Matching Items (428)
Description
Although opera is the last musical genre one typically associates with Latin America, Mexican composer Daniel Catán (1949-2011) found surprising success across the United States and overseas with his opera Florencia en el Amazonas (1996). Catán blends colorful music with literary elements to create a representation of Latin American culture through language, drama, scenery, and music. Among these elements is realism mágico (magical realism), a significant characteristic of Latin American literature. Indeed, the plot of the opera is influenced by Gabriel García Márquez's novel, El amor en los tiempos del cólera (Love in the Time of Cholera, 1985), as well as the poem "Mariposa de obsidiana" (Obsidian Butterfly, 1951) and the short story "La hija de Rappaccini" (Rappaccini's Daughter, 1953), both by Octavio Paz. To create his protagonist in the opera, Florencia Grimaldi, Catán combines the dramatic qualities of several European soprano heroines. This figure's character development is conveyed largely through her Act I, Scene 2, aria, "Florencia Grimaldi," and her Act II, Scene 17, aria, "Escúchame." An overview of the opera places these two arias into context, and their musical content and text-setting are closely examined in relation to the character of Florencia. Finally, how Daniel Catán creates a soprano heroine from the Latin American perspective is discussed.
ContributorsFlores, Andrea, D.M.A (Author) / FitzPatrick, Carole (Thesis advisor) / Dreyfoos, Dale (Committee member) / Holbrook, Amy (Committee member) / May, Judy (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2013
Description
Libby Larsen is one of the most performed and acclaimed composers today. She is a spirited, compelling, and sensitive composer whose music enhances the poetry of America's most prominent authors. Notable among her works are song cycles for soprano based on the poetry of female writers, among them novelist and poet Willa Cather (1873-1947). Larsen has produced two song cycles on works from Cather's substantial output of fiction: one based on Cather's short story, "Eric Hermannson's Soul," titled Margaret Songs: Three Songs from Willa Cather (1996); and later, My Antonia (2000), based on Cather's novel of the same title. In Margaret Songs, Cather's poetry and short stories--specifically the character of Margaret Elliot--combine with Larsen's unique compositional style to create a surprising collaboration. This study explores how Larsen in these songs delves into the emotional and psychological depths of Margaret's character, not fully formed by Cather. It is only through Larsen's music and Cather's poetry that Margaret's journey through self-discovery and love become fully realized. This song cycle is a glimpse through the eyes of two prominent female artists on the societal pressures placed upon Margaret's character, many of which still resonate with women in today's culture. This study examines the work Margaret Songs by discussing Willa Cather, her musical influences, and the conditions surrounding the writing of "Eric Hermannson's Soul." It looks also into Cather's influence on Libby Larsen and the commission leading to Margaret Songs. Finally, a description of the musical, dramatic, and textual content of the songs completes this interpretation of the interactions of Willa Cather, Libby Larsen, and the character of Margaret Elliot.
ContributorsMcLain, Christi Marie (Author) / FitzPatrick, Carole (Thesis advisor) / Dreyfoos, Dale (Committee member) / Holbrook, Amy (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2013
Description
Structural health management (SHM) is emerging as a vital methodology to help engineers improve the safety and maintainability of critical structures. SHM systems are designed to reliably monitor and test the health and performance of structures in aerospace, civil, and mechanical engineering applications. SHM combines multidisciplinary technologies including sensing, signal processing, pattern recognition, data mining, high fidelity probabilistic progressive damage models, physics based damage models, and regression analysis. Due to the wide application of carbon fiber reinforced composites and their multiscale failure mechanisms, it is necessary to emphasize the research of SHM on composite structures. This research develops a comprehensive framework for the damage detection, localization, quantification, and prediction of the remaining useful life of complex composite structures. To interrogate a composite structure, guided wave propagation is applied to thin structures such as beams and plates. Piezoelectric transducers are selected because of their versatility, which allows them to be used as sensors and actuators. Feature extraction from guided wave signals is critical to demonstrate the presence of damage and estimate the damage locations. Advanced signal processing techniques are employed to extract robust features and information. To provide a better estimate of the damage for accurate life estimation, probabilistic regression analysis is used to obtain a prediction model for the prognosis of complex structures subject to fatigue loading. Special efforts have been applied to the extension of SHM techniques on aerospace and spacecraft structures, such as UAV composite wings and deployable composite boom structures. Necessary modifications of the developed SHM techniques were conducted to meet the unique requirements of the aerospace structures. The developed SHM algorithms are able to accurately detect and quantify impact damages as well as matrix cracking introduced.
ContributorsLiu, Yingtao (Author) / Chattopadhyay, Aditi (Thesis advisor) / Rajadas, John (Committee member) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012
Description
In this thesis, an integrated waveform-agile multi-modal tracking-beforedetect sensing system is investigated and the performance is evaluated using an experimental platform. The sensing system of adapting asymmetric multi-modal sensing operation platforms using radio frequency (RF) radar and electro-optical (EO) sensors allows for integration of complementary information from different sensors. However, there are many challenges to overcome, including tracking low signal-to-noise ratio (SNR) targets, waveform configurations that can optimize tracking performance and statistically dependent measurements. Address some of these challenges, a particle filter (PF) based recursive waveformagile track-before-detect (TBD) algorithm is developed to avoid information loss caused by conventional detection under low SNR environments. Furthermore, a waveform-agile selection technique is integrated into the PF-TBD to allow for adaptive waveform configurations. The embedded exponential family (EEF) approach is used to approximate distributions of parameters of dependent RF and EO measurements and to further improve target detection rate and tracking performance. The performance of the integrated algorithm is evaluated using real data from three experimental scenarios.
ContributorsLiu, Shubo (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Duman, Tolga (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2012
Description
Super-Resolution (SR) techniques are widely developed to increase image resolution by fusing several Low-Resolution (LR) images of the same scene to overcome sensor hardware limitations and reduce media impairments in a cost-effective manner. When choosing a solution for the SR problem, there is always a trade-off between computational efficiency and High-Resolution (HR) image quality. Existing SR approaches suffer from extremely high computational requirements due to the high number of unknowns to be estimated in the solution of the SR inverse problem. This thesis proposes efficient iterative SR techniques based on Visual Attention (VA) and perceptual modeling of the human visual system. In the first part of this thesis, an efficient ATtentive-SELective Perceptual-based (AT-SELP) SR framework is presented, where only a subset of perceptually significant active pixels is selected for processing by the SR algorithm based on a local contrast sensitivity threshold model and a proposed low complexity saliency detector. The proposed saliency detector utilizes a probability of detection rule inspired by concepts of luminance masking and visual attention. The second part of this thesis further enhances on the efficiency of selective SR approaches by presenting an ATtentive (AT) SR framework that is completely driven by VA region detectors. Additionally, different VA techniques that combine several low-level features, such as center-surround differences in intensity and orientation, patch luminance and contrast, bandpass outputs of patch luminance and contrast, and difference of Gaussians of luminance intensity are integrated and analyzed to illustrate the effectiveness of the proposed selective SR frameworks. The proposed AT-SELP SR and AT-SR frameworks proved to be flexible by integrating a Maximum A Posteriori (MAP)-based SR algorithm as well as a fast two-stage Fusion-Restoration (FR) SR estimator. By adopting the proposed selective SR frameworks, simulation results show significant reduction on average in computational complexity with comparable visual quality in terms of quantitative metrics such as PSNR, SNR or MAE gains, and subjective assessment. The third part of this thesis proposes a Perceptually Weighted (WP) SR technique that incorporates unequal weighting parameters in the cost function of iterative SR problems. The proposed approach is inspired by the unequal processing of the Human Visual System (HVS) to different local image features in an image. Simulation results show an enhanced reconstruction quality and faster convergence rates when applied to the MAP-based and FR-based SR schemes.
ContributorsSadaka, Nabil (Author) / Karam, Lina J (Thesis advisor) / Spanias, Andreas S (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Abousleman, Glen P (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
The legacy of the great double bassist and pedagogue Joseph Prunner (1886-1969) includes his scale and arpeggio exercise book, Progressive Studies for the Double Bass, composed in 1955. Progressive Studies was originally written for Prunner's students at the Bucharest Conservatoire and was not intended for a wide publication. In the work Prunner presents major and harmonic and melodic minor scales that are performed in one octave and then extended diatonically through all their modes, progressing through this pattern for three octaves, followed by a series of arpeggio exercises. These exercises are based on a modernized fingering system and are offered in the traditional positions and in what Prunner called "Fixed-Position" scales. A series of chromatic scale exercises are also included that follow the template of the major and minor scales. The study at hand is a revision and expansion of Prunner's work. The edition presented here intends to preserve the information that Prunner provided, fix the errors made in editing, and expand the study greatly by increasing the range of the exercises, providing more arpeggio exercises, creating melodic and harmonic minor "Fixed-Position" scales and arpeggio exercises, and including the study of double-stops. In support of the revised and updated version of Progressive Studies, this study includes a biography of Joseph Prunner and a summary of the importance of the type of scale and arpeggio practice the collection of exercises supports. An explanation of the revisions made to Prunner's work and recommendations for using the exercises also precede the new edition.
ContributorsStotz, Daniel Aaron (Author) / Rotaru, Catalin (Thesis advisor) / Holbrook, Amy (Committee member) / Kennedy, Jeffery (Committee member) / Koonce, Frank (Committee member) / Landschoot, Thomas (Committee member) / Arizona State University (Publisher)
Created2012
Description
New works for the bass clarinet as a solo instrument are uncommon. In the interest of expanding the repertoire of the bass clarinet, three new works for bass clarinet were commissioned from three different composers, all with different instrumentations. The resulting works are Industrial Strength for bass clarinet and piano by Kenji Bunch; Dark Embers for two bass clarinets by Theresa Martin; and Shovelhead for bass clarinet and interactive electronics by Steven Snowden. Although all three works feature the bass clarinet, they are all very different and pose unique challenges to the performer. To accompany these pieces, and as an aid to future performers, a performance practice guide has been included with recommendations for individuals who wish to perform these works. Included in the guide are recommended fingerings, practice techniques, and possible adjustments to the bass clarinet parts designed in collaboration with the composers that make the works more technically accessible. Accompanying this guide are full scores of all three works, a recording of them performed by the author, and a chart that contains recommended altissimo fingerings.
ContributorsMiracle, Matthew (Author) / Spring, Robert (Thesis advisor) / Gardner, Joshua (Committee member) / Holbrook, Amy (Committee member) / Micklich, Albie (Committee member) / Rogers, Rodney (Committee member) / Arizona State University (Publisher)
Created2012
Description
This paper is the writing component of a project the author under took to create an entertaining program for a chamber ensemble. It discusses ways for chamber ensembles to create entertaining concert programs for today's audiences. Information was gathered by analyzing four interesting and successful groups--The Canadian Brass, Mnozil Brass, Les Trompettes de Lyon, and The Blue Man Group--and identifying common traits. These traits help facilitate the ultimate goal of making connections with audiences and include originality, comedy, choreography, memorization, continuous presentation, musical appeal, high quality presentations, and the proper personnel. These attributes were then implemented into the author's experimental group, the Omni Brass Ensemble, for testing with live audiences. Materials were used from published interviews, articles, newspapers, ensemble websites, and recordings of their performances. From the author's performances with the Omni Brass Ensemble, indications are that these findings work with live audiences.
ContributorsLee, Randolph Thomas (Author) / Hickman, David (Thesis advisor) / Ericson, John (Committee member) / Holbrook, Amy (Committee member) / Pilafian, J. Samuel (Committee member) / Russell, Timothy (Committee member) / Arizona State University (Publisher)
Created2012
Description
Research on developing new algorithms to improve information on brain functionality and structure is ongoing. Studying neural activity through dipole source localization with electroencephalography (EEG) and magnetoencephalography (MEG) sensor measurements can lead to diagnosis and treatment of a brain disorder and can also identify the area of the brain from where the disorder has originated. Designing advanced localization algorithms that can adapt to environmental changes is considered a significant shift from manual diagnosis which is based on the knowledge and observation of the doctor, to an adaptive and improved brain disorder diagnosis as these algorithms can track activities that might not be noticed by the human eye. An important consideration of these localization algorithms, however, is to try and minimize the overall power consumption in order to improve the study and treatment of brain disorders. This thesis considers the problem of estimating dynamic parameters of neural dipole sources while minimizing the system's overall power consumption; this is achieved by minimizing the number of EEG/MEG measurements sensors without a loss in estimation performance accuracy. As the EEG/MEG measurements models are related non-linearity to the dipole source locations and moments, these dynamic parameters can be estimated using sequential Monte Carlo methods such as particle filtering. Due to the large number of sensors required to record EEG/MEG Measurements for use in the particle filter, over long period recordings, a large amounts of power is required for storage and transmission. In order to reduce the overall power consumption, two methods are proposed. The first method used the predicted mean square estimation error as the performance metric under the constraint of a maximum power consumption. The performance metric of the second method uses the distance between the location of the sensors and the location estimate of the dipole source at the previous time step; this sensor scheduling scheme results in maximizing the overall signal-to-noise ratio. The performance of both methods is demonstrated using simulated data, and both methods show that they can provide good estimation results with significant reduction in the number of activated sensors at each time step.
ContributorsMichael, Stefanos (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2012
Description
Composite materials are increasingly being used in aircraft, automobiles, and other applications due to their high strength to weight and stiffness to weight ratios. However, the presence of damage, such as delamination or matrix cracks, can significantly compromise the performance of these materials and result in premature failure. Structural components are often manually inspected to detect the presence of damage. This technique, known as schedule based maintenance, however, is expensive, time-consuming, and often limited to easily accessible structural elements. Therefore, there is an increased demand for robust and efficient Structural Health Monitoring (SHM) techniques that can be used for Condition Based Monitoring, which is the method in which structural components are inspected based upon damage metrics as opposed to flight hours. SHM relies on in situ frameworks for detecting early signs of damage in exposed and unexposed structural elements, offering not only reduced number of schedule based inspections, but also providing better useful life estimates. SHM frameworks require the development of different sensing technologies, algorithms, and procedures to detect, localize, quantify, characterize, as well as assess overall damage in aerospace structures so that strong estimations in the remaining useful life can be determined. The use of piezoelectric transducers along with guided Lamb waves is a method that has received considerable attention due to the weight, cost, and function of the systems based on these elements. The research in this thesis investigates the ability of Lamb waves to detect damage in feature dense anisotropic composite panels. Most current research negates the effects of experimental variability by performing tests on structurally simple isotropic plates that are used as a baseline and damaged specimen. However, in actual applications, variability cannot be negated, and therefore there is a need to research the effects of complex sample geometries, environmental operating conditions, and the effects of variability in material properties. This research is based on experiments conducted on a single blade-stiffened anisotropic composite panel that localizes delamination damage caused by impact. The overall goal was to utilize a correlative approach that used only the damage feature produced by the delamination as the damage index. This approach was adopted because it offered a simplistic way to determine the existence and location of damage without having to conduct a more complex wave propagation analysis or having to take into account the geometric complexities of the test specimen. Results showed that even in a complex structure, if the damage feature can be extracted and measured, then an appropriate damage index can be associated to it and the location of the damage can be inferred using a dense sensor array. The second experiment presented in this research studies the effects of temperature on damage detection when using one test specimen for a benchmark data set and another for damage data collection. This expands the previous experiment into exploring not only the effects of variable temperature, but also the effects of high experimental variability. Results from this work show that the damage feature in the data is not only extractable at higher temperatures, but that the data from one panel at one temperature can be directly compared to another panel at another temperature for baseline comparison due to linearity of the collected data.
ContributorsVizzini, Anthony James, II (Author) / Chattopadhyay, Aditi (Thesis advisor) / Fard, Masoud (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012