stack project that lays down a foundation for all of our goals while focusing primarily on the proposed recommendation algorithms that enable its users to discover events that are likely to pique their interest. The development of our recommendation algorithms took inspiration from existing implementations, such as those at Amazon, YouTube, and Netflix, and resulted in a creative amalgamation.
ContributorsRussell, Preston (Co-author) / Sonnier, Connor (Co-author) / Chen, Yinong (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
One of the major sources of authentication is through the use of username and password systems. Ideally, each password is a unique identifier known by a single individual. In reality however, exposed passwords from past data breaches reveal vulnerabilities that are traceable to passwords created today. Vulnerabilities include repetitions of characters, words, character sequences, and phrases that are used in a password. This project was observed in English to highlight the vulnerabilities that can come from utilizing the English language. However, the vulnerabilities highlighted in this project can also be applicable in languages across the world. It was observed that through the common types of digital attacks, brute force attack and dictionary attack work effectively against weak passwords. Brute force attack revealed that a user could expose an alphanumeric password of length eight in as little as one and a half days. In addition, dictionary attacks revealed that an alphanumeric password of length eight can be exposed in a shorter amount of time if the password contains a single long word or phrase thought to be secure. During this attack analysis, it found that passwords become significantly more secure in the utilization of alphanumeric passwords of minimal length of eight. In addition, the password must also not be a particular phrase or word with simplistic characteristics for adequate strength against dictionary attack. The solution to using username and password systems is to create a password utilizing as many characters as possible while still retaining memorability. If creating a password of this type is not feasible, there is a need to use technological solutions to keep the current system of username and passwords as secure as possible under daily life. Otherwise, there will be a need to replace the username and password system altogether before it becomes insecure by technology.
ContributorsTipton, Tony T (Co-author) / Tipton, Tony (Co-author) / Meuth, Ryan (Thesis director) / Tirupalavanam, Ganesh (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05