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Description
As pointed out in the keynote speech by H. V. Jagadish in SIGMOD'07, and also commonly agreed in the database community, the usability of structured data by casual users is as important as the data management systems' functionalities. A major hardness of using structured data is the problem of easily retrieving information from them given a user's information needs. Learning and using a structured query language (e.g., SQL and XQuery) is overwhelmingly burdensome for most users, as not only are these languages sophisticated, but the users need to know the data schema. Keyword search provides us with opportunities to conveniently access structured data and potentially significantly enhances the usability of structured data. However, processing keyword search on structured data is challenging due to various types of ambiguities such as structural ambiguity (keyword queries have no structure), keyword ambiguity (the keywords may not be accurate), user preference ambiguity (the user may have implicit preferences that are not indicated in the query), as well as the efficiency challenges due to large search space. This dissertation performs an expansive study on keyword search processing techniques as a gateway for users to access structured data and retrieve desired information. The key issues addressed include: (1) Resolving structural ambiguities in keyword queries by generating meaningful query results, which involves identifying relevant keyword matches, identifying return information, composing query results based on relevant matches and return information. (2) Resolving structural, keyword and user preference ambiguities through result analysis, including snippet generation, result differentiation, result clustering, result summarization/query expansion, etc. (3) Resolving the efficiency challenge in processing keyword search on structured data by utilizing and efficiently maintaining materialized views. These works deliver significant technical contributions towards building a full-fledged search engine for structured data.
ContributorsLiu, Ziyang (Author) / Chen, Yi (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Jagadish, H V (Committee member) / Arizona State University (Publisher)
Created2011
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
A new arrangement of the Concerto for Two Horns in E-flat Major, Hob. VIId/6, attributed by some to Franz Joseph Haydn, is presented here. The arrangement reduces the orchestral portion to ten wind instruments, specifically a double wind quintet, to facilitate performance of the work. A full score and a complete set of parts are included. In support of this new arrangement, a discussion of the early treatment of horns in pairs and the subsequent development of the double horn concerto in the eighteenth century provides historical context for the Concerto for Two Horns in E-flat major. A summary of the controversy concerning the identity of the composer of this concerto is followed by a description of the content and structure of each of its three movements. Some comments on the procedures of the arrangement complete the background information.
ContributorsYeh, Guan-Lin (Author) / Ericson, John (Thesis advisor) / Holbrook, Amy (Committee member) / Micklich, Albie (Committee member) / Pilafian, J. Samuel (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this project is to introduce Bryan Johanson's composition for two guitars, 13 Ways of Looking at 12 Strings, and present an authoritative recording appropriate for publishing. This fifty-minute piece represents a fascinating suite in thirteen movements. The author of this project performed both guitar parts, recorded them separately in a music studio, then mixed them together into one recording. This document focuses on the critical investigation and description of the piece with a brief theoretical analysis, a discussion of performance difficulties, and guitar preparation. The composer approved the use and the scope of this project. Bryan Johanson is one of the leading contemporary composers for the guitar today. 13 Ways of Looking at 12 Strings is a unique guitar dictionary that takes us from Bach to Hendrix and highlights the unique capabilities of the instrument. It utilizes encoded messages, glass slides, metal mutes, explosive "riffs," rhythmic propulsion, improvisation, percussion, fugual writing, and much more. It has a great potential to make the classical guitar attractive to wider audiences, not limited only to guitarists and musicians. The main resources employed in researching this document are existing recordings of Johanson's other compositions and documentation of his personal views and ideas. This written document uses the composer's prolific and eclectic compositional output in order to draw conclusions and trace motifs. This project is a significant and original contribution in expanding the guitar's repertoire, and it uniquely contributes to bringing forth a significant piece of music.
ContributorsSavic, Nenad (Author) / Koonce, Frank (Thesis advisor) / Rotaru, Catalin (Committee member) / McLin, Katherine (Committee member) / Feisst, Sabine (Committee member) / Landschoot, Thomas (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this project was to commission, perform, and discuss a new work for an instrument pairing not often utilized, oboe and percussion. The composer, Alyssa Morris, was selected in June 2009. Her work, titled Forecast, was completed in October of 2009 and premiered in February of 2010, as part of a program showcasing music for oboe and percussion. Included in this document is a detailed biography of the composer, a description of the four movements of Forecast, performance notes for each movement, a diagram for stage set-up, the full score, the program from the premiere performance with biographies of all the performers involved, and both a live recording and MIDI sound file. The performance notes discuss issues that arose during preparation for the premiere and should help avoid potential pitfalls. TrevCo Music, publisher of the work, graciously allowed inclusion of the full score. This score is solely for use in this document; please visit the publisher's website for purchasing information. The commission and documentation of this composition are intended to add to the repertoire for oboe in an unusual instrument pairing and to encourage further exploration of such combinations.
ContributorsCreamer, Caryn (Author) / Schuring, Martin (Thesis advisor) / Hill, Gary (Committee member) / Holbrook, Amy (Committee member) / Micklich, Albie (Committee member) / Spring, Robert (Committee member) / Arizona State University (Publisher)
Created2011
Description
The focus of this study was the first Serbian opera, Na Uranku (At Dawn). It was written by Stanislav Binièki (1872-1942) and was first performed in 1903 at the National Theatre in Belgrade. There were two objectives of this project: (1) a live concert performance of the opera, which produced an audio recording that can be found as an appendix; and, (2) an accompanying document containing a history and an analysis of the work. While Binièki's opera is recognized as an extraordinary artistic achievement, and a new genre of musical enrichment for Serbian music, little had been previously written either about the composer or the work. At Dawn is a romantic opera in the verismo tradition with national elements. The significance of this opera is not only in its artistic expression but also in how it helped the music of Serbia evolve. Early opera settings in Serbia in the mid-nineteenth to early twentieth century did not have the same wealth of history upon which to draw as had existed in the rich operatic oeuvre in Western Europe and Russia. Similarly, conditions for performance were not satisfactory, as were no professional orchestras or singers. Furthermore, audiences were not accustomed to this type of art form. The opera served as an educational instrument for the audience, not only training them to a different type of music but also evolving its national consciousness. Binièki's opera was a foundation on which later generations of composers built. The artistic value of this opera is emphasized. The musical language includes an assimilation of various influences from Western Europe and Russia, properly incorporated into the Serbian musical core. Audience reaction is discussed, a positive affirmation that Binièki was moving in the right direction in establishing a path for the further development of the artistic field of Serbian musical culture. A synopsis of the work as well as the requisite performing forces is also included.
ContributorsMinov, Jana (Author) / Russell, Timothy (Thesis advisor) / Levy, Benjamin (Committee member) / Schildkret, David (Committee member) / Rogers, Rodney (Committee member) / Reber, William (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study utilized symbolic interaction as a framework to examine the impact of mobility on four veteran elementary general music teachers' identities, roles, and perceptions of role support. Previous research has focused on teacher identity formation among preservice and novice teachers; veteran teachers are less frequently represented in the literature. Teacher mobility research has focused on student achievement, teachers' reasons for moving, and teacher attrition. The impact of mobility on veteran teachers' identities, roles, and perceptions of role support has yet to be considered. A multiple case design was employed for this study. The criteria for purposeful selection of the participants were elementary general music teachers who had taught for at least ten years, who had changed teaching contracts and taught in at least two different schools, and who were viewed as effective music educators by fine arts coordinators. Data were collected over a period of eight months through semi-structured interviews, email correspondence, observations, review of videotapes of the participants' teaching in previous schools, and collection of artifacts. Data were analyzed within and across cases. The cross-case analysis revealed themes within the categories of identity, role, and role support for the participants. The findings suggest that the participants perceived their music teacher roles as multi-dimensional. They claimed their core identities remained stable over time; however, shifts in teacher identity occurred throughout their years as teachers. The participants asserted that mobility at the start of their careers had a positive impact because they each were challenged to solidify their own teacher identities and music teacher roles in varied school contexts. Mobility negatively impacted role and teacher practices during times when the participants adjusted to new school climates and role expectations. Role support varied depending upon school context, and the participants discovered active involvement in the school community was an effective means of seeking and acquiring role support. Reflection experiences in music teacher preparation programs, as well as mentoring and professional development geared toward teacher identity formation and role maturation, may assist teachers in matching their desired school context with their teacher identities and perceptions of the music teacher role.
ContributorsGray, Lori F (Author) / Stauffer, Sandra (Committee member) / Schmidt, Margaret (Committee member) / Sullivan, Jill (Committee member) / Bush, Jeffrey (Committee member) / Tobias, Evan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Dr. Jerold D. Ottley's twenty-five years leading the Mormon Tabernacle Choir resulted in many distinguished awards and recognitions for the ensemble. Included among these are two Platinum and three Gold records from the Recording Industry Association of America, an Emmy from the Academy of Television Arts and Sciences, and two Freedom Foundation Awards for service to the country. He conducted the Choir at two presidential inaugurations, Ronald Reagan's in 1981 and George H. W. Bush's in 1989, as well as performances at the 1984 Los Angeles Olympics Gala. He presided over eleven international tours to twenty-six countries and crisscrossed the United States for engagements in nearly every region of the country. Despite the awards, commendations, and increased recognition of the Choir, Ottley's greatest contributions were largely internal to the organization. Jerold Ottley is a skilled music educator, administrator, and emissary. Application of these proficiencies while at the helm of the Choir, led to what are, arguably, his three largest contributions: 1) as educator, he instituted in-service training for choir members, raising the level of their individual musicianship, thereby improving the technical level of the entire Choir; 2) as administrator, Ottley created policies and procedures that resulted in a more disciplined, refined ensemble; and 3) as emissary, he raised the ensemble's reputation among the general public and with music professionals. For the general public, he significantly broadened the Choir's repertoire and traveled frequently thereby reaching a wider audience. He secured greater respect among music professionals by inviting many of them to work directly with the Choir. The results were unparalleled. Ottley's twenty-five year tenure with the Choir is reflected in broader audiences, increased professional acceptance, added organizational discipline, and unprecedented musical proficiency. It is a notable legacy for a man who reportedly never felt comfortable as director of the Mormon Tabernacle Choir.
ContributorsArchibald, Lyle Jay (Author) / Gentry, Gregory (Thesis advisor) / Britton, David (Committee member) / DeMars, James (Committee member) / Doan, Jerry (Committee member) / Solis, Theodore (Committee member) / Arizona State University (Publisher)
Created2011
Description
Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive.
ContributorsLee, Jang (Author) / Gonzalez, Graciela (Thesis advisor) / Ye, Jieping (Committee member) / Davulcu, Hasan (Committee member) / Gallitano-Mendel, Amelia (Committee member) / Arizona State University (Publisher)
Created2011
Description
More than 30% of college entrants are placed in remedial mathematics (RM). Given that an explicit relationship exists between students' high school mathematics and college success in science, technology, engineering, and mathematical (STEM) fields, it is important to understand RM students' characteristics in high school. Using the Education Longitudinal Survey 2002/2006 data, this study evaluated more than 130 variables for statistical and practical significance. The variables included standard demographic data, prior achievement and transcript data, family and teacher perceptions, school characteristics, and student attitudinal variables, all of which are identified as influential in mathematical success. These variables were analyzed using logistic regression models to estimate the likelihood that a student would be placed into RM. As might be expected, student test scores, highest mathematics course taken, and high school grade point average were the strongest predictors of success in college mathematics courses. Attitude variables had a marginal effect on the most advantaged students, but their effect cannot be evaluated for disadvantaged students, due to a non-random pattern of missing data. Further research should concentrate on obtaining answers to the attitudinal questions and investigating their influence and interaction with academic indicators.
ContributorsBarber, Rebecca (Author) / Garcia, David R. (Thesis advisor) / Powers, Jeanne (Committee member) / Rodrigue Mcintyre, Lisa (Committee member) / Arizona State University (Publisher)
Created2011