某些非循环2-群模表示空间的强平坦性和平坦性（英文）

研究特征为2域上,某些非循环2-群模表示空间的强平坦性和平坦性,确定对应模不变式环的深度。在阶数不为4的非循环交换2-群的不可分解表示中,有两种表示空间的类型是平坦的。对于非交换2群而言,如果群G是阶数为2^(n+2)的二面体群或广义四元数群,则其在维数为1+2~n的忠实表示都是平坦的,但都不是强平坦的。

Multipartite State Representations in Multi-mode Fock Space and Their Squeezing Transformations

We present the continuous state vector of the total coordinate of multi-partlcle and the state vector of their total momentum, respectively, which possess completeness relation in multi-mode Fock space by virtue of the integration within an order product （IWOP） technique. We also calculate the transition from classical transformation of variables in the states to quantum unitary operator, deduce a new multi-mode squeezing operator, and discuss its squeezing effect. In progress, it indicates that the IWOP technique provides a convenient way to construct new representation in quantum mechanics.

Knowledge representation and rule-based solution system for dynamic programming model

A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.

Knowledge Representation for the Geometrical Shapes

This paper outlines the necessity of the knowledge representation for the geometrical shapes （KRGS）. We advocate that KRGS for being powerful must contain at least three major components, namely （1） fuzzy logic scheme; （2） the machine learning technique; and （3） an integrated algebraic and logical reasoning. After arguing the need for using fuzzy expressions in spatial reasoning, then inducing the spatial graph generalized and maximal common part of the expressions is discussed. Finally, the integration of approximate references into spatial reasoning using absolute measurements is outlined. The integration here means that the satisfiability of a fuzzy spatial expression is conducted by both logical and algebraic reasoning.

The relations among the three kinds of conditional risk measures

Let（Ω , E, P） be a probability space, F a sub-σ-algebra of E, L^p（E）（1 p ＋∞） the classical function space and LF^p（E） the L^0（F）-module generated by L^p（E）, which can be made into a random normed module in a natural way. Up to the present time, there are three kinds of conditional risk measures, whose model spaces are L^∞（E）, L^p（E）（1 p ＋∞） and LF^p（E）（1 p ＋∞） respectively, and a conditional convex dual representation theorem has been established for each kind. The purpose of this paper is to study the relations among the three kinds of conditional risk measures together with their representation theorems. We first establish the relation between L^p（E） and LF^p（E）, namely LF^p（E） = Hcc（L^p（E））, which shows that LF^p（E）is exactly the countable concatenation hull of L^p（E）. Based on the precise relation, we then prove that every L^0（F）-convex L^p（E）-conditional risk measure（1 p ＋∞） can be uniquely extended to an L^0（F）-convex LF^p（E）-conditional risk measure and that the dual representation theorem of the former can also be regarded as a special case of that of the latter, which shows that the study of L^p-conditional risk measures can be incorporated into that of LF^p（E）-conditional risk measures. In particular, in the process we find that combining the countable concatenation hull of a set and the local property of conditional risk measures is a very useful analytic skill that may considerably simplify and improve the study of L^0-convex conditional risk measures.

A ubiquitous knowledgeable data representation model(UKRM) for three-dimensional geographic information systems(3D GIS)

In the face of complicated, diversified three-dimensional world, the existing 3D GIS data models suffer from certain issues such as data incompatibility, insufficiency in data representation and representation types, among others. It is often hard to meet the requirements of multiple application purposes(users) related to GIS spatial data management and data query and analysis, especially in the case of massive spatial objects. In this study, according to the habits of human thinking and recognition, discrete expressions(such as discrete curved surface(DCS), and discrete body(DB)) were integrated and two novel representation types(including function structure and mapping structure) were put forward. A flexible and extensible ubiquitous knowledgeable data representation model(UKRM) was then constructed, in which structurally heterogeneous multiple expressions(including boundary representation(B-rep), constructive solid geometry(CSG), functional/parameter representation, etc.) were normalized. GIS's ability in representing the massive, complicated and diversified 3D world was thus greatly enhanced. In addition, data reuse was realized, and the bridge linking static GIS to dynamic GIS was built up. Primary experimental results illustrated that UKRM was overwhelmingly superior to the current data models(e.g. IFC, City GML) in describing both regular and irregular spatial objects.

Functional Ontology for Conceptual Design Oriented Model Representation and Reuse

Functionality represents a blueprint of a product and plays a crucial role in problem-solving such as design.This article discusses the model representation from the angle of functional ontology by function deployment.We construct a framework of functional ontology which decomposes the function and contains a library of vocabulary to comprehensively represent the conceptual design model.The ontology enables the automatic identification system to search in the functional space.Furthermore,the functional ontology can form a systematic representation for the model so that it can be reused in the conceptual design and can be applied in the domain of knowledge fusion in our further work.