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.
Displaying 1 - 10 of 187
Filtering by
- Creators: Jiao, Yang
- Creators: Shen, Wei
- Creators: Gu, Bin
Description
Social media offers a powerful platform for the independent digital content producer community to develop, disperse, and maintain their brands. In terms of information systems research, the broad majority of the work has not examined hedonic consumption on Social Media Sites (SMS). The focus has mostly been on the organizational perspectives and utilitarian gains from these services. Unlike through traditional commerce channels, including e-commerce retailers, consumption enhancing hedonic utility is experienced differently in the context of a social media site; consequently, the dynamic of the decision-making process shifts when it is made in a social context. Previous research assumed a limited influence of a small, immediate group of peers. But the rules change when the network of peers expands exponentially. The assertion is that, while there are individual differences in the level of susceptibility to influence coming from others, these are not the most important pieces of the analysis--unlike research centered completely on influence. Rather, the context of the consumption can play an important role in the way social influence factors affect consumer behavior on Social Media Sites. Over the course of three studies, this dissertation will examine factors that influence consumer decision-making and the brand personalities created and interpreted in these SMS. Study one examines the role of different types of peer influence on consumer decision-making on Facebook. Study two observes the impact of different types of producer message posts with the different types of influence on decision-making on Twitter. Study three will conclude this work with an exploratory empirical investigation of actual twitter postings of a set of musicians. These studies contribute to the body of IS literature by evaluating the specific behavioral changes related to consumption in the context of digital social media: (a) the power of social influencers in contrast to personal preferences on SMS, (b) the effect on consumers of producer message types and content on SMS at both the profile level and the individual message level.
ContributorsSopha, Matthew (Author) / Santanam, Raghu T (Thesis advisor) / Goul, Kenneth M (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2013
Description
In accordance with the Principal Agent Theory, Property Right Theory, Incentive Theory, and Human Capital Theory, firms face agency problems due to “separation of ownership and management”, which call for effective corporate governance. Ownership structure is a core element of the corporate governance. The differences in ownership structures thus may result in differential incentives in governance through the selection of senior management and in the design of senior management compensation system. This thesis investigates four firms with four different types of ownership structures: a public listed firm with the controlling interest by the state, a public listed firm with a non-state-owned controlling interest, a public listed firm a family-owned controlling interest, and a Sino-foreign joint venture firm. By using a case study approach, I focus on two dimensions of ownership structure characteristics – ownership diversification and differences in property rights so as to document whether there are systematic differences in governance participation and executive compensation design. Specifically, I focused on whether such differences are reflected in management selection (which is linked to adverse selection and moral hazard problems) and in compensation design (the choices of performance measurements, performance pay, and in stock option or restricted stock). The results are consistent with my expectation – the nature of ownership structure does affect senior management compensation design. Policy implications are discussed accordingly.
ContributorsGao, Shenghua (Author) / Pei, Ker-Wei (Thesis advisor) / Li, Feng (Committee member) / Shen, Wei (Committee member) / Arizona State University (Publisher)
Created2015
Description
For decades, microelectronics manufacturing has been concerned with failures related to electromigration phenomena in conductors experiencing high current densities. The influence of interconnect microstructure on device failures related to electromigration in BGA and flip chip solder interconnects has become a significant interest with reduced individual solder interconnect volumes. A survey indicates that x-ray computed micro-tomography (µXCT) is an emerging, novel means for characterizing the microstructures' role in governing electromigration failures. This work details the design and construction of a lab-scale µXCT system to characterize electromigration in the Sn-0.7Cu lead-free solder system by leveraging in situ imaging.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
ContributorsMertens, James Charles Edwin (Author) / Chawla, Nikhilesh (Thesis advisor) / Alford, Terry (Committee member) / Jiao, Yang (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2015
Description
Mobile applications (Apps) markets with App stores have introduced a new approach to define and sell software applications with access to a large body of heterogeneous consumer population. Several distinctive features of mobile App store markets including – (a) highly heterogeneous consumer preferences and values, (b) high consumer cognitive burden of searching a large selection of similar Apps, and (c) continuously updateable product features and price – present a unique opportunity for IS researchers to investigate theoretically motivated research questions in this area. The aim of this dissertation research is to investigate the key determinants of mobile Apps success in App store markets. The dissertation is organized into three distinct and related studies. First, using the key tenets of product portfolio management theory and theory of economies of scope, this study empirically investigates how sellers’ App portfolio strategies are associated with sales performance over time. Second, the sale performance impacts of App product cues, generated from App product descriptions and offered from market formats, are examined using the theories of market signaling and cue utilization. Third, the role of App updates in stimulating consumer demands in the presence of strong ranking effects is appraised. The findings of this dissertation work highlight the impacts of sellers’ App assortment, strategic product description formulation, and long-term App management with price/feature updates on success in App market. The dissertation studies make key contributions to the IS literature by highlighting three key managerially and theoretically important findings related to mobile Apps: (1) diversification across selling categories is a key driver of high survival probability in the top charts, (2) product cues strategically presented in the descriptions have complementary relationships with market cues in influencing App sales, and (3) continuous quality improvements have long-term effects on App success in the presence of strong ranking effects.
ContributorsLee, Gun Woong (Author) / Santanam, Raghu (Thesis advisor) / Gu, Bin (Committee member) / Park, Sungho (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD) employed to generate the packing ensembles will be discussed. A large number of 2D packing configurations of superdisks are subsequently analyzed, through which a relatively accurate theoretical scheme for packing-fraction prediction based on local particle contact configurations is proposed and validated via additional numerical simulations. Moreover, the studies on binary ellipsoid packing in 3D are briefly discussed and the effects of different geometrical parameters on the final packing fraction are analyzed.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Oswald, Jay (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
The theme for this work is the development of fast numerical algorithms for sparse optimization as well as their applications in medical imaging and source localization using sensor array processing. Due to the recently proposed theory of Compressive Sensing (CS), the $\ell_1$ minimization problem attracts more attention for its ability to exploit sparsity. Traditional interior point methods encounter difficulties in computation for solving the CS applications. In the first part of this work, a fast algorithm based on the augmented Lagrangian method for solving the large-scale TV-$\ell_1$ regularized inverse problem is proposed. Specifically, by taking advantage of the separable structure, the original problem can be approximated via the sum of a series of simple functions with closed form solutions. A preconditioner for solving the block Toeplitz with Toeplitz block (BTTB) linear system is proposed to accelerate the computation. An in-depth discussion on the rate of convergence and the optimal parameter selection criteria is given. Numerical experiments are used to test the performance and the robustness of the proposed algorithm to a wide range of parameter values. Applications of the algorithm in magnetic resonance (MR) imaging and a comparison with other existing methods are included. The second part of this work is the application of the TV-$\ell_1$ model in source localization using sensor arrays. The array output is reformulated into a sparse waveform via an over-complete basis and study the $\ell_p$-norm properties in detecting the sparsity. An algorithm is proposed for minimizing a non-convex problem. According to the results of numerical experiments, the proposed algorithm with the aid of the $\ell_p$-norm can resolve closely distributed sources with higher accuracy than other existing methods.
ContributorsShen, Wei (Author) / Mittlemann, Hans D (Thesis advisor) / Renaut, Rosemary A. (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gelb, Anne (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2011
Description
The study of deflagration to detonation transition (DDT) in explosives is of prime importance with regards to insensitive munitions (IM). Critical damage owing to thermal or shock stimuli could translate to significant loss of life and material. The present study models detonation and deflagration of a commonly used granular explosive: cyclotetramethylene-tetranitramine, HMX. A robust literature review is followed by computational modeling of gas gun and DDT tube test data using the Sandia National Lab three-dimensional multi-material Eulerian hydrocode CTH. This dissertation proposes new computational practices and models that aid in predicting shock stimulus IM response. CTH was first used to model experimental data sets of DDT tubes from both Naval Surface Weapons Center and Los Alamos National Laboratory which were initiated by pyrogenic material and a piston, respectively. Analytical verification was performed, where possible, for detonation via empirical based equations at the Chapman Jouguet state with errors below 2.1%, and deflagration via pressure dependent burn rate equations. CTH simulations include inert, history variable reactive burn and Arrhenius models. The results are in excellent agreement with published HMX detonation velocities. Novel additions include accurate simulation of the pyrogenic material BKNO3 and the inclusion of porosity in energetic materials. The treatment of compaction is especially important in modeling precursory hotspots, caused by hydrodynamic collapse of void regions or grain interactions, prior to DDT of granular explosives. The CTH compaction model of HMX was verified within 11% error via a five pronged validation approach using gas gun data and employed use of a newly generated set of P-α parameters for granular HMX in a Mie-Gruneisen Equation of State. Next, the additions of compaction were extended to a volumetric surface burning model of HMX and compare well to a set of empirical burn rates. Lastly, the compendium of detonation and deflagration models was applied to the aforementioned DDT tubes and demonstrate working functionalities of all models, albeit at the expense of significant computational resources. A robust hydrocode methodology is proposed to make use of the deflagration, compaction and detonation models as a means to predict IM response to shock stimulus of granular explosive materials.
ContributorsMahon, Kelly Susan (Author) / Lee, Taewoo (Thesis advisor) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Jiao, Yang (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Materials with unprecedented properties are necessary to make dramatic changes in current and future aerospace platforms. Hybrid materials and composites are increasingly being used in aircraft and spacecraft frames; however, future platforms will require an optimal design of novel materials that enable operation in a variety of environments and produce known/predicted damage mechanisms. Nanocomposites and nanoengineered composites with CNTs have the potential to make significant improvements in strength, stiffness, fracture toughness, flame retardancy and resistance to corrosion. Therefore, these materials have generated tremendous scientific and technical interest over the past decade and various architectures are being explored for applications to light-weight airframe structures. However, the success of such materials with significantly improved performance metrics requires careful control of the parameters during synthesis and processing. Their implementation is also limited due to the lack of complete understanding of the effects the nanoparticles impart to the bulk properties of composites. It is common for computational methods to be applied to explain phenomena measured or observed experimentally. Frequently, a given phenomenon or material property is only considered to be fully understood when the associated physics has been identified through accompanying calculations or simulations.
The computationally and experimentally integrated research presented in this dissertation provides improved understanding of the mechanical behavior and response including damage and failure in CNT nanocomposites, enhancing confidence in their applications. The computations at the atomistic level helps to understand the underlying mechanochemistry and allow a systematic investigation of the complex CNT architectures and the material performance across a wide range of parameters. Simulation of the bond breakage phenomena and development of the interface to continuum scale damage captures the effects of applied loading and damage precursor and provides insight into the safety of nanoengineered composites under service loads. The validated modeling methodology is expected to be a step in the direction of computationally-assisted design and certification of novel materials, thus liberating the pace of their implementation in future applications.
The computationally and experimentally integrated research presented in this dissertation provides improved understanding of the mechanical behavior and response including damage and failure in CNT nanocomposites, enhancing confidence in their applications. The computations at the atomistic level helps to understand the underlying mechanochemistry and allow a systematic investigation of the complex CNT architectures and the material performance across a wide range of parameters. Simulation of the bond breakage phenomena and development of the interface to continuum scale damage captures the effects of applied loading and damage precursor and provides insight into the safety of nanoengineered composites under service loads. The validated modeling methodology is expected to be a step in the direction of computationally-assisted design and certification of novel materials, thus liberating the pace of their implementation in future applications.
ContributorsSubramanian, Nithya (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2018
Description
Aluminum alloys are ubiquitously used in almost all structural applications due to their high strength-to-weight ratio. Their superior mechanical performance can be attributed to complex dispersions of nanoscale intermetallic particles that precipitate out from the alloy’s solid solution and offer resistance to deformation. Although they have been extensively investigated in the last century, the traditional approaches employed in the past haven’t rendered an authoritative microstructural understanding in such materials. The effect of the precipitates’ inherent complex morphology and their three-dimensional (3D) spatial distribution on evolution and deformation behavior have often been precluded. In this study, for the first time, synchrotron-based hard X-ray nano-tomography has been implemented in Al-Cu alloys to measure growth kinetics of different nanoscale phases in 3D and reveal mechanistic insights behind some of the observed novel phase transformation reactions occurring at high temperatures. The experimental results were reconciled with coarsening models from the LSW theory to an unprecedented extent, thereby establishing a new paradigm for thermodynamic analysis of precipitate assemblies. By using a unique correlative approach, a non-destructive means of estimating precipitation-strengthening in such alloys has been introduced. Limitations of using existing mechanical strengthening models in such alloys have been discussed and a means to quantify individual contributions from different strengthening mechanisms has been established.
The current rapid pace of technological progress necessitates the demand for more resilient and high-performance alloys. To achieve this, a thorough understanding of the relationships between material properties and its structure is indispensable. To establish this correlation and achieve desired properties from structural alloys, microstructural response to mechanical stimuli needs to be understood in three-dimensions (3D). To that effect, in situ tests were conducted at the synchrotron (Advanced Photon Source) using Transmission X-Ray Microscopy as well as in a scanning electron microscope (SEM) to study real-time damage evolution in such alloys. Findings of precipitate size-dependent transition in deformation behavior from these tests have inspired a novel resilient aluminum alloy design.
The current rapid pace of technological progress necessitates the demand for more resilient and high-performance alloys. To achieve this, a thorough understanding of the relationships between material properties and its structure is indispensable. To establish this correlation and achieve desired properties from structural alloys, microstructural response to mechanical stimuli needs to be understood in three-dimensions (3D). To that effect, in situ tests were conducted at the synchrotron (Advanced Photon Source) using Transmission X-Ray Microscopy as well as in a scanning electron microscope (SEM) to study real-time damage evolution in such alloys. Findings of precipitate size-dependent transition in deformation behavior from these tests have inspired a novel resilient aluminum alloy design.
ContributorsKaira, Chandrashekara Shashank (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran (Committee member) / Jiao, Yang (Committee member) / De Andrade, Vincent (Committee member) / Arizona State University (Publisher)
Created2017
Description
How to play the advantages of network loan platform to reduce the financing costs of net loan platform both in theory and practice has important significance. In this paper, we use the method of qualitative and quantitative combination. First of all, through the interview of the net loan platform practitioners, the financing cost of the net loan platform comes from the internal and external parts. Part of the network loan platform should be righteous, but counterproductive human and material costs, credit costs, information efficiency, transaction costs and matching costs; part of the emerging industry as a challenge, compliance costs, technical costs and safety costs and other cost. And put forward the top design credit system, promote the credit system; build a unified development of regulatory policies to reduce compliance risks; increase investment in technology, share the improvement of technological progress bonuses. Through the establishment of the regression model, the paper analyzes the influence of various indexes of network loan platform on the cost of network reception. It is found that the background of net loan platform with shareholder and executive team as the proxy variable has significant influence on the cost of network loan platform. The effect is not significant. Risk control indicators on the net loan platform cost has a significant negative effect. The impact of operating capacity on the cost of net loan platform differentiation, the acquisition of the cost of positive relations, the other is negative relations. Policy compliance indicators of financial security on the net loan platform cost significantly, the other did not significantly affect the role of liquidity indicators of differentiation, the average borrowing period will significantly affect the net loan platform costs, liquidity is a negative impact. And finally put forward the policy and recommendations and research limitations and future direction.
ContributorsRen, Junxia (Author) / Gu, Bin (Thesis advisor) / Chang, Chun (Thesis advisor) / Qian, Jun (Committee member) / Arizona State University (Publisher)
Created2017