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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

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
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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

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
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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

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
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Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find

Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
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Description

Waste pickers are the victims of harsh economic and social factors that have hurt many<br/>developing countries and billions of people around the world. Due to the rise of industrialization<br/>since the 19th century, waste and disposable resources have been discarded around the world to<br/>provide more resources, products, and services to wealthy

Waste pickers are the victims of harsh economic and social factors that have hurt many<br/>developing countries and billions of people around the world. Due to the rise of industrialization<br/>since the 19th century, waste and disposable resources have been discarded around the world to<br/>provide more resources, products, and services to wealthy countries. This has put developing<br/>countries in a precarious position where people have had very few economic opportunities<br/>besides taking on the role of waste pickers, who not only face physical health consequences due<br/>to the work they do but also face exclusion from society due to the negative views of waste<br/>pickers. Many people view waste pickers as scavengers and people who survive off of doing<br/>dirty work, which creates tensions between waste pickers and others in society. This even leads<br/>to many countries outlawing waste picking and has led to the brutal treatment of waste pickers<br/>throughout the world and has even led to thousands of waste pickers being killed by anti-waste<br/>picker groups and law enforcement organizations in many countries.<br/>Waste pickers are often at the bottom of supply chains as they take resources that have<br/>been used and discarded, and provide them to recyclers, waste management organizations, and<br/>others who are able to turn these resources into usable materials again. Waste pickers do not have<br/>many opportunities to rise above the situation they are in as waste picking has become the only<br/>option for many people who need to provide for themselves and their families. They are not<br/>compensated very well for the work they do, which also contributes to the situation where waste<br/>pickers are forced into a position of severe health risks, backlash from society and governments,<br/>not being able to seek better opportunities due to a lack of earning potential, and not being<br/>connected with end-users. Now is the time to create new business models that solve these large<br/>problems in our global society and create a sustainable way to ensure that waste pickers are<br/>treated properly around the world.

ContributorsKapps, Jack Michael (Co-author) / Kidd, Isabella (Co-author) / Urbina-Bernal, Alejandro (Co-author) / Bryne, Jared (Thesis director) / Marseille, Alicia (Committee member) / Jordan, Amanda (Committee member) / Department of Management and Entrepreneurship (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

From exploring coffee plantations with an old Irishman in the mountains of Colombia to watching the sun set over the Strait of Gibraltar from the terrace of an ancient Moroccan cafe, this thesis sent Charles and Zane on an elaborate cafe-crawl across ten countries, with stops at a few of

From exploring coffee plantations with an old Irishman in the mountains of Colombia to watching the sun set over the Strait of Gibraltar from the terrace of an ancient Moroccan cafe, this thesis sent Charles and Zane on an elaborate cafe-crawl across ten countries, with stops at a few of the world’s most interesting coffee houses. Some of these cafes, such as the world-renowned Caffé Florian (opened in 1720) and Caffé Greco (1760), are built on long-standing traditions. Others are led by innovators championing high-quality boutique shops, challenging mass production chains such as Starbucks and Tim Hortons. These newer cafes fuel a movement classified as the “Third Wave”. With a foundation gained from specialized courses with Patrick O’Malley, North America’s leading voice in coffee, Zane and Charles conducted first-hand research into the unique coffee preferences of multiple cultures, the emergence and impact of the Third Wave in these countries, and what the future may hold for coffee lovers.

ContributorsFerguson, Charles William (Co-author) / Jarecke, Zane (Co-author) / Eaton, John (Thesis director) / Bonfiglio, Thomas (Committee member) / Dean, W.P. Carey School of Business (Contributor, Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

This thesis research aims to define, identify, and promote community theatre as a “third space” for disadvantaged youth. A third space is defined by the Oxford dictionary as “...the in-between, or hybrid, spaces, where the first and second spaces work together to generate a new third space. First and second

This thesis research aims to define, identify, and promote community theatre as a “third space” for disadvantaged youth. A third space is defined by the Oxford dictionary as “...the in-between, or hybrid, spaces, where the first and second spaces work together to generate a new third space. First and second spaces are two different, and possibly conflicting, spatial groupings where people interact physically and socially: such as home (everyday knowledge) and school (academic knowledge)” (Oxford Dictionary, 2021). For disadvantaged youth, the creation of a third space in the theatre can give them a safe environment away from issues they may have at home or at school, it can further their learning about themselves and others, and it can also help those youth feel a sense of belonging to a community larger than themselves. Because of these benefits, it is clear that performing arts programs can offer a great impact on disadvantaged youth; however, many theatre companies struggle to market their programming to said communities. This may be in part, due to low marketing budgets, no specificity in labor resources dedicated to youth programming, or ineffective marketing strategies and tactics.<br/>In order to ideate marketing recommendations for these organizations, primary research was conducted to determine the attitudes and beliefs revolving around youth participation in community theatre, as well as the current marketing strategies and tactics being utilized by programmers. Participants included program managers of youth theatre programs, as well as youth participants from several major cities in the U. S. The secondary research aims to better understand the target demographic (disadvantaged youth), the benefits derived from participation in arts programming, and marketing strategies for the performing arts. Following data analysis are several recommendations for the learning, planning, and implementation of marketing strategies for theatre programmers.

ContributorsNarducci, Emily Nicole (Co-author) / Feuerstein, Kaleigh (Co-author) / Gray, Nancy (Thesis director) / Woodson, Stephani (Committee member) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Walter Cronkite School of Journalism and Mass Comm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

This thesis research aims to define, identify, and promote community theatre as a “third space” for disadvantaged youth. A third space is defined by the Oxford dictionary as “...the in-between, or hybrid, spaces, where the first and second spaces work together to generate a new third space. First and second

This thesis research aims to define, identify, and promote community theatre as a “third space” for disadvantaged youth. A third space is defined by the Oxford dictionary as “...the in-between, or hybrid, spaces, where the first and second spaces work together to generate a new third space. First and second spaces are two different, and possibly conflicting, spatial groupings where people interact physically and socially: such as home (everyday knowledge) and school (academic knowledge)” (Oxford Dictionary, 2021). For disadvantaged youth, the creation of a third space in the theatre can give them a safe environment away from issues they may have at home or at school, it can further their learning about themselves and others, and it can also help those youth feel a sense of belonging to a community larger than themselves. Because of these benefits, it is clear that performing arts programs can offer a great impact on disadvantaged youth; however, many theatre companies struggle to market their programming to said communities. This may be in part, due to low marketing budgets, no specificity in labor resources dedicated to youth programming, or ineffective marketing strategies and tactics. This research aims to provide tangible recommendations for youth programmers to better involve their target audience.

ContributorsFeuerstein, Kaleigh Nicole (Co-author) / Narducci, Emily (Co-author) / Gray, Nancy (Thesis director) / Woodson, Stephani (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Marketing (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Music has consistently been documented as a manner to bring people together across cultures throughout the world. In this research, we propose that people use similar musical taste as a strong sign of potential social connection. To investigate this notion, we draw on literature examining how music merges the public/private

Music has consistently been documented as a manner to bring people together across cultures throughout the world. In this research, we propose that people use similar musical taste as a strong sign of potential social connection. To investigate this notion, we draw on literature examining how music merges the public/private self, the link to personality, and group identity, as well as how it is linked to romantic relationships. Thus, music can be a tool when wanting to get to know someone else and/or forge a platonic relationship. To test this hypothesis, we designed an experiment comparing music relative to another commonality (sharing a sports team in common) to see which factor is stronger in triggering an online social connection. We argue that people believe they have more in common with someone who shares similar music taste compared to other commonalities. We discuss implications for marketers on music streaming platforms.

ContributorsDrambarean, Julianna Rose (Co-author) / Simmons, Logan (Co-author) / Samper, Adriana (Thesis director) / Martin, Nathan (Committee member) / Department of Marketing (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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In this paper, our Founders Lab team members — Jacob Benevento, Sydney Evans, and Alec Whiteley — recount the year-long entrepreneurial journey that led to the creation and launch of our venture, Certified Circular. Certified Circular is a program that certifies on-campus events for implementing circular practices into their activities

In this paper, our Founders Lab team members — Jacob Benevento, Sydney Evans, and Alec Whiteley — recount the year-long entrepreneurial journey that led to the creation and launch of our venture, Certified Circular. Certified Circular is a program that certifies on-campus events for implementing circular practices into their activities as well as off-campus businesses. The venture was formed in response to our group’s propelling question and industry selection, which called on us to create and market a venture within the ethical circular economy.

ContributorsBenevento, Jacob Keith (Co-author) / Evans, Sydney (Co-author) / Whiteley, Alexander (Co-author) / Byrne, Jared (Thesis director) / Marseille, Alicia (Committee member) / Jordan, Amanda (Committee member) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05