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
This dissertation investigates the long-term consequences of human land-use practices in general, and in early agricultural villages in specific. This pioneering case study investigates the "collapse" of the Early (Pre-Pottery) Neolithic lifeway, which was a major transformational event marked by significant changes in settlement patterns, material culture, and social markers. To move beyond traditional narratives of cultural collapse, I employ a Complex Adaptive Systems approach to this research, and combine agent-based computer simulations of Neolithic land-use with dynamic and spatially-explicit GIS-based environmental models to conduct experiments into long-term trajectories of different potential Neolithic socio-environmental systems. My analysis outlines how the Early Neolithic "collapse" was likely instigated by a non-linear sequence of events, and that it would have been impossible for Neolithic peoples to recognize the long-term outcome of their actions. The experiment-based simulation approach shows that, starting from the same initial conditions, complex combinations of feedback amplification, stochasticity, responses to internal and external stimuli, and the accumulation of incremental changes to the socio-natural landscape, can lead to widely divergent outcomes over time. Thus, rather than being an inevitable consequence of specific Neolithic land-use choices, the "catastrophic" transformation at the end of the Early Neolithic was an emergent property of the Early Neolithic socio-natural system itself, and thus likely not an easily predictable event. In this way, my work uses the technique of simulation modeling to connect CAS theory with the archaeological and geoarchaeological record to help better understand the causes and consequences of socio-ecological transformation at a regional scale. The research is broadly applicable to other archaeological cases of resilience and collapse, and is truly interdisciplinary in that it draws on fields such as geomorphology, computer science, and agronomy in addition to archaeology.
ContributorsUllah, Isaac (Author) / Barton, C. Michael (Thesis advisor) / Banning, Edward B. (Committee member) / Clark, Geoffrey (Committee member) / Arrowsmith, J. Ramon (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 causes and consequences of stylistic change have been a concern of archaeologists over the past several decades. The actual process of stylistic innovation, however, has received less attention. This project explores the relationship between the process of stylistic innovation on decorated pottery and the social context in which it occurred in the Hohokam area of south-central Arizona between A.D. 800 and 1300. This interval was punctuated by three episodes of reorganization, each of which was characterized to varying degrees by significant shifts in ideology, economics, and politics. Each reorganization episode was also accompanied by a rapid profusion of stylistic innovation on buff ware pottery. The goal of this study was to build a framework to understand the variation in the process of innovation as a response to different incentives and opportunities perceived in the changing social environment. By bringing stylistic analyses and provenance data together for the first time in Hohokam red-on-buff studies, I investigated how the process of innovation was variously influenced by social reorganizations at three different periods of time: the 9th, 11th, and 12th centuries A.D. Four variables were used to evaluate the process of innovation at each temporal period: 1) The origin of a stylistic invention, 2) the rate of its adoption, 3) the pattern of its adoption, and 4) the uniformity of its adoption among all buff ware potting communities. To accomplish the task, stylistic innovations and provenance were recorded on over 3,700 red-on-buff sherds were analyzed from 20 sites in the Phoenix Basin. The innovation process was found to vary with each reorganization episode, but often in different ways than expected. The results revealed the complexity and unpredictability of the process of stylistic innovation among the Hohokam. They also challenged some assumptions archaeologists have made regarding the scale and extent of the changes associated with some of the reorganization episodes. The variables utilized to measure the innovation process were found to be effective at providing a composite picture of that process, and thus warrant broader application to other archaeological contexts.
ContributorsLack, Andrew D (Author) / Abbott, David R. (Thesis advisor) / Hegmon, Michelle (Committee member) / Spielmann, Katherine A. (Committee member) / Nelson, Ben A. (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
Irrigation agriculture has been heralded as the solution to feeding the world's growing population. To this end, irrigation agriculture is both extensifying and intensifying in arid regions across the world in an effort to create highly productive agricultural systems. Over one third of modern irrigated fields, however, show signs of serious soil degradation, including salinization and waterlogging, which threaten the productivity of these fields and the world's food supply. Surprisingly, little ecological data on agricultural soils have been collected to understand and address these problems. How, then, can expanding and intensifying modern irrigation systems remain agriculturally productive for the long-term? Archaeological case studies can provide critical insight into how irrigated agricultural systems may be sustainable for hundreds, if not thousands, of years. Irrigation systems in Mesopotamia, for example, have been cited consistently as a cautionary tale of the relationship between mismanaged irrigation systems and the collapse of civilizations, but little data expressly link how and why irrigation failed in the past. This dissertation presents much needed ecological data from two different regions of the world - the Phoenix Basin in southern Arizona and the Pampa de Chaparrí on the north coast of Peru - to explore how agricultural soils were affected by long-term irrigation in a variety of social and economic contexts, including the longevity and intensification of irrigation agriculture. Data from soils in prehispanic and historic agricultural fields indicate that despite long-lived and intensive irrigation farming, farmers in both regions created strategies to sustain large populations with irrigation agriculture for hundreds of years. In the Phoenix Basin, Hohokam and O'odham farmers relied on sedimentation from irrigation water to add necessary fine sediments and nutrients to otherwise poor desert soils. Similarly, on the Pampa, farmers relied on sedimentation in localized contexts, but also constructed fields with ridges and furrows to draw detrimental salts away from planting surfaces in the furrows on onto the ridges. These case studies are then compared to failing modern and ancient irrigated systems across the world to understand how the centralization of management may affect the long-term sustainability of irrigation agriculture.
ContributorsStrawhacker, Colleen (Author) / Spielmann, Katherine A. (Thesis advisor) / Hall, Sharon J (Committee member) / Nelson, Margaret C. (Committee member) / Sandor, Jonathan A (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