Applying XML for designing and interchanging information for multidimensional model

In order to exchange and share information among the conceptual models of data warehouse, and to build a solid base for the integration and share of metadata, a new multidimensional concept model is presented based on XML and its DTD is defined, which can perfectly describe various semantic characteristics of multidimensional conceptual model. According to the multidimensional conceptual modeling technique which is based on UML, the mapping algorithm between the multidimensional conceptual model is described based on XML and UML class diagram, and an application base for the wide use of this technique is given.

Precise large deviations for sums of random vectors in a multidimensional size-dependent renewal risk model

Consider a multidimensional renewal risk model, in which the claim sizes {Xk, k ≥1} form a sequence of independent and identically distributed random vectors with nonnegative components that are allowed to be dependent on each other. The univariate marginal distributions of these vectors have consistently varying tails and finite means. Suppose that the claim sizes and inter-arrival times correspondingly form a sequence of independent and identically distributed random pairs, with each pair obeying a dependence structure. A precise large deviation for the multidimensional renewal risk model is obtained.

The Application of Genetic Algorithms and Multidimensional Distinguishing Model in Forecasting and Evaluating Credits for Mobile Clients

To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client’s credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.

Research on Multidimensional Data Model in Data Warehouse

Data structure and semantics of the traditional data model cannot effectively represent the data warehouse, it is difficult to effectively support online analytical processing （referred to as OLAP）. This paper is propose a new multidimensional data model based on the partial ordering and mapping. The data model can fully express the complex data structure and semantics of data warehouse, and provide an OLAP operation as the core of the operation of algebra, support structure in levels of complex aggregation operation sequence, which can effectively support the application of OLAE The data model supports the concept of aggregation function constraint, and provides constraint mechanism of the hierarchy aggregation function.

A multidimensional examination of performances of HSR (High-Speed Rail) systems

This paper deals with a multidimensional examination of the infrastructural, technical/technological, operational, economic, social, and environmental performances of high-speed rail （HSR） systems, including their overview, analysis of some real-life cases, and limited （analytical） modeling. The infrastructural performances reflect design and geometrical characteristics of the HSR lines and stations. The technical/technological performances relate to the characteristics of rolling stock, i.e., high-speed trains, and supportive facilities and equipment, i.e., the power supply, signaling, and traffic control and management system（s）. The operational performances include the capacity and productivity of HSR lines and rolling stock, and quality of services. The economic per- formances refer to the HSR systems＇ costs, revenues, and their relationship. The social performances relate to the impacts of HSR systems on the society such as congestion, noise, and safety, and their externalities, and the effects in terms of contribution to the local and global/country social- economic development. Finally, the environmental performances of the HSR systems reflect their energy consumption and related emissions of green house gases, land use, and corresponding externalities.

User-Level Sentiment Evolution Analysis in Microblog

People's attitudes towards public events or products may change overtime,rather than staying on the same state.Understanding how sentiments change overtime is an interesting and important problem with many applications.Given a certain public event or product,a user's sentiments expressed in microblog stream can be regarded as a vector.In this paper,we define a novel problem of sentiment evolution analysis,and develop a simple yet effective method to detect sentiment evolution in user-level for public events.We firstly propose a multidimensional sentiment model with hierarchical structure to model user's complicate sentiments.Based on this model,we use FP-growth tree algorithm to mine frequent sentiment patterns and perform sentiment evolution analysis by Kullback-Leibler divergence.Moreover,we develop an improve Affinity Propagation algorithm to detect why people change their sentiments.Experimental evaluations on real data sets show that sentiment evolution could be implemented effectively using our method proposed in this article.

The Impact of Global Value Chain Embedment on Energy Conservation and Emissions Reduction:Theory and Empirical Evidence

An in-depth investigation into the effect of embedment in global value chain(GVC)on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation,and promoting high-quality development in China.This paper incorporates GVC embedment,energy consumption and carbon emissions into the same analysis framework for the first time.Based on the WIOD database,this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions:energy consumption intensity and energy consumption structure.The study found that GVC embedment significantly reduced the industry’s carbon emission intensity;developing economies’embedment in GVC helped reduce their carbon emission intensity,while the effect was not obvious in developed economies.GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries,but not conducive to carbon reduction of lowtech manufacturing.The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction,but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure.

Buildings and terrain unified-multidimensional dual data structure for GIS

3D city models are widely used in many disciplines and applications,such as urban planning,disaster management,and environmental simulation.Usually,the terrain and embedded objects like buildings are taken into consideration.A consistent model integrating these elements is vital for GIS analysis,especially if the geometry is accompanied by the topological relations between neighboring objects.Such a model allows for more efficient and errorless analysis.The memory consumption is another crucial aspect when the wide area of a city is considered-light models are highly desirable.Three methods of the terrain representation using the geometrical-topological data structure-the dual half-edge-are proposed in this article.The integration of buildings and other structures like bridges with the terrain is also presented.

ON IDENTIFIABILITY FOR MULTIDIMENSIONAL ARMAX MODEL

This paper gives a definition of identifiability for multidimensional linear input-output systems and presents a necessary and sufficient condition for its satisfaction.For a class of identifiable systems it is also shown that the unknown coeffcients of the system can consistently be estimated by a recursive algorithm.

Nonparametric Estimation for the Diffusion Coefficient of Multidimensional Time-Varying Diffusion Processes

This paper proposes a kernel estimator for the coefficient of multidimensional time-varying diffusion processes as an extension of the estimation model for one dimensional diffusion coefficient to the multidimensional case.By using"time division",the authors overcome the problem of sample observation in time varying model.In addition,the authors prove the strong consistency and limit distribution of the estimator.Finally,the authors test the performance of the estimator through a simulation experiment and an empirical application.