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
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
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
After a decade of efforts, accurate and affordable DNA sequencing continues to remain an important goal in current research landscape. This thesis starts with a brief overview of the recent updates in the field of DNA sequencing technologies followed by description of the nanofluidics route to single molecule DNA detection. Chapter 2 presents discusses carbon nanotube(CNT) based nanofluidics. The fabrication and DNA sensing measurements of CNT forest membrane devices are presented. Chapter 3 gives the background for functionalization and recognition aspects of reader molecules. Chapter 4 marks the transition to solid state nanopore nanofluidics. The fabrication of Imidazole functionalized nanopores is discussed. The Single Molecule detection results of DNA from Palladium nanopore devices are presented next. Combining chemical recognition to nanopore technology, it has been possible to prolong the duration of single molecule events from the order of a few micro seconds to upto a few milliseconds. Overall, the work presented in this thesis promises longer single molecule detection time in a nanofludic set up and paves way for novel nanopore- tunnel junction devices that combine recognition chemistry, tunneling device and nanopore approach.
ContributorsKrishnakumar, Padmini (Author) / Lindsay, Stuart (Thesis advisor) / He, Jin (Committee member) / Vaiana, Sara (Committee member) / Schmidt, Kevin (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
The thesis studies new methods to fabricate optoelectronic Ge1-ySny/Si(100) alloys and investigate their photoluminescence (PL) properties for possible applications in Si-based photonics including IR lasers. The work initially investigated the origin of the difference between the PL spectrum of bulk Ge, dominated by indirect gap emission, and the PL spectrum of Ge-on-Si films, dominated by direct gap emission. It was found that the difference is due to the supression of self-absorption effects in Ge films, combined with a deviation from quasi-equilibrium conditions in the conduction band of undoped films. The latter is confirmed by a model suggesting that the deviation is caused by the shorter recombination lifetime in the films relative to bulk Ge. The knowledge acquired from this work was then utilized to study the PL properties of n-type Ge1-ySny/Si (y=0.004-0.04) samples grown via chemical vapor deposition of Ge2H6/SnD4/P(GeH3)3. It was found that the emission intensity (I) of these samples is at least 10x stronger than observed in un-doped counterparts and that the Idir/Iind ratio of direct over indirect gap emission increases for high-Sn contents due to the reduced gamma-L valley separation, as expected. Next the PL investigation was expanded to samples with y=0.05-0.09 grown via a new method using the more reactive Ge3H8 in place of Ge2H6. Optical quality, 1-um thick Ge1-ySny/Si(100) layers were produced using Ge3H10/SnD4 and found to exhibit strong, tunable PL near the threshold of the direct-indirect bandgap crossover. A byproduct of this study was the development of an enhanced process to produce Ge3H8, Ge4H10, and Ge5H12 analogs for application in ultra-low temperature deposition of Group-IV semiconductors. The thesis also studies synthesis routes of an entirely new class of semiconductor compounds and alloys described by Si5-2y(III-V)y (III=Al, V= As, P) comprising of specifically designed diamond-like structures based on a Si parent lattice incorporating isolated III-V units. The common theme of the two thesis topics is the development of new mono-crystalline materials on ubiquitous silicon platforms with the objective of enhancing the optoelectronic performance of Si and Ge semiconductors, potentially leading to the design of next generation optical devices including lasers, detectors and solar cells.
ContributorsGrzybowski, Gordon (Author) / Kouvetakis, John (Thesis advisor) / Chizmeshya, Andrew (Committee member) / Menéndez, Jose (Committee member) / Arizona State University (Publisher)
Created2013
Description
Dimensionality assessment is an important component of evaluating item response data. Existing approaches to evaluating common assumptions of unidimensionality, such as DIMTEST (Nandakumar & Stout, 1993; Stout, 1987; Stout, Froelich, & Gao, 2001), have been shown to work well under large-scale assessment conditions (e.g., large sample sizes and item pools; see e.g., Froelich & Habing, 2007). It remains to be seen how such procedures perform in the context of small-scale assessments characterized by relatively small sample sizes and/or short tests. The fact that some procedures come with minimum allowable values for characteristics of the data, such as the number of items, may even render them unusable for some small-scale assessments. Other measures designed to assess dimensionality do not come with such limitations and, as such, may perform better under conditions that do not lend themselves to evaluation via statistics that rely on asymptotic theory. The current work aimed to evaluate the performance of one such metric, the standardized generalized dimensionality discrepancy measure (SGDDM; Levy & Svetina, 2011; Levy, Xu, Yel, & Svetina, 2012), under both large- and small-scale testing conditions. A Monte Carlo study was conducted to compare the performance of DIMTEST and the SGDDM statistic in terms of evaluating assumptions of unidimensionality in item response data under a variety of conditions, with an emphasis on the examination of these procedures in small-scale assessments. Similar to previous research, increases in either test length or sample size resulted in increased power. The DIMTEST procedure appeared to be a conservative test of the null hypothesis of unidimensionality. The SGDDM statistic exhibited rejection rates near the nominal rate of .05 under unidimensional conditions, though the reliability of these results may have been less than optimal due to high sampling variability resulting from a relatively limited number of replications. Power values were at or near 1.0 for many of the multidimensional conditions. It was only when the sample size was reduced to N = 100 that the two approaches diverged in performance. Results suggested that both procedures may be appropriate for sample sizes as low as N = 250 and tests as short as J = 12 (SGDDM) or J = 19 (DIMTEST). When used as a diagnostic tool, SGDDM may be appropriate with as few as N = 100 cases combined with J = 12 items. The study was somewhat limited in that it did not include any complex factorial designs, nor were the strength of item discrimination parameters or correlation between factors manipulated. It is recommended that further research be conducted with the inclusion of these factors, as well as an increase in the number of replications when using the SGDDM procedure.
ContributorsReichenberg, Ray E (Author) / Levy, Roy (Thesis advisor) / Thompson, Marilyn S. (Thesis advisor) / Green, Samuel B. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The work contained in this dissertation is focused on the optical properties of direct band gap semiconductors which crystallize in a wurtzite structure: more specifically, the III-nitrides and ZnO. By using cathodoluminescence spectroscopy, many of their properties have been investigated, including band gaps, defect energy levels, carrier lifetimes, strain states, exciton binding energies, and effects of electron irradiation on luminescence. Part of this work is focused on p-type Mg-doped GaN and InGaN. These materials are extremely important for the fabrication of visible light emitting diodes and diode lasers and their complex nature is currently not entirely understood. The luminescence of Mg-doped GaN films has been correlated with electrical and structural measurements in order to understand the behavior of hydrogen in the material. Deeply-bound excitons emitting near 3.37 and 3.42 eV are observed in films with a significant hydrogen concentration during cathodoluminescence at liquid helium temperatures. These radiative transitions are unstable during electron irradiation. Our observations suggest a hydrogen-related nature, as opposed to a previous assignment of stacking fault luminescence. The intensity of the 3.37 eV transition can be correlated with the electrical activation of the Mg acceptors. Next, the acceptor energy level of Mg in InGaN is shown to decrease significantly with an increase in the indium composition. This also corresponds to a decrease in the resistivity of these films. In addition, the hole concentration in multiple quantum well light emitting diode structures is much more uniform in the active region when Mg-doped InGaN (instead of Mg-doped GaN) is used. These results will help improve the efficiency of light emitting diodes, especially in the green/yellow color range. Also, the improved hole transport may prove to be important for the development of photovoltaic devices. Cathodoluminescence studies have also been performed on nanoindented ZnO crystals. Bulk, single crystal ZnO was indented using a sub-micron spherical diamond tip on various surface orientations. The resistance to deformation (the "hardness") of each surface orientation was measured, with the c-plane being the most resistive. This is due to the orientation of the easy glide planes, the c-planes, being positioned perpendicularly to the applied load. The a-plane oriented crystal is the least resistive to deformation. Cathodoluminescence imaging allows for the correlation of the luminescence with the regions located near the indentation. Sub-nanometer shifts in the band edge emission have been assigned to residual strain the crystals. The a- and m-plane oriented crystals show two-fold symmetry with regions of compressive and tensile strain located parallel and perpendicular to the ±c-directions, respectively. The c-plane oriented crystal shows six-fold symmetry with regions of tensile strain extending along the six equivalent a-directions.
ContributorsJuday, Reid (Author) / Ponce, Fernando A. (Thesis advisor) / Drucker, Jeff (Committee member) / Mccartney, Martha R (Committee member) / Menéndez, Jose (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microwave dielectrics are widely used to make resonators and filters in telecommunication systems. The production of thin films with high dielectric constant and low loss could potentially enable a marked reduction in the size of devices and systems. However, studies of these materials in thin film form are very sparse. In this research, experiments were carried out on practical high-performance dielectrics including ZrTiO4-ZnNb2O6 (ZTZN) and Ba(Co,Zn)1/3Nb2/3O3 (BCZN) with high dielectric constant and low loss tangent. Thin films were deposited by laser ablation on various substrates, with a systematical study of growth conditions like substrate temperature, oxygen pressure and annealing to optimize the film quality, and the compositional, microstructural, optical and electric properties were characterized. The deposited ZTZN films were randomly oriented polycrystalline on Si substrate and textured on MgO substrate with a tetragonal lattice change at elevated temperature. The BCZN films deposited on MgO substrate showed superior film quality relative to that on other substrates, which grow epitaxially with an orientation of (001) // MgO (001) and (100) // MgO (100) when substrate temperature was above 500 oC. In-situ annealing at growth temperature in 200 mTorr oxygen pressure was found to enhance the quality of the films, reducing the peak width of the X-ray Diffraction (XRD) rocking curve to 0.53o and the χmin of channeling Rutherford Backscattering Spectrometry (RBS) to 8.8% when grown at 800oC. Atomic Force Microscopy (AFM) was used to study the topography and found a monotonic decrease in the surface roughness when the growth temperature increased. Optical absorption and transmission measurements were used to determine the energy bandgap and the refractive index respectively. A low-frequency dielectric constant of 34 was measured using a planar interdigital measurement structure. The resistivity of the film is ~3×1010 ohm·cm at room temperature and has an activation energy of thermal activated current of 0.66 eV.
ContributorsLi, You (Author) / Newman, Nathan (Thesis advisor) / Alford, Terry (Committee member) / Singh, Rakesh (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation is focused on material property exploration and analysis using computational quantum mechanics methods. Theoretical calculations were performed on the recently discovered hexahydride materials A2SiH6 (A=Rb, K) to calculate the lattice dynamics of the systems in order to check for structural stability, verify the experimental Raman and infrared spectrospcopy results, and obtain the theoretical free energies of formation. The electronic structure of the systems was calculated and the bonding and ionic properties of the systems were analyzed. The novel hexahydrides were compared to the important hydrogen storage material KSiH3. This showed that the hypervalent nature of the SiH62- ions reduced the Si-H bonding strength considerably. These hydrogen rich compounds could have promising energy applications as they link to alternative hydrogen fuel technology. The carbide systems Li-C (A=Li,Ca,Mg) were studied using \emph{ab initio} and evolutionary algorithms at high pressures. At ambient pressure Li2C2 and CaC2 are known to contain C22- dumbbell anions and CaC2 is polymorphic. At elevated pressure both CaC2 and Li2C2 display polymorphism. At ambient pressure the Mg-C system contains several experimentally known phases, however, all known phases are shown to be metastable with respect to the pure elements Mg and C. First principle investigation of the configurational space of these compounds via evolutionary algorithms results in a variety of metastable and unique structures. The binary compounds ZnSb and ZnAs are II-V electron-poor semiconductors with interesting thermoelectric properties. They contain rhomboid rings composed of Zn2Sb2 (Zn2As2) with multi-centered covalent bonds which are in turn covalently bonded to other rings via two-centered, two-electron bonds. Ionicity was explored via Bader charge analysis and it appears that the low ionicity that these materials display is a necessary condition of their multicentered bonding. Both compounds were found to have narrow, indirect band gaps with multi-valley valence and conduction bands; which are important characteristics for high thermopower in thermoelectric materials. Future work is needed to analyze the lattice properties of the II-V CdSb-type systems, especially in order to find the origin of the extremely low thermal conductivity that these systems display.
ContributorsBenson, Daryn Eugene (Author) / Häussermann, Ulrich (Thesis advisor) / Shumway, John (Thesis advisor) / Chamberlin, Ralph (Committee member) / Sankey, Otto (Committee member) / Treacy, Mike (Committee member) / Arizona State University (Publisher)
Created2013