ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 12,321 - 12,330 of 12,704
Filtering by
- Language: English
Description
Lowell Liebermann (b.1961) is one of America’s most frequently performed contemporary composers. He has written a large number of piano pieces and his works are often featured in major competitions and doctoral dissertations. Liebermann’s relationship with the piano began early in life and he considers it to be his principal instrument. His understanding of the strengths and limitations of the piano makes his keyboard creations powerful, expressive, and virtuosic. Although many of his pieces have been performed, his Piano Sonata No. 3, Op. 82 has not yet found a large audience or used as the subject of in-depth discussion. It is the author’s hope to stimulate performances of this work through a descriptive analysis and performance guide. This research document begins with a concise biography of the composer, including the composer’s early musical experiences, his education in academia, and his composition career. The second chapter provides a review of the composer’s major works. The third chapter provides a descriptive analysis and performer’s guide, with insights into Liebermann’s expectations of the performer. The present study includes a lecture recital, found online at https://youtu.be/Uf-SpK8cIr0?si=usxy5_AaWu7VoKP4
ContributorsWei, Jialin (Author) / Meir, Baruch (Thesis advisor) / Hamilton, Robert (Thesis advisor) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2024
Description
The Kiki scene, an autonomous youth subculture within the broader House Ballroom community, has recently emerged in Arizona, serving as a critical space for Black and Latinx LGBTQIA+ individuals to find belonging, resistance, and creative self-expression. Amidst Arizona's sociopolitical landscape, where transgender identities face legal discrimination, Kiki house members navigate complex intersections of identity, community building, and gender performance. This dissertation explores the lived experiences, perceptions, and aspirations of the Arizona Ballroom Kiki community through Community-Based Participatory Research (CBPR), Participatory Action Research (PAR), autoethnography, and qualitative interviews. The first paper employs autoethnography to examine the researcher's personal journey as a white non-binary transmasculine individual navigating identity and gender expression within the predominantly Black and Latinx LGBTQIA+ Ballroom Kiki scene, a community that embraces femininity in all its diverse forms. The second paper presents findings from semi-structured interviews with members of two Kiki houses, uncovering themes related to their perceptions of Ballroom culture, aspirations for representing their stories, and concerns in working with researchers, such as cultural appropriation and misrepresentation. The Arizona Ballroom Kiki scene is a testament to the resilience, creativity, and talent of its members, who have built a thriving community despite facing numerous challenges. The third paper examines the application of CBPR and PAR methodologies through themes developed from focus group interviews with Kiki house members, discussing ethical and practical considerations of conducting collaborative research with marginalized LGBTQIA+ communities. Key findings underscore the importance of honoring the history and legacy of Ballroom, cultural preservation, authentic representation, community agency, empowerment, and equitable tangible benefits for the community and its members. The study highlights the transformative potential of the Ballroom scene in fostering resilience, creativity, and social change while addressing the challenges of navigating power dynamics and the potential for unintended harm from the actions of researchers, policymakers, and society at large. By centering the voices and experiences of the Arizona Ballroom Kiki community, this research contributes to understanding the sociocultural significance of Ballroom culture and its impact on LGBTQIA+ People of Color, emphasizing the need for inclusive, participatory, and empowering approaches in documenting and supporting marginalized communities.
ContributorsGleason, Lea (Author) / SturtzSreetharan, Cindi (Thesis advisor) / Glegziabher, Meskerem (Committee member) / Wutich, Amber (Committee member) / Arizona State University (Publisher)
Created2024
Description
Solar power, as an important part of renewable energy, has become one of the main choices for countries around the world in their energy strategic layout due to its cleanliness, renewability, and distributed attributes. In the context of the booming photovoltaic industry, China has emerged a large number of excellent photovoltaic companies, driving the whole industry to reduce costs and increase efficiency, making many contributions to the grid parity of photovoltaic power generation. In the development lifecycle of the photovoltaic industry, various companies choose different competitive strategies to deal with industry cyclical changes and external uncertainty based on their core competitiveness and market opportunities. Vertical integration is one of the strategic paths chosen by many photovoltaic companies. Therefore, it is an important issue to explore the impact of vertical integration on the development of Chinese photovoltaic companies.Based on the data of China's A-share listed photovoltaic companies from 2018 to 2022, this paper uses panel fixed effect model to empirically test the impact of vertical integration on corporate valuation, explores its influencing mechanism, and further analyzes the moderating effect of enterprise heterogeneity factors. The research in this paper shows that: (1) under other conditions unchanged, vertical integration significantly improves the valuation level of enterprises, and this positive impact will not change with the measurement method of enterprise valuation level. This is because the higher the vertical integration degree of enterprises, the stronger their ability to respond to external uncertainty. The more enterprises can obtain capital market preferences, the higher the enterprise valuation will be. This also means that the higher the vertical integration degree of photovoltaic enterprises, the higher their market share is, and they are more able to avoid the impact of external uncertainty, thus obtaining a higher valuation level in the secondary market. (2) The intermediary effect test shows that the channel for vertical integration of photovoltaic enterprises to affect enterprise valuation levels is to increase their market share. (3) Further heterogeneity analysis shows that enterprise profitability and enterprise size positively regulate the impact of vertical integration on enterprise valuation, while enterprise management shareholding ratio and enterprise operating cost ratio will weaken the positive promotion effect of vertical integration.
The research conclusions of this paper provide micro-empirical evidence for how photovoltaic companies can improve their enterprise valuation, and also provide some management references for other unlisted companies in the same industry.
Keywords: Photovoltaic enterprises; Vertical integration; Corporate valuation; Fixed effect model
ContributorsZheng, Ren (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhao, Yanfei (Committee member) / Arizona State University (Publisher)
Created2024
Description
Ge Gan-ru (b. 1954) is considered one of the most innovative composers of his time and is referred to in The New Grove Dictionary of Music and Musicians as “China's first avant-garde composer.”[ Stanley Sadie, The New Grove Dictionary of Music and Musicians, 2nd edition. Oxford: Oxford University Press,( January 29, 2004): 258.] In 1986, Ge composed Ancient Music, a piece employs extended piano techniques to express the composer's reimagination of ancient Chinese music.
This project explores the life and music of Ge Gan-ru by providing a historical background of Ge’s life as a composer during the Chinese Cultural Revolution[ The Chinese Cultural Revolution was a decade-long era of political and social upheaval ignited by Mao Zedong's attempt to restore his authority over the Communist Party through the mistreatment of the Chinese people. ] and the changes after he came to America. In addition, a technical analysis and performance guide of Ancient Music are included, in order to discuss how he expresses his individual compositional language and integrates Chinese musical concepts into a western contemporary compositional system. In this document, I take a close look at Ge Gan-ru’s perspectives on Chinese music and the revolutionary reforms he made. Chapter One is a review of sources about Ge’s life and study in China and America and a brief introduction to his Ancient Music. Chapter Two discusses why the concept of composer in the context of Western music is missing in Chinese music, as most traditional Chinese works were not created by a single person and therefore do not reflect the individual voice of one composer. This point can also be extended to explain why Chinese society has historically encouraged homogenization including in music. Chapter Three serves as a performance guide, as well as a musical and technical analysis of Ancient Music. This will involve outlining and comparing the performance of traditional Chinese instruments with the internal piano techniques employed throughout this piece. Chapter Four is a summary of Ge’s Ancient Music and his musical contributions.
ContributorsWang, Yun (Author) / Breslin, Cathal (Thesis advisor) / Solís, Ted (Committee member) / Creviston, Hannah (Committee member) / Arizona State University (Publisher)
Created2024
Description
In current international environment, the important goal of improving China industry is to strengthen the independence of the industrial chain. Sci-tech innovation enterprises are the main carrier. They are also the service objects of the Sci-Tech innovation board (“SSE STAR MARKET”).Some sci-tech innovation enterprises are “capital intensive”, some are “technology intensive”, and the others are both. “Capital intensive” enterprises are controlled by the capital side, “technology intensive” enterprises are controlled by core technical team. The importance of “capital” and “technology” should be reflected in the shareholding ratio, which will impact on corporate governance.
This paper aim to find out the relationship between team ownership and enterprise attributes. Team shareholding ratio uses ESOP as indicator (ESOP includes core management shareholding and Employee Stock Ownership Plans), and enterprise attributes are quantified by heavy asset ratio, R&D input, company counterbalance system, and institutional investors shareholding ratio.
The research object is the listed companies on the SSE STAR MARKET as of June 30, 2023. Datas range from 2019 to 2023. According to the regression result, it is found that: at first, the heavy asset ratio is negatively correlated with ESOP. The higher heavy asset ratio is. the lower ESOP shareholding ratio the enterprises have. Secondly, company counterbalance system is negatively correlated with ESOP. The higer shareholding ratio of 2-5 major shareholders is, the lower ESOP shareholding ratio the enterprises have. Thirdly, there is no significant influence between institutional investors shareholding ratio and ESOP. Fourthly, there is no significant influence between R&D input and ESOP. But along with heavy asset ratio, there has a significant positive correlation with ESOP. That is, R&D input does not affect ESOP alone, it needs to be combined with heavy asset ratio. Fifthly, the results of sub-industry regression are different from the whole.
This paper hopes the study can be further extended to the operation of other sci-tech innovative enterprises, and provide an effective way to build a stable corporate governance structure for those enterprises.
ContributorsHan, Bing (Author) / Tang, YiYuan (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Qian, Cuili (Committee member) / Arizona State University (Publisher)
Created2024
Description
Deep metric learning has recently shown extremely promising results in the classical data domain, creating well-separated feature spaces. This idea was also adapted to quantum computers via Quantum Metric Learning (QMeL). QMeL consists of a 2 step process with a classical model to compress the data to fit into the limited number of qubits, then train a Parameterized Quantum Circuit (PQC) to create better separation in Hilbert Space. However, on Noisy Intermediate Scale Quantum (NISQ) devices, QMeL solutions result in high circuit width and depth, both of which limit scalability. The proposed Quantum Polar Metric Learning (QPMeL ), uses a classical model to learn the parameters of the polar form of a qubit. A shallow PQC with Ry and Rz gates is then utilized to create the state and a trainable layer of ZZ(θ)-gates to learn entanglement. The circuit also computes fidelity via a SWAP Test for the proposed Fidelity Triplet Loss function, used to train both classical and quantum components. When compared to QMeL approaches, QPMeL achieves 3X better multi-class separation, while using only 1/2 the number of gates and depth. QPMeL is shown to outperform classical networks with similar configurations, presentinga promising avenue for future research on fully classical models with quantum loss functions.
ContributorsSharma, Vinayak (Author) / Shrivastava, Aviral (Thesis advisor) / Jiang, Zilin (Committee member) / Kambhampati, Subbarao (Committee member) / Arizona State University (Publisher)
Created2024
Description
Understanding the drivers of diet selection by carnivores is key for wildlife conservation and management, particularly in the Anthropocene. Yet, most assessments of predation do not consider how spatio-temporal prey availability or nutrition influence carnivore diet selection. Using a novel data integration approach for camera trap and scat data, I assessed how spatial and temporal components of prey availability influenced diet selection by bobcats (Lynx rufus) in Colorado, USA (Chapter 1) and coyotes (Canis latrans) in Arizona, USA (Chapter 2) in areas of low and moderate levels of urbanization. I also assessed coyote diets using the nutritional geometric framework to determine coyote macronutrient consumption seasonally and relative to urbanization (Chapter 3). My results suggest that cottontail rabbit availability largely drove bobcat predation, and that bobcats consumed prey relative to its availability overall and in wildland areas, but that this relationship weakened in anthropogenic regions. I also found that, overall, models of prey availability that incorporated the temporal overlap between predator and prey taxa predicted bobcat diet selection better than models assessing the spatial availability of prey. Similarly, I found coyotes consumed prey relative to its availability overall and in sites with lower levels of human influence across seasons, but not in moderately urbanized sites. I also found that models of prey availability that incorporated time better predicted coyote diets compared to models assessing the spatial availability of prey. Finally, I observed that the macronutrient composition of coyote diets was similar between moderately and less urbanized sites, particularly in the spring-summer season. However, coyote macronutrient consumption differed seasonally, with coyotes eating more non-protein energy relative to protein energy when carbohydrate-rich mesquite (Prosopis spp.) was more available in the fall-winter. In addition, the consistently high consumption of lipid-rich domestic cats in moderately urbanized sites further supports the hypothesis that coyotes increased their consumption of non-protein energy when available and when assuming protein needs were already met. This dissertation provides new insights into how urbanized landscapes impact carnivore ecology. Since diet selection drives many human-carnivore conflicts, this research can also be used to help inform wildlife management and decision-making in anthropogenic areas.
ContributorsWeiss, Katherine (Author) / Sterner, Beckett (Thesis advisor) / Schipper, Jan (Thesis advisor) / Deviche, Pierre (Committee member) / Lewis, Jesse S (Committee member) / Strauss, Eric G (Committee member) / Arizona State University (Publisher)
Created2024
Description
Multivariate timeseries data are highly common in the healthcare domain, especially in the neuroscience field for detecting and predicting seizures to monitoring intracranial hypertension (ICH). Unfortunately, conventional techniques to leverage the available time series data do not provide high degrees of accuracy. To address this challenge, the dissertation focuses on onset prediction models for children with brain trauma in collaboration with neurologists at Phoenix Children’s Hospital. The dissertation builds on the key hypothesis that leveraging spatial information underlying the electroencephalogram (EEG) sensor graphs can significantly boost the accuracy in a multi-modal environment, integrating EEG with intracranial pressure (ICP), arterial blood pressure (ABP) and electrocardiogram (ECG) modalities. Based on this key hypothesis, the dissertation focuses on novel metadata supported multi-variate time series analysis algorithms for onset detection and prediction. In particular, the dissertation investigates a model architecture with a dual attention mechanism to draw global dependencies between inputs and outputs, leveraging self-attention in EEG data using multi-head attention for transformers, and long short-term memory (LSTM). However, recognizing that the positional encoding used traditionally in transformers does not help capture the spatial/neighborhood context of EEG sensors, the dissertation investigates novel attention techniques for performing explicit spatial learning using a coupled model network. This dissertation has answered the question of leveraging transformers and LSTM to perform implicit and explicit learning using a metadata supported coupled model network a) Robust Multi-variate Temporal Features (RMT) model and LSTM, b) the convolutional neural network - scale space attention (CNN-SSA) and LSTM mapped together using Multi-Head Attention with explicit spatial metadata for EEG sensor graphs for seizure and ICH onset prediction respectively. In addition, this dissertation focuses on transfer learning between multiple groups where target patients have lesser number of EEG channels than the source patients. This incomplete data poses problems during pre-processing. Two approaches are explored using all predictors approach considering spatial context to guide the variates who are used as predictors for the missing EEG channels, and common core/subset of EEG channels. Under data imputation K-Nearest Neighbors (KNN) regression and multi-variate multi-scale neural network (M2NN) are implemented, to address the problem for target patients.
ContributorsRavindranath, Manjusha (Author) / Candan, K. Selcuk (Thesis advisor) / Davulcu, Hasan (Committee member) / Zou, Jia (Committee member) / Luisa Sapino, Maria (Committee member) / Arizona State University (Publisher)
Created2024
Description
Since the start of the war on drugs, studies have found racial and ethnic disparities in sentencing outcomes among defendants convicted of drug offenses; however, several gaps in the drug literature remain regarding disparity-producing mechanisms, the role of drug offense characteristics, disparities in understudied groups, and possible solutions to unwarranted disparities in drug case outcomes. Using felony case-level data from the state of Florida (n = 3,058 felony drug cases), this dissertation examines three interrelated studies. Study 1 examines bail and pretrial detention practices as disparity-producing mechanisms in drug offense cases. The results of Study 1 suggest that significant variations in bail schedules in Florida’s 20 judicial circuits result in jurisdictional variation in the likelihood of pretrial detention, which subsequently, results in jurisdictional variation in pretrial and sentencing outcomes among drug offenders, given the direct effect of pretrial detention on case outcomes. Study 2 examines racial, ethnic, and immigration status disparities in pretrial and sentencing outcomes across various types of drug offenses and drug substances. The results of Study 2 suggest the presence of racial and ethnic disparities in drug case outcomes in Florida’s circuit courts, as well as the moderating role of drug offense characteristics on the effects of race and ethnicity on pretrial and sentencing outcomes. Study 3 examines whether progressive chief prosecutors, who campaign on a platform to reduce and, in some cases, refuse to prosecute low-level drug offenses, handle drug offenses differently than traditional prosecutors. The results of Study 3 indicate support that progressive chief prosecutors in Florida reduce mass incarceration and unwarranted racial and ethnic disparities in case processing and sentencing outcomes in drug offenses; however, there is still room for improvement in the progressive prosecution movement in Florida. The results of each study have direct implications for theory and policies aimed at creating a more effective and fair criminal justice system.
ContributorsOramas Mora, Daniela (Author) / Mitchell, Ojmarrh (Thesis advisor) / Spohn, Cassia (Thesis advisor) / Pizarro, Jesenia (Committee member) / Peguero, Anthony (Committee member) / Arizona State University (Publisher)
Created2024
Description
With the significant advancements of wireless communication systems that aim to meet exponentially increasing data rate demands, two promising concepts have appeared: (i) Cell-free massive MIMO, which entails the joint transmission and processing of the signals allowing the removal of classical cell boundaries, and (ii) integrated sensing and communication (ISAC), unifying communication and sensing in a single framework. This dissertation aims to take steps toward overcoming the key challenges in each concept and eventually merge them for efficient future communication and sensing networks.Cell-free massive MIMO is a distributed MIMO concept that eliminates classical cell boundaries and provides a robust performance. A significant challenge in realizing the cell-free massive MIMO in practice is its deployment complexity. In particular, connecting its many distributed access points with the central processing unit through wired fronthaul is an expensive and time-consuming approach. To eliminate this problem and enhance scalability, in this dissertation, a cell-free massive MIMO architecture adopting a wireless fronthaul is proposed, and the optimization of achievable rates for the end-to-end system is carried out. The evaluation has shown the strong potential of employing wireless fronthaul in cell-free massive MIMO systems. ISAC merges radar and communication systems, allowing effective sharing of resources, including bandwidth and hardware. The ISAC framework also enables sensing to aid communications, which shows a significant potential in mobile communication applications. Specifically, radar sensing data can address challenges like beamforming overhead and blockages associated with higher frequency, large antenna arrays, and narrow beams. To that end, this dissertation develops radar-aided beamforming and blockage prediction approaches using low-cost radar devices and evaluates them in real-world systems to verify their potential. At the intersection of these two paradigms, the integration of sensing into cell-free massive MIMO systems emerges as an intriguing prospect for future technologies. This integration, however, presents the challenge of considering both sensing and communication objectives within a distributed system. With the motivation of overcoming this challenge, this dissertation investigates diverse beamforming and power allocation solutions. Comprehensive evaluations have shown that the incorporation of sensing objectives into joint beamforming designs offers substantial capabilities for next-generation wireless communication and sensing systems.
ContributorsDemirhan, Umut (Author) / Alkhateeb, Ahmed (Thesis advisor) / Dasarathy, Gautam (Committee member) / Trichopoulos, Georgios (Committee member) / Michelusi, Nicolò (Committee member) / Arizona State University (Publisher)
Created2024