An eighteenth century Mexican folding screen or biombo is located at Virginia House in Richmond, Virginia. A similar three-paneled screen is also located at this site. Upon seeing the similarities between each screen I concluded that the seven panels were at one point a part of one folding screen. The top sections of these folding screens show emblems that depict images of virtues and vices. The source of the emblems on the Virtue Screen is Otto Van Veen's Homtii Emblemata. The text on the screen is taken from a Spanish translation of the Horatii Emblemata entitled the Theatro Moral de toda la Philosophia de los Antiguos y Modernos. This thesis will examine each emblem in a panel-by-panel discussion as well as the iconography found throughout the screen. It will also provide a brief history of the folding screen with its origins in Asia and a comparison of similar screens that have been discovered in the Western Hemisphere.

This work focuses on the problem of planning solar array operations on the International Space Station. The goal is to find a viable orientation for ten joints which attach panels to the station. These orientations and modes must satisfy various constraints and the final schedule should also take into account certain preferences. This is a task suitable for automated planning and scheduling, but new technologies are gaining very slowly in the field of the human spaceflights. In this work we will analyze the current solution of this problem and then we will propose a new algorithm that will exploit techniques of automated planning and scheduling. In the contrast with the original greedy algorithm, the suggested algorithm initially finds any solution and then tries to improve it by optimazing partial objective functions. Due to the size of the search space, the search attempts are limited by the time limit. Powered by TCPDF (www.tcpdf.org)

The main purpose of this thesis is to investigate the effect of corruption on income inequality (that could serve as indicator of the welfare of whole society). Since post-communist countries of Central and Eastern Europe had issues with providing effective policies for adapting to the market economy, we want to discover main drivers of this situation. We examined previous researches that suggest both positive and negative correlation between corruption level and income inequality. Main obstacle of the research is inherent heterogeneity present across countries. Our analysis was performed on two datasets: 11 post- communist countries CEE and additional 17 European Union countries. We implemented different estimation methods and discovered that panel Vector autoregressive model is the best choice. Within the panel structure we tackled individual heterogeneity by estimating fixed effects and clustering on the country level, implemented dynamic relationship in the dependent variable and solved endogeneity problem by using instrumental variable. We found that corruption has positive relationship with income inequality. Furthermore, other important drivers are: social spending, education level and unemployment. As a result, we suggested the ways to decrease corruption on the appropriate example of...

Axxor is one the main leader in paper honeycomb production by supplying automotive, furniture, and door manufacturers. Paper honeycomb material holds the lead over any existing cores in performance, price and density ratio. The main drawback of PHC products is its lack of water/fire resistance which reduces significantly its scope of applications. Consequently, the Axxor company intends to perform a new type of product which could withstand a water exposition: impregnated paper honeycomb. By coating the paper honeycomb cellulose fibers, the mechanical properties are significantly improved with three times higher compressive strength compared to PHC. Two impregnated resins have been selected for a potential large scale production: Epoxy and Polyurethane resins. The totality of IPHC is produced through two processes which are a manual impregnation performed by hand or a continuous impregnation performed by an impregnation machine. With these independent variables in mind, this study concerns the degree of water resistance by comparing three IPHC samples: - Epoxy IPHC performed with handmade impregnation - Polyurethane IPHC performed with handmade impregnation - Polyurethane IPHC performed with the impregnation machine (higher resin content) By using the available characterization devices, water resistance is defined by measuring the decreases of the mechanical performances depending on the remaining water content in each samples.

The influence of ‘credit crunch’ on Small and Medium sized Enterprises (SMEs) has been of concern to the government, regulators, banks, the enterprises and the public. Using a large dataset of UK SMEs’ records covering the early period of the ‘credit crunch’, the influence of the ‘credit crunch’ on SMEs have been studied. It uses cross-sectional method, panel data models and GAM to provide a detailed examination of SMEs performance. Both newly established and matured SMEs, segmented by age, are considered separately. The data contains 79 variables which covered obligors’ general condition, financial information, directors’ portfolio and other relevant credit histories. The ‘credit crunch’ is a typical ‘black swan’ phenomenon. As such there is a need to examine whether the stepwise logistic model, the industries prime modelling tool, could deal with the sudden change in SMEs credit risk. Whilst it may be capable of modelling the situation alternatives models may be more appropriate. It provides a benchmark for comparison to other models and shows how well the industry’s standard model performs. Given cross-sectional models only provide aggregative level single time period analysis, panel models are used to study SMEs performance through the crisis period. To overcome the pro-cyclic feature of logistic model, macroeconomic variables were added to panel data model. This allows examination of how economic conditions influence SMEs during ‘credit crunch’. The use of panel data model leads to a discussion of fixed and random effects estimation and the use of explanatory macroeconomic variables. The panel data model provides a detailed analyse of SMEs’ behaviour during the crisis period. Under parametric models, especially logistic regression, data is usually transformed to allow for the non-linear correlation between independent variable and dependent variable. However, this brings difficulty in understanding influence of each independent variable’s marginal effects. Another way of dealing with this is to add non-parametric effects. In this study, Generalized Additive Models (GAM) allows for non-parametric effects. A natural extension of logistic regression is a GAM model with logistic link function. In order to use the data in their original state an alternative method of processing missing values is proposed, which avoids data transformation, such as the use of weights of evidence (WoE). GAM with original data could derive a direct marginal trend and plot how explanatory variables influence SMEs’ ‘bad’ rate. Significant non-parametric effects are found for both ‘start-ups’ and ‘non-start-ups’. Using GAM models results in higher prediction accuracy and improves model transparency by deriving explanatory variables’ marginal effects.

My dissertation consists of three chapters that focus on panel data models in econometrics and under high dimensionality; that is, both the number of individuals and the number of time periods are large. This high dimensionality is widely applicable in practice, as economists increasingly face large dimensional data sets. This dissertation contributes to the methodology and techniques that deal with large data sets. All the models studied in the three chapters contain a factor structure, which provides various ways to extract information from large data sets. Chapter 1 and Chapter 2 use the factor structure to capture the comovement of economic variables, where the factors represent the common shocks and the factor loadings represent the heterogeneous responses to these shocks. Common shocks are widely present in the real world, for example, global financial shocks, macroeconomic shocks and energy price shocks. In applications where common shocks exist, failing to capture these common shocks would lead to biased estimation. Factor models provide a way to capture these common shocks. In contrast to Chapter 1 and Chapter 2, Chapter 3 directly focuses on the factor model with the loadings being constrained, in order to reduce the number of parameters to be estimated. In addition to the common shocks effect, Chapter 1 considers two other effects: spatial effects and simultaneous effects. The spatial effect is present in models where dependent variables are spatially interacted and spatial weights are specified based on location and distance, in a geographic space or in more general economic, social or network spaces. The simultaneous effect comes from the endogeneity of the dependent variables in a simultaneous equations system, and it is important in many structural economic models. A model including all these three effects would be useful in various fields. In estimation, all the three chapters propose quasi-maximum likelihood (QML) based estimation methods and further study the asymptotic properties of these estimators by providing a full inferential theory, which includes consistency, convergence rate and limiting distribution. Moreover, I conduct Monte-Carlo simulations to investigate the finite sample performance of these proposed estimators. Specifically, Chapter 1 considers a simultaneous spatial panel data model with common shocks. Chapter 2 studies a panel data model with heterogenous coefficients and common shocks. Chapter 3 studies a high dimensional constrained factor model. In Chapter 1, I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a QML method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the two estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further investigate the finite sample performance of both methods using Monte-Carlo simulations. I find that both methods perform well and that the simulation results corroborate the inferential theories. Some extensions of the model are considered. Finally, I apply the model to analyze the relationship between trade and GDP using a panel data over time and across countries. Chapter 2 investigates efficient estimation of heterogeneous coefficients in panel data models with common shocks, which have been a particular focus of recent theoretical and empirical literature. It proposes a new two-step method to estimate the heterogeneous coefficients. In the first step, a QML method is first conducted to estimate the loadings and idiosyncratic variances. The second step estimates the heterogeneous coefficients by using the structural relations implied by the model and replacing the unknown parameters with their QML estimates. Further, Chapter 2 establishes the asymptotic theory of the estimator, including consistency, asymptotic representation, and limiting distribution. The two-step estimator is asymptotically efficient in the sense that it has the same limiting distribution as the infeasible generalized least squares (GLS) estimator. Intensive Monte-Carlo simulations show that the proposed estimator performs robustly in a variety of data setups. Chapter 3 documents the estimation and inferential theory of high dimensional constrained factor models. Factor models have been widely used in practice. However, an undesirable feature of a high dimensional factor model is that the model has too many parameters. An effective way to address this issue, proposed in Tsai and Tsay (2010), is to decompose the loadings matrix by a high-dimensional known matrix multiplying with a low-dimensional unknown matrix, which Tsai and Tsay (2010) name the constrained factor models. Chapter 3 proposes a QML method to estimate the model and develops the asymptotic properties of its estimators. A new statistic is proposed for testing the null hypothesis of constrained factor models against the alternative of standard factor models. Partially constrained factor models are also investigated. Monte-Carlo simulations confirm the theoretical results and show that the QML estimators and the proposed new statistic perform well in finite samples. Chapter 3 also considers the extension to an approximate constrained factor model where the idiosyncratic errors are allowed to be weakly dependent processes.

Precast concrete sandwich wall panels (PCSWPs) have been used in the precast industry for decades due to their durability, rapid construction, and thermal efficiency. Shear connectors are used to connect the two wythes of concrete to allow composite action of the system. The use of glass fiber reinforced polymer (GFRP) connectors is a relatively recent breakthrough in PCSWP design. GFRP connectors allow full composite action to occur, while still maintaining the thermal efficiency of the system by not allowing thermal bridging to occur. In order to design concrete sandwich panel systems to act compositely, the engineer must obtain design values from a connector manufacturer, often times making engineers uncomfortable. Shear connectors are typically proprietary and are required to first have design values often times varies by each company. This project aimed to compare existing testing methodologies in order to better inform engineers about design decisions. This project used two methodologies of shear testing on five different types of composite action connectors. Testing was performed using single-shear and double-shear "push-off" tests. In order to gather enough statistical data to compare the testing methodologies, 22 single-shear and 48 double-shear small scale specimens were designed, fabricated, and loaded through failure at the Utah State University SMASH Lab. Testing was performed by applying loads perpendicular to the connectors and measuring the load and amount of deflection that occurred. Using the load-deflection relationships obtained, stiffness values were calculated and recorded for each test. A statistical analysis was performed based on the observed data. This study concluded that the ultimate strength capacity and stiffness of connectors will change depending on the testing methodology used. Single-shear testing will generally provide less ultimate strength and less stiffness when compared to double-shear testing.

The study examines the development of telecommunications and its impacts on Chinese economic growth since telecommunications has been undergoing dramatic reforms in the 1980s. On November 2001, China was officially the WTO member to open the market for foreign investors. It is obvious that the telecommunications infrastructure development can play a key role in economic growth in China. Furthermore, China has become the world’s single largest telecommunications market since 2002. In this research, I present evidence that it empirically not only investigates the telecommunications development and its impacts on economic growth, but also tests their relationship with initial economic condition, fixed investment, population growth, foreign direct investment as well as telecommunications infrastructure development using the panel data approach with a dynamic fixed effect model for the span of time from 2003 to 2008. I find that that mobile phone user density to be the new proxy for telecommunications infrastructure in China contributes in a major way to the economic growth. It means that mobile communication systems do have positive impact and effect on the regional economy of China. It is a crucial determinant as findings indicate a significant and positive correlation between telecommunications development and regional growth in China, after controlling for a number of other factors. Results also show that investment in telecommunications is subject to diminishing returns.

<p>The efficacy and accuracy of information is very important for making decision in stock markets. In this paper, we study on the effect of information diffusion in Chinese stock market before and after the owership release in February 19, 2001, by testing the stationary of A share premium and cointegration between A and B share prices. The panel unit root tests we propose on A share premium are Augmented Dickey-Fullar (ADF) tests for individual firm and Fisher tests for the panel, based on combining pvalues from each individual cross-section. The panel cointegration tests on A and B shares we use is Johansen’s likelihood ratio tests for individual firm and likelihoodbased panel cointegraion tests for panel, based on combining the test statistics. The results show that before the opening of B share markets to domestic investors, A share premiums have a unit root and there is no cointegration relationship between A and B share markets. On the contrary, after ownership release, A share premium is stationary and there is cointegration relationship between A and B share markets.</p>

The efficacy and accuracy of information is very important for making decision in stock markets. In this paper, we study on the effect of information diffusion in Chinese stock market before and after the owership release in February 19, 2001, by testing the stationary of A share premium and cointegration between A and B share prices. The panel unit root tests we propose on A share premium are Augmented Dickey-Fullar (ADF) tests for individual firm and Fisher tests for the panel, based on combining pvalues from each individual cross-section. The panel cointegration tests on A and B shares we use is Johansen’s likelihood ratio tests for individual firm and likelihoodbased panel cointegraion tests for panel, based on combining the test statistics. The results show that before the opening of B share markets to domestic investors, A share premiums have a unit root and there is no cointegration relationship between A and B share markets. On the contrary, after ownership release, A share premium is stationary and there is cointegration relationship between A and B share markets.