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This paper introduces MisophoniAPP, a new website for managing misophonia. It will briefly discuss the nature of this chronic syndrome, which is the experience of reacting strongly to certain everyday sounds, or “triggers”. Various forms of Cognitive Behavioral Therapy and the Neural Repatterning Technique are currently used to treat misophonia,

This paper introduces MisophoniAPP, a new website for managing misophonia. It will briefly discuss the nature of this chronic syndrome, which is the experience of reacting strongly to certain everyday sounds, or “triggers”. Various forms of Cognitive Behavioral Therapy and the Neural Repatterning Technique are currently used to treat misophonia, but they are not guaranteed to work for every patient. Few apps exist to help patients with their therapy, so this paper describes the design and creation of a new website that combines exposure therapy,
relaxation, and gamification to help patients alleviate their misophonic reflexes.
ContributorsNoziglia, Rachel Elisabeth (Author) / McDaniel, Troy (Thesis director) / Anderson, Derrick (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
The Luminosity Lab, located at Arizona State University, is a prototype for a novel model of interdisciplinary, student-led innovation. The model’s design was informed by the following desired outcomes: i) the model would be well-suited for the 21st century, ii) it would attract, motivate, and retain the university’s strongest student

The Luminosity Lab, located at Arizona State University, is a prototype for a novel model of interdisciplinary, student-led innovation. The model’s design was informed by the following desired outcomes: i) the model would be well-suited for the 21st century, ii) it would attract, motivate, and retain the university’s strongest student talent, iii) it would operate without the oversight of faculty, and iv) it would work towards the conceptualization, design, development, and deployment of solutions that would positively impact society. This model of interdisciplinary research was tested at Arizona State University across four academic years with participation of over 200 students, who represented more than 20 academic disciplines. The results have shown successful integration of interdisciplinary expertise to identify unmet needs, design innovative concepts, and develop research-informed solutions. This dissertation analyzes Luminosity’s model to determine the following: i) Can a collegiate, student-driven interdisciplinary model of innovation designed for the 21st century perform without faculty management? ii) What are the motivators and culture that enable student success within this model? and iii) How does Luminosity differ from traditional research opportunities and learning experiences?
Through a qualitative, grounded theory analysis, this dissertation examines the phenomena of the students engaging in Luminosity’s model, who have demonstrated their ability to serve as the principal investigators and innovators in conducting substantial discovery, research, and innovation work through full project life cycles. This study supports a theory that highly talented students often feel limited by the pace and scope of their college educations, and yearn for experiences that motivate them with agency, achievement, mastery, affinity for colleagues, and a desire to impact society. Through the cumulative effect of these motivators and an organizational design that facilitates a bottom-up approach to student-driven innovation, Luminosity has established itself as a novel model of research and development in the collegiate space.
ContributorsNaufel, Mark Naufel (Author) / Becker, David V (Thesis advisor) / Cooke, Nancy J. (Committee member) / Anderson, Derrick (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library,

Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.

Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
ContributorsDiMuro, Louis (Author) / Balasooriya, Janaka (Thesis director) / Chen, Yinong (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05