Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 155
Description
The North American Monsoon System (NAMS) contributes ~55% of the annual rainfall in the Chihuahuan Desert during the summer months. Relatively frequent, intense storms during the NAMS increase soil moisture, reduce surface temperature and lead to runoff in ephemeral channels. Quantifying these processes, however, is difficult due to the sparse nature of coordinated observations. In this study, I present results from a field network of rain gauges (n = 5), soil probes (n = 48), channel flumes (n = 4), and meteorological equipment in a small desert shrubland watershed (~0.05 km2) in the Jornada Experimental. Using this high-resolution network, I characterize the temporal and spatial variability of rainfall, soil conditions and channel runoff within the watershed from June 2010 to September 2011, covering two NAMS periods. In addition, CO2, water and energy measurements at an eddy covariance tower quantify seasonal, monthly and event-scale changes in land-atmosphere states and fluxes. Results from this study indicate a strong seasonality in water and energy fluxes, with a reduction in Bowen ratio (B, the ratio of sensible to latent heat fluxes) from winter (B = 14) to summer (B = 3.3). This reduction is tied to shallow soil moisture availability during the summer (s = 0.040 m3/m3) as compared to the winter (s = 0.004 m3/m3). During the NAMS, I analyzed four consecutive rainfall-runoff events to quantify the soil moisture and channel flow responses and how water availability impacted the land-atmosphere fluxes. Spatial hydrologic variations during events occur over distances as short as ~15 m. The field network also allowed comparisons of several approaches to estimate evapotranspiration (ET). I found a more accurate ET estimate (a reduction of mean absolute error by 38%) when using distributed soil moisture data, as compared to a standard water balance approach based on the tower site. In addition, use of spatially-varied soil moisture data yielded a more reasonable relationship between ET and soil moisture, an important parameterization in many hydrologic models. The analyses illustrates the value of high-resolution sampling for quantifying seasonal fluxes in desert shrublands and their improvements in closing the water balance in small watersheds.
ContributorsTempleton, Ryan (Author) / Vivoni, Enrique R (Thesis advisor) / Mays, Larry (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Laminated composites are increasingly being used in various industries including <br/>automotive and aerospace. Under a variety of extreme loading conditions such as low and <br/>high-velocity impacts and crash, laminated composites delaminate. To understand how and<br/>when delamination occurs, two types of laboratory tests are conducted - End-notched <br/>Flexure (ENF) test and Double Cantilever Beam (DCB) test. The ENF test is designed to <br/>find the mode II interlaminar fracture toughness, and the DCB test, the mode I interlaminar <br/>fracture toughness. In this thesis, thermopressed Honeywell Spectra Shield® 5231 <br/>composite specimens made of ultra-high molecular weight polyethylene (UHMWPE), <br/>manufactured under two different pressures (3000 psi and 6000 psi), are tested in the <br/>laboratory to find its delamination properties. The test specimen preparation, experimental <br/>procedures, and data reduction to determine the mode I and mode II interlaminar fracture <br/>properties are discussed. The ENF test results show a 15.8% increase in strain energy <br/>release rate for the 6000 psi specimens when compared to the 3000 psi specimens. <br/>Conducting the DCB tests proved to be challenging due to the low compressive strength <br/>of the material and hence required modifications to the test specimens. An estimate of the <br/>mode I interlaminar fracture toughness was found for only two of the 6000 psi specimens.
ContributorsRyder, Chandler (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Neithalath, Narayanan (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
With the rapid growth of mobile computing and sensor technology, it is now possible to access data from a variety of sources. A big challenge lies in linking sensor based data with social and cognitive variables in humans in real world context. This dissertation explores the relationship between creativity in teamwork, and team members' movement and face-to-face interaction strength in the wild. Using sociometric badges (wearable sensors), electronic Experience Sampling Methods (ESM), the KEYS team creativity assessment instrument, and qualitative methods, three research studies were conducted in academic and industry R&D; labs. Sociometric badges captured movement of team members and face-to-face interaction between team members. KEYS scale was implemented using ESM for self-rated creativity and expert-coded creativity assessment. Activities (movement and face-to-face interaction) and creativity of one five member and two seven member teams were tracked for twenty five days, eleven days, and fifteen days respectively. Day wise values of movement and face-to-face interaction for participants were mean split categorized as creative and non-creative using self- rated creativity measure and expert-coded creativity measure. Paired-samples t-tests [t(36) = 3.132, p < 0.005; t(23) = 6.49 , p < 0.001] confirmed that average daily movement energy during creative days (M = 1.31, SD = 0.04; M = 1.37, SD = 0.07) was significantly greater than the average daily movement of non-creative days (M = 1.29, SD = 0.03; M = 1.24, SD = 0.09). The eta squared statistic (0.21; 0.36) indicated a large effect size. A paired-samples t-test also confirmed that face-to-face interaction tie strength of team members during creative days (M = 2.69, SD = 4.01) is significantly greater [t(41) = 2.36, p < 0.01] than the average face-to-face interaction tie strength of team members for non-creative days (M = 0.9, SD = 2.1). The eta squared statistic (0.11) indicated a large effect size. The combined approach of principal component analysis (PCA) and linear discriminant analysis (LDA) conducted on movement and face-to-face interaction data predicted creativity with 87.5% and 91% accuracy respectively. This work advances creativity research and provides a foundation for sensor based real-time creativity support tools for teams.
ContributorsTripathi, Priyamvada (Author) / Burleson, Winslow (Thesis advisor) / Liu, Huan (Committee member) / VanLehn, Kurt (Committee member) / Pentland, Alex (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis deals with the analysis of interpersonal communication dynamics in online social networks and social media. Our central hypothesis is that communication dynamics between individuals manifest themselves via three key aspects: the information that is the content of communication, the social engagement i.e. the sociological framework emergent of the communication process, and the channel i.e. the media via which communication takes place. Communication dynamics have been of interest to researchers from multi-faceted domains over the past several decades. However, today we are faced with several modern capabilities encompassing a host of social media websites. These sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information, our modes of social engagement, and mechanisms of how the media characteristics impact our interactional behavior. The outcomes of this research are manifold. We present our contributions in three parts, corresponding to the three key organizing ideas. First, we have observed that user context is key to characterizing communication between a pair of individuals. However interestingly, the probability of future communication seems to be more sensitive to the context compared to the delay, which appears to be rather habitual. Further, we observe that diffusion of social actions in a network can be indicative of future information cascades; that might be attributed to social influence or homophily depending on the nature of the social action. Second, we have observed that different modes of social engagement lead to evolution of groups that have considerable predictive capability in characterizing external-world temporal occurrences, such as stock market dynamics as well as collective political sentiments. Finally, characterization of communication on rich media sites have shown that conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Based on all these outcomes, we believe that this research can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.
ContributorsDe Choudhury, Munmun (Author) / Sundaram, Hari (Thesis advisor) / Candan, K. Selcuk (Committee member) / Liu, Huan (Committee member) / Watts, Duncan J. (Committee member) / Seligmann, Doree D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Local municipalities in the Phoenix Metropolitan Area have voiced an interest in purchasing alternate source water with lower DBP precursors. Along the primary source is a hydroelectric dam in which water will be diverted from. This project is an assessment of optimizing the potential blends of source water to a water treatment plant in an effort to enable them to more readily meet DBP regulations. To perform this analysis existing water treatment models were used in conjunction with historic water quality sampling data to predict chemical usage necessary to meet DBP regulations. A retrospective analysis was performed for the summer months of 2007 regarding potential for the WTP to reduce cost through optimizing the source water by an average of 30% over the four-month period, accumulating to overall treatment savings of $154 per MG ($82 per AF).
ContributorsRice, Jacelyn (Author) / Westerhoff, Paul (Thesis advisor) / Fox, Peter (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011
Analysis of photocatalysis for precursor removal and formation inhibition of disinfection byproducts
Description
Disinfection byproducts are the result of reactions between natural organic matter (NOM) and a disinfectant. The formation and speciation of DBP formation is largely dependent on the disinfectant used and the natural organic matter (NOM) concentration and composition. This study examined the use of photocatalysis with titanium dioxide for the oxidation and removal of DBP precursors (NOM) and the inhibition of DBP formation. Water sources were collected from various points in the treatment process, treated with photocatalysis, and chlorinated to analyze the implications on total trihalomethane (TTHM) and the five haloacetic acids (HAA5) formations. The three sub-objectives for this study included: the comparison of enhanced and standard coagulation to photocatalysis for the removal of DBP precursors; the analysis of photocatalysis and characterization of organic matter using size exclusion chromatography and fluorescence spectroscopy and excitation-emission matrices; and the analysis of photocatalysis before GAC filtration. There were consistencies in the trends for each objective including reduced DBP precursors, measured as dissolved organic carbon DOC concentration and UV absorbance at 254 nm. Both of these parameters decreased with increased photocatalytic treatment and could be due in part to the adsorption to as well as the oxidation of NOM on the TiO2 surface. This resulted in lower THM and HAA concentrations at Medium and High photocatalytic treatment levels. However, at No UV exposure and Low photocatalytic treatment levels where oxidation reactions were inherently incomplete, there was an increase in THM and HAA formation potential, in most cases being significantly greater than those found in the raw water or Control samples. The size exclusion chromatography (SEC) results suggest that photocatalysis preferentially degrades the higher molecular mass fraction of NOM releasing lower molecular mass (LMM) compounds that have not been completely oxidized. The molecular weight distributions could explain the THM and HAA formation potentials that decreased at the No UV exposure samples but increased at Low photocatalytic treatment levels. The use of photocatalysis before GAC adsorption appears to increase bed life of the contactors; however, higher photocatalytic treatment levels have been shown to completely mineralize NOM and would therefore not require additional GAC adsorption after photocatalysis.
ContributorsDaugherty, Erin (Author) / Abbaszadegan, Morteza (Thesis advisor) / Fox, Peter (Committee member) / Mayer, Brooke (Committee member) / Arizona State University (Publisher)
Created2011
Description
As the information available to lay users through autonomous data sources continues to increase, mediators become important to ensure that the wealth of information available is tapped effectively. A key challenge that these information mediators need to handle is the varying levels of incompleteness in the underlying databases in terms of missing attribute values. Existing approaches such as Query Processing over Incomplete Autonomous Databases (QPIAD) aim to mine and use Approximate Functional Dependencies (AFDs) to predict and retrieve relevant incomplete tuples. These approaches make independence assumptions about missing values--which critically hobbles their performance when there are tuples containing missing values for multiple correlated attributes. In this thesis, I present a principled probabilis- tic alternative that views an incomplete tuple as defining a distribution over the complete tuples that it stands for. I learn this distribution in terms of Bayes networks. My approach involves min- ing/"learning" Bayes networks from a sample of the database, and using it do both imputation (predict a missing value) and query rewriting (retrieve relevant results with incompleteness on the query-constrained attributes, when the data sources are autonomous). I present empirical studies to demonstrate that (i) at higher levels of incompleteness, when multiple attribute values are missing, Bayes networks do provide a significantly higher classification accuracy and (ii) the relevant possible answers retrieved by the queries reformulated using Bayes networks provide higher precision and recall than AFDs while keeping query processing costs manageable.
ContributorsRaghunathan, Rohit (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Lee, Joohyung (Committee member) / Arizona State University (Publisher)
Created2011
Description
Source selection is one of the foremost challenges for searching deep-web. For a user query, source selection involves selecting a subset of deep-web sources expected to provide relevant answers to the user query. Existing source selection models employ query-similarity based local measures for assessing source quality. These local measures are necessary but not sufficient as they are agnostic to source trustworthiness and result importance, which, given the autonomous and uncurated nature of deep-web, have become indispensible for searching deep-web. SourceRank provides a global measure for assessing source quality based on source trustworthiness and result importance. SourceRank's effectiveness has been evaluated in single-topic deep-web environments. The goal of the thesis is to extend sourcerank to a multi-topic deep-web environment. Topic-sensitive sourcerank is introduced as an effective way of extending sourcerank to a deep-web environment containing a set of representative topics. In topic-sensitive sourcerank, multiple sourcerank vectors are created, each biased towards a representative topic. At query time, using the topic of query keywords, a query-topic sensitive, composite sourcerank vector is computed as a linear combination of these pre-computed biased sourcerank vectors. Extensive experiments on more than a thousand sources in multiple domains show 18-85% improvements in result quality over Google Product Search and other existing methods.
ContributorsJha, Manishkumar (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Strong communities are important for society. One of the most important community builders, making friends, is poorly supported online. Dating sites support it but in romantic contexts. Other major social networks seem not to encourage it because either their purpose isn't compatible with introducing strangers or the prevalent methods of introduction aren't effective enough to merit use over real word alternatives. This paper presents a novel digital social network emphasizing creating friendships. Research has shown video chat communication can reach in-person levels of trust; coupled with a game environment to ease the discomfort people often have interacting with strangers and a recommendation engine, Zazzer, the presented system, allows people to meet and get to know each other in a manner much more true to real life than traditional methods. Its network also allows players to continue to communicate afterwards. The evaluation looks at real world use, measuring the frequency with which players choose the video chat game versus alternative, more traditional methods of online introduction. It also looks at interactions after the initial meeting to discover how effective video chat games are in creating sticky social connections. After initial use it became apparent a critical mass of users would be necessary to draw strong conclusions, however the collected data seemed to give preliminary support to the idea that video chat games are more effective than traditional ways of meeting online in creating new relationships.
ContributorsSorensen, Asael (Author) / VanLehn, Kurt (Thesis advisor) / Liu, Huan (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2011