Matching Items (262)
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Description
There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such

There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such interventions. In this thesis, an approach is proposed to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone, an opioid antagonist, as treatment for a chronic pain condition known as fibromyalgia. System identification techniques are employed to model the dynamics from the daily diary reports completed by participants of a blind naltrexone intervention trial. These self-reports include assessments of outcomes of interest (e.g., general pain symptoms, sleep quality) and additional external variables (disturbances) that affect these outcomes (e.g., stress, anxiety, and mood). Using prediction-error methods, a multi-input model describing the effect of drug, placebo and other disturbances on outcomes of interest is developed. This discrete time model is approximated by a continuous second order model with zero, which was found to be adequate to capture the dynamics of this intervention. Data from 40 participants in two clinical trials were analyzed and participants were classified as responders and non-responders based on the models obtained from system identification. The dynamical models can be used by a model predictive controller for automated dosage selection of naltrexone using feedback/feedforward control actions in the presence of external disturbances. The clinical requirement for categorical (i.e., discrete-valued) drug dosage levels creates a need for hybrid model predictive control (HMPC). The controller features a multiple degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed loop system. The nominal and robust performance of the proposed control scheme is examined via simulation using system identification models from a representative participant in the naltrexone intervention trial. The controller evaluation described in this thesis gives credibility to the promise and applicability of control engineering principles for optimizing adaptive interventions.
ContributorsDeśapāṇḍe, Sunīla (Author) / Rivera, Daniel E. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban

The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. The PHD is based on the theory of random finite sets and it is implemented using the particle filter. Unlike data association methods, it can be used to estimate the number of targets as well as their corresponding tracks. A modified maximum-likelihood version of the PHD (MPHD) is proposed to automatically and adaptively estimate the measurement types available at each time step. Specifically, the MPHD allows measurement-to-nonlinearity associations such that the best matched measurement can be used at each time step, resulting in improved radar coverage and scene visibility. Numerical simulations demonstrate the effectiveness of the MPHD in improving tracking performance, both for tracking multiple targets and targets in clutter.
ContributorsZhou, Meng (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Owen Middleton (b. 1941) enjoys an established and growing reputation as a composer of classical guitar music, but his works for piano are comparatively little known. The close investigation offered here of Middleton's works for piano reveals the same impressive craftsmanship, compelling character, and innovative spirit found in his works

Owen Middleton (b. 1941) enjoys an established and growing reputation as a composer of classical guitar music, but his works for piano are comparatively little known. The close investigation offered here of Middleton's works for piano reveals the same impressive craftsmanship, compelling character, and innovative spirit found in his works for guitar. Indeed, the only significant thing Middleton's piano music currently lacks is the well-deserved attention of professional players and a wider audience. Middleton's piano music needs to be heard, not just discussed, so one of this document's purposes is to provide a recorded sample of his piano works. While the overall repertoire for solo piano is vast, and new works become established in that repertoire with increasing difficulty, Middleton's piano works have a significant potential to find their way into the concert hall as well as the private teaching studio. His solo piano music is highly effective, well suited to the instrument, and, perhaps most importantly, fresh sounding and truly original. His pedagogical works are of equal value. Middleton's piano music offers something for everyone: there one finds daring virtuosity, effusions of passion, intellectual force, colorful imagery, poetry, humor, and even a degree of idiomatic innovation. This study aims to reveal key aspects of the composer's musical style, especially his style of piano writing, and to provide pianists with helpful analytical, technical, and interpretive insights. These descriptions of the music are supported with recorded examples, selected from the works for solo piano written between 1962 and 1993: Sonata for Piano, Childhood Scenes, Katie's Collection, and Toccata for Piano. The complete scores of the recorded works are included in the appendix. A chapter briefly describing the piano pieces since 1993 concludes the study and invites the reader to further investigations of this unique and important body of work.
ContributorsMoreau, Barton Andrew (Author) / Hamilton, Robert (Thesis advisor) / Holbrook, Amy (Committee member) / Campbell, Andrew (Committee member) / Spring, Robert (Committee member) / Gardner, Joshua (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Genomic and proteomic sequences, which are in the form of deoxyribonucleic acid (DNA) and amino acids respectively, play a vital role in the structure, function and diversity of every living cell. As a result, various genomic and proteomic sequence processing methods have been proposed from diverse disciplines, including biology, chemistry,

Genomic and proteomic sequences, which are in the form of deoxyribonucleic acid (DNA) and amino acids respectively, play a vital role in the structure, function and diversity of every living cell. As a result, various genomic and proteomic sequence processing methods have been proposed from diverse disciplines, including biology, chemistry, physics, computer science and electrical engineering. In particular, signal processing techniques were applied to the problems of sequence querying and alignment, that compare and classify regions of similarity in the sequences based on their composition. However, although current approaches obtain results that can be attributed to key biological properties, they require pre-processing and lack robustness to sequence repetitions. In addition, these approaches do not provide much support for efficiently querying sub-sequences, a process that is essential for tracking localized database matches. In this work, a query-based alignment method for biological sequences that maps sequences to time-domain waveforms before processing the waveforms for alignment in the time-frequency plane is first proposed. The mapping uses waveforms, such as time-domain Gaussian functions, with unique sequence representations in the time-frequency plane. The proposed alignment method employs a robust querying algorithm that utilizes a time-frequency signal expansion whose basis function is matched to the basic waveform in the mapped sequences. The resulting WAVEQuery approach is demonstrated for both DNA and protein sequences using the matching pursuit decomposition as the signal basis expansion. The alignment localization of WAVEQuery is specifically evaluated over repetitive database segments, and operable in real-time without pre-processing. It is demonstrated that WAVEQuery significantly outperforms the biological sequence alignment method BLAST for queries with repetitive segments for DNA sequences. A generalized version of the WAVEQuery approach with the metaplectic transform is also described for protein sequence structure prediction. For protein alignment, it is often necessary to not only compare the one-dimensional (1-D) primary sequence structure but also the secondary and tertiary three-dimensional (3-D) space structures. This is done after considering the conformations in the 3-D space due to the degrees of freedom of these structures. As a result, a novel directionality based 3-D waveform mapping for the 3-D protein structures is also proposed and it is used to compare protein structures using a matched filter approach. By incorporating a 3-D time axis, a highly-localized Gaussian-windowed chirp waveform is defined, and the amino acid information is mapped to the chirp parameters that are then directly used to obtain directionality in the 3-D space. This mapping is unique in that additional characteristic protein information such as hydrophobicity, that relates the sequence with the structure, can be added as another representation parameter. The additional parameter helps tracking similarities over local segments of the structure, this enabling classification of distantly related proteins which have partial structural similarities. This approach is successfully tested for pairwise alignments over full length structures, alignments over multiple structures to form a phylogenetic trees, and also alignments over local segments. Also, basic classification over protein structural classes using directional descriptors for the protein structure is performed.
ContributorsRavichandran, Lakshminarayan (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Spanias, Andreas S (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Lacroix, Zoé (Committee member) / Arizona State University (Publisher)
Created2011
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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

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
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Description
Bohuslav Martinù (1890-1959) was a prolific composer who wrote nearly 100 works for piano. His highly imaginative and eclectic style blends elements of the Baroque, Impressionism, Twentieth-century idioms and Czech folk music. His music is fresh and appealing to the listener, yet it remains intriguing as to how all the

Bohuslav Martinù (1890-1959) was a prolific composer who wrote nearly 100 works for piano. His highly imaginative and eclectic style blends elements of the Baroque, Impressionism, Twentieth-century idioms and Czech folk music. His music is fresh and appealing to the listener, yet it remains intriguing as to how all the elements are combined in a cohesive manner. Martinù himself provides clues to his compositional process. He believed in pure musical expression and the intensity of the musical idea, without the need for extra-musical or programmatic connotations. He espoused holistic and organic views toward musical perception and composition, at times referring to a work as an "organism." This study examines Martinù's piano style in light of his many diverse influences and personal philosophy. The first portion of this paper discusses Martinù's overall style through several piano miniatures written throughout his career. It takes into consideration the composer's personal background, musical influences and aesthetic convictions. The second portion focuses specifically on Martinù's first large-scale work for piano, the Fantasie et Toccata, H. 281. Written during a time in which Martinù was black-listed by the Nazis and forced to flee Europe, this piece bears witness to the chaotic events of WWII through its complexity and intensity of character. The discussion and analysis of the Fantasie et Toccata intends to serve as a guide to interpretation for the performer or listener and also seeks to promote the piano music of Bohuslav Martinù to a wider audience.
ContributorsCrane-Waleczek, Jennifer (Author) / Hamilton, Robert (Thesis advisor) / Hackbarth, Glenn (Committee member) / Meyer Thompson, Janice (Committee member) / Norton, Kay (Committee member) / Campbell, Andrew (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Despite a quickly growing repertoire list for the brass quintet, the music of the early Argentine tango has remained relatively neglected by brass quintet arrangers and performers. With the goal of bringing a neglected art form to the brass quintet repertoire, three arrangements based on early twentieth century Argentine tango

Despite a quickly growing repertoire list for the brass quintet, the music of the early Argentine tango has remained relatively neglected by brass quintet arrangers and performers. With the goal of bringing a neglected art form to the brass quintet repertoire, three arrangements based on early twentieth century Argentine tango songs are presented here: "Elegante Papirusa" by Tito Roccatagliata, "A La Gran Muñeca" by Jesús Ventura, and "La Cotorrita" by Samuel Castriota. The arrangements follow the style of three early recordings produced by The Victor Talking Machine in 1920 and 1922, as performed by two authentic Argentine orquesta típicas: Orquesta Típica Select and Orquesta Típica Fresedo. A brief history of the style and instrumental evolution of tango music from its influences and origins up until 1920 is discussed, followed by a detailed account of the musicians and circumstances involved in the three early recordings. An explanation of the issues encountered by the author in adapting the early tango style to the brass quintet setting is discussed, along with the solutions realized in order to make the project successful and practical for a moderately advanced brass quintet. The full brass quintet scores are provided as part of the Appendix.
ContributorsCamacho, Gustavo (Musician) (Author) / Ericson, John Q (Thesis advisor) / Pilafian, Samuel (Committee member) / Schuring, Martin (Committee member) / Campbell, Andrew (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2011
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Description
As clarinet compositions created by Taiwanese composers have not been widely discussed and published in academia, this research paper examines three unaccompanied clarinet works by three Taiwanese composers: Ballade by Hsiao-Wen Tseng, Chin Thoughts III by Ling-Huei Tsai, and Pointe de Flame by Chia-Lin Pan, all commissioned by the author

As clarinet compositions created by Taiwanese composers have not been widely discussed and published in academia, this research paper examines three unaccompanied clarinet works by three Taiwanese composers: Ballade by Hsiao-Wen Tseng, Chin Thoughts III by Ling-Huei Tsai, and Pointe de Flame by Chia-Lin Pan, all commissioned by the author in 2007. This research also includes a compact disc with recordings of these works, aiming to document the creativity of Taiwanese composers. This research paper examines these three commissioned works by analyzing their overall musical styles, notations, formal structures, rhythmical and melodic materials, unconventional clarinet techniques as well as the influence of Chinese musical elements. The analysis reveals the distinctive characteristic of each piece. Moreover, the author provides composers' insights and performance guides to help interested readers practice these pieces. To further understand how the composers create these pieces by drawing upon different life experiences, the paper also includes information about their backgrounds, program notes, lists of compositions, and music examples for reference. The author found that collaborating with these composers helped to establish a closer composer-performer relationship in interpreting the music. It is hoped that this compact disc recording will help make Taiwanese composers' clarinet works more accessible to a wider audience. Moreover, this research paper hopes to generate more interest in performing and appreciating music composed by Taiwanese composers.
ContributorsChuang, Yenting (Author) / Spring, Robert (Thesis advisor) / Schuring, Martin (Committee member) / Campbell, Andrew (Committee member) / Jiang, Danwen (Committee member) / Hackbarth, Glenn (Committee member) / Arizona State University (Publisher)
Created2011
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Description
In the late 1960s, Granger published a seminal study on causality in time series, using linear interdependencies and information transfer. Recent developments in the field of information theory have introduced new methods to investigate the transfer of information in dynamical systems. Using concepts from Chaos and Markov theory, much of

In the late 1960s, Granger published a seminal study on causality in time series, using linear interdependencies and information transfer. Recent developments in the field of information theory have introduced new methods to investigate the transfer of information in dynamical systems. Using concepts from Chaos and Markov theory, much of these methods have evolved to capture non-linear relations and information flow between coupled dynamical systems with applications to fields like biomedical signal processing. This thesis deals with the application of information theory to non-linear multivariate time series and develops measures of information flow to identify significant drivers and response (driven) components in networks of coupled sub-systems with variable coupling in strength and direction (uni- or bi-directional) for each connection. Transfer Entropy (TE) is used to quantify pairwise directional information. Four TE-based measures of information flow are proposed, namely TE Outflow (TEO), TE Inflow (TEI), TE Net flow (TEN), and Average TE flow (ATE). First, the reliability of the information flow measures on models, with and without noise, is evaluated. The driver and response sub-systems in these models are identified. Second, these measures are applied to electroencephalographic (EEG) data from two patients with focal epilepsy. The analysis showed dominant directions of information flow between brain sites and identified the epileptogenic focus as the system component typically with the highest value for the proposed measures (for example, ATE). Statistical tests between pre-seizure (preictal) and post-seizure (postictal) information flow also showed a breakage of the driving of the brain by the focus after seizure onset. The above findings shed light on the function of the epileptogenic focus and understanding of ictogenesis. It is expected that they will contribute to the diagnosis of epilepsy, for example by accurate identification of the epileptogenic focus from interictal periods, as well as the development of better seizure detection, prediction and control methods, for example by isolating pathologic areas of excessive information flow through electrical stimulation.
ContributorsPrasanna, Shashank (Author) / Jassemidis, Leonidas (Thesis advisor) / Tsakalis, Konstantinos (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2011
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Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended

This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013