ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
Communication skills within dating contexts are developed during the adolescent years, and are associated with a lifelong ability to have satisfying, enduring, and non-violent partnerships. As such, they are currently and increasingly implemented into both more general forms of healthy relationship education, as well as that targeting the prevention of teen dating violence specifically. Reaching Mexican American youth with culturally and developmentally appropriate relationship education, including communication skills, may be particularly important given their earlier transitions to marital and parenting relationships, acculturative stressors that present them with unique coupling challenges, and their higher rates of teen dating violence as compared to European American youth. We know very little about how Mexican American dating couples communicate about areas of conflict. This dissertation research utilizes Bell and Naugle's (2008) framework of interpersonal violence to explore how cultural and developmental considerations may be integrated in order to better understand how communication behaviors contribute to Mexican American middle adolescents' experiences with dating conflict. I use an observational study design in order to 1.) Qualitatively explore the communication strategies used by a sample of committed couples, including integration of culturally- and developmentally-relevant contexts, 2.) Quantitatively examine whether couple-level discrepancies in acculturation are associated with observed negativity, including whether this relationship may be mediated by dissimilar gender-related beliefs, and to 3.) Review empirical findings pertaining to the communication behaviors of Mexican American adolescents and to integrate ecodevelopmental theory in said framework as informed by Papers 1, 2, and literature specific to this topic area. The ultimate aim of this dissertation research is to generate findings that may improve the dating health of Mexican American adolescents living in the United States.
ContributorsAdams, Heidi (Author) / Rankin Williams, Lela (Thesis advisor) / Marsiglia, Flavio (Committee member) / Anthony, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
One of the main challenges in planetary robotics is to traverse the shortest path through a set of waypoints. The shortest distance between any two waypoints is a direct linear traversal. Often times, there are physical restrictions that prevent a rover form traversing straight to a waypoint. Thus, knowledge of the terrain is needed prior to traversal. The Digital Terrain Model (DTM) provides information about the terrain along with waypoints for the rover to traverse. However, traversing a set of waypoints linearly is burdensome, as the rovers would constantly need to modify their orientation as they successively approach waypoints. Although there are various solutions to this problem, this research paper proposes the smooth traversability of the rover using splines as a quick and easy implementation to traverse a set of waypoints. In addition, a rover was used to compare the smoothness of the linear traversal along with the spline interpolations. The data collected illustrated that spline traversals had a less rate of change in the velocity over time, indicating that the rover performed smoother than with linear paths.
ContributorsKamasamudram, Anurag (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
Description
As the complexity of robotic systems and applications grows rapidly, development of high-performance, easy to use, and fully integrated development environments for those systems is inevitable. Model-Based Design (MBD) of dynamic systems using engineering software such as Simulink® from MathWorks®, SciCos from Metalau team and SystemModeler® from Wolfram® is quite popular nowadays. They provide tools for modeling, simulation, verification and in some cases automatic code generation for desktop applications, embedded systems and robots. For real-world implementation of models on the actual hardware, those models should be converted into compilable machine code either manually or automatically. Due to the complexity of robotic systems, manual code translation from model to code is not a feasible optimal solution so we need to move towards automated code generation for such systems. MathWorks® offers code generation facilities called Coder® products for this purpose. However in order to fully exploit the power of model-based design and code generation tools for robotic applications, we need to enhance those software systems by adding and modifying toolboxes, files and other artifacts as well as developing guidelines and procedures. In this thesis, an effort has been made to propose a guideline as well as a Simulink® library, StateFlow® interface API and a C/C++ interface API to complete this toolchain for NAO humanoid robots. Thus the model of the hierarchical control architecture can be easily and properly converted to code and built for implementation.
ContributorsRaji Kermani, Ramtin (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation explores vulnerability to extreme heat hazards in the Maricopa County, Arizona metropolitan region. By engaging an interdisciplinary approach, I uncover the epidemiological, historical-geographical, and mitigation dimensions of human vulnerability to extreme heat in a rapidly urbanizing region characterized by an intense urban heat island and summertime heat waves. I first frame the overall research within global climate change and hazards vulnerability research literature, and then present three case studies. I conclude with a synthesis of the findings and lessons learned from my interdisciplinary approach using an urban political ecology framework. In the first case study I construct and map a predictive index of sensitivity to heat health risks for neighborhoods, compare predicted neighborhood sensitivity to heat-related hospitalization rates, and estimate relative risk of hospitalizations for neighborhoods. In the second case study, I unpack the history and geography of land use/land cover change, urban development and marginalization of minorities that created the metropolitan region's urban heat island and consequently, the present conditions of extreme heat exposure and vulnerability in the urban core. The third study uses computational microclimate modeling to evaluate the potential of a vegetation-based intervention for mitigating extreme heat in an urban core neighborhood. Several findings relevant to extreme heat vulnerability emerge from the case studies. First, two main socio-demographic groups are found to be at higher risk for heat illness: low-income minorities in sparsely-vegetated neighborhoods in the urban core, and the elderly and socially-isolated in the expansive suburban fringe of Maricopa County. The second case study reveals that current conditions of heat exposure in the region's urban heat island are the legacy of historical marginalization of minorities and large-scale land-use/land cover transformations of natural desert land covers into heat-retaining urban surfaces of the built environment. Third, summertime air temperature reductions in the range 0.9-1.9 °C and of up to 8.4 °C in surface temperatures in the urban core can be achieved through desert-adapted canopied vegetation, suggesting that, at the microscale, the urban heat island can be mitigated by creating vegetated park cool islands. A synthesis of the three case studies using the urban political ecology framework argues that climate changed-induced heat hazards in cities must be problematized within the socio-ecological transformations that produce and reproduce urban landscapes of risk. The interdisciplinary approach to heat hazards in this dissertation advances understanding of the social and ecological drivers of extreme heat by drawing on multiple theories and methods from sociology, urban and Marxist geography, microclimatology, spatial epidemiology, environmental history, political economy and urban political ecology.
ContributorsDeclet-Barreto, Juan (Author) / Harlan, Sharon L (Thesis advisor) / Bolin, Bob (Thesis advisor) / Hirt, Paul (Committee member) / Boone, Christopher (Committee member) / Arizona State University (Publisher)
Created2013
Community-based development: scaling up the correct use of misoprostol at home births in Afghanistan
Description
Globally, more than 350 000 women die annually from complications during pregnancy and childbirth (UNFPA, 2011). Nearly 99% of these, according to World Health Organization (WHO) trends (2010) occur in the developing world outside of a hospital setting with limited resources including emergency care (WHO, 2012; UNFPA, 2011). The most prevalent cause of death is postpartum hemorrhage (PPH), accounting for 25% of deaths according to WHO statistics (2012). Conditions in Afghanistan are reflective of the scope and magnitude of the problem. In Afghanistan, maternal mortality is thought to be among the highest in the world. The Afghan Mortality Survey (AMS) data implies that one Afghan woman dies about every 2 hours from pregnancy-related causes (AMS, 2010). Lack of empowerment, education and access to health care resources increase a woman's risk of dying during pregnancy (AMS, 2010). This project aims to investigate the prospects of scaling-up the correct use of misoprostol, a prostaglandin E1 analogue, to treat PPH in developing countries where skilled assistance and resources are scant. As there has been little published on the lessons learned from programs already in place, this study is experience-driven, based on the knowledge of industry experts. This study employs a concurrent triangulation approach to synthesize quantitative data obtained from previous studies with qualitative information gathered through the testimonies of key personnel who participated in pilot programs involving misoprostol. There are many obstacles to scaling-up training initiatives in Afghanistan and other low-resource areas. The analysis concludes that the most crucial factors for scaling-up community-based programs include: more studies analyzing lessons learns from community driven approaches; stronger partnerships with community health care workers; overcoming barriers like association with abortion, misuse and product issues; and a heightened global and community awareness of the severity of PPH without treatment. These results have implications for those who actively work in Afghanistan to promote maternal health and other countries that may use Afghanistan's work as a blueprint for reducing maternal mortality through community-based approaches. Keywords: Afghanistan, community-based interventions, community-driven, maternal mortality, MDG5, misoprostol, postpartum hemorrhage, reproduction, scale-up
ContributorsCristy, Candice (Author) / Grossman, Gary (Thesis advisor) / Parmentier, Mary-Jane (Committee member) / Byrd, Denise (Committee member) / Arizona State University (Publisher)
Created2013
Description
Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.
ContributorsSwaminathan, Neelakantan (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013