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
Scholars have written much about home and meaning, yet they have said little about the professionally furnished model home viewed as a cultural artifact. Nor is there literature addressing how the home building industry uses these spaces to promote images of family life to increase sales. This research notes that not only do the structure, design, and layout of the model home formulate cultural identity but also the furnishings and materials within. Together, the model home and carefully selected artifacts placed therein help to express specific chosen lifestyles as that the home builder determines. This thesis considers the model home as constructed as well as builder's publications, descriptions, and advertisements. The research recognizes the many facets of merchandising, consumerism, and commercialism influencing the design and architecture of the suburban home. Historians of visual and cultural studies often investigate these issues as separate components. By contrast, this thesis offers an integrated framework of inquiry, drawing upon such disciplines as cultural history, anthropology, and material culture. The research methodology employs two forms of content analysis - image and text. The study analyzes 36 model homes built in Phoenix, Arizona, during the period 1955-1956. The thesis explores how the builder sends a message, i.e. images, ideals, and aspirations, to the potential home buyer through the design and decoration of the model home. It then speculates how the home buyer responds to those messages. The symbiotic relationship between the sender and receiver, together, tells a story about the Phoenix lifestyle and the domestic ideals of the 1950s. Builders sent messages surrounding convenience, spaciousness, added luxury, and indoor-outdoor living to a growing and discriminating home buying market.
ContributorsGolab, Coreen R (Author) / Brandt, Beverly K. (Thesis advisor) / Bernardi, Jose (Committee member) / Schleif, Corine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many longitudinal studies, especially in clinical trials, suffer from missing data issues. Most estimation procedures assume that the missing values are ignorable or missing at random (MAR). However, this assumption leads to unrealistic simplification and is implausible for many cases. For example, an investigator is examining the effect of treatment on depression. Subjects are scheduled with doctors on a regular basis and asked questions about recent emotional situations. Patients who are experiencing severe depression are more likely to miss an appointment and leave the data missing for that particular visit. Data that are not missing at random may produce bias in results if the missing mechanism is not taken into account. In other words, the missing mechanism is related to the unobserved responses. Data are said to be non-ignorable missing if the probabilities of missingness depend on quantities that might not be included in the model. Classical pattern-mixture models for non-ignorable missing values are widely used for longitudinal data analysis because they do not require explicit specification of the missing mechanism, with the data stratified according to a variety of missing patterns and a model specified for each stratum. However, this usually results in under-identifiability, because of the need to estimate many stratum-specific parameters even though the eventual interest is usually on the marginal parameters. Pattern mixture models have the drawback that a large sample is usually required. In this thesis, two studies are presented. The first study is motivated by an open problem from pattern mixture models. Simulation studies from this part show that information in the missing data indicators can be well summarized by a simple continuous latent structure, indicating that a large number of missing data patterns may be accounted by a simple latent factor. Simulation findings that are obtained in the first study lead to a novel model, a continuous latent factor model (CLFM). The second study develops CLFM which is utilized for modeling the joint distribution of missing values and longitudinal outcomes. The proposed CLFM model is feasible even for small sample size applications. The detailed estimation theory, including estimating techniques from both frequentist and Bayesian perspectives is presented. Model performance and evaluation are studied through designed simulations and three applications. Simulation and application settings change from correctly-specified missing data mechanism to mis-specified mechanism and include different sample sizes from longitudinal studies. Among three applications, an AIDS study includes non-ignorable missing values; the Peabody Picture Vocabulary Test data have no indication on missing data mechanism and it will be applied to a sensitivity analysis; the Growth of Language and Early Literacy Skills in Preschoolers with Developmental Speech and Language Impairment study, however, has full complete data and will be used to conduct a robust analysis. The CLFM model is shown to provide more precise estimators, specifically on intercept and slope related parameters, compared with Roy's latent class model and the classic linear mixed model. This advantage will be more obvious when a small sample size is the case, where Roy's model experiences challenges on estimation convergence. The proposed CLFM model is also robust when missing data are ignorable as demonstrated through a study on Growth of Language and Early Literacy Skills in Preschoolers.
ContributorsZhang, Jun (Author) / Reiser, Mark R. (Thesis advisor) / Barber, Jarrett (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / St Louis, Robert D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has been done in the ALT area and optimal design for ALT is a major topic. This dissertation consists of three main studies. First, a methodology of finding optimal design for ALT with right censoring and interval censoring have been developed and it employs the proportional hazard (PH) model and generalized linear model (GLM) to simplify the computational process. A sensitivity study is also given to show the effects brought by parameters to the designs. Second, an extended version of I-optimal design for ALT is discussed and then a dual-objective design criterion is defined and showed with several examples. Also in order to evaluate different candidate designs, several graphical tools are developed. Finally, when there are more than one models available, different model checking designs are discussed.
ContributorsYang, Tao (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Borror, Connie (Committee member) / Rigdon, Steve (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many of the scholars that have chronicled the creation of the modern American kitchen have written about how the technological, societal, and cultural revolutions of the twentieth century played a role in dramatically changing its structure and design. More recently, some scholarly research has focused on the evolution of the kitchen and its meaning over time. In several of these research publications scholars profess that the modern American kitchen, more than any other room, has come to symbolize the center or heart of the home, and the warmest room in the house. However, they are quick to acknowledge that, at the beginning of the twentieth century, the kitchen was not so fondly regarded. Little research exists regarding why individuals increasingly became attached to the kitchen or how that attachment influenced the layout, size, objects, and activities conducted in the kitchen. This thesis fills this void by exploring the implications of place attachment on the evolution of the American kitchen from 1901 through 1964. By approaching this research from a combination of design history and environmental psychology, this thesis provides a new perspective to our understanding of the evolution of kitchen design. Using this two-pronged approach, this study contributes to our understanding of the evolution of the kitchen. This study traces the evolution of the modern American kitchen using two qualitative methodologies: material culture and phenomenology. Drawing from a variety of floor plans, advertisements, and articles contained in the House Beautiful magazine 1901 through 1964, as well as writings from popular domestic advisors of the period, this thesis charts the transformation of the modern American kitchen from a "hell on earth" into the "heart and soul of the home." By combining place attachment theory and kitchen design research this thesis provides interior designers new insight into designing kitchens that foster endearing emotional attachment for our clients.
ContributorsTassell, Toni J (Author) / Brandt, Beverly (Thesis advisor) / Heywood, William (Thesis advisor) / Warren-Findley, Janelle (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the problem in education of determining teacher effectiveness in student achievement. Value-added models (VAMs), constructed as linear mixed models, use students’ test scores as outcome variables and teachers’ contributions as random effects to ascribe changes in student performance to the teachers who have taught them. The VAMs teacher score is the empirical best linear unbiased predictor (EBLUP). This approach is limited by the adequacy of the assumed model specification with respect to the unknown underlying model. In that regard, this study proposes alternative ways to rank teacher effects that are not dependent on a given model by introducing two variable importance measures (VIMs), the node-proportion and the covariate-proportion. These VIMs are novel because they take into account the final configuration of the terminal nodes in the constitutive trees in a random forest. In a simulation study, under a variety of conditions, true rankings of teacher effects are compared with estimated rankings obtained using three sources: the newly proposed VIMs, existing VIMs, and EBLUPs from the assumed linear model specification. The newly proposed VIMs outperform all others in various scenarios where the model was misspecified. The second study develops two novel interaction measures. These measures could be used within but are not restricted to the VAM framework. The distribution-based measure is constructed to identify interactions in a general setting where a model specification is not assumed in advance. In turn, the mean-based measure is built to estimate interactions when the model specification is assumed to be linear. Both measures are unique in their construction; they take into account not only the outcome values, but also the internal structure of the trees in a random forest. In a separate simulation study, under a variety of conditions, the proposed measures are found to identify and estimate second-order interactions.
ContributorsValdivia, Arturo (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Reiser, Mark R. (Committee member) / Kao, Ming-Hung (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
There is a popular notion that creativity is highly valued in our culture. However, those "in the trenches," people in creative endeavors that actually produce the acts of creativity, say this is not so. There is a negative correlation between the value stated and the true value placed on creativity by our contemporary culture. The primary purpose of this study was to investigate that correlation as well as a possible contributing factor to this negative correlation--the fear of risk involved in enacting and accepting creativity. The methods used in this study were literature review and interview. An extensive literature review was done, as much has been written on creativity. The review was done in four parts: 1) the difficulty in defining creativity; 2) fear and the fear of creativity; 3) solutions - ways to be, express, and accept creativity; and 4) the plethora of articles written about creativity. Six one-on-one interviews were conducted with creative individuals from a variety of commercial creative endeavors. Creatives in commercial fields were chosen specifically because of their ability to influence the culture. The results of this study showed that the hypothesis, that there is a negative correlation between the value stated and the true value placed on creativity, is true. The fear of risk involved in enacting and accepting creativity as a factor in this dichotomy was also shown to be true.
ContributorsGelman, Howard P (Author) / Heywood, Wil (Thesis advisor) / Patel, Mookesh (Committee member) / Knox, Gordon (Committee member) / Arizona State University (Publisher)
Created2013
Description
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile technology that could potentially provide rich, contextualized learning for understanding concepts related to statistics education. This study examined the effects of AR experiences for learning basic statistical concepts. Using a 3 x 2 research design, this study compared learning gains of 252 undergraduate and graduate students from a pre- and posttest given before and after interacting with one of three types of augmented reality experiences, a high AR experience (interacting with three dimensional images coupled with movement through a physical space), a low AR experience (interacting with three dimensional images without movement), or no AR experience (two dimensional images without movement). Two levels of collaboration (pairs and no pairs) were also included. Additionally, student perceptions toward collaboration opportunities and engagement were compared across the six treatment conditions. Other demographic information collected included the students' previous statistics experience, as well as their comfort level in using mobile devices. The moderating variables included prior knowledge (high, average, and low) as measured by the student's pretest score. Taking into account prior knowledge, students with low prior knowledge assigned to either high or low AR experience had statistically significant higher learning gains than those assigned to a no AR experience. On the other hand, the results showed no statistical significance between students assigned to work individually versus in pairs. Students assigned to both high and low AR experience perceived a statistically significant higher level of engagement than their no AR counterparts. Students with low prior knowledge benefited the most from the high AR condition in learning gains. Overall, the AR application did well for providing a hands-on experience working with statistical data. Further research on AR and its relationship to spatial cognition, situated learning, high order skill development, performance support, and other classroom applications for learning is still needed.
ContributorsConley, Quincy (Author) / Atkinson, Robert K (Thesis advisor) / Nguyen, Frank (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2013
Description
Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival estimates are based upon accurate direct sequence spread spectrum (DSSS) code and carrier phase tracking. Current multipath mitigating GNSS solutions include fixed radiation pattern antennas and windowed delay-lock loop code phase discriminators. A new multipath mitigating code tracking algorithm is introduced that utilizes a non-symmetric correlation kernel to reject multipath. Independent parameters provide a means to trade-off code tracking discriminant gain against multipath mitigation performance. The algorithm performance is characterized in terms of multipath phase error bias, phase error estimation variance, tracking range, tracking ambiguity and implementation complexity. The algorithm is suitable for modernized GNSS signals including Binary Phase Shift Keyed (BPSK) and a variety of Binary Offset Keyed (BOC) signals. The algorithm compensates for unbalanced code sequences to ensure a code tracking bias does not result from the use of asymmetric correlation kernels. The algorithm does not require explicit knowledge of the propagation channel model. Design recommendations for selecting the algorithm parameters to mitigate precorrelation filter distortion are also provided.
ContributorsMiller, Steven (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Tsakalis, Konstantinos (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Since its launch by the US Green Building Council (USGBC), Leadership in Energy and Environmental Design (LEED) certification has been postured as the "gold standard" for environmentally conscious, sustainable building design, construction and operations. However, as a "living measurement", one which requires ongoing evaluation and reporting of attainment and compliance with LEED certification requirements, there is none. Once awarded, LEED certification does not have a required reporting component to effectively track continued adherence to LEED standards. In addition, there is no expiry tied to the certification; once obtained, a LEED certification rating is presumed to be a valid representation of project certification status. Therefore, LEED lacks a requirement to demonstrate environmental impact of construction materials and building systems over the entire life of the project. Consequently, LEED certification is merely a label rather than a true representation of ongoing adherence to program performance requirements over time. Without continued monitoring and reporting of building design and construction features, and in the absence of recertification requirements, LEED is, in reality, a gold star rather than a gold standard. This thesis examines the lack of required ongoing monitoring, reporting, or recertification requirements following the award by the USGBC of LEED certification; compares LEED with other international programs which do have ongoing reporting or recertification requirements; demonstrates the need and benefit of ongoing reporting or recertification requirements; and explores possible methods for implementation of mandatory reporting requirements within the program.
ContributorsCarpenter, Anne Therese (Author) / Olson, Larry (Thesis advisor) / Hild, Nicholas (Committee member) / Brown, Albert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objective: The aim of this research is to uncover, via a comprehensive cross study analysis, data patterns that could potentially point to a positive correlation between two main variables: anesthetic monitoring equipment and anesthetic decision making. Of particular interest is the equipment's monitor screen and the extent to which its user interface design influences anesthetic situation awareness (SA) and hence, decision making. It is hypothesized that poor anesthetic diagnosis from inadequate SA may be largely attributable to patient data displays lacking in human factors design considerations. Methods: A systematic search was conducted of existing empirical studies pertaining to patient physiologic monitoring that spanned across interrelated domains, namely, ergonomics, medical informatics, visual computing, cognitive psychology, human factors, clinical monitoring, intensive care medicine, and intelligent systems etc. all published in scholarly research journals between 1970 to August 2012. Anesthetic-related keywords were queried i.e. anesthetic mishaps, patient physiological data displays, anesthetic vigilance etc. (found in Appendix A). This approach yielded a few thousand results, of which 65 empirical studies were pulled. Further extraction of articles having direct connection to the use of data displays within the anesthetic context produced a total of 20 empirical studies. These studies were grouped under two broad categories of Monitoring and Monitors whereby factors directly contributing to the studies' results were identified with the aim to find emerging themes that provide insights involving interface design and medical decision making. Results: There is a direct correlation between user-interface design and decision making. The situation awareness (SA) required for decision making heavily relies upon data displays oriented towards information extraction and integration. In the systematic assessment of empirical studies, it is undeniable how strikingly prominent visual attributes show up as contributing factors to subjects' enhanced performance in the studies. Conclusions: How and to what users direct their perceptual and cognitive resources necessarily influence their perception of the environment, and by extension, their development of situation awareness (SA). Although patient monitoring equipment employed in anesthetic practice has proven to be indispensable in quality patient care, graphical representations of patient data is still far from optimal in the clinical setting. User-interfaces that lend decision support to facilitate SA and subsequent decision making is critical in crisis management.
ContributorsNguyen, Angie (Author) / Velasquez, Joseph (Thesis advisor) / McDermott, Lauren (Thesis advisor) / Herring, Don (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2013