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 study is about Thai English (ThaiE), a variety of World Englishes that is presently spoken in Thailand, as the result of the spread of English and the recent Thai government policies towards English communication in Thailand. In the study, I examined the linguistic data of spoken ThaiE, collected from

This study is about Thai English (ThaiE), a variety of World Englishes that is presently spoken in Thailand, as the result of the spread of English and the recent Thai government policies towards English communication in Thailand. In the study, I examined the linguistic data of spoken ThaiE, collected from multiple sources both in the U.S.A. and Thailand. The study made use of a qualitative approach in examining the data, which were from (i) English interviews and questionnaires with 12 highly educated Thai speakers of English during my fieldwork in the Southwestern U.S.A., Central Thailand, and Northeastern Thailand, (ii) English speech samples from the media in Thailand, i.e. television programs, a news report, and a talk radio program, and (iii) the research articles on English used by Thai speakers of English. This study describes the typology of ThaiE in terms of its morpho-syntax, phonology, and sociolinguistics, with the main focus being placed on the structural characteristics of ThaiE. Based on the data, the results show that some of the ThaiE features are similar to the World Englishes features, but some are unique to ThaiE. Therefore, I argue that ThaiE is structurally considered a new variety of World Englishes at the present time. The findings also showed an interesting result, regarding the notion of ThaiE by the fieldwork interview participants. The majority of these participants (n=6) denied the existence of ThaiE, while the minority of the participants (n=5) believed ThaiE existed, and one participant was reluctant to give the answer. The study suggested that the participants' academic backgrounds, the unfamiliar notion of ThaiE, and the level of the participants' social interaction with everyday persons may have influenced their answers to the main research question.
ContributorsRogers, Uthairat (Author) / Gelderen, Elly van (Thesis advisor) / Mailhammer, Robert (Committee member) / Adams, Karen (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Despite the vast research on language carried out by the generative linguistics of Noam Chomsky and his followers since the 1950s, for theoretical reasons (mainly their attention to the mental abstraction of language structure rather than language as a performed product), historical linguistics from the start lay outside their research

Despite the vast research on language carried out by the generative linguistics of Noam Chomsky and his followers since the 1950s, for theoretical reasons (mainly their attention to the mental abstraction of language structure rather than language as a performed product), historical linguistics from the start lay outside their research interest. This study is an attempt to bridge the gap between the formalism and theoretical constructs introduced by generative grammar, whose ultimate goal is to provide not only a description but also an explanation to linguistic phenomena, and historical linguistics, which studies the evolution of language over time. This main objective is met by providing a formal account of the changes hwæðer undergoes throughout the Old English (OE) period. This seemingly inconspicuous word presents itself as a case of particular investigative interest in that it reflects the different stages proclaimed by the theoretical assumptions implemented in the study, namely the economy principles responsible for what has become known as the CP cycle: the Head Preference Principle and the Late Merge Principle, whereby pronominal hwæðer would raise to the specifier position for topicalization purposes, then after frequent use in that position, it would be base-generated there under Late Merge, until later reanalysis as the head of the Complementizer Phrase (CP) under Head Preference. Thus, I set out to classify the diverse functions of OE hwæðer by identifying and analyzing all instances as recorded in the diachronic part of the Helsinki Corpus. Both quantitative and qualitative analyses of the data have rendered the following results: 1) a fully satisfactory functional and chronological classification has been obtained by analyzing the data under investigation following a formal theoretical approach; and 2) a step-by-step historical analysis proves to be indispensable for understanding how language works at the abstract level from a historical point of view. This project is part of a growing body of research on language change which attempts to describe and explain the evolution of certain words as these change in form and function.
ContributorsParra-Guinaldo, Víctor (Author) / Gelderen, Elly van (Thesis advisor) / Bjork, Robert (Committee member) / Nilsen, Don L. F. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis

Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
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Description
With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic

With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic monitoring and management, etc. To better understand movement behaviors from the raw mobility data, this doctoral work provides analytic models for analyzing trajectory data. As a first contribution, a model is developed to detect changes in trajectories with time. If the taxis moving in a city are viewed as sensors that provide real time information of the traffic in the city, a change in these trajectories with time can reveal that the road network has changed. To detect changes, trajectories are modeled with a Hidden Markov Model (HMM). A modified training algorithm, for parameter estimation in HMM, called m-BaumWelch, is used to develop likelihood estimates under assumed changes and used to detect changes in trajectory data with time. Data from vehicles are used to test the method for change detection. Secondly, sequential pattern mining is used to develop a model to detect changes in frequent patterns occurring in trajectory data. The aim is to answer two questions: Are the frequent patterns still frequent in the new data? If they are frequent, has the time interval distribution in the pattern changed? Two different approaches are considered for change detection, frequency-based approach and distribution-based approach. The methods are illustrated with vehicle trajectory data. Finally, a model is developed for clustering and outlier detection in semantic trajectories. A challenge with clustering semantic trajectories is that both numeric and categorical attributes are present. Another problem to be addressed while clustering is that trajectories can be of different lengths and also have missing values. A tree-based ensemble is used to address these problems. The approach is extended to outlier detection in semantic trajectories.
ContributorsKondaveeti, Anirudh (Author) / Runger, George C. (Thesis advisor) / Mirchandani, Pitu (Committee member) / Pan, Rong (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and geovisualization techniques. Three different types of spatiotemporal activity data were collected through different data collection approaches: (1) crowd sourced geo-tagged digital photos, representing people's travel activity, were retrieved from the website Panoramio.com through information retrieval techniques; (2) the same techniques were used to crawl crowd sourced GPS trajectory data and related metadata of their daily activities from the website OpenStreetMap.org; and finally (3) preschool children's daily activities and interactions tagged with time and geographical location were collected with a novel TabletPC-based behavioral coding system. The proposed methodology is applied to these data to (1) automatically recommend optimal multi-day and multi-stay travel itineraries for travelers based on discovered attractions from geo-tagged photos, (2) automatically detect movement types of unknown moving objects from GPS trajectories, and (3) explore dynamic social and socio-spatial patterns of preschool children's behavior from both geographic and social perspectives.
ContributorsLi, Xun (Author) / Anselin, Luc (Thesis advisor) / Koschinsky, Julia (Committee member) / Maciejewski, Ross (Committee member) / Rey, Sergio (Committee member) / Griffin, William (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This document presents a new implementation of the Smoothed Particles Hydrodynamics algorithm using DirectX 11 and DirectCompute. The main goal of this document is to present to the reader an alternative solution to the largely studied and researched problem of fluid simulation. Most other solutions have been implemented using the

This document presents a new implementation of the Smoothed Particles Hydrodynamics algorithm using DirectX 11 and DirectCompute. The main goal of this document is to present to the reader an alternative solution to the largely studied and researched problem of fluid simulation. Most other solutions have been implemented using the NVIDIA CUDA framework; however, the proposed solution in this document uses the Microsoft general-purpose computing on graphics processing units API. The implementation allows for the simulation of a large number of particles in a real-time scenario. The solution presented here uses the Smoothed Particles Hydrodynamics algorithm to calculate the forces within the fluid; this algorithm provides a Lagrangian approach for discretizes the Navier-Stockes equations into a set of particles. Our solution uses the DirectCompute compute shaders to evaluate each particle using the multithreading and multi-core capabilities of the GPU increasing the overall performance. The solution then describes a method for extracting the fluid surface using the Marching Cubes method and the programmable interfaces exposed by the DirectX pipeline. Particularly, this document presents a method for using the Geometry Shader Stage to generate the triangle mesh as defined by the Marching Cubes method. The implementation results show the ability to simulate over 64K particles at a rate of 900 and 400 frames per second, not including the surface reconstruction steps and including the Marching Cubes steps respectively.
ContributorsFigueroa, Gustavo (Author) / Farin, Gerald (Thesis advisor) / Maciejewski, Ross (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Linguistic subjectivity and subjectification are fields of research that are relatively new to those working in English linguistics. After a discussion of linguistic subjectivity and subjectification as they relate to English, I investigate the subjectification of a specific English adjective, and how its usage has changed over time. Subjectivity is

Linguistic subjectivity and subjectification are fields of research that are relatively new to those working in English linguistics. After a discussion of linguistic subjectivity and subjectification as they relate to English, I investigate the subjectification of a specific English adjective, and how its usage has changed over time. Subjectivity is held by many linguists of today to be the major governing factor behind the ordering of English prenominal adjectives. Through the use of a questionnaire, I investigate the effect of subjectivity on English prenominal adjective order from the perspective of the native English speaker. I then discuss the results of the questionnaire, what they mean in relation to how subjectivity affects that order, and a few of the patterns that emerged as I analyzed the data.
ContributorsSkarstedt, Luke (Author) / Gelderen, Elly van (Thesis advisor) / Bjork, Robert (Committee member) / Adams, Karen (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set

In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The speech of non-native (L2) speakers of a language contains phonological rules that differentiate them from native speakers. These phonological rules characterize or distinguish accents in an L2. The Shibboleth program creates combinatorial rule-sets to describe the phonological pattern of these accents and classifies L2 speakers into their native language.

The speech of non-native (L2) speakers of a language contains phonological rules that differentiate them from native speakers. These phonological rules characterize or distinguish accents in an L2. The Shibboleth program creates combinatorial rule-sets to describe the phonological pattern of these accents and classifies L2 speakers into their native language. The training and classification is done in Shibboleth by support vector machines using a Gaussian radial basis kernel. In one experiment run using Shibboleth, the program correctly identified the native language (L1) of a speaker of unknown origin 42% of the time when there were six possible L1s in which to classify the speaker. This rate is significantly better than the 17% chance classification rate. Chi-squared test (1, N=24) =10.800, p=.0010 In a second experiment, Shibboleth was not able to determine the native language family of a speaker of unknown origin at a rate better than chance (33-44%) when the L1 was not in the transcripts used for training the language family rule-set. Chi-squared test (1, N=18) =1.000, p=.3173 The 318 participants for both experiments were from the Speech Accent Archive (Weinberger, 2013), and ranged in age from 17 to 80 years old. Forty percent of the speakers were female and 60% were male. The factor that most influenced correct classification was higher age of onset for the L2. A higher number of years spent living in an English-speaking country did not have the expected positive effect on classification.
ContributorsFrost, Wende (Author) / Gelderen, Elly van (Thesis advisor) / Perzanowski, Dennis (Committee member) / Gee, Elisabeth (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as: visual boosting to allow for quicker consumption of large data

In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as: visual boosting to allow for quicker consumption of large data sets, the bond energy algorithm to find finer patterns and anomalies through contrast, multi-dimensional scaling, flow lines, user guided clustering, and row-column ordering. User input is applied on precomputed data sets to provide for real time interaction. General applicability of the techniques are tested against industrial trade, social networking, financial, and sparse data sets of varying dimensionality.
ContributorsHayden, Thomas (Author) / Maciejewski, Ross (Thesis advisor) / Wang, Yalin (Committee member) / Runger, George C. (Committee member) / Mack, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2014