A Comparative Study of Piano Performance Programs at University-Level Institutions in China and the United States

Jiang, Yuan ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

As we work and study in our increasingly globalized society, there is a growing trend of Chinese piano students choosing to pursue their higher education in the United States. Elite music institutions in America are also seeking and recruiting a large number of Chinese pianists. This trend raises questions regarding the similarities and differences between Chinese and American piano performance programs in university-level institutions. The purpose of this study was to promote a greater understanding of Chinese and American piano performance programs in higher education through examining selected university-level institutions. To accomplish this goal, (1) the researcher collected data from the selected university-level institutions in both countries regarding their piano-related degree offerings, audition requirements, curriculum requirements, and core course offerings for the piano performance programs. These data were used to analyze and compare the structure and design of piano performance degree programs in both countries.

Using State Policy Determinants to Predict For-Profit Undergrraduate Enrollment Share at Degree-Granting Institutions

Kleuver, Steven A ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

For-profit institutions are thought to fill the educational gap when traditional nonprofit colleges fail to serve the needs of an evolving student population. Over the past several decades, the enrollment share of undergraduate students attending for-profit institutions in lieu of traditional nonprofit institutions has expanded substantially. While this growth has been noted by researchers, comparatively little is known about what determinants impact the state enrollment share of students attending for-profit institutions. Furthermore, the chronicling of state policy directed at for-profit institutions has not been completed in a concise and accessible manner. This study uses a panel dataset spanning the years 1997 to 2015 to measure for-profit enrollment to determine the effects of select state-level policy variables on the undergraduate enrollment share of for-profit institutions.Results of this study showed that state policies do impact for-profit enrollment share. After cataloging relevant state policies, 18 laws across 10 states were found to directly address the for-profit sector. As predicted, laws favorable to for-profit institutions (positive laws) were found to increase for-profit enrollment share and laws regulating for-profit institutions (negative laws) were found to decrease for-profit enrollment share. Educational appropriations per student FTE and the existence of a consolidated governing board were also found as controllable variables that impact for-profit enrollment share.

A Simulation-Based Optimization of Multiyear Infrastructure Planning for Connected and Automated Vehicles

Sanusi, Fehintola B ProQuest Dissertations & Theses The Florida State 2022 해외박사(DDOD)

A wide adoption of connected and automated vehicles (CAVs) is anticipated in the near future given their demonstrated benefits of the in terms of safety, mobility, and environmental sustainability. Such prediction highlights a need to prepare the roadway infrastructure to facilitate safer and more reliable operation of these technologies. While acknowledging this notion, many state and local planning agencies have developed multiyear infrastructure programs for successful deployment of CAVs in a timely manner within their limited budgets. Meanwhile, the traffic environment does not remain static but will evolve over time as CAV technologies become available (i.e., toward the mixed environment of autonomous and human-driven vehicles), which requires infrastructure plans specific to different planning terms (i.e., short-, middle-, and long-term) to accommodate changing infrastructure needs. To develop an effective long-range plan, planning agencies need to understand changing infrastructure needs over time, identify alternative infrastructure options for different planning terms, and develop an optimal portfolio of CAV infrastructure projects, based on the varying infrastructure needs of the traffic environment. This study develops an analytical framework to guide a holistic approach to multiyear infrastructure planning for CAVs. To be more specific, the proposed framework uses a five-step approach. First, the framework uses a systematic literature review to identify a group of infrastructure options to support CAV system functions (e.g., merging and platooning). The next step is to prioritize roadway locations in need of infrastructure improvement based on the potential contribution of CAVs to their local traffic through a geographical information system analysis. To predict future infrastructure needs, the framework develops a generalized Bass diffusion model to forecast CAV adoption rates for short-, medium-, and long-term planning phases. Fourth, a traffic micro-simulation model is employed to evaluate the performance of the future mixed traffic environment under various infrastructure planning scenarios. Lastly, a genetic algorithm-based metaheuristic optimization model is proposed to guide effective selection of an optimal infrastructure plan that improves traffic performance in the entire network while minimizing the cost of implementation of infrastructure options for each planning term. As a proof concept, this study demonstrates the application of the proposed multiyear infrastructure planning framework for CAVs with a case study of selected freeway segments on Interstate-4 in Florida state. Results of the analysis indicate that the proposed method can identify optimal infrastructure plans comprising of optimal set of infrastructure improvements that can minimize travel time while satisfying budgetary constraints. It is also observed that the proposed framework consistently allocates more than 50% of the budget to the long-term planning phase while it seeks to evenly distribute the remaining budget between the medium-term and short-term planning phases. This analytical framework can therefore serve as a useful tool to decision makers to guide an effective multiyear CAV infrastructure plan for their transportation system.

The Star-Spangled Consciousness: Musical Theatre Anthems of Unity and The Performance of National Identity

Gibbes, Allison B ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

Musical theatre scholars agree that as popular culture, musical theatre has had a profound effect on the development of national identity in the United States. In particular, the genre reaches audiences both inside and outside the theatre through the dissemination of cast recordings, sheet music, and other media. In early incarnations of musical theatre such as the works of George Gershwin and George M. Cohan, musicals typically included overt nationalist anthems designed to inspire and unite the audience in the name of America. With "Oklahoma," the title song of Rodgers and Hammerstein's Oklahoma! (1943), and the subsequent Golden Age of musical theatre, the convention of the anthem shifted to express nationalism through the lens of a community within the fictional world of the musical. These anthems serve as models for patriotic unity. In the decades following the Golden Age, some works of musical theatre challenged nationalism, and the anthems in these pieces reflect that sense of questioning. This project considers anthems of unity in musical theatre and the way they formulate identity through musical structures and conventions. I investigate four musical theatre anthems: "Oklahoma" from Oklahoma! (1943), "My Texas" from Giant (2012), "Southern Days" from The Scottsboro Boys (2010), and "Another National Anthem" from Assassins (1991).By analyzing the way that each anthem constructs group identity, I consider the way these constructions speak to national identity within both the musical and the historical context of the original production. Each anthem approaches national identity and nationalism in a different way by using and/or distorting musical conventions that hold cultural meaning in specific time periods. Additionally, I consider the way the anthem functions in conversation with the way the musical constructs history and popular memory, and how these formulations work together to create communities of insiders and outsiders through national identity and nationalism. I argue that each anthem operates dramaturgically, musically, and within a specific historical moment to address and reify or subvert constructions of mainstream national identity. This dissertation asks: what is the role of anthem-singing in US national identity? How does national identity create constructions of belonging and otherness? And how might we reconsider the way musical theatre as a genre is particularly effective site for conversations about the ramifications of othering.

An Exploration of the Effects of Primary and Secondary Trauma on Child Welfare Workers' Mental Health and Commitment to the Field

King, Erin Albrecht ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

The field of child welfare continues to suffer due to high rates of worker turnover. The child welfare workforce plays a crucial role in promoting child well-being and preventing abuse and neglect. When workers leave their jobs, sometimes after only a few months, at-risk children are negatively impacted. Work-related trauma exposure of workers is an understudied area. This study revealed three categories of trauma workers experience as a part of their jobs. Analyses examined the relationship between type of trauma exposure and personal and work-related outcomes of child welfare workers in the state of Florida.This study examined workers' exposure to trauma from a stress-response framework. Conservation of resources theory and identity theory informed the conceptual model for this study. This model examined how different typologies of trauma influence workers' mental health and commitment to the field of child welfare. Mental health was examined as a potential mediator in the relationship between trauma and commitment to the field.A sample of child welfare workers who had been employed in the field for 18-months (n = 657) responded to items relating to their experiences of client perpetrated violence, deaths or injuries on their caseloads, and secondary trauma. They also completed scales measuring their current levels of depression, anxiety, PTSD (at 18 months), and their overall commitment to the field of child welfare (measured at 2 years post-hire). T-tests, ANOVA analyses, and structural equation modeling (consisting of confirmatory factor analysis and path analysis) were used to determine the prevalence, severity, and effects of trauma exposure on workers.Three typologies of trauma emerged: primary trauma, caseload trauma, and secondary trauma. Threat emerged as the most reported form of primary trauma in this sample (78.4%), followed by non-physical violence (44.8%), and then assault (5.7%). Twenty-six percent (26%) of workers met the criteria for moderate to severe secondary trauma symptomatology. Relating to caseload trauma, 7.7% (n = 49) of workers reported death of a child on their caseload due to maltreatment, 16.7% (n = 106) reported the death of a child due to accident/injury, and 29.4% (n = 187) reported the severe illness/injury of a child on their caseload. Moderate to severe levels of anxiety and PTSD were found in 4.3% and 3.7% of these child welfare workers. Depression levels for workers were higher, with 16.6% reporting moderate levels of depression. Structural equation modeling (SEM) analysis indicated that primary trauma had a small, but positive relationship with commitment to the field (B = .17, p < .05). Caseload trauma predicted workers' levels of secondary trauma (B = .14, p < .05), and secondary trauma had a strong, predictive relationship with worker mental health (B = .77, p < .001).Each type of trauma contributed differentially to workers' personal and organizational outcome. These findings contribute important information about the prevalence and effects of different types of trauma child welfare workers face as a part of their job. Results of this study have implications for administrative practice, training, and intervention development in child welfare.Limitations of this study included participant attrition, a limited measurement period for mental health, and the use of dichotomous variables to measure primary and caseload trauma. Future research should focus on exploring these relationships between worker trauma exposure and personal/organization outcomes longitudinally and by using qualitative research methods to examine workers' experiences in more depth.

One Year Later: A Study of the Motivational Profiles of Students Who Participated in a Grit and Growth Mindset Themed First-year Experience Course at An Urban Community College

Gibson, Kandeice A ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

The issue of low community college retention and completion rates has become an important concern in recent years. The lack of persistence among college students has led to a variety of institutional initiatives including first-year experience courses, intrusive advising, and other innovative approaches. Among these approaches, First-Year Experience (FYE) courses are consistently supported as a promising retention strategy. To that end, the purpose of this mixed-method study was to investigate the motivation and first-year experience of students who participated in a Grit and Growth Mindset themed FYE course and persisted beyond the first year. Survey data were collected from 122 students and focus group interviews were conducted with 10 students at a large community college in southeast Florida. The survey data analyses using Independent Samples T-test, ANOVA, and Correlation showed that female students and older students reported a higher level of motivation than male and younger students, but there was no statistically significant difference in their motivation level by race/ethnicity. The focus group interviews revealed that students found three aspects of the FYE course influential to their motivation: (1) short-term and long-term goal setting, (2) self-reflection, and (3) support and resources. They also reported that time management strategies and supports from professors, peers, and family helped them overcome their challenges associated with balancing jobs and coursework, as well as anxiety and nervousness about their ability to complete college. An important implication of this study is for community colleges to continue emphasizing FYE courses to ensure that incoming students feel confident about their ability to achieve success during the first year and persist by overcoming obstacles. In addition, colleges should continue to equip students with practical tools and resources, such as time-management and the SMART goal framework, that support their competence and autonomy in charting their path to success.

Populated Polygons to Networks: A Population-Centric Approach to Spatial Network Allocation

Gaboardi, James D ProQuest Dissertations & Theses The Florida State 2019 해외박사(DDOD)

This dissertation establishes an original solution for allocating populations onto networks, which is demonstrated through empirical examples within the comprising census geographies of a single census tract and the comprising census geographies for an entire county. The novel method, populated polygons to networks (pp2n), is shown to perform as accurately as a current state-of-the-art method, while being less computationally complex. Benchmark datasets are utilized to represent household-level population distributions. Datasets generated from the methods of network allocation are applied to optimal facility location modeling scenarios.Networks are an underlying part of the human experience and, as such, attention must be given to their study in the spatial analysis of anthropocentric phenomena. However, transformations in spatial data must frequently be performed in order to allow for the integration of original disparate data formats. Such is often the case with spatial population data, which are generally available as polygons. As a means to build network-based models for analysis, certain methods have been developed for allocating populations onto networks for the purpose of calculating origin-to-destination cost (distance) matrices. Two of these methods include (1) simply snapping polygon centroids onto the nearest network segment and (2) dividing population values by area and proximity to the network. Here the new method, pp2n, is proposed that incorporates the strengths of both the existing methods, while mitigating their weaknesses. The traditional approach, the state-of-the-art approach, and the pp2n method are tested against a benchmark dataset representing population-weighted estimates for property parcels. It is shown that the pp2n method is less computationally complex in the worst-case scenario than the current state-of-the-art method and more representationally accurate that the traditional method. Further, in an empirical example within one census tract in Leon County, FL, the pp2n method is found to perform with comparable accuracy to the state-of-the-art approach when compared to both the traditional approach and the benchmark dataset. Also, it is shown that the algorithm for generating pp2n population weights runs in significantly less realtime.Extending the empirical example within a single census tract (and comprising geographies), another complete empirical example is performed on the full spatial extent of Leon County, Florida. Here the focus shifts from purely how the population data are being allocated to the network, to validating the spatial data utilized in modeling and understanding the inherent associated uncertainty. Permission to access a highly-restricted address data file, the Master Address File (MAF), was granted by the U.S. Census Bureau. Within this study, the MAF functions as an ultimate gold-standard benchmark to test all the methods used in this dissertation within the context of the 2010 Decennial Census. Disclosure and privacy are discussed and a critique is given for the method used to produce the population-weighted estimates for property parcels. It is then shown, as in the single census tract example, that the pp2n method performs as well as the state-of-the-art method, while doing so in substantially less runtime. Further, the property parcel dataset is validated as an acceptable surrogate for true housing units available from the MAF.Facility location modeling is utilized to determine the effects of the network allocation methods on optimal site selection. Following a review of mathematical programming and the uncertainty involved in spatial optimization, the network allocation methods are tested with four fundamental models within a spatial optimization framework: the location set covering problem, maximal covering location problem, p-median problem, and p-center problem. The linear integer programs are solved for each model, for each method at each spatial extent with 15 sets of parameters. In total, 780 models are solved to optimality. The results of the abstract population representation models are compared again to the population-weighted estimates for property parcels, which act as a surrogate for the benchmark truth of census microdata. Results show that the method of network allocation has a non-negligible effect on the solutions to facility location models. Specifically, optimal facility configurations of the location models are affected within the selected spatio-temporal study area: 2010 Leon County, FL.

What Fire Chiefs Think and Organizational Directors Know: A Study of the Potential Benefits of Higher Education for the Fire Service

Dilks, John Daniel, Jr ProQuest Dissertations & Theses The Florida State 2018 해외박사(DDOD)

The fire chiefs of today realize the importance of higher education. This is evident in the seminal works of the 1966 Wing Spread I conference and the United States Fire Administration's Fire and Emergency Services Higher Education Project (FESH. The mixed methods approach demonstrated that the quantitative study results were more than adequate to provide a snap shot of Florida's Fire Service in regards to their perception of necessity for higher education in the development of future of.

Inference from Longitudinal Imaging Data Using SPDM Trajectories

Dai, Mengyu ProQuest Dissertations & Theses The Florida State 2020 해외박사(DDOD)

This dissertation includes mainly four chapters. The first chapter studies change-points in human brain functional connectivity (FC) and seek patterns that are common across multiple subjects under identical external stimulus. FC, represented mathematically as a covariance or a correlation matrix, relates to the similarity of fMRI responses across different brain regions when a brain is simply resting or performing a task. While the dynamical nature of FC is well accepted, this paper develops a formal statistical test for finding change-points in times series associated with FC. It represents instantaneous (or short term) connectivity by a symmetric positive-definite matrix, and uses a Riemannian metric on this space to develop a graphical method for detecting change-points in a time series of such matrices. It also provides a graphical representation of estimated FC for stationary subintervals in between the detected change-points. Furthermore, it uses a temporal alignment of the test statistic, viewed as a real-valued function over time, to remove intersubject variability and to discover common change-point patterns across subjects.The second aims to quantitively compare the dynamic nature of human brain functional connectivity (FC) using a distance measure and use the distance feature for classifications at network level across multiple subjects under external stimulus or during resting state. It represents dynamic FCs by a sequence of SPDMs, and uses a Riemannian metric on this space to quantify the dissimilarity between such trajectories. It also proposes a metric-based dimensionality reduction technique for SPDMs to improve the method's efficiency with tolerent information loss. Both methods are illustrated using data from Human Connectome Project (HCP) database for multiple subjects and tasks.While the first two chapters mainly focus on studying medical imaging problems, the third and fourth chapters aim to provide solutions to some computer vision tasks. The third chapter talks about classifications of covariance trajectories in the application of video action recognition. One can first extract features from video frames using existing CNN frameworks. Each frame is represented by a covariance matrix estimated from the extracted features and, thus, a video is represented as a sequence of covariance matrices. Next, the dimension-reduction approach introduced in Chapter 2, based on the chosen Riemannian metric of SPDMs, are applied to bring down dimensions of individual covariances for comparing these reduced trajectories. Finally, the distance features acquired from these trajectories are used for video classification.The fourth chapter introcudes a new approach of Generative Adversarial Networks (GAN) based on a nonparametric geometric transformation called the square-root velocity function (SRVF). In the proposed framework, the output feature vectors of the last dense layer in the discriminator are treated as real-valued functions rather than a vector of numbers. The geometric central moments are then defined using a certain distance, termed {\\it Fisher-Rao distance} (FRD), between data points and a reference point in a function space. By using SRVF transformation, calculating FRD in the original function space is equivalent to calculating L2 distance between their corresponding transformed objects. Thus, computing FRD between objects become fast and simple.

Numerical Solutions of the Many-Electron Ground State

McFarland, John ProQuest Dissertations & Theses The Florida State 2022 해외박사(DDOD)

We examine two wave function optimization methods for producing the ground state. The first is a novel method for optimizing the location of the nodes of the fermion ground-state using a combination of diffusion Monte Carlo (DMC) and projected gradient descent (PGD). A PGD iteration shifts the parameters of a node-fixing trial function in the opposite direction of the DMC energy gradient, while maintaining the cusp condition for atomic electrons if necessary. The energy gradient required for this is calculated from DMC walker distributions by one of three methods derived from an exact analytical expression. The energy gradient calculation methods are combined with different gradient descent algorithms and a projection operator that maintains the cusp condition of atomic systems. We apply this PGD method to trial functions with randomized variational parameters, for simple atomic systems and the homogeneous electron gas, and the nodes are dramatically improved. For atomic systems, PGD lowered the DMC energy to the same level as nodes optimized by variational Monte Carlo (VMC). This PGD method departs from the standard procedure of optimizing the nodes with a non-DMC scheme such as variational Monte Carlo, Density function theory, or configuration interaction based calculation, which do not directly minimize the DMC energy. The second ground state optimization method that we examine implements imaginary-time time-dependent Density functional theory (it-TDDFT) propagation to periodic systems by modifying the Quantum ESPRESSO (QE) package. This implementation of it-TDDFT propagation converges to the exact energy produced by the standard self consistent field (SCF) method in all but one case, where it converged to a slightly lower value than SCF. This suggests it-TDDFT is a useful alternative for systems where SCF has difficulty reaching the Kohn-Sham ground state.