A UML profile for multidimensional modeling in data warehouses

The multidimensional (MD) modeling, which is the foundation of data warehouses (DWs), MD databases, and On-Line Analytical Processing (OLAP) applications, is based on several properties different from those in traditional database modeling. In the past few years, there have been some proposals, providing their own formal and graphical notations, for representing the main MD properties at the conceptual level. However, unfortunately none of them has been accepted as a standard for conceptual MD modeling.

In this paper, we present an extension of the Unified Modeling Language (UML) using a UML profile. This profile is defined by a set of stereotypes, constraints and tagged values to elegantly represent main MD properties at the conceptual level. We make use of the Object Constraint Language (OCL) to specify the constraints attached to the defined stereotypes, thereby avoiding an arbitrary use of these stereotypes. We have based our proposal in UML for two main reasons: (i) UML is a well known standard modeling language known by most database designers, thereby designers can avoid learning a new notation, and (ii) UML can be easily extended so that it can be tailored for a specific domain with concrete peculiarities such as the multidimensional modeling for data warehouses. Moreover, our proposal is Model Driven Architecture (MDA) compliant and we use the Query View Transformation (QVT) approach for an automatic generation of the implementation in a target platform. Throughout the paper, we will describe how to easily accomplish the MD modeling of DWs at the conceptual level. Finally, we show how to use our extension in Rational Rose for MD modeling.     

An Application of Extreme Value Theory for Measuring Financial Risk

Assessing the probability of rare and extreme events is an important issue in the risk management of financial portfolios. Extreme value theory provides the solid fundamentals needed for the statistical modelling of such events and the computation of extreme risk measures. The focus of the paper is on the use of extreme value theory to compute tail risk measures and the related confidence intervals, applying it to several major stock market indices.     

一种基于文本行和对角侧面特性的数字水印方法

针对文本文件的特点，提出一种基于文本的行和对角侧面特性水印方法．该方法利用文本具有行的特征嵌入水印信息，大大增加水印容量，提取水印只需要行对角侧面，可以不用原始文本参照，同时该方法还可以用文本对角侧面特性来检测文本的完整性．实验表明，这种方法对于典型的剪切和噪声干扰具有一定鲁棒性．     

On Measuring the Root-Mean-Square Value of a Finite Record Length Periodic Waveform

An analysis of the uncertainty in measuring the root-mean-square, rms or R_q, value of a periodic waveform which results from the use of a finite record length is presented. Even though the results of the analysis are somewhat as expected, i.e., that the uncertainty is inversely proportional to the number of periods in the record, the explicit relationship between the magnitude of the uncertainty and properties of the waveform does not appear to be available in the literature. The paper first presents an introductory example in terms of the reasonably well known case of bandwidth limited Gaussian waveform to introduce definitions. Following this is an analysis of the periodic waveform using the same approach. It is shown that for a large number of periods, n, in the record length, the normalized three standard deviation of the rms value is given by 3/(8πn).     

基于支持向量机的微阵列基因表达数据分析方法

DNA微阵列技术，使人们可以同时观测成千上万个基因的表达水平，对其数据的分析已成为生物信息学研究的焦点．针对微阵列基因表达数据维数高、样本小、非线性的特点，设计了一种基于支持向量机的基因表达数据分类识别方法，该方法采用信噪比进行基因特征提取，运用支持向量机的不同核函数进行性能测试，针对几个典型数据集的实验表明其识别效果良好．     

Diffusion tensor interpolation profile control using non-uniform motion on a Riemannian geodesic

Tensor interpolation is a key step in the processing algorithms of diffusion tensor imaging (DTI), such as registration and tractography. The diffusion tensor (DT) in biological tissues is assumed to be positive definite. However, the tensor interpolations in most clinical applications have used a Euclidian scheme that does not take this assumption into account. Several Rie-mannian schemes were developed to overcome this limitation. Although each of the Riemannian schemes uses different metrics, they all result in a ‘fixed’ interpolation profile that cannot adapt to a variety of diffusion patterns in biological tissues. In this paper, we propose a DT interpolation scheme to control the interpolation profile, and explore its feasibility in clinical applications. The profile controllability comes from the non-uniform motion of interpolation on the Riemannian geodesic. The interpolation experiment with medical DTI data shows that the profile control improves the interpolation quality by assessing the reconstruction errors with the determinant error, Euclidean norm, and Riemannian norm.     

OSI ISP国际功能标准

功能标准是指导OSI系统研制、开发、集成和应用的标准体系。本文介绍了OSI标准化现状和功能标准的由来,并重点描述了OSI ISP国际功能标准的概念、作用、分类及用法等内容。最后就我国的功能标准化工作提出了一些看法。     

南京老虎山黄土-古土壤剖面不同粒级组分的磁化率及其古气候意义

利用沉降离心法将老虎山黄土-古土壤的酸不溶相分离成<2μm、2～45μm和>45μm三个粒级组分,并分别测定了这些组分和全岩的磁化率。结果表明,无论是全岩,还是三个不同粒级组分,它们的磁化率都可以单独作为长江中下游地区古气候演变的参考指标。其中,<2μm粒级的质量磁化率明显大于全岩和2～45μm、>45μm两粒级,而且其分辨率也明显高于2～45μm和>45μm这两个粒级组分。本实验结果还显示,虽然<2μum的质量磁化率最大,但对全岩质量磁化率的贡献率与2～45μm粒级相当,>45μm粒级的贡献率较低。     

基于故障剖面的安全关键系统可靠性测试与评估

可靠性测试是安全关键系统可靠性评估的重要手段。论文结合在某电信系统的工程实践,介绍一种基于故障剖面的可靠性测试和评估的方法：通过逆向工程从已有的安全关键系统的失效事件中分析提取出故障概率数据,结合故障注入测试对系统的可靠性进行评估。该方法直接从故障入手,不受缺乏缺陷引发故障概率数据问题的困扰,并通过故障模式的双层模型明确测试范围,简化了评估过程。     

大数据环境下数字档案馆信息安全保障研究

随着大数据时代的全面来临,大数据分析技术下的信息安全问题逐渐引起社会各界的普遍关注,受多种因素影响,大数据环境下数字档案馆信息安全呈现出新特点,对信息安全保障建设提出更高要求。