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- Genre: Academic theses
- Creators: Davulcu, Hasan
Description
Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
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
The increasing isolation and segregation of children in American cities and suburbs is of special significance. This has meant a loss of freedom for children to explore their neighborhood and city as they get older, their exclusion from varied contacts with diverse adults in a variety of settings, and their consequent inability to learn from personal experience and observation, so essential to social and emotional development. The purpose of this study is to measure the differences in child-friendliness between neighborhoods with different income levels by developing an indicator framework that can be used by planning departments and other local authorities based on available data. The research also focus on what other factor (besides income) influences child-friendliness in a city at the neighborhood level. If a relationship does exist, how big is the difference in terms of child-friendliness between low-income and high-income neighborhoods, and what indicators play the most important role in creating the difference? Neighborhoods in the city of Glendale, Arizona serve as case studies to aid in refining the assessment method, and show the potential for how cities can become more child-friendly. The neighborhoods were selected based on income, same size and different location.
ContributorsRakhimova, Nelya (Author) / Stein, Jay (Thesis advisor) / Pijawka, David (Committee member) / Crewe, Katherine (Committee member) / Arizona State University (Publisher)
Created2011
Description
The United States has a long history of providing public parks and amenities, especially for children. Unfortunately, children today are spending less time in public parks, less time getting physical activity and more time being indoors and sedentary. While multiple factors may be responsible for this lack of activity, multiple researchers have found the availability of parks is a significant influence on the physical activity levels of children as well as on the occurrence of obesity related illness. Public parks are ideal locations for children to get physical activity, however they are not always equitably distributed within communities. Income and race/ethnicity especially are common variables found to impact availability of parks. Such socioeconomic variables typically have an impact on the availability of public parks within a community. Such variables may also impact the quality of the parks provided. A case study of Scottsdale, Arizona was conducted analyzing the availability of public parks within the City between the years of 1990 and 2000 and the current quality of the parks. Statistical analysis and observation were utilized to assess the amount of park space available (in acres) and the quality of the parks in comparison to selected socioeconomic variables including ethnicity, income and total percent housing type (single family or multi-family). All analysis was conducted using U.S. Census data from the years 1990 and 2000 and was at the tract level. The results of the analysis indicate that in contrast to the initial hypothesis and past research, within the City of Scottsdale, lower income neighborhoods actually have more public park space available to them than higher income neighborhoods. Between 1990 and 2000 the difference in park space between the lowest and highest income quartiles increased considerably, approximately 230% over the ten years. The quality analysis results indicate that the overall quality of parks is slightly higher in the highest income neighborhoods, which also have no parks that could be considered of poor quality. Given the atypical results of this analysis, further research is necessary to better understand the impacts of socioeconomic characteristics on park, especially regarding children.
ContributorsSamples, Samantha (Author) / Crewe, Katherine (Thesis advisor) / Booze, Randy (Committee member) / Pijawka, David (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
There is a conflict in the profession of interior design over regulation through legislation. For some organizations and individuals, regulation via legislation is the next perceived step in the professionalization process which has been evolving for over 40 years and is needed to protect the health, safety and welfare (HSW) of the public. For other organizations and individuals, legislation is deemed unnecessary and an affront to the free trade market and serves only to create anti-competitive barriers resulting in the formation of a "design cartel" (Campo-Flores, 2011; Carpenter, 2007). Research exists on the professionalization of interior design and on the reasons stated for and against legislation (ASID, 2010, Anderson, Honey, Dudek, 2007, Martin, 2008). However, there is little research on understanding how the actual stake-holders view legislation. For the purpose of this research, the stake-holders are the professional interior designers themselves. The purpose of this study was to examine the current status of relevant issues to the subject of regulation in interior design and to pose the question if there is an option to legislation. If so, could third party certification be an acceptable alternative? An on-line survey was developed and posted on interior design networking sites on LinkedIn. The results of the survey suggest that interior designers are completely divided on the issue of legislation but favorably view certification. The survey has also revealed the lack of understanding of the legislative process in interior design and confusion in the role that interior design organizations play. The study has also revealed that interior designers identify the distorted view the public has of this industry as a problem. Interior designers surveyed in this study see a need to separate commercial and residential interior design. Overall, this study has concluded that interior designers would actually prefer a certification process to legislation.
ContributorsPliess, Catherine (Author) / Bender, Diane (Thesis advisor) / Crewe, Katherine (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study addresses the landscape connectivity pattern at two different scales. The county-level analysis aims to understand how urban ecosystem structure is likely to evolve in response to the proposed development plans in Maricopa County, Arizona. To identify the spatio-temporal land pattern change, six key landscape metrics were quantified in relative to the urban development scenarios based on the certainty of the proposed urban plans with different level of urban footprints. The effects of future development plans from municipalities on landscape connectivity were then analyzed in the scaled temporal and spatial frame to identify in which urban condition the connectivity value would most likely to decrease. The results demonstrated that tremendous amount of lands will be dedicated to future urbanization, and especially urban agricultural lands will be likely to be vulnerable. The metro-level analysis focuses on a group of species that represent urban desert landscape and have different degrees of fragmentation sensitivity and habitat type requirement. It hypothesizes that the urban habitat patch connectivity is impacted upon by urban density. Two underlying propositions were set: first, lower connectivity is predominant in areas with high urbanization cover; second, landscape connectivity will be impacted largely on the interfaces between urban, suburban, and rural areas. To test this, a GIS-based connectivity modeling was employed. The resultant change in connectivity values was examined for exploring the spatial relation to predefined spatial frames, such as urban, suburban, and rural zones of which boundaries were delineated by buffering method with two criteria of human population density and urban cover proportion. The study outcomes provide a practical guidance to minimize connectivity loss and degradation by informing planners with more optimal alternatives among various policy decisions and implementation. It also gives an inspiration for ecological landscape planning in urbanized or urbanizing regions which can ultimately leads urban landscape sustainability.
ContributorsPak, So-hyŏn (Author) / Cook, Edward (Thesis advisor) / Crewe, Katherine (Committee member) / Wu, Jianguo (Jingle) (Committee member) / Arizona State University (Publisher)
Created2011
Description
Most existing approaches to complex event processing over streaming data rely on the assumption that the matches to the queries are rare and that the goal of the system is to identify these few matches within the incoming deluge of data. In many applications, such as stock market analysis and user credit card purchase pattern monitoring, however the matches to the user queries are in fact plentiful and the system has to efficiently sift through these many matches to locate only the few most preferable matches. In this work, we propose a complex pattern ranking (CPR) framework for specifying top-k pattern queries over streaming data, present new algorithms to support top-k pattern queries in data streaming environments, and verify the effectiveness and efficiency of the proposed algorithms. The developed algorithms identify top-k matching results satisfying both patterns as well as additional criteria. To support real-time processing of the data streams, instead of computing top-k results from scratch for each time window, we maintain top-k results dynamically as new events come and old ones expire. We also develop new top-k join execution strategies that are able to adapt to the changing situations (e.g., sorted and random access costs, join rates) without having to assume a priori presence of data statistics. Experiments show significant improvements over existing approaches.
ContributorsWang, Xinxin (Author) / Candan, K. Selcuk (Thesis advisor) / Chen, Yi (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
As a significant level of the reformation and transformation of our society has been provoked by environmental deterioration, ecological approaches in environmental design have drawn much attention from professionals as an alternative world view and also as a practical design approach. Particularly in landscape architecture, ecological understanding has been at the very core of the profession since its emergence and plays an important role in the decision making processes. While ecology supports the profession with an objective rationale, aesthetics plays another major role in providing various understandings about the aesthetic experience of people, which is rather subjective. However, the ways to seek the balance between them are still controversial. Furthermore, the conventional aesthetic value system of landscape appears to have limitations for guiding us to an appropriate appreciation, especially in dealing with newly emerging urban landscape patterns such as regeneration of post-industrial landscapes. Understanding these issues, there have been continuous attempts to describe the relation between ecology and aesthetics, suggesting that a new approach known as "ecological aesthetics," can bring us a new set of viewpoints seeking a reunion of nature and culture, and science and art. It asserts that "there is a type of beauty" in the landscape associated with its ecological health which people could aesthetically appreciate; and therefore, revealing the "hidden" beauty of nature in more visible ways should be the primary concern of today's ecological designers. This research mainly consists of extensive literature research and a case study on two landscape restructuring projects of post-industrial landscapes in Seoul, Korea. The literature research redefines the tasks of landscape architecture based on the idea of ecological aesthetics, and the case study seeks the potentials and limitations of current design projects. This research proposes a framework for landscape perception and reflects on the lessons that would be useful for better practice and research.
ContributorsMin, Byoung Wook (Author) / Cook, Edward (Thesis advisor) / Crewe, Katherine (Committee member) / Pijawka, David (Committee member) / Arizona State University (Publisher)
Created2011
Description
Data-driven applications are becoming increasingly complex with support for processing events and data streams in a loosely-coupled distributed environment, providing integrated access to heterogeneous data sources such as relational databases and XML documents. This dissertation explores the use of materialized views over structured heterogeneous data sources to support multiple query optimization in a distributed event stream processing framework that supports such applications involving various query expressions for detecting events, monitoring conditions, handling data streams, and querying data. Materialized views store the results of the computed view so that subsequent access to the view retrieves the materialized results, avoiding the cost of recomputing the entire view from base data sources. Using a service-based metadata repository that provides metadata level access to the various language components in the system, a heuristics-based algorithm detects the common subexpressions from the queries represented in a mixed multigraph model over relational and structured XML data sources. These common subexpressions can be relational, XML or a hybrid join over the heterogeneous data sources. This research examines the challenges in the definition and materialization of views when the heterogeneous data sources are retained in their native format, instead of converting the data to a common model. LINQ serves as the materialized view definition language for creating the view definitions. An algorithm is introduced that uses LINQ to create a data structure for the persistence of these hybrid views. Any changes to base data sources used to materialize views are captured and mapped to a delta structure. The deltas are then streamed within the framework for use in the incremental update of the materialized view. Algorithms are presented that use the magic sets query optimization approach to both efficiently materialize the views and to propagate the relevant changes to the views for incremental maintenance. Using representative scenarios over structured heterogeneous data sources, an evaluation of the framework demonstrates an improvement in performance. Thus, defining the LINQ-based materialized views over heterogeneous structured data sources using the detected common subexpressions and incrementally maintaining the views by using magic sets enhances the efficiency of the distributed event stream processing environment.
ContributorsChaudhari, Mahesh Balkrishna (Author) / Dietrich, Suzanne W (Thesis advisor) / Urban, Susan D (Committee member) / Davulcu, Hasan (Committee member) / Chen, Yi (Committee member) / Arizona State University (Publisher)
Created2011