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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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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
Semiconductor nanowires are featured by their unique one-dimensional structure which makes them promising for small scale electronic and photonic device applications. Among them, III-V material nanowires are particularly outstanding due to their good electronic properties. In bulk, these materials reveal electron mobility much higher than conventional silicon based devices, for

Semiconductor nanowires are featured by their unique one-dimensional structure which makes them promising for small scale electronic and photonic device applications. Among them, III-V material nanowires are particularly outstanding due to their good electronic properties. In bulk, these materials reveal electron mobility much higher than conventional silicon based devices, for example at room temperature, InAs field effect transistor (FET) has electron mobility of 40,000 cm2/Vs more than 10 times of Si FET. This makes such materials promising for high speed nanowire FETs. With small bandgap, such as 0.354 eV for InAs and 1.52 eV for GaAs, it does not need high voltage to turn on such devices which leads to low power consumption devices. Another feature of direct bandgap allows their applications of optoelectronic devices such as avalanche photodiodes. However, there are challenges to face up. Due to their large surface to volume ratio, nanowire devices typically are strongly affected by the surface states. Although nanowires can be grown into single crystal structure, people observe crystal defects along the wires which can significantly affect the performance of devices. In this work, FETs made of two types of III-V nanowire, GaAs and InAs, are demonstrated. These nanowires are grown by catalyst-free MOCVD growth method. Vertically nanowires are transferred onto patterned substrates for coordinate calibration. Then electrodes are defined by e-beam lithography followed by deposition of contact metals. Prior to metal deposition, however, the substrates are dipped in ammonium hydroxide solution to remove native oxide layer formed on nanowire surface. Current vs. source-drain voltage with different gate bias are measured at room temperature. GaAs nanowire FETs show photo response while InAs nanowire FETs do not show that. Surface passivation is performed on GaAs FETs by using ammonium surfide solution. The best results on current increase is observed with around 20-30 minutes chemical treatment time. Gate response measurements are performed at room temperature, from which field effect mobility as high as 1490 cm2/Vs is extracted for InAs FETs. One major contributor for this is stacking faults defect existing along nanowires. For InAs FETs, thermal excitations observed from temperature dependent results which leads us to investigate potential barriers.
ContributorsLiang, Hanshuang (Author) / Yu, Hongbin (Thesis advisor) / Ferry, David (Committee member) / Tracy, Clarence (Committee member) / Arizona State University (Publisher)
Created2011
Description

The purpose of this study is to create and establish an efficient and cost-effective solution to decrease the effects of sedentarism in pregnant women. Our team was given a propelling question, from which we had to narrow down our scope and conduct primary and secondary research to determine our ideal

The purpose of this study is to create and establish an efficient and cost-effective solution to decrease the effects of sedentarism in pregnant women. Our team was given a propelling question, from which we had to narrow down our scope and conduct primary and secondary research to determine our ideal customers. The design of our study intends to imitate the development of a startup where ideas are created from scratch and the final deliverable is a business model plan that shows some sort of traction. Our first major finding is that a sedentary lifestyle can be treated without major challenges in low risk pregnancies. We determined that uncertainty and lack of concise and clear information is one of the main causes of an increased level of sedentary behavior in low risk pregnancies. A significant driver for women to do some sort of activity or exercise stems from feeling supported, which doesn’t necessarily come from their partner or couple, but instead from other women that are going to a similar process as them. There are apps in the market that intend to serve pregnant women; however, there is not one that incorporates a social aspect to achieve their goal. In conclusion, there is opportunity in the market for a socially integrated pregnancy fitness app. The Gleam concept has been consciously developed to decrease sedentary behavior through concise, clear, and reliable information and by encouraging women through a socialization platform.

ContributorsMosier, Jacob Ryan (Co-author) / Flores, Valeria (Co-author) / McCreary, Liam (Co-author) / Byrne, Jared (Thesis director) / Hall, Rick (Committee member) / Silverstein, Taylor (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (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

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.

ContributorsJarecke, Zane Micheal (Co-author) / Ferguson, Charles (Co-author) / Eaton, John (Thesis director) / Bonfiglio, Thomas (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

In this thesis I will explore deficits in Theory of Mind (ToM) in autistic people due to new evidence that they do not completely lack a ToM. A new theory is proposed, claiming that autistic people use a Hyper Theory of Mind (HyperToM) which has some application and processing differences

In this thesis I will explore deficits in Theory of Mind (ToM) in autistic people due to new evidence that they do not completely lack a ToM. A new theory is proposed, claiming that autistic people use a Hyper Theory of Mind (HyperToM) which has some application and processing differences from typical ToM. The HyperToM test will be administered as an online questionnaire that includes a self-reported Autism Quotient (AQ) section. The study is done in low support needs autistic (LSA) adults, which should have a developed ToM due to age and ability. Results showed some correlations with the AQ symptoms and HyperToM, but not enough diagnosed autistic people (9) participated in this study for significant results.

ContributorsMarkov, Vlada A (Author) / Fabricius, William (Thesis director) / Philips, Ben (Committee member) / Department of Psychology (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of Life Sciences (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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Description

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

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

ContributorsKidd, Isabella Joy (Co-author) / Kapps, Jack (Co-author) / Urbina-Bernal, Alejandro (Thesis director) / Byrne, Jared (Committee member) / Marseille, Alicia (Committee member) / Jordan, Amanda (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Morrison School of Agribusiness (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05