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Rainbow Connection is an integrated choir with members on and off the autism spectrum. It was founded in the spring of 2012 by Barrett students Ali Friedman, Megan Howell, and Victoria Gilman as part of an honors thesis creative project. Rainbow Connection uses the rehearsal process and other creative endeavors

Rainbow Connection is an integrated choir with members on and off the autism spectrum. It was founded in the spring of 2012 by Barrett students Ali Friedman, Megan Howell, and Victoria Gilman as part of an honors thesis creative project. Rainbow Connection uses the rehearsal process and other creative endeavors to foster natural relationship building across social gaps. A process-oriented choir, Rainbow Connection's main goals concern the connections made throughout the experience rather than the final musical product. The authors believe that individual, non-hierarchical relationships are the keys to breaking down systemized gaps between identity groups and that music is an ideal facilitator for fostering such relationships. Rainbow Connection operates under the premise that, like colors in a rainbow, choir members create something beautiful not by melding into one homogenous group, but by collaboratively showcasing their individual gifts. This paper will highlight the basic premise and structure of Rainbow Connection, outline the process of enacting the choir, and describe the authors' personal reactions and takeaways from the project.
ContributorsFriedman, Alexandra (Co-author) / Gilman, Victoria (Co-author) / Howell, Megan (Co-author) / Rio, Robin (Thesis director) / Schildkret, David (Committee member) / Barrett, The Honors College (Contributor) / School of Music (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-12
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Description
Advances in computational processing have made big data analysis in fields like music information retrieval (MIR) possible. Through MIR techniques researchers have been able to study information on a song, its musical parameters, the metadata generated by the song's listeners, and contextual data regarding the artists and listeners (Schedl, 2014).

Advances in computational processing have made big data analysis in fields like music information retrieval (MIR) possible. Through MIR techniques researchers have been able to study information on a song, its musical parameters, the metadata generated by the song's listeners, and contextual data regarding the artists and listeners (Schedl, 2014). MIR research techniques have been applied within the field of music and emotions research to help analyze the correlative properties between the music information and the emotional output. By pairing methods within music and emotions research with the analysis of the musical features extracted through MIR, researchers have developed predictive models for emotions within a musical piece. This research has increased our understanding of the correlative properties of certain musical features like pitch, timbre, rhythm, dynamics, mel frequency cepstral coefficients (MFCC's), and others, to the emotions evoked by music (Lartillot 2008; Schedl 2014) This understanding of the correlative properties has enabled researchers to generate predictive models of emotion within music based on listeners' emotional response to it. However, robust models that account for a user's individualized emotional experience and the semantic nuances of emotional categorization have eluded the research community (London, 2001). To address these two main issues, more advanced analytical methods have been employed. In this article we will look at two of these more advanced analytical methods, machine learning algorithms and deep learning techniques, and discuss the effect that they have had on music and emotions research (Murthy, 2018). Current trends within MIR research, the application of support vector machines and neural networks, will also be assessed to explain how these methods help to address the two main issues within music and emotion research. Finally, future research within the field of machine and deep learning will be postulated to show how individuate models may be developed from a user or a pool of user's listening libraries. Also how developments of semi-supervised classification models that assess categorization by cluster instead of by nominal data, may be helpful in addressing the nuances of emotional categorization.
ContributorsMcgeehon, Timothy Makoto (Author) / Middleton, James (Thesis director) / Knowles, Kristina (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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Description
Concentrated Solar Power and Thermal Energy Storage are two technologies that are currently being explored as environmentally friendly methods of energy generation. The two technologies are often combined in an overall system to increase efficiency and reliability of the energy generation system. A collaborative group of researchers from Australia and

Concentrated Solar Power and Thermal Energy Storage are two technologies that are currently being explored as environmentally friendly methods of energy generation. The two technologies are often combined in an overall system to increase efficiency and reliability of the energy generation system. A collaborative group of researchers from Australia and the United States formed a project to design solar concentrators that utilize Concentrated Solar Power and Thermal Energy Storage. The collaborators from Arizona State designed a Latent Heat Thermal Energy Storage system for the project. It was initially proposed that the system utilize Dowtherm A as the Heat Transfer Fluid and a tin alloy as the storage material. Two thermal reservoirs were designed as part of the system; one reservoir was designed to be maintained at 240˚ C, while the other reservoir was designed to be maintained at 210˚ C. The tin was designed to receive heat from the hot reservoir during a charging cycle and discharge heat to the cold reservoir during a discharge cycle. From simulation, it was estimated that the system would complete a charging cycle in 17.5 minutes and a discharging cycle in 6.667 minutes [1]. After the initial design was fabricated and assembled, the system proved ineffective and did not perform as expected. Leaks occurred within the system under high pressure and the reservoirs could not be heated to the desired temperatures. After adding a flange to one of the reservoirs, it was decided that the system would be run with one reservoir, with water as the Heat Transfer Fluid. The storage material was changed to paraffin wax, because it would achieve phase change at a temperature lower than the boiling point of water. Since only one reservoir was available, charging cycle tests were performed on the system to gain insight on system performance. It was found that the paraffin sample only absorbs 3.29% of the available heat present during a charging cycle. This report discusses the tests performed on the system, the analysis of the data from these tests, the issues with the system that were revealed from the analyses, and potential design changes that would increase the efficiency of the system.
ContributorsKocher, Jordan Daniel (Author) / Wang, Robert (Thesis director) / Phelan, Patrick (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
Description
This creative project focused on the process of making an album from scratch. From songwriting to recording, this three-year project ended with the release of a ten-song album available on all streaming platforms. The goal of this project was to experience the same general process as professional recording artists and

This creative project focused on the process of making an album from scratch. From songwriting to recording, this three-year project ended with the release of a ten-song album available on all streaming platforms. The goal of this project was to experience the same general process as professional recording artists and gain a better understanding of the music industry.
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05
ContributorsStone, Amanda (Author) / Myers, Nathan (Thesis director) / Steiner, Kiernan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Music, Dance and Theatre (Contributor)
Created2023-05