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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
Rabies disease remains enzootic among raccoons, skunks, foxes and bats in the United States. It is of primary concern for public-health agencies to control spatial spread of rabies in wildlife and its potential spillover infection of domestic animals and humans. Rabies is invariably fatal in wildlife if untreated, with a non-negligible incubation period. Understanding how this latency affects spatial spread of rabies in wildlife is the concern of chapter 2 and 3. Chapter 1 deals with the background of mathematical models for rabies and lists main objectives. In chapter 2, a reaction-diffusion susceptible-exposed-infected (SEI) model and a delayed diffusive susceptible-infected (SI) model are constructed to describe the same epidemic process -- rabies spread in foxes. For the delayed diffusive model a non-local infection term with delay is resulted from modeling the dispersal during incubation stage. Comparison is made regarding minimum traveling wave speeds of the two models, which are verified using numerical experiments. In chapter 3, starting with two Kermack and McKendrick's models where infectivity, death rate and diffusion rate of infected individuals can depend on the age of infection, the asymptotic speed of spread $c^\ast$ for the cumulated force of infection can be analyzed. For the special case of fixed incubation period, the asymptotic speed of spread is governed by the same integral equation for both models. Although explicit solutions for $c^\ast$ are difficult to obtain, assuming that diffusion coefficient of incubating animals is small, $c^\ast$ can be estimated in terms of model parameter values. Chapter 4 considers the implementation of realistic landscape in simulation of rabies spread in skunks and bats in northeast Texas. The Finite Element Method (FEM) is adopted because the irregular shapes of realistic landscape naturally lead to unstructured grids in the spatial domain. This implementation leads to a more accurate description of skunk rabies cases distributions.
ContributorsLiu, Hao (Author) / Kuang, Yang (Thesis advisor) / Jackiewicz, Zdzislaw (Committee member) / Lanchier, Nicolas (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Arizona State University (Publisher)
Created2013
Description
One explanation for membrane accommodation in response to a slowly rising current, and the phenomenon underlying the dynamics of elliptic bursting in nerves, is the mathematical problem of dynamic Hopf bifurcation. This problem has been studied extensively for linear (deterministic and stochastic) current ramps, nonlinear ramps, and elliptic bursting. These studies primarily investigated dynamic Hopf bifurcation in space-clamped excitable cells. In this study we introduce a new phenomenon associated with dynamic Hopf bifurcation. We show that for excitable spiny cables injected at one end with a slow current ramp, the generation of oscillations may occur an order one distance away from the current injection site. The phenomenon is significant since in the model the geometric and electrical parameters, as well as the ion channels, are uniformly distributed. In addition to demonstrating the phenomenon computationally, we analyze the problem using a singular perturbation method that provides a way to predict when and where the onset will occur in response to the input stimulus. We do not see this phenomenon for excitable cables in which the ion channels are embedded in the cable membrane itself, suggesting that it is essential for the channels to be isolated in the spines.
ContributorsBilinsky, Lydia M (Author) / Baer, Steven M. (Thesis advisor) / Crook, Sharon M (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gardner, Carl L (Committee member) / Jung, Ranu (Committee member) / Arizona State University (Publisher)
Created2012
Description
Entrepreneurship entails a transition from status quo to a founder/leader of a new organization, and the dominant view in the literature focuses on opportunities in a hypothetical situation, namely an entrepreneurial option. This study shifts the attention from an entrepreneurial option to a current situation and proposes that a perception of costliness in status quo as a driver of entrepreneurial decisions and strategies. Specifically, I propose that a perception of inequality due to the local hierarchy of an organization engenders motivation of disadvantaged employees to become a leader of his/her own entrepreneurial organization. Utilizing hierarchy-based power dynamics and attribution biases, I theorize that i) status gap between a leader and a member and ii) status distinctiveness of a leader in the current organization affect an entrepreneurial decision because of inequality perception. Furthermore, I hypothesize that entrepreneurial organizations driven by such status inequality are more likely to replicate the local structure of the previous employer in terms of status hierarchy to compensate for the perceived disadvantages in the previous employer. The empirical analyses of this study investigate entrepreneurial decisions and entrepreneurial team formation of jazz musicians from jazz discographies between 1950 and 2018, and I found supportive results. This study contributes to the entrepreneurship and inequality literature by bridging two research spaces. It first uncovers the roles of a negative perception of the status quo in entrepreneurship, in addition to the established idea of a positive perception of an alternative option. It also suggests a novel explanation of the long-standing question of inequality reproduction by looking at whether and how inequality spreads via entrepreneurship.
ContributorsJeon, Chunhu (Author) / Shen, Wei (Thesis advisor) / Bundy, Jonathan N (Thesis advisor) / Certo, S. Trevis (Committee member) / Arizona State University (Publisher)
Created2022
Description
This paper analyzes China's transformative changes over the past four decades through a microeconomic lens focused on enterprises. Market-oriented non-state-owned enterprises have emerged as a pivotal force driving China's economic development within this context. The article investigates the determinants of their development. Notably, more than half of market-oriented non-state-owned enterprises have entered the inheritance stage, necessitating the exploration of novel attributes for sustained growth.The study's research scope is defined across four dimensions, with a specific focus on approximately 4,000 market-oriented non-state-owned enterprises. It investigates the driving factors behind sustained performance growth at various stages of these enterprises, emphasizing five variables: "partnership governance, entrepreneurial spirit, development strategy, incentive mechanisms, and innovation capability." Employing a combination of "typical case studies" and "group validation" methods, the research examines the factors influencing sustained growth in these enterprises and their interrelationships. The goal is to construct a model for enterprise succession and development, ultimately offering recommendations to foster sustained growth.
The research paper is structured into an introduction, literature review and theoretical foundation, typical case studies, empirical research on a group, and a conclusion.
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Key findings include: Partnership governance positively impacts partners' entrepreneurial spirit, promoting sustained performance growth. Trajectory-oriented development strategies, effective incentive mechanisms, and leading innovation capabilities have a positive moderating effect on entrepreneurial spirit, fostering sustained performance growth. During the innovation development phase, partnership governance significantly influences entrepreneurial spirit with a noteworthy environmental moderation effect.
The paper recommends implementing a "Dual-Factor Improvement Model" that enhances both partnership governance systems and the selection and functioning mechanisms of entrepreneurial spirit partners. This approach aims to boost partners' entrepreneurial spirit and facilitate high-quality succession in market-oriented non-state-owned enterprises，，ultimately achieving sustained high-quality growth.
In conclusion, this research contributes to a deeper understanding of sustained performance growth in enterprises. It offers valuable insights for the succession and development of market-oriented non-state-owned enterprises and innovation-driven entrepreneurship. This research holds significant value in advancing sustained high-quality development among market-oriented non-state-owned enterprises in China, optimizing resource allocation, and nurturing talented individuals.
ContributorsDeng, Cheng (Author) / Shen, Wei (Thesis advisor) / Cheng, Shijun (Thesis advisor) / Wu, Fei (Committee member) / Arizona State University (Publisher)
Created2023
Description
With the increasing aging population in China, the public's emphasis on health has been on the rise. Many innovative pharmaceutical companies have undertaken multiple rounds of financing, with some going public through IPOs. As a high-tech industry, it is essential to study the relationship between the level of corporate publicity and the financing process.This study collected information on the number of promotional articles, timing, and platforms of dozens of pharmaceutical companies that have already gone public through IPOs using Python. An analysis was conducted on the temporal variations of promotional articles for ten representative companies. It was found that the number of promotional articles experienced a significant increase in the month of IPO or the month before, and remained relatively high even after the IPO.
Furthermore, the Pearson correlation coefficient method was used to analyze the correlation between the number of promotional articles and various stages of financing. The study found a positive correlation between the daily average number of promotional articles before IPO and the final financing amount. Additionally, a strong positive correlation was observed between the daily average number of promotional articles from 7 days before IPO to IPO day and the turnover rate on IPO day. Grey correlation analysis was also employed to analyze the impact of publicity on the financing amount of each
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financing round, revealing that the financing round and the Shanghai Composite Index had a significant influence.
Finally, a multiple regression analysis was conducted to examine the relationship between the pre-IPO financing scale, IPO-day trading amount, and the level of corporate publicity. The regression results indicated that the pre-IPO financing scale was mainly influenced by the number of promotional articles in the 7 days preceding IPO, particularly for pharmaceutical companies listed on the A-share market. Moreover, a negative correlation was observed between the financing round and the financing amount, particularly among companies that experienced a decline in share price on the IPO day. However, the study found a weak association between the IPO-day trading amount and the level of corporate publicity, primarily observed among pharmaceutical companies listed on the A-share market.
ContributorsMiao, Yujia (Author) / Shen, Wei (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Cheng, Shijun (Committee member) / Arizona State University (Publisher)
Created2024
Description
Solar power, as an important part of renewable energy, has become one of the main choices for countries around the world in their energy strategic layout due to its cleanliness, renewability, and distributed attributes. In the context of the booming photovoltaic industry, China has emerged a large number of excellent photovoltaic companies, driving the whole industry to reduce costs and increase efficiency, making many contributions to the grid parity of photovoltaic power generation. In the development lifecycle of the photovoltaic industry, various companies choose different competitive strategies to deal with industry cyclical changes and external uncertainty based on their core competitiveness and market opportunities. Vertical integration is one of the strategic paths chosen by many photovoltaic companies. Therefore, it is an important issue to explore the impact of vertical integration on the development of Chinese photovoltaic companies.Based on the data of China's A-share listed photovoltaic companies from 2018 to 2022, this paper uses panel fixed effect model to empirically test the impact of vertical integration on corporate valuation, explores its influencing mechanism, and further analyzes the moderating effect of enterprise heterogeneity factors. The research in this paper shows that: (1) under other conditions unchanged, vertical integration significantly improves the valuation level of enterprises, and this positive impact will not change with the measurement method of enterprise valuation level. This is because the higher the vertical integration degree of enterprises, the stronger their ability to respond to external uncertainty. The more enterprises can obtain capital market preferences, the higher the enterprise valuation will be. This also means that the higher the vertical integration degree of photovoltaic enterprises, the higher their market share is, and they are more able to avoid the impact of external uncertainty, thus obtaining a higher valuation level in the secondary market. (2) The intermediary effect test shows that the channel for vertical integration of photovoltaic enterprises to affect enterprise valuation levels is to increase their market share. (3) Further heterogeneity analysis shows that enterprise profitability and enterprise size positively regulate the impact of vertical integration on enterprise valuation, while enterprise management shareholding ratio and enterprise operating cost ratio will weaken the positive promotion effect of vertical integration.
The research conclusions of this paper provide micro-empirical evidence for how photovoltaic companies can improve their enterprise valuation, and also provide some management references for other unlisted companies in the same industry.
Keywords: Photovoltaic enterprises; Vertical integration; Corporate valuation; Fixed effect model
ContributorsZheng, Ren (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhao, Yanfei (Committee member) / Arizona State University (Publisher)
Created2024
Description
During the inversion of discrete linear systems, noise in data can be amplified and result in meaningless solutions. To combat this effect, characteristics of solutions that are considered desirable are mathematically implemented during inversion. This is a process called regularization. The influence of the provided prior information is controlled by the introduction of non-negative regularization parameter(s). Many methods are available for both the selection of appropriate regularization parame- ters and the inversion of the discrete linear system. Generally, for a single problem there is just one regularization parameter. Here, a learning approach is considered to identify a single regularization parameter based on the use of multiple data sets de- scribed by a linear system with a common model matrix. The situation with multiple regularization parameters that weight different spectral components of the solution is considered as well. To obtain these multiple parameters, standard methods are modified for identifying the optimal regularization parameters. Modifications of the unbiased predictive risk estimation, generalized cross validation, and the discrepancy principle are derived for finding spectral windowing regularization parameters. These estimators are extended for finding the regularization parameters when multiple data sets with common system matrices are available. Statistical analysis of these estima- tors is conducted for real and complex transformations of data. It is demonstrated that spectral windowing regularization parameters can be learned from these new esti- mators applied for multiple data and with multiple windows. Numerical experiments evaluating these new methods demonstrate that these modified methods, which do not require the use of true data for learning regularization parameters, are effective and efficient, and perform comparably to a supervised learning method based on es- timating the parameters using true data. The theoretical developments are validated for one and two dimensional image deblurring. It is verified that the obtained estimates of spectral windowing regularization parameters can be used effectively on validation data sets that are separate from the training data, and do not require known data.
ContributorsByrne, Michael John (Author) / Renaut, Rosemary (Thesis advisor) / Cochran, Douglas (Committee member) / Espanol, Malena (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2023
Description
On January 30, 2019, the China Securities Regulatory Commission issued the Implementation Opinions on the Establishment of the Science and Technology Innovation Board on the Shanghai Stock Exchange and the Pilot Registration-based System, announcing the establishment of a new Science and Technology Innovation Board(STAR). The STAR Market is an important measure in China's capital market reform, aiming to promote the transformation of China's economy from a stage of rapid growth to a stage of high-quality development. The companies listed on the Science and Technology Innovation Board are mainly scientific and technological innovation enterprises that are at the forefront of the world's science and technology, the main battlefield of the economy, and the major needs of the country, in line with the national strategy, breaking through key core technologies, and with high market recognition. Since its launch on July 22, 2019, to May, 15, 2023, there are 522 companies have been listed on the STAR Market, with a total market capitalization of more than RMB 7 trillion. The successful listing of these enterprises will provide strong support for the deep integration of China's high-tech industries and strategic emerging industries.This paper analyzes the influencing factors of IPO listing pricing on the STAR Market, and studies 1478 companies listed on the three listing platforms of the STAR Market, ChiNext and Hong Kong stocks. Through descriptive statistical analysis and multivariate regression model, the influencing factors of the 1st day and the 20th day were empirically studied. The results of the study will provide a pricing reference for
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listed companies in the future, and provide a reference for policymakers to meet the expectations of the new regulatory reforms.
Through analysis of multiple factors includes but not limited as the NR,IPE, LEAD, ISCA, T10, AOL, BC, STL, RDI, CAGR, DTOR, these influencing factors have an important impact on the IPO of the STAR Market.
ContributorsHuang, Danyang (Author) / Shen, Wei (Thesis advisor) / Cheng, Shijun (Thesis advisor) / Jiang, Zhan (Committee member) / Arizona State University (Publisher)
Created2024
Description
Over the past two decades, propelled by urbanization, domestic investment and construction of commercial complexes have rapidly accelerated. This has led to a dramatic expansion of these complexes with swift operational iterations and related data changes. The impact of changing domestic and international financial policies, along with political environments, has seen e-commerce gradually seize the middle and low-end retail markets. Additionally, the global spread of the COVID-19 pandemic in the last three years has resulted in a substantial slowdown in domestic economic growth. Despite this, there is still developmental potential, prompting unprecedented attention to corporate investment and commercial operations.However, acquiring basic operational data in commerce is challenging, with inconsistent measurement standards among enterprises, hindering accurate and systematic judgments of operational performance. The factors influencing the operational performance of commercial complexes in China remain inadequately researched.At this juncture, the scientific measurement of commercial complex operational performance is crucial for their healthy development. This study explores the relationship between enterprise investment behavior, operational management behavior, and commercial complex operational performance. It measures influencing factors using resource configuration theory to control uncontrollable environmental factors, such as urban hierarchy, surrounding population, per capita GDP, surrounding commercial inventory and increment, and location planning support. Dynamic capability theory is then applied to investigate the impact of variables like the number of leases, area, brands, lease cost income, marketing activity types, activity funds, and activity time on operational performance. A model is established to analyze operational performance, contrasting significant variables before and after the pandemic, identifying factors affecting operational performance in early-stage investment and later-stage management strategies. Post-pandemic adjustments are suggested to adapt to changing environmental conditions.In the empirical research section, this paper validates the theoretical model through data analysis, studying the volatility of operational performance based on factors influencing commercial complexes. Integrating theoretical backgrounds, it analyzes investment and management strategies for enterprises in different situations, emphasizing key indicators. This provides enterprises with better choices for future projects and empowers commercial complex managers for effective future management, enhancing operational performance. The study offers a theoretical basis and guidance for promoting the healthy development of the market.
ContributorsHuang, Ke (Author) / Shen, Wei (Thesis advisor) / Zhu, Qigui (Thesis advisor) / Hu, Yu (Committee member) / Arizona State University (Publisher)
Created2024