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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- Creators: Shen, Wei
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 traditional newspaper industry has been under tremendous pressure in recent years due to the emergence and growth of new media. Experiencing of a fast-shrinking market share, many traditional newspaper companies are either pushed out of business or are forced to innovate and reform. In this thesis, I investigate the organizational changes at one of the largest newspaper groups in China, particularly regarding its incentive systems as the group adjusts its business scopes under both internal and external institutional constraints.
Publishers of newspapers were traditionally considered non-profit organizations or social institutions in China. Because of their focus on social goals, their activities were not market driven, including the incentive systems for editorial staff members who were central to the content of the newspapers. As the competition from market-driven new media companies increased, many traditional newspaper organizations started to transform themselves into profit-seeking companies. To survive and grow stronger in the new environment, the traditional newspaper industry needs to effectively motivate its workforce by implementing an effective incentive system for the editorial staff.
In this study I first explain the difficulities the traditional newspaper organizations face to implement an incentive system that both satisfies media’s social responsibility and creates sufficient incentive for for editorial staff. Next, I provides a brief history of the reforms occurred in the Chinese newspaper industry in general and the reforms in Shanghai in particular. I then conduct in-depth case analyses of the incentive systems adopted by four successful companies, including one U.S. media company, two Chinese media groups, and one private non-media company in China. Based on the findings from these case analyses and a demographic analysis of the challenges in motivating editorial staff, a new incentive system is designed and implemented in a major newspaper/media group in Shanghai, followed by a survey of its effects on the editorial staff months later. According to the survey, I find that editorial staff members are generally positive about the reforms that have been carried out at this media group, reinforcing the confidence of the group’s leaders in continuing to push the reforms forward. This study concludes by proposing a framework that can be used to guide the transformation of the traditional newspaper organizations to market-driven new media companies.
Publishers of newspapers were traditionally considered non-profit organizations or social institutions in China. Because of their focus on social goals, their activities were not market driven, including the incentive systems for editorial staff members who were central to the content of the newspapers. As the competition from market-driven new media companies increased, many traditional newspaper organizations started to transform themselves into profit-seeking companies. To survive and grow stronger in the new environment, the traditional newspaper industry needs to effectively motivate its workforce by implementing an effective incentive system for the editorial staff.
In this study I first explain the difficulities the traditional newspaper organizations face to implement an incentive system that both satisfies media’s social responsibility and creates sufficient incentive for for editorial staff. Next, I provides a brief history of the reforms occurred in the Chinese newspaper industry in general and the reforms in Shanghai in particular. I then conduct in-depth case analyses of the incentive systems adopted by four successful companies, including one U.S. media company, two Chinese media groups, and one private non-media company in China. Based on the findings from these case analyses and a demographic analysis of the challenges in motivating editorial staff, a new incentive system is designed and implemented in a major newspaper/media group in Shanghai, followed by a survey of its effects on the editorial staff months later. According to the survey, I find that editorial staff members are generally positive about the reforms that have been carried out at this media group, reinforcing the confidence of the group’s leaders in continuing to push the reforms forward. This study concludes by proposing a framework that can be used to guide the transformation of the traditional newspaper organizations to market-driven new media companies.
ContributorsQiu, Xin (Author) / Shen, Wei (Thesis advisor) / Hwang, Yuhchang (Committee member) / Zhang, Anming (Committee member) / Arizona State University (Publisher)
Created2016