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ContributorsChang, Ruihong (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-29
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Description
Four Souvenirs for Violin and Piano was composed by Paul Schoenfeld (b.1947) in 1990 as a showpiece, spotlighting the virtuosity of both the violin and piano in equal measure. Each movement is a modern interpretation of a folk or popular genre, re- envisioned over intricate jazz harmonies and rhythms. The

Four Souvenirs for Violin and Piano was composed by Paul Schoenfeld (b.1947) in 1990 as a showpiece, spotlighting the virtuosity of both the violin and piano in equal measure. Each movement is a modern interpretation of a folk or popular genre, re- envisioned over intricate jazz harmonies and rhythms. The work was commissioned by violinist Lev Polyakin, who specifically requested some short pieces that could be performed in a local jazz establishment named Night Town in Cleveland, Ohio. The result is a work that is approximately fifteen minutes in length. Schoenfeld is a respected composer in the contemporary classical music community, whose Café Music (1986) for piano trio has recently become a staple of the standard chamber music repertoire. Many of his other works, however, remain in relative obscurity. It is the focus of this document to shed light on at least one other notable composition; Four Souvenirs for Violin and Piano. Among the topics to be discussed regarding this piece are a brief history behind the genesis of this composition, a structural summary of the entire work and each of its movements, and an appended practice guide based on interview and coaching sessions with the composer himself. With this project, I hope to provide a better understanding and appreciation of this work.
ContributorsJanczyk, Kristie Annette (Author) / Ryan, Russell (Thesis advisor) / Campbell, Andrew (Committee member) / Norton, Kay (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures

Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
ContributorsASU Library. Music Library (Publisher)
Created2018-02-23
ContributorsWhite, Aaron (Performer) / Kim, Olga (Performer) / Hammond, Marinne (Performer) / Shaner, Hayden (Performer) / Yoo, Katie (Performer) / Shoemake, Crista (Performer) / Gebe, Vladimir, 1987- (Performer) / Wills, Grace (Performer) / McKinch, Riley (Performer) / Freshmen Four (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-27
ContributorsRosenfeld, Albor (Performer) / Pagano, Caio, 1940- (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-03
ContributorsASU Library. Music Library (Publisher)
Created2018-10-04
ContributorsCao, Yuchen (Performer) / Chen, Sicong (Performer) / Soberano, Chino (Performer) / Nam, Michelle (Performer) / Collins, Clarice (Performer) / Witt, Juliana (Performer) / Liu, Jingting (Performer) / Chen, Neilson (Performer) / Zhang, Aihua (Performer) / Jiang, Zhou (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-25
ContributorsMcLin, Katherine (Performer) / Campbell, Andrew (Pianist) (Performer) / Ericson, John Q. (John Quincy), 1962- (Performer) / McLin/Campbell Duo (Performer) / ASU Library. Music Library (Publisher)
Created2018-09-23
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Description
Samuel Máynez Prince (1886-1966), was a prolific and important Mexican musician. Prince’s musical style followed the trends of the nineteenth-century salon music genre. His compositions include lullabies, songs, dances, marches, mazurkas, waltzes, and revolutionary anthems. Prince’s social status and performances in the famed Café Colón in Mexico City increased his

Samuel Máynez Prince (1886-1966), was a prolific and important Mexican musician. Prince’s musical style followed the trends of the nineteenth-century salon music genre. His compositions include lullabies, songs, dances, marches, mazurkas, waltzes, and revolutionary anthems. Prince’s social status and performances in the famed Café Colón in Mexico City increased his popularity among high-ranking political figures during the time of the Mexican Revolution as well as his status in the Mexican music scene.

Unfortunately there is virtually no existing scholarship on Prince and even basic information regarding his life and works is not readily available. The lack of organization of the manuscript scores and the absence of dates of his works has further pushed the composer into obscurity. An investigation therefore was necessary in order to explore the neglected aspects of the life and works of Prince as a violinist and composer. This document is the result of such an investigation by including extensive new biographical information, as well as the first musical analysis and edition of the complete recovered works for violin and piano.

In order to fill the gaps present in the limited biographical information regarding Prince’s life, investigative research was conducted in Mexico City. Information was drawn from archives of the composer’s grandchildren, the Palacio de Bellas Artes, the Conservatorio Nacional de Música de México, and the Orquesta Sinfónica Nacional. The surviving relatives provided first-hand details on events in the composer’s life; one also offered the researcher access to their personal archive including, important life documents, photographs, programs from concert performances, and manuscript scores of the compositions. Establishing connections with the relatives also led the researcher to examining the violins owned and used by the late violinist/composer.

This oral history approach led to new and updated information, including the revival of previously unpublished music for violin and piano. These works are here compiled in an edition that will give students, teachers, and music-lovers access to this unknown repertoire. Finally, this research seeks to promote the beauty and nuances of Mexican salon music, and the complete works for violin and piano of Samuel Máynez Prince in particular.
ContributorsEkenes, Spencer Arvin (Author) / McLin, Katherine (Thesis advisor) / Feisst, Sabine (Committee member) / Jiang, Danwen (Committee member) / Arizona State University (Publisher)
Created2016