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Description
Yannis Constantinidis was the last of the handful of composers referred to collectively as the Greek National School. The members of this group strove to create a distinctive national style for Greece, founded upon a synthesis of Western compositional idioms with melodic, rhyhmic, and modal features of their local folk traditions. Constantinidis particularly looked to the folk melodies of his native Asia Minor and the nearby Dodecanese Islands. His musical output includes operettas, musical comedies, orchestral works, chamber and vocal music, and much piano music, all of which draws upon folk repertories for thematic material. The present essay examines how he incorporates this thematic material in his piano compositions, written between 1943 and 1971, with a special focus on the 22 Songs and Dances from the Dodecanese. In general, Constantinidis's pianistic style is expressed through miniature pieces in which the folk tunes are presented mostly intact, but embedded in accompaniment based in early twentieth-century modal harmony. Following the dictates of the founding members of the Greek National School, Manolis Kalomiris and Georgios Lambelet, the modal basis of his harmonic vocabulary is firmly rooted in the characteristics of the most common modes of Greek folk music. A close study of his 22 Songs and Dances from the Dodecanese not only offers a valuable insight into his harmonic imagination, but also demonstrates how he subtly adapts his source melodies. This work also reveals his care in creating a musical expression of the words of the original folk songs, even in purely instrumental compositon.
ContributorsSavvidou, Dina (Author) / Hamilton, Robert (Thesis advisor) / Little, Bliss (Committee member) / Meir, Baruch (Committee member) / Thompson, Janice M (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this project was to examine the lives and solo piano works of four members of the early generation of female composers in Taiwan. These four women were born between 1950 and 1960, began to appear on the Taiwanese musical scene after 1980, and were still active as composers at the time of this study. They include Fan-Ling Su (b. 1955), Hwei-Lee Chang (b. 1956), Shyh-Ji Pan-Chew (b. 1957), and Kwang-I Ying (b. 1960). Detailed biographical information on the four composers is presented and discussed. In addition, the musical form and features of all solo piano works at all levels by the four composers are analyzed, and the musical characteristics of each composer's work are discussed. The biography of a fifth composer, Wei-Ho Dai (b. 1950), is also discussed but is placed in the Appendices because her piano music could not be located. This research paper is presented in six chapters: (1) Prologue; the life and music of (2) Fan-Ling Su, (3) Hwei-Lee Chang, (4) Shyh-Ji Pan-Chew, and (5) Kwang-I Ying; and (6) Conclusion. The Prologue provides an overview of the development of Western classical music in Taiwan, a review of extant literature on the selected composers and their music, and the development of piano music in Taiwan. The Conclusion is comprised of comparisons of the four composers' music, including their personal interests and preferences as exhibited in their music. For example, all of the composers have used atonality in their music. Two of the composers, Fan-Ling Su and Kwang-I Ying, openly apply Chinese elements in their piano works, while Hwei-Lee Chang tries to avoid direct use of the Chinese pentatonic scale. The piano works of Hwei-Lee Chang and Shyh-Ji Pan-Chew are chromatic and atonal, and show an economical usage of material. Biographical information on Wei-Ho Dai and an overview of Taiwanese history are presented in the Appendices.
ContributorsWang, Jinding (Author) / Pagano, Caio (Thesis advisor) / Campbell, Andrew (Committee member) / Humphreys, Jere T. (Committee member) / Meyer-Thompson, Janice (Committee member) / Norton, Kay (Committee member) / Arizona State University (Publisher)
Created2011
Description
Over the years, the growing penetration of renewable energy into the electricity market has resulted in a significant change in the electricity market price. This change makes the existing forecasting method prone to error, decreasing the economic benefits. Hence, more precise forecasting methods need to be developed. This paper starts with a survey and benchmark of existing machine learning approaches for forecasting the real-time market (RTM) price. While these methods provide sufficient modeling capability via supervised learning, their accuracy is still limited due to the single data source, e.g., historical price information only. In this paper, a novel two-stage supervised learning approach is proposed by diversifying the data sources such as highly correlated power data. This idea is inspired by the recent load forecasting methods that have shown extremely well performances. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules. The first one is the mapping between the historical wind power and the historical price. The second is the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the first learned mapping between power and price. Additionally, we observed that it is not the more training data the better, leading to our validation steps to quantify the best training intervals for different datasets. We conduct comparisons of numerical results between existing methods and the proposed methods based on datasets from the Electric Reliability Council of Texas (ERCOT). For each machine learning step, we examine different learning methods, such as polynomial regression, support vector regression, neural network, and deep neural network. The results show that the proposed method is significantly better than existing approaches when renewables are involved.
ContributorsLuo, Shuman (Author) / Weng, Yang (Thesis advisor) / Lei, Qin (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2019
Description
My research aims to determine the effectiveness of meditation and sleep applications (apps) on the reduction of anxiety and stress in college students, with a focus on sedative piano music. Results showed a significant reduction of stress and anxiety levels in college students when listening to sedative piano music versus non-sedative piano music. Music along with other therapy modalities in meditation and sleep apps show promise in reducing students’ anxiety and stress and promoting their successes.
ContributorsPantha, Bidur (Author) / Brian, Jennifer (Thesis director) / Patten, Kristopher (Committee member) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05