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- Genre: Doctoral Dissertation
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
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
ABSTRACT Water resources in many parts of the world are subject to increasing stress because of (a) the growth in demand caused by population increase and economic development, (b) threats to supply caused by climate and land cover change, and (c) a heightened awareness of the importance of maintaining water supplies to other parts of the ecosystem. An additional factor is the quality of water management. The United States-Mexican border provides an example of poor water management combined with increasing demand for water resources that are both scarce and uncertain. This dissertation focuses on the problem of water management in the border city of Ciudad Juarez, Chihuahua. The city has attracted foreign investment during the last few decades, largely due to relatively low environmental and labor costs, and to a range of tax incentives and concessions. This has led to economic and population growth, but also to higher demand for public services such as water which leads to congestion and scarcity. In particular, as water resources have become scarce, the cost of water supply has increased. The dissertation analyzes the conditions that allow for the efficient use of water resources at sustainable levels of economic activity--i.e., employment and investment. In particular, it analyzes the water management strategies that lead to an efficient and sustainable use of water when the source of water is either an aquifer, or there is conjunctive use of ground and imported water. The first part of the dissertation constructs a model of the interactive effects of water supply, wage rates, inward migration of labor and inward investment of capital. It shows how growing water scarcity affects population growth through the impact it has on real wage rates, and how this erodes the comparative advantage of Ciudad Juarez--low wages--to the point where foreign investment stops. This reveals the very close connection between water management and the level of economic activity in Ciudad Juarez. The second part of the dissertation examines the effect of sustainable and efficient water management strategies on population and economic activity levels under two different settings. In the first Ciudad Juarez relies exclusively on ground water to meet demand--this reflects the current situation of Ciudad Juarez. In the second Ciudad Juarez is able both to import water and to draw on aquifers to meet demand. This situation is motivated by the fact that Ciudad Juarez is considering importing water from elsewhere to maintain its economic growth and mitigate the overdraft of the Bolson del Hueco aquifer. Both models were calibrated on data for Ciudad Juarez, and then used to run experiments with respect to different environmental and economic conditions, and different water management options. It is shown that for a given set of technological, institutional and environmental conditions, the way water is managed in a desert environment determines the long run equilibrium levels of employment, investment and output. It is also shown that the efficiency of water management is consistent with the sustainability of water use and economic activity. Importing water could allow the economy to operate at higher levels of activity than where it relies solely on local aquifers. However, at some scale, water availability will limit the level of economic activity, and the disposable income of the residents of Ciudad Juarez.
ContributorsGarduno Angeles, Gustavo Leopoldo (Author) / Perrings, Charles (Thesis advisor) / Holway, Jim (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Arizona State University (Publisher)
Created2011
Description
The greatest challenge facing humanity in the twenty-first century is our ability to reconcile the capacity of natural systems to support continued improvement in human welfare around the globe. Over the last decade, the scientific community has attempted to formulate research agendas in response to what they view as the problems of sustainability. Perhaps the most prominent and wide-ranging of these efforts has been sustainability science, an interdisciplinary, problem-driven field that seeks to address fundamental questions on human-environment interactions. This project examines how sustainability scientists grapple with and bound the deeply social, political and normative dimensions of both characterizing and pursuing sustainability. Based on in-depth interviews with leading researchers and a content analysis of the relevant literature, this project first addresses three core questions: (1) how sustainability scientists define and bound sustainability; (2) how and why various research agendas are being constructed to address these notions of sustainability; (3) and how scientists see their research contributing to societal efforts to move towards sustainability. Based on these results, the project explores the tensions between scientific efforts to study and inform sustainability and social action. It discusses the implications of transforming sustainability into the subject of scientific analysis with a focus on the power of science to constrain discourse and the institutional and epistemological contexts that link knowledge to societal outcomes. Following this analysis, sustainability science is repositioned, borrowing Herbert Simon's concept, as a "science of design." Sustainability science has thus far been too focused on understanding the "problem-space"--addressing fundamental questions about coupled human-natural systems. A new set objectives and design principles are proposed that would move the field toward a more solutions-oriented approach and the enrichment of public reasoning and deliberation. Four new research streams that would situate sustainability science as a science of design are then discussed: creating desirable futures, socio-technical change, sustainability values, and social learning. The results serve as a foundation for a sustainability science that is evaluated on its ability to frame sustainability problems and solutions in ways that make them amenable to democratic and pragmatic social action.
ContributorsMiller, Thaddeus R. (Author) / Minteer, Ben A (Thesis advisor) / Redman, Charles L. (Committee member) / Sarewitz, Daniel (Committee member) / Wiek, Arnim (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
Service based software (SBS) systems are software systems consisting of services based on the service oriented architecture (SOA). Each service in SBS systems provides partial functionalities and collaborates with other services as workflows to provide the functionalities required by the systems. These services may be developed and/or owned by different entities and physically distributed across the Internet. Compared with traditional software system components which are usually specifically designed for the target systems and bound tightly, the interfaces of services and their communication protocols are standardized, which allow SBS systems to support late binding, provide better interoperability, better flexibility in dynamic business logics, and higher fault tolerance. The development process of SBS systems can be divided to three major phases: 1) SBS specification, 2) service discovery and matching, and 3) service composition and workflow execution. This dissertation focuses on the second phase, and presents a privacy preserving service discovery and ranking approach for multiple user QoS requirements. This approach helps service providers to register services and service users to search services through public, but untrusted service directories with the protection of their privacy against the service directories. The service directories can match the registered services with service requests, but do not learn any information about them. Our approach also enforces access control on services during the matching process, which prevents unauthorized users from discovering services. After the service directories match a set of services that satisfy the service users' functionality requirements, the service discovery approach presented in this dissertation further considers service users' QoS requirements in two steps. First, this approach optimizes services' QoS by making tradeoff among various QoS aspects with users' QoS requirements and preferences. Second, this approach ranks services based on how well they satisfy users' QoS requirements to help service users select the most suitable service to develop their SBSs.
ContributorsYin, Yin (Author) / Yau, Stephen S. (Thesis advisor) / Candan, Kasim (Committee member) / Dasgupta, Partha (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2011
Description
The uncertainty of change inherent in issues such as climate change and regional growth has created a significant challenge for public decision makers trying to decide what adaptation actions are needed to respond to these possible changes. This challenge threatens the resiliency and thus the long term sustainability of our social-ecological systems. Using an empirical embedded case study approach to explore the application of advanced scenario analysis methods to regional growth visioning projects in two regions, this dissertation provides empirical evidence that for issues with high uncertainty, advanced scenario planning (ASP) methods are effective tools for helping decision makers to anticipate and prepare to adapt to change.
ContributorsQuay, Ray (Author) / Pijawka, David (Thesis advisor) / Shangraw, Ralph (Committee member) / Holway, James (Committee member) / Arizona State University (Publisher)
Created2011
Description
A systematic approach to composition has been used by a variety of composers to control an assortment of musical elements in their pieces. This paper begins with a brief survey of some of the important systematic approaches that composers have employed in their compositions, devoting particular attention to Pierre Boulez's Structures Ia . The purpose of this survey is to examine several systematic approaches to composition by prominent composers and their philosophy in adopting this type of approach. The next section of the paper introduces my own systematic approach to composition: the Take-Away System. The third provides several musical applications of the system, citing my work, Octulus for two pianos, as an example. The appendix details theorems and observations within the system for further study.
ContributorsHarbin, Doug (Author) / Hackbarth, Glenn (Thesis advisor) / DeMars, James (Committee member) / Etezady, Roshanne, 1973- (Committee member) / Rockmaker, Jody (Committee member) / Rogers, Rodney (Committee member) / Arizona State University (Publisher)
Created2011