PARAMETRIZATION AND SHAPE RECONSTRUCTION TECHNIQUES FOR DOO-SABIN SUBDIVISION SURFACES

This thesis presents a new technique for the reconstruction of a smooth surface from a set of 3D data points. The reconstructed surface is represented by an everywhere -continuous subdivision surface which interpolates all the given data points. And the topological structure of the reconstructed surface is exactly the same as that of the data points. The new technique consists of two major steps. First, use an efficient surface reconstruction method to produce a polyhedral approximation to the given data points. Second, construct a Doo-Sabin subdivision surface that smoothly passes through all the data points in the given data set. A new technique is presented for the second step in this thesis. The new technique iteratively modifies the vertices of the polyhedral approximation 1CM until a new control meshM, whose Doo-Sabin subdivision surface interpolatesM, is reached. It is proved that, for any mesh M with any size and any topology, the iterative process is always convergent with Doo-Sabin subdivision scheme. The new technique has the advantages of both a local method and a global method, and the surface reconstruction process can reproduce special features such as edges and corners faithfully

An Empirical Study About the Effects of ‘Business Tax Reformed to VAT’ on Firms’ Bargaining Power: Based on DID Model

This study empirically examines whether the Business Tax reformed to value added tax (VAT) policy has an impact on the bargaining power of reformed industry firms based on Difference-in-Difference (DID) Model by using the A-share companies listed in both Shanghai Stock Exchange and Shenzhen Stock Exchange from 2010-2015. The bargaining power of firms is divided into two parts: the bargaining power of firms when negotiating with their suppliers and the bargaining power of firms when negotiating with their distributors. We find that the policy does have an impact on the bargaining power of reformed industry firms, specifically, the impact of the policy is to reduce firms’ bargaining power when negotiating with suppliers and improve their bargaining power when negotiating with dealers

Tobacco advertising

Tobacco advertising involves a variety of media formats (i.e., print, radio, television, billboards, point-of-sale, movie placement, Internet or social media, direct mail) and applies multiple persuasive tactics (e.g., visual appeal, sex appeal, masculinity and femininity cues, celebrity endorsement, motivational appeal) to encourage tobacco purchase and use. Scientific evidence points to the association between exposure to tobacco advertisements and subsequent increases in tobacco use. Due to the health risks of tobacco use, especially for youth, tobacco advertising is among the most regulated types of advertising. Globally, empirical research found that comprehensive tobacco advertising bans can reduce tobacco consumption, whereas partial tobacco advertising bans will have little or no effect as manufacturers may turn to non-banned media formats of advertisements. Other factors, such as transnational tobacco advertising, promotion and sponsorship, as well as electronic word-of-mouth (eWOM) enabled by the Internet, social media, and mobile communication, also pose additional challenges to health communication programs in tobacco control and prevention. This entry consists of five sections: (i) tobacco products and health risks, (ii) tobacco advertising and persuasive tactics, (iii) regulatory activities, (iv) anti-tobacco health communication, and (v) implications for health communication.Accepted manuscrip

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality

Learning Large-Scale MTP2_2 Gaussian Graphical Models via Bridge-Block Decomposition

This paper studies the problem of learning the large-scale Gaussian graphical models that are multivariate totally positive of order two ($\text{MTP}_2$). By introducing the concept of bridge, which commonly exists in large-scale sparse graphs, we show that the entire problem can be equivalently optimized through (1) several smaller-scaled sub-problems induced by a \emph{bridge-block decomposition} on the thresholded sample covariance graph and (2) a set of explicit solutions on entries corresponding to bridges. From practical aspect, this simple and provable discipline can be applied to break down a large problem into small tractable ones, leading to enormous reduction on the computational complexity and substantial improvements for all existing algorithms. The synthetic and real-world experiments demonstrate that our proposed method presents a significant speed-up compared to the state-of-the-art benchmarks