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
Many psychology-rooted studies into the games industry seek to identify emotions players experience during gameplay. However, there is a need to extend this kind of research beyond the realm of emotion into more long-term concepts, like satisfaction. This experiment tested whether a specific game mechanic was enjoyable. Other literature has established a way to describe and quantify enjoyability. Using a survey based on that work, this study evaluated the addition of a 'gel gun' to a platforming game. The fun was found to significantly increase players' affective experiences, concentration, and sense of control, all being components of an enjoyable experience. It also exposed some conflicts within the survey that merit investigation. It was concluded that the 'gel gun' feature increased gameplay enjoyability without significantly diminishing any other enjoyable factors. Future work may explore the connections between this feature and specific elements of enjoyment.
ContributorsMints, John (Author) / Meuth, Ryan (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor)
Created2014-12
Description
This project was centered around designing a processor model (using the C programming language) based on the Coldfire computer architecture that will run on third party software known as Open Virtual Platforms. The end goal is to have a fully functional processor that can run Coldfire instructions and utilize peripheral devices in the same way as the hardware used in the embedded systems lab at ASU. This project would cut down the substantial amount of time students spend commuting to the lab. Having the processor directly at their disposal would also encourage them to spend more time outside of class learning the hardware and familiarizing themselves with development on an embedded micro-controller. The model will be accurate, fast and reliable. These aspects will be achieved through rigorous unit testing and use of the OVP platform which provides instruction accurate simulations at hundreds of MIPS (million instructions per second) for the specified model. The end product was able to accurately simulate a subset of the Coldfire instructions at very high rates.
ContributorsDunning, David Connor (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-12
Description
In this paper we explore the design, implementation, and analysis of two different approaches for providing music recommendations to targeted users by implementing the Gram-ART unsupervised learning algorithm. We provide a content filtering approach using a dataset of one million songs which include various metadata tags and a collaborative filtering approach using the listening histories of over one million users. The two methods are evaluated by their results from Million Song Dataset Challenge. While both placed near the top third of the 150 challenge participants, the knowledge gained from the experiments will help further refine the process and likely produced much higher results in a system with the potential to scale several magnitudes.
ContributorsMeiss, Trevor (Author) / Meuth, Ryan (Thesis director) / Miller, Phill (Committee member) / Barrett, The Honors College (Contributor)
Created2015-05
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