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Description
The quality and quantity of talented members of the US STEM workforce has

been a subject of great interest to policy and decision makers for the past 40 years.

Recent research indicates that while there exist specific shortages in specific disciplines

and areas of expertise in the private sector and the federal government,

The quality and quantity of talented members of the US STEM workforce has

been a subject of great interest to policy and decision makers for the past 40 years.

Recent research indicates that while there exist specific shortages in specific disciplines

and areas of expertise in the private sector and the federal government, there is no

noticeable shortage in any STEM academic discipline, but rather a surplus of PhDs

vying for increasingly scarce tenure track positions. Despite the seeming availability

of industry and private sector jobs, recent PhDs still struggle to find employment in

those areas. I argue that the decades old narrative suggesting a shortage of STEM

PhDs in the US poses a threat to the value of the natural science PhD, and that

this narrative contributes significantly to why so many PhDs struggle to find career

employment in their fields. This study aims to address the following question: what is

the value of a STEM PhD outside academia? I begin with a critical review of existing

literature, and then analyze programmatic documents for STEM PhD programs at

ASU, interviews with industry employers, and an examination the public face of value

for these degrees. I then uncover the nature of the value alignment, value disconnect,

and value erosion in the ecosystem which produces and then employs STEM PhDs,

concluding with specific areas which merit special consideration in an effort to increase

the value of these degrees for all stakeholders involved.
ContributorsGarbee, Elizabeth (Author) / Maynard, Andrew D. (Thesis advisor) / Wetmore, Jameson (Committee member) / Anderson, Derrick (Committee member) / Arizona State University (Publisher)
Created2018
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Description
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
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