国内外智能公交技术发展动态

进入信息时代，经济的快速发展和城市现代化进程的加快，大中城市不断在扩张，农村城市化的步伐也在加快。公共交通，这一世界各大中城市优先发展的行业面临着空前的巨大压力。传统的管理方式已不再能满足这种根本性变化，而一种先进的智能化管理就显得非常必要了。     

Handling measurement function changes with Slowly Changing Measures

Data Warehouses (DWs) are historical databases on business events, organized as multi-dimensional hypercubes that support analytical decision making. Extract, Transform, and Load (ETL) processes apply measurement functions to compute parameterized scores from the business events, such as sales figures, customer reliability scores, churn likelihood, or sentiment indices. These scores, saved as measures in the DW, serve as basis for analytical reports and corporate performance analysis. Dimensions model subject-oriented data used as analysis perspectives when interpreting the measures. While measures and measurement functions are traditionally regarded as stable within the DW schema, its dimension values commonly change over time.In reality, measures are also subject to change if DW designers (i) tune a parameter of the underlying measurement function, or (ii) update the scoring algorithm as a whole. In both scenarios, the changes must be obvious to the business analysts. Otherwise the changed measure semantics leads to incomparable measure values, and thus unsound and worthless analysis results.To handle measure evolution properly, this paper proposes Slowly Changing Measures (SCMs) as an additional DW modeling concept. Its core idea is a valid time for measurement functions, analogous to dimensions. The paper proposes four increasingly rich SCM types, each specifying a set of options for the change history management of measure definitions. Most of the SCM types provide for probable changes of measurement functions at design time, reducing manual interference to the necessary minimum upon the actual change.Each SCM type is explained in detail, and illustrated using a practical scenario. Furthermore, the paper presents a proof-of-concept prototype based on the TPC-H business model, and implemented in a simple relational database system. The pros and cons of every SCM type are discussed, and recommendations given for their implementation in a practical DW system.     

A review of: “ANTICIPATORY SYSTEMS”, by Robert Rosen,Pergamon Press,Oxford, 1985, X + 436pp.

In rough set theory there exists a pair of approximation operators, the upper and lower approximations, whereas in Dempster-Shafer theory of evidence there exists a dual pair of uncertainty measures, the plausibility and belief functions. It seems that there is some kind of natural connection between the two theories. The purpose of this paper is to establish the relationship between rough set theory and Dempster-Shafer theory of evidence. Various generalizations of the Dempster-Shafer belief structure and their induced uncertainty measures, the plausibility and belief functions, are first reviewed and examined. Generalizations of Pawlak approximation space and their induced approximation operators, the upper and lower approximations, are then summarized. Concepts of random rough sets, which include the mechanisms of numeric and non-numeric aspects of uncertain knowledge, are then proposed. Notions of the Dempster-Shafer theory of evidence within the framework of rough set theory are subsequently formed and interpreted. It is demonstrated that various belief structures are associated with various rough approximation spaces such that different dual pairs of upper and lower approximation operators induced by the rough approximation spaces may be used to interpret the corresponding dual pairs of plausibility and belief functions induced by the belief structures.     

基于径向基函数的高效网格变形算法研究

在流固耦合时域仿真与气动外形优化中,网格变形技术得到了普遍应用。基于径向基函数的网格变形技术以其诸多优良的特性,在近年来得到了广泛的关注。其基本原理是采用物面网格节点的位移构造一个径向基函数序列,再利用此序列将物面的位移光滑的插值到空间网格上。其计算耗时与物面插值节点数与空间等插值节点数的乘积成正比,为了减少其计算量,目前多数文献集中于使用数据精简算法减少物面插值节点数。本文通过引入子空间逐级逼近思想,构造了一种精简空间待插值节点数的方案,该方案主要思想是采用多次插值,每一次插值的对象为上一次插值在物面产生的误差,并且通过限制每一次插值的插值区域来实现减缩空间节点的目的。计算结果表明此方案可以支持大变形运动,同时显著的减少了计算时间。     

A Topological Semantics for Rule Extraction with Neural Networks

Rule extraction with neural networks is a subject of increasing interest. Research in this area could benefit from the availability of a formal model of the semantics of the rules. A model of this kind would express the relationship between the application data, the neural network learning model and the extracted rules with mathematical rigor, allowing systematic analysis and modification of rule extraction approaches and the neural network architectures used. However, formal models of this kind are not in common use. This paper proposes a formal semantic model and includes an analysis of an example rule extraction architecture and some issues raised by it and other architectures. In the formal model, the semantics of a neural network is expressed through a form of model theory based upon concepts from topology, including limit points and continuous functions. A state of adaptation of the neural network in which it has learned a set of rules from training data corresponds to a continuous function between topological systems. Topological systems, the domains of inputs to the network, are a generalization of the concept of a topological space. The results of an example analysis with this model suggest a direction for improvements to the example architecture and the desirability of applying the model to other rule extraction approaches.     

Reduced Functional Consistency of Uninterpreted Functions

A reduction of Equality Logic with Uninterpreted Functions (EUF) to Equality Logic with Ackermann's method suffers from a quadratic growth in the number of functional consistency constraints (constraints of the form x=y→F(x)=F(y)). We propose a framework in which syntactic characteristics of function instances (their signature) is used for guessing which constraints will possibly be needed for the proof. This framework can be either combined in an abstraction-refinement loop, or, in some cases, be used without refinement iterations. The framework is suitable for equivalence verification problems, which is one of the typical uses of Uninterpreted Functions. It enabled us to verify dozens of verification conditions resulting from Translation Validation that we could not prove otherwise.     

Incidence and lattice calculus with applications to stochastic geometry and image analysis

Incidence between subsets is a basic concept of stochastic geometry and mathematical morphology. In this note we discuss a formal generalisation of incidence (and the dual notion of dominance) in the setting of complete lattices. We discuss applications to mathematical morphology, random set theory and combinatorial geometrical probability. We also suggest possible applications to transmission microscopy, digital image discretization and robot motion planning. The generalised incidence structure turns out to be equivalent to the established idea of a lattice adjunction. Using this, many problems in stochastic geometry (Buffon-Sylvester problem, local knowledge, overprojection effects) can be reformulated as lattice calculations.     

基于 Givens旋转变换的PSWF脉冲调制信号PAPR抑制方法

针对基于椭圆球面波函数(Prolate Spheroidal Wave Function, PSWF)脉冲的调制信号峰均功率比过高的问题,该文提出一种基于Givens旋转的PSWF脉冲峰均功率比抑制方法.该方法从正交PSWF脉冲组的特征向量加权表示入手,利用 Givens旋转矩阵(,,)i j qG 对所有子坐标平面(,)i j 进行q角度的旋转,搜寻使脉冲组PAPR (Peak-to-Average Power Ratio, PAPR)值最小的旋转矩阵,最后利用该矩阵对原PSWF脉冲组进行Givens变换,从而实现降低PAPR的目标.针对Givens旋转次数较多导致计算复杂度大的问题,该文提出分组flipping迭代的算法实现方案.理论证明了该变换方法能够保持脉冲组的带内能量聚集和正交性.仿真结果表明,该方法有效降低了脉冲组的PAPR,同时系统传输效率、调制信号功率谱密度与系统误码率性能均保持不变.     

PSWF非正弦时域正交调制系统有限字长效应研究

在基于PSWF的非正弦数字通信中,二进制定点数的截尾误差与舍入误差对系统的性能影响不容忽视.首先分析了二进制定点数产生有限字长效应的原因,接着对二进制定点数的截尾误差与舍入误差进行了理论分析,同时,利用MATLAB针对PSWF通信系统中的具体参数进行了误差仿真,归纳与总结了仿真结果,可为工程应用提供参考.     

纳豆的营养保健作用及制作技术

纳豆营养丰富，保健价值极高。它具有防止骨质疏松、抑制高血糖、溶解血栓、抗菌消毒、预防高血压、抗癌等功能，本丈对纳豆的营养成分、生理功能、食用方法作一综述，并介绍了纳豆的制作工艺技术。