Matching Items (522)
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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

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
Description

A survey was created to help gain some insight on the opinions of homeowners across the <br/>Phoenix Metro Area. This survey consisted of 7 questions relating to personal experiences and <br/>the homeowners’ opinions or concerns. The results of the survey showed that there are a few <br/>concerns surrounding solar energy

A survey was created to help gain some insight on the opinions of homeowners across the <br/>Phoenix Metro Area. This survey consisted of 7 questions relating to personal experiences and <br/>the homeowners’ opinions or concerns. The results of the survey showed that there are a few <br/>concerns surrounding solar energy with an emphasis on the cost of maintenance of panels and <br/>the payback period where the homeowners would see a return on their investment. Most of the <br/>homeowners answered that they do not use solar energy but have thought about using it for their <br/>main source of energy before. The homeowners in the survey also thought that solar energy was <br/>overall too expensive and that it would take a long time before they would see any payoff or <br/>savings from the solar panels. It was found that the payback period for panels is around 7 years <br/>and that depending on the size of the solar system installed or on the model used, solar panels <br/>cost much less than many people think. This was found by researching non-biased resources <br/>from government websites and from local energy companies’ websites. To combat the concerns <br/>found from the survey, an infographic was created to help inform the public about solar energy <br/>and allow the homeowners to make decisions that are well informed and not based on <br/>misinformation. The infographic included information related to the survey by explaining the <br/>survey and explaining topics that were of concern to the homeowners who took the survey. In <br/>addition, the infographic displayed information about solar energy and that the decision to use <br/>solar is ultimately up to the audience.

ContributorsGobiel, Erin (Author) / Taylor, David (Thesis director) / Koster, Auriane (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

Human beings have long sought to conquer the unconquerable and to push the boundaries of human endurance. There are few such endeavors more challenging than venturing into the coldest and harshest environments on the planet. The challenges these adventurers face are nearly countless, but one that is often underestimated is

Human beings have long sought to conquer the unconquerable and to push the boundaries of human endurance. There are few such endeavors more challenging than venturing into the coldest and harshest environments on the planet. The challenges these adventurers face are nearly countless, but one that is often underestimated is the massive risk of dehydration in high mountains and the lack of sufficient technology to meet this important need. Astronauts and mountaineers of NASA's Johnson Space Center have created a technology that solves this problem: a freeze-resistant hydration system that helps stop water from freezing at sub-zero temperatures by using cutting-edge technology and materials science to insulate and heat enough water to prevent dehydration over the course of the day, so that adventurers no longer need to worry about their equipment stopping them. This patented technology is the basis of the founding of Aeropak, an advanced outdoor hydration brand developed by three ASU students (Kendall Robinson, Derek Stein, and Thomas Goers) in collaboration with W.P. Carey’s Founder’s Lab. The primary goal was to develop traction among winter sport enthusiasts to create a robust customer base and evaluate the potential for partnership with hydration solution companies as well as direct sales through online and brick-and-mortar retail avenues. To this end, the Aeropak team performed market research to determine the usefulness and need for the product through a survey sent out to a number of outdoor sporting clubs on Arizona State University’s campus. After determining an interest in a potential product, the team developed a marketing strategy and business model which was executed through Instagram as well as a standalone website, with the goal of garnering interest and traction for a future product. Future goals of the project will be to bring a product to market and expand Aeropak’s reach into a variety of winter sport subcommunities, as well as evaluate the potential for further expansion into large-scale retailers and collaboration with established companies.

ContributorsStein, Derek W (Co-author) / Robinson, Kendall (Co-author) / Goers, Thomas (Co-author) / Byrne, Jared (Thesis director) / Sebold, Brent (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Much of Nepal lacks access to clean drinking water, and many water sources are contaminated with arsenic at concentrations above both World Health Organization and local Nepalese guidelines. While many water treatment technologies exist, it is necessary to identify those that are easily implementable in developing areas. One simple treatment

Much of Nepal lacks access to clean drinking water, and many water sources are contaminated with arsenic at concentrations above both World Health Organization and local Nepalese guidelines. While many water treatment technologies exist, it is necessary to identify those that are easily implementable in developing areas. One simple treatment that has gained popularity is biochar—a porous, carbon-based substance produced through pyrolysis of biomass in an oxygen-free environment. Arizona State University’s Engineering Projects in Community Service (EPICS) has partnered with communities in Nepal in an attempt to increase biochar production in the area, as it has several valuable applications including water treatment. Biochar’s arsenic adsorption capability will be investigated in this project with the goal of using the biochar that Nepalese communities produce to remove water contaminants. It has been found in scientific literature that biochar is effective in removing heavy metal contaminants from water with the addition of iron through surface activation. Thus, the specific goal of this research was to compare the arsenic adsorption disparity between raw biochar and iron-impregnated biochar. It was hypothesized that after numerous bed volumes pass through a water treatment column, iron from the source water will accumulate on the surface of raw biochar, mimicking the intentionally iron-impregnated biochar and further increasing contaminant uptake. It is thus an additional goal of this project to compare biochar loaded with iron through an iron-spiked water column and biochar impregnated with iron through surface oxidation. For this investigation, the biochar was crushed and sieved to a size between 90 and 100 micrometers. Two samples were prepared: raw biochar and oxidized biochar. The oxidized biochar was impregnated with iron through surface oxidation with potassium permanganate and iron loading. Then, X-ray fluorescence was used to compare the composition of the oxidized biochar with its raw counterpart, indicating approximately 0.5% iron in the raw and 1% iron in the oxidized biochar. The biochar samples were then added to batches of arsenic-spiked water at iron to arsenic concentration ratios of 20 mg/L:1 mg/L and 50 mg/L:1 mg/L to determine adsorption efficiency. Inductively coupled plasma mass spectrometry (ICP-MS) analysis indicated an 86% removal of arsenic using a 50:1 ratio of iron to arsenic (1.25 g biochar required in 40 mL solution), and 75% removal with a 20:1 ratio (0.5 g biochar required in 40 mL solution). Additional samples were then inserted into a column process apparatus for further adsorption analysis. Again, ICP-MS analysis was performed and the results showed that while both raw and treated biochars were capable of adsorbing arsenic, they were exhausted after less than 70 bed volumes (234 mL), with raw biochar lasting 60 bed volumes (201 mL) and oxidized about 70 bed volumes (234 mL). Further research should be conducted to investigate more affordable and less laboratory-intensive processes to prepare biochar for water treatment.

ContributorsLaird, Ashlyn (Author) / Schoepf, Jared (Thesis director) / Westerhoff, Paul (Committee member) / Chemical Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This project analyzes the diversity of the various Chinese languages present in the Phoenix metropolitan area. The diversity and presence of these languages can be used to make inferences about different aspects of the Chinese American community in the Phoenix area, and therefore the dialects and compared to other aspects

This project analyzes the diversity of the various Chinese languages present in the Phoenix metropolitan area. The diversity and presence of these languages can be used to make inferences about different aspects of the Chinese American community in the Phoenix area, and therefore the dialects and compared to other aspects of the Chinese American immigration experience, such as where immigrants are from, what areas of Phoenix they reside, and the Chinese language skills of both the participants and their children. The data is then presented with historical context of the Phoenix Chinese community as well as a brief discussion on the current Chinese community in Phoenix as well as the acculturation of Chinese American children.

ContributorsMartin, Adam (Author) / Li, Wei (Thesis director) / Xie, Siqiao (Committee member) / Chemical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This thesis explores the investigation of the project “Designing for a Post-Diesel Engine World”, a collaborative experiment between organizations within Arizona State University and an undisclosed company. This investigation includes the analysis of various renewable energy technologies and their potential to replace industrial diesel engines as used in the company’s

This thesis explores the investigation of the project “Designing for a Post-Diesel Engine World”, a collaborative experiment between organizations within Arizona State University and an undisclosed company. This investigation includes the analysis of various renewable energy technologies and their potential to replace industrial diesel engines as used in the company’s business. In order to be competitive with diesel engines, the technology should match or exceed diesel in power output, have reduced environmental impact, and meet other criteria standards as determined by the company. The team defined the final selection criteria as: low environmental impact, high efficiency, high power, and high technology readiness level. I served as the lead Hydrogen Fuel Cell Researcher and originally hypothesized that PEM fuel cells would be the most viable solution. Results of the analysis led to PEM fuel cells and Li-ion batteries being top contenders, and the team developed a hybrid solution incorporating both of these technologies in a technical and strategic solution. The resulting solution design from this project has the potential to be modified and implemented in various industries and reduce overall anthropogenic emissions from industrial processes.

ContributorsFernandez, Alexandra Marie (Author) / Heller, Cheryl (Thesis director) / Smith, Tyler (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The ongoing Global Coronavirus Pandemic has been upheving social norms for over a year at this point. For countless people, our lives look very different at this point in time than they did before the pandemic began. Quarantine, Shelter in Place, Work from Home, and Online classes have led global

The ongoing Global Coronavirus Pandemic has been upheving social norms for over a year at this point. For countless people, our lives look very different at this point in time than they did before the pandemic began. Quarantine, Shelter in Place, Work from Home, and Online classes have led global populations to become less active leading to an increase in sedentary lifestyles. The final impact of this consequence is unknown, but emerging studies have led to concrete evidence of decreased physical and mental wellbeing, particularly in children. VirusFreeSports was the brainchild of three ASU Honors students who sought to remedy these devastating consequences by creating environments where children can participate in sports and exercise safely, free of the threat COVID-19 or other transmissible illnesses. The ultimate goal for the project team was to build traction for their idea, which culminated in a video pitch sent to potential investors. Although largely created as an exercise and we did not create a full certification course, merely a prototype through a website with sample questions to gauge interest, the project was a success as a large target market for this product was identified that showed great promise. Our team believes that early entrance to the market, as well as the lack of any other competitors would give the team a tremendous advantage in creating an impactful and influential service.

ContributorsVrbanac, Matthew Thomas (Co-author) / Tanveer, Samad (Co-author) / Israel, Natasha (Co-author) / Byrne, Jared (Thesis director) / Lee, Chris (Committee member) / Kunowski, Jeff (Committee member) / Chemical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05