This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

Displaying 1 - 10 of 201
Description
CYOA is a prototype of an iPhone application that produces a single, generative, musical work. This document details some of the thoughts and practices that informed its design, and specifically addresses the overlap between application structure and musical form. The concept of composed instruments is introduced and briefly discussed, some

CYOA is a prototype of an iPhone application that produces a single, generative, musical work. This document details some of the thoughts and practices that informed its design, and specifically addresses the overlap between application structure and musical form. The concept of composed instruments is introduced and briefly discussed, some features of video game design that relate to this project are considered, and some specifics of hardware implementation are addressed.
ContributorsPeterson, Julian (Author) / Hackbarth, Glenn (Thesis advisor) / DeMars, James (Committee member) / Feisst, Sabine (Committee member) / Levy, Benjamin (Committee member) / Tobias, Evan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a

The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Johann Sebastian Bach's violin Sonata I in G minor, BWV 1001, is a significant and widely performed work that exists in numerous editions and also as transcriptions or arrangements for various other instruments, including the guitar. A pedagogical guitar performance edition of this sonata, however, has yet to be published.

Johann Sebastian Bach's violin Sonata I in G minor, BWV 1001, is a significant and widely performed work that exists in numerous editions and also as transcriptions or arrangements for various other instruments, including the guitar. A pedagogical guitar performance edition of this sonata, however, has yet to be published. Therefore, the core of my project is a transcription and pedagogical edition of this work for guitar. The transcription is supported by an analysis, performance and pedagogical practice guide, and a recording. The analysis and graphing of phrase structures illuminate Bach's use of compositional devices and the architectural function of the work's harmonic gravities. They are intended to guide performers in their assessment of the surface ornamentation and suggest a reduction toward its fundamental purpose. The end result is a clarification of the piece through the organization of phrase structures and the prioritization of harmonic tensions and resolutions. The compiling process is intended to assist the performer in "seeing the forest from the trees." Based on markings from Bach's original autograph score, the transcription considers fingering ease on the guitar that is critical to render the music to a functional and practical level. The goal is to preserve the composer's indications to the highest degree possible while still adhering to the technical confines that allow for actual execution on the guitar. The performance guide provides suggestions for articulation, phrasing, ornamentation, and other interpretive decisions. Considering the limitations of the guitar, the author's suggestions are grounded in various concepts of historically informed performance, and also relate to today's early-music sensibilities. The pedagogical practice guide demonstrates procedures to break down and assimilate the musical material as applied toward the various elements of guitar technique and practice. The CD recording is intended to demonstrate the transcription and the connection to the concepts discussed. It is hoped that this pedagogical edition will provide a rational that serves to support technical decisions within the transcription and generate meaningful interpretive realizations based on principles of historically informed performance.
ContributorsFelice, Joseph Philip (Author) / Koonce, Frank (Thesis advisor) / Feisst, Sabine (Committee member) / Swartz, Jonathan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems.

In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems. The greatest challenge in developing such systems is the subject-dependent data variations or subject-based variability in physiological and biomedical data, which leads to difference in data distributions making the task of modeling these data, using traditional machine learning algorithms, complex and challenging. As a result, despite the wide application of machine learning, efficient deployment of its principles to model real-world data is still a challenge. This dissertation addresses the problem of subject based variability in physiological and biomedical data and proposes person adaptive prediction models based on novel transfer and active learning algorithms, an emerging field in machine learning. One of the significant contributions of this dissertation is a person adaptive method, for early detection of muscle fatigue using Surface Electromyogram signals, based on a new multi-source transfer learning algorithm. This dissertation also proposes a subject-independent algorithm for grading the progression of muscle fatigue from 0 to 1 level in a test subject, during isometric or dynamic contractions, at real-time. Besides subject based variability, biomedical image data also varies due to variations in their imaging techniques, leading to distribution differences between the image databases. Hence a classifier learned on one database may perform poorly on the other database. Another significant contribution of this dissertation has been the design and development of an efficient biomedical image data annotation framework, based on a novel combination of transfer learning and a new batch-mode active learning method, capable of addressing the distribution differences across databases. The methodologies developed in this dissertation are relevant and applicable to a large set of computing problems where there is a high variation of data between subjects or sources, such as face detection, pose detection and speech recognition. From a broader perspective, these frameworks can be viewed as a first step towards design of automated adaptive systems for real world data.
ContributorsChattopadhyay, Rita (Author) / Panchanathan, Sethuraman (Thesis advisor) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Currently, to interact with computer based systems one needs to learn the specific interface language of that system. In most cases, interaction would be much easier if it could be done in natural language. For that, we will need a module which understands natural language and automatically translates it to

Currently, to interact with computer based systems one needs to learn the specific interface language of that system. In most cases, interaction would be much easier if it could be done in natural language. For that, we will need a module which understands natural language and automatically translates it to the interface language of the system. NL2KR (Natural language to knowledge representation) v.1 system is a prototype of such a system. It is a learning based system that learns new meanings of words in terms of lambda-calculus formulas given an initial lexicon of some words and their meanings and a training corpus of sentences with their translations. As a part of this thesis, we take the prototype NL2KR v.1 system and enhance various components of it to make it usable for somewhat substantial and useful interface languages. We revamped the lexicon learning components, Inverse-lambda and Generalization modules, and redesigned the lexicon learning algorithm which uses these components to learn new meanings of words. Similarly, we re-developed an inbuilt parser of the system in Answer Set Programming (ASP) and also integrated external parser with the system. Apart from this, we added some new rich features like various system configurations and memory cache in the learning component of the NL2KR system. These enhancements helped in learning more meanings of the words, boosted performance of the system by reducing the computation time by a factor of 8 and improved the usability of the system. We evaluated the NL2KR system on iRODS domain. iRODS is a rule-oriented data system, which helps in managing large set of computer files using policies. This system provides a Rule-Oriented interface langauge whose syntactic structure is like any procedural programming language (eg. C). However, direct translation of natural language (NL) to this interface language is difficult. So, for automatic translation of NL to this language, we define a simple intermediate Policy Declarative Language (IPDL) to represent the knowledge in the policies, which then can be directly translated to iRODS rules. We develop a corpus of 100 policy statements and manually translate them to IPDL langauge. This corpus is then used for the evaluation of NL2KR system. We performed 10 fold cross validation on the system. Furthermore, using this corpus, we illustrate how different components of our NL2KR system work.
ContributorsKumbhare, Kanchan Ravishankar (Author) / Baral, Chitta (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This project features three new pieces for clarinet commissioned from three different composers. Two are for unaccompanied clarinet and one is for clarinet, bass clarinet, and laptop. These pieces are Storm's a Comin' by Chris Burton, Light and Shadows by Theresa Martin, and My Own Agenda by Robbie McCarthy. These

This project features three new pieces for clarinet commissioned from three different composers. Two are for unaccompanied clarinet and one is for clarinet, bass clarinet, and laptop. These pieces are Storm's a Comin' by Chris Burton, Light and Shadows by Theresa Martin, and My Own Agenda by Robbie McCarthy. These three solos challenge the performer in various ways including complex rhythm, use of extended techniques such as growling, glissando, and multiphonics, and the incorporation of technology into a live performance. In addition to background information, a performance practice guide has also been included for each of the pieces. This guide provides recommendations and suggestions for future performers wishing to study and perform these works. Also included are transcripts of interviews done with each of the composers as well as full scores for each of the pieces. Accompanying this document are recordings of each of the three pieces, performed by the author.
ContributorsVaughan, Melissa Lynn (Author) / Spring, Robert (Thesis advisor) / Micklich, Albie (Committee member) / Gardner, Joshua (Committee member) / Hill, Gary (Committee member) / Feisst, Sabine (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Three Meditations on the Philosophy of Boethius is a musical piece for guitar, piano interior, and computer. Each of the three movements, or meditations, reflects one level of music according to the medieval philosopher Boethius: Musica Mundana, Musica Humana, and Musica Instrumentalis. From spatial aspects, through the human element, to

Three Meditations on the Philosophy of Boethius is a musical piece for guitar, piano interior, and computer. Each of the three movements, or meditations, reflects one level of music according to the medieval philosopher Boethius: Musica Mundana, Musica Humana, and Musica Instrumentalis. From spatial aspects, through the human element, to letting sound evolve freely, different movements revolve around different sounds and sound producing techniques.
ContributorsDori, Gil (Contributor) / Hackbarth, Glenn (Thesis advisor) / DeMars, James (Committee member) / Feisst, Sabine (Committee member) / Arizona State University (Publisher)
Created2013
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Description
There is a lack of music therapy services for college students who have problems with depression and/or anxiety. Even among universities and colleges that offer music therapy degrees, there are no known programs offering music therapy to the institution's students. Female college students are particularly vulnerable to depression and anxiety

There is a lack of music therapy services for college students who have problems with depression and/or anxiety. Even among universities and colleges that offer music therapy degrees, there are no known programs offering music therapy to the institution's students. Female college students are particularly vulnerable to depression and anxiety symptoms compared to their male counterparts. Many students who experience mental health problems do not receive treatment, because of lack of knowledge, lack of services, or refusal of treatment. Music therapy is proposed as a reliable and valid complement or even an alternative to traditional counseling and pharmacotherapy because of the appeal of music to young women and the potential for a music therapy group to help isolated students form supportive networks. The present study recruited 14 female university students to participate in a randomized controlled trial of short-term group music therapy to address symptoms of depression and anxiety. The students were randomly divided into either the treatment group or the control group. Over 4 weeks, each group completed surveys related to depression and anxiety. Results indicate that the treatment group's depression and anxiety scores gradually decreased over the span of the treatment protocol. The control group showed either maintenance or slight worsening of depression and anxiety scores. Although none of the results were statistically significant, the general trend indicates that group music therapy was beneficial for the students. A qualitative analysis was also conducted for the treatment group. Common themes were financial concerns, relationship problems, loneliness, and time management/academic stress. All participants indicated that they benefited from the sessions. The group progressed in its cohesion and the participants bonded to the extent that they formed a supportive network which lasted beyond the end of the protocol. The results of this study are by no means conclusive, but do indicate that colleges with music therapy degree programs should consider adding music therapy services for their general student bodies.
ContributorsAshton, Barbara (Author) / Crowe, Barbara J. (Thesis advisor) / Rio, Robin (Committee member) / Davis, Mary (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Piano Quintet> is a three movement piece, inspired by music of Eastern Europe. Sunrise in Hungary starts with a legato song in the first violin unfolding over slow moving sustained harmonics in the rest of the strings. This is contrasted with a lively Hungarian dance which starts in the piano

Piano Quintet> is a three movement piece, inspired by music of Eastern Europe. Sunrise in Hungary starts with a legato song in the first violin unfolding over slow moving sustained harmonics in the rest of the strings. This is contrasted with a lively Hungarian dance which starts in the piano and jumps throughout all of the voices. Armenian Lament introduces a mournful melody performed over a subtly shifting pedal tone in the cello. The rest of the voices are slowly introduced until the movement builds into a canonic threnody. Evening in Bulgaria borrows from the vast repertoire of Bulgarian dances, including rhythms from the horo and rachenitsa. Each time that the movement returns to the primary theme, it incorporates aspects of the dance that directly preceded it. The final return is the crux of the piece, with the first violin playing a virtuosic ornaments run on the melody.
ContributorsGiese, Adam (Composer) / Hackbarth, Glenn (Thesis advisor) / DeMars, James (Committee member) / Feisst, Sabine (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Sometimes difficult life events challenge our existing resources in such a way that routinized responses are inadequate to handle the challenge. Some individuals will persist in habitual, automatic behavior, regardless of environmental cues that indicate a mismatch between coping strategy and the demands of the stressor. Other individuals will marshal

Sometimes difficult life events challenge our existing resources in such a way that routinized responses are inadequate to handle the challenge. Some individuals will persist in habitual, automatic behavior, regardless of environmental cues that indicate a mismatch between coping strategy and the demands of the stressor. Other individuals will marshal adaptive resources to construct new courses of action and reconceptualize the problem, associated goals and/or values. A mixed methods approach was used to describe and operationalize cognitive shift, a relatively unexplored construct in existing literature. The study was conducted using secondary data from a parent multi-year cross-sectional study of resilience with eight hundred mid-aged adults from the Phoenix metro area. Semi-structured telephone interviews were analyzed using a purposive sample (n=136) chosen by type of life event. Participants' beliefs, assumptions, and experiences were examined to understand how they shaped adaptation to adversity. An adaptive mechanism, "cognitive shift," was theorized as the transition from automatic coping to effortful cognitive processes aimed at novel resolution of issues. Aims included understanding when and how cognitive shift emerges and manifests. Cognitive shift was scored as a binary variable and triangulated through correlational and logistic regression analyses. Interaction effects revealed that positive personality attributes influence cognitive shift most when people suffered early adversity. This finding indicates that a certain complexity, self-awareness and flexibility of mind may lead to a greater capacity to find meaning in adversity. This work bridges an acknowledged gap in literature and provides new insights into resilience.
ContributorsRivers, Crystal T (Author) / Zautra, Alex (Thesis advisor) / Davis, Mary (Committee member) / Kurpius, Sharon (Committee member) / Arizona State University (Publisher)
Created2014