Improving the preconditioning of linear systems from interior point methods

This paper deals with preconditioners for solving linear systems arising from interior point methods, using iterative methods. The main focus is the development of a set of results that allows a more efficient computation of the splitting preconditioner. During the interior point methods iterations, the linear system matrix becomes ill conditioned, leading to numerical difficulties to find a solution, even with iterative methods. Therefore, the choice of an effective preconditioner is essential for the success of the approach. The paper proposes a new ordering for a splitting preconditioner, taking advantage of the sparse structure of the original matrix. A formal demonstration shows that performing this new ordering the preconditioned matrix condition number is limited; numerical experiments reinforce the theoretical results. Case studies show that the proposed idea has better sparsity features than the original version of the splitting preconditioner and that it is competitive regarding the computational time.     

Exploratory product search using top-k join queries

Given a relation that contains main products and a set of relations corresponding to accessory products that can be combined with a main product, the Exploratory Top-k Join query retrieves the k best combinations of main and accessory products based on user preferences. As a result, the user is presented with a set of k combinations of distinct main products, where a main product is combined with accessory products only if the combination has a better score than the single main product. We model this problem as a rank-join problem, where each combination is represented by a tuple from the main relation and a set of tuples from (some of) the accessory relations. The nature of the problem is challenging because the inclusion of accessory products is not predefined by the user, but instead all potential combinations (joins) are explored during query processing in order to identify the highest scoring combinations. Existing approaches cannot be directly applied to this problem, as they are designed for joining a predefined set of relations. In this paper, we present algorithms for processing exploratory top-k joins that adopt the pull-bound framework for rank-join processing. We introduce a novel algorithm (XRJN) which employs a more efficient bounding scheme and allows earlier termination of query processing. We also provide theoretical guarantees on the performance of this algorithm, by proving that XRJN is instance-optimal. In addition, we consider a pulling strategy that boosts the performance of query processing even further. Finally, we conduct a detailed experimental study that demonstrates the efficiency of the proposed algorithms in various setups.     

Political connections and corporate environmental responsibility: Adopting or escaping?

Corporate environmental responsibility (CER) is increasingly viewed as an important business strategy by researchers, investors, and society as a whole. While prior research has emphasized the role of social pressures, firm-specific factors, as well as CEO characteristics in CER, little attention has been paid to the impacts of political connections. We propose a mechanism-based framework to study how political connections affect firm's propensity to engage in CER. Using comprehensive environmental information disclosure data on China's listed firms, augmented by unique data on political connections, we find that political connections have a positive effect on CER. This effect is more pronounced for state-owned firms and in cities with stringent environmental regulations. With respect to the channels through which political connections increase CER, we further find that political connections help firms to receive government grants, subsidies and tax reduction related to the environment protection, and implement government environmental policies.     

NLP-based faceted search: Experience in the development of a science and technology search engine

An appropriate promotion, distribution and dissemination of scientific, artistic and technology developments can foster the collaboration between a country’s productive and academic sectors. The purpose of this paper is to present a novel search engine aiming at helping people to access science and technology advances, researchers and institutions working in specific areas of research. Our search engine first collects information disseminated on the Web in academic institution sites and in researchers personal homepages. Then, after intensive text processing, it summarizes the information in an enriched and user-friendly presentation oriented to non-expert users. Stable performance and an acceptable level of effectiveness for automatic named entities recognition indicate the potential of our approach for bridging the gap between the heterogeneous and unstructured information available on the Web about the research and development advances in a country and the innovation required by the productive sectors.     

Industrial structural transformation and carbon dioxide emissions in China

Using provincial panel data from the period 1995–2009 to analyze the relationship between the industrial structural transformation and carbon dioxide emissions in China, we find that the first-order lag of industrial structural adjustment effectively reduced the emissions; technical progress itself did not reduce the emissions, but indirectly led to decreasing emissions through the upgrading and optimization of industrial structure. Foreign direct investment and intervention by local governments reduced carbon dioxide emissions, but urbanization significantly increased the emissions. Thus, industrial structural adjustment is an important component of the development of a low-carbon economy. In the context of industrial structural transformation, an effective way to reduce a region’s carbon dioxide emissions is to promote the upgrading and optimization of industrial structure through technical progress. Tighter environmental access policies, selective utilization of foreign direct investment, and improvements in energy efficiency can help to reduce carbon dioxide emissions.     

Oil price effects on personal consumption expenditures

This paper uses a logistic smooth transition model to examine the impact of rising oil prices on personal consumption expenditures in open and industrialized economies. The empirical results suggest a nonlinear and asymmetric relation between oil price changes and personal consumption expenditures. In particular, the effects of rising oil prices on personal consumption expenditures are greater than those of falling oil prices. While oil price changes affect personal consumption expenditures via real balance effects, smooth transition effects also come into play. Below a threshold value, an increase in oil prices reduces personal consumption expenditures. In other words, in the face of uncertainty regarding future oil prices, consumers initially rationally postpone spending. However, once oil prices above the threshold after a prolonged upward trend, the prices of domestic production factors rise. This fuels continued price hikes and further increases personal consumption expenditures until a cost-pushed inflation takes hold. Due to differences in economic developments and structures, the effects of rising oil prices vary from one country to another, with different countries usually to different monetary policies from each other. As a result, personal consumption expenditures also show various patterns across countries.     

一种输入图像的色彩误差校正新模型

在分析扫描物呈色原理和误差产生原因的基础上，提出了一种扫描输入图像的色空间转换的修正模型。首先重新解释Neugebauer方程的参数含意，使原本只适用于印刷网点图像的Neugebauer方程也适用于非印刷网点图像。随后结合Neugebauer方程和RBF神经网络，分单色、双色和三色逐步导出输入图像的色彩修正方程。最后给出的实验结果表明，与目前具有较高转换精度的主流模型比较，本文模型能够明显提高转换精度。     

一种基于BP神经网络和呈色原理的扫描仪色彩管理新模型

在计算机技术和多媒体技术中,扫描仪是图象信息输入的主要输入设备之一,其色彩管理模型是图像在随后复制和传输过程中保持色彩一致性的关键.本文在分析扫描物呈色原理的基础上,提出了一种基于BP神经网络的扫描仪色彩管理模型.首先,该模型对扫描数据进行归一化的预处理,以满足BP网络对数据取值范围的要求;其次,该模型以彩色梯尺区色块代表整个色空间,以减少模型的运算量;再次,模型采用运动量动态调整模型步长,以加快BP网络收敛速度.最后,实验结果表明本文模型提高了色彩转换精度,能够满足扫描仪色彩管理的工程应用需求.     

合成信息系统与子信息系统的属性特征

数据库的合成和分解在实际应用中是一个很重要的问题，它所对应的数学模型就是信息系统的合成与分解，该文给出了对象合成信息系统、属性合成信息系统、对象子信息系统及属性子信息系统的定义，讨论了合成信息系统、子信息系统与原信息系统等属性特征之间的关系。