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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

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
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Description
With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications

With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (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

This 15-week long course is designed to introduce students, specifically in Arizona, to basic sustainability and conservation principles in the context of local reptile wildlife. Throughout the course, the students work on identifying the problem, creating visions for the desired future, and finally developing a strategy to help with reptile

This 15-week long course is designed to introduce students, specifically in Arizona, to basic sustainability and conservation principles in the context of local reptile wildlife. Throughout the course, the students work on identifying the problem, creating visions for the desired future, and finally developing a strategy to help with reptile species survival in the valley. Research shows that animals in the classroom have led to improved academic success for students. Thus, through creating this course I was able to combine conservation and sustainability curriculum with real-life animals whose survival is directly being affected in the valley. My hope is that this course will help students identify a newfound passion and call to action to protect native wildlife. The more awareness and actionable knowledge which can be brought to students in Arizona about challenges to species survival the more likely we are to see a change in the future and a stronger sense of urgency for protecting wildlife. In order to accomplish these goals, the curriculum was developed to begin with basic concepts of species needs such as food and shelter and basic principles of sustainability. As the course progresses the students analyze current challenges reptile wildlife faces, like urban sprawl, and explore options to address these challenges. The course concludes with a pilot pitch where students present their solution projects to the school.

ContributorsGoethe, Emma Rae (Author) / Brundiers, Katja (Thesis director) / Bouges, Olivia (Committee member) / School of Sustainability (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

The concept of Nature Made Candles was to “educate candle lovers on the importance of knowing what is in the candle. Everyone should know what they are inhaling...no matter how nice (or not) it smells. Earth needed a candle for enjoying scents and sights without hindering health, so we made

The concept of Nature Made Candles was to “educate candle lovers on the importance of knowing what is in the candle. Everyone should know what they are inhaling...no matter how nice (or not) it smells. Earth needed a candle for enjoying scents and sights without hindering health, so we made one.” The objective evolved into educating the student population of Arizona State University (ASU) about what ingredients go into commercial candles, with a particular focus on the wax and scent, as well as giving students a free candle that emulated the holistic ingredients they were educated on. This project was designed to be a quality improvement and health promotion project with an emphasis on the ASU student population. The purpose of the project was to find a type of candle that was friendly to the lungs of all individuals who wanted candles in their household.

ContributorsMuenchen, Cassandra (Co-author) / Waterman, Grace (Co-author) / Jaurigue, Lisa (Thesis director) / Kenny, Katherine (Committee member) / Edson College of Nursing and Health Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Though about 75 percent of American waste is recyclable, only 30 percent of it is actually recycled and less than ten percent of plastics disposed of in the United States in 2015 were recycled. A statistic like this demonstrates the immense need to increase recycling rates in order to move

Though about 75 percent of American waste is recyclable, only 30 percent of it is actually recycled and less than ten percent of plastics disposed of in the United States in 2015 were recycled. A statistic like this demonstrates the immense need to increase recycling rates in order to move towards cultivating a circular economy and benefiting the environment. With Arizona State University’s (ASU) extensive population of on-campus students and faculty, our team was determined to create a solution that would increase recycling rates. After conducting initial market research, our team incentives or education. We conducted market research through student surveys to determine the level of knowledge of our target audience and barriers to entry for local recycling and composting resources. Further, we gained insight into the medium of recycling and sustainability programs they would be interested in participating in. Overall, the results of our surveys demonstrated that a majority of students were interested in participating in these programs, if they were not already involved, and most students on-campus already had access to these resources. Despite having access to these sustainable practices, we identified a knowledge gap between students and their information on how to properly execute sustainable practices such as composting and recycling. In order to address this audience, our team created Circulearning, an educational program that aims to bridge the gap of knowledge and address immediate concerns regarding circular economy topics. By engaging audiences through our quick, accessible educational modules and teaching them about circular practices, we aim to inspire everyone to implement these practices into their own lives. Though our team began the initiative with a focus on implementing these practices solely to ASU campus, we decided to expand our target audience to implement educational programs at all levels after discovering the interest and need for this resource in our community. Our team is extremely excited that our Circulearning educational modules have been shared with a broad audience including students at Mesa Skyline High School, ASU students, and additional connections outside of ASU. With Circulearning, we will educate and inspire people of all ages to live more sustainably and better the environment in which we live.

ContributorsTam, Monet (Co-author) / Chakravarti, Renuka (Co-author) / Carr-Taylor, Kathleen (Co-author) / Byrne, Jared (Thesis director) / Marseille, Alicia (Committee member) / Jordan, Amanda (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

The academic environment has historically been somewhat slow to implement and adopt new technologies. However, developments in video games have created an opportunity for students to learn new skills and topics through nontraditional mediums of education. The disruption caused by the COVID-19 pandemic further highlighted the need for flexible learning

The academic environment has historically been somewhat slow to implement and adopt new technologies. However, developments in video games have created an opportunity for students to learn new skills and topics through nontraditional mediums of education. The disruption caused by the COVID-19 pandemic further highlighted the need for flexible learning opportunities. Joystick Education is our approach to addressing this need. Through online, game-based tutoring and a database of video games with high educational value, Joystick Education creates a learning environment that is effective, fun, and engaging for students. We analyzed popular, mainstream video games for educational content and selected nine games that teach concepts like history, biology, or physics while playing the game. Through promotion on social media, we generated buzz around our website which led to 103 unique visitors over our first month online and two customers requesting to book our tutoring service. We are confident that given more time to grow, Joystick Education can generate profit and become a successful business.

ContributorsBarrong, Tanner Allen (Co-author) / Bartels, Parker (Co-author) / VanLue, Aleczander (Co-author) / Byrne, Jared (Thesis director) / Pierce, John (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

When earning a teaching certification, there is no curriculum when it comes to the treatment of students with a diagnosis as well as how to educate their fellow classmates. Diagnoses affect the process of child development of the diagnosed as well as the friends and family. Children of all different

When earning a teaching certification, there is no curriculum when it comes to the treatment of students with a diagnosis as well as how to educate their fellow classmates. Diagnoses affect the process of child development of the diagnosed as well as the friends and family. Children of all different ages have different responses and reactions to the world of health. Looking at a developmental perspective, teachers can properly educate themselves and their students about these diagnoses. To be able to successfully inform students of diagnoses, there must be an overall understanding of how well they are able to acquire the knowledge. According to Jean Piaget, a key researcher in cognitive development, the age of the child correlates with their overall understanding and comprehension. In his theory, he explained how he believed that the environment of an organism affects how it will respond and adapt to the situations at hand. There are four stages that are connected to age, from infancy to adolescence and adulthood. Therefore, this project will focus on school-age children who are in the concrete operational stage. The concrete operational stage is made up of elementary and early adolescents and focuses on intelligence that is demonstrated through logical and precise thinking of concrete ideas (Huitt, W., & Hummel, J, 2003). This type of thinking applies to all parts of the child’s life and informs their behaviors on how to “adapt” to new information. Knowing this information, we will be able to create a curriculum of lectures, informational videos, worksheets and quizzes that can properly assess the student’s and their knowledge of the diagnoses.

ContributorsGreer, Rebecca E. (Author) / Visconti, Kari (Thesis director) / Collins, Jena (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Community Resources and Development (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Though about 75 percent of American waste is recyclable, only 30 percent of it is actually recycled and less than ten percent of plastics disposed of in the United States in 2015 were recycled. A statistic like this demonstrates the immense need to increase recycling rates in order to move

Though about 75 percent of American waste is recyclable, only 30 percent of it is actually recycled and less than ten percent of plastics disposed of in the United States in 2015 were recycled. A statistic like this demonstrates the immense need to increase recycling rates in order to move towards cultivating a circular economy and benefiting the environment. With Arizona State University’s (ASU) extensive population of on-campus students and faculty, our team was determined to create a solution that would increase recycling rates. After conducting initial market research, our team incentives or education. We conducted market research through student surveys to determine the level of knowledge of our target audience and barriers to entry for local recycling and composting resources. Further, we gained insight into the medium of recycling and sustainability programs they would be interested in participating in. Overall, the results of our surveys demonstrated that a majority of students were interested in participating in these programs, if they were not already involved, and most students on-campus already had access to these resources. Despite having access to these sustainable practices, we identified a knowledge gap between students and their information on how to properly execute sustainable practices such as composting and recycling. In order to address this audience, our team created Circulearning, an educational program that aims to bridge the gap of knowledge and address immediate concerns regarding circular economy topics. By engaging audiences through our quick, accessible educational modules and teaching them about circular practices, we aim to inspire everyone to implement these practices into their own lives. Though our team began the initiative with a focus on implementing these practices solely to ASU campus, we decided to expand our target audience to implement educational programs at all levels after discovering the interest and need for this resource in our community. Our team is extremely excited that our Circulearning educational modules have been shared with a broad audience including students at Mesa Skyline High School, ASU students, and additional connections outside of ASU. With Circulearning, we will educate and inspire people of all ages to live more sustainably and better the environment in which we live.

ContributorsChakravarti, Renuka (Co-author) / Tam, Monet (Co-author) / Carr-Taylor, Kathleen (Co-author) / Byrne, Jared (Thesis director) / Marseille, Alicia (Committee member) / Jordan, Amanda (Committee member) / School of Art (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Brundtland’s definition of sustainability is the ability to “meet the needs of the present<br/>without compromising the ability of future generations to meet their needs” (IISD, 2021). But<br/>what if there are no future generations? Social sustainability, the sector of sustainability that<br/>foregrounds the well-being and livelihoods of people (and thereby continuation of

Brundtland’s definition of sustainability is the ability to “meet the needs of the present<br/>without compromising the ability of future generations to meet their needs” (IISD, 2021). But<br/>what if there are no future generations? Social sustainability, the sector of sustainability that<br/>foregrounds the well-being and livelihoods of people (and thereby continuation of humanity), is<br/>included in definitions within the sustainability field, but less developed in sustainability<br/>practice. In an effort to bridge this gap of knowledge, 14 U.S. cities and over 100 sustainability<br/>policies were analyzed for their social sustainability performance. An eight-item analytical<br/>framework that deals with differing areas of social equity guided the analysis. Results found that<br/>most cities’ sustainability departments fell short of truly addressing social sustainability<br/>concerns. Out of the eight items, the most frequently addressed were housing security and racial<br/>and gender equality whereas few, if any, cities addressed the more specific social concerns of<br/>immigration, technology and media, or arts/cultural preservation. Future research is<br/>recommended to gain a better understanding of the ways existing cities can improve in this area.

ContributorsWeekes, Daniel Buckner (Co-author) / Tam, Joey (Co-author) / Brian, Jennifer (Thesis director) / Keeler, Lauren Withycombe (Thesis director) / N/A, N/A (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05