Measures of Association and Visualization of Log Odds Ratio Structure for a Two Way Contingency Table

The odds ratio (OR) is a measure of association used for analysing an I × J contingency table. The total number of ORs to check grows with I and J. Several statistical methods have been developed for summarising them. These methods begin from two different starting points, the I × J contingency table and the two‐way table composed by the ORs. In this paper we focus our attention on the relationship between these methods and point out that, for an exhaustive analysis of association through log ORs, it is necessary to consider all the outcomes of these methods. We also introduce some new methodological and graphical features. In order to illustrate previously used methodologies, we consider a data table of the cross‐classification of the colour of eyes and hair of 5387 children from Scotland. We point out how, through the log OR analysis, it is possible to extract useful information about the association between variables.     

记忆素与北京城市文化身份--对1980年代京味小说的一种解读

与老舍小说展现老北京广阔的社会历史风貌不同,1980年代京味小说对于北京城市文化身份的型构,是通过极度浓缩简化并重复出现的“记忆素”来实现的。这些由人物、行动、空间与情节组成的“记忆素”具有高度的趋同性。而这些“记忆素”作为一种“传统的发明”,并不是要对老北京的历史文化进行多么精致的还原,而是为了应对“文革”结束后和北京城现代化过程中所出现的城市与人的身份危机而作出的一种解答。     

后发企业如何构建创新网络—基于知识架构的视角

构建创新网络是后发企业快速进行技术追赶的重要路径。那么，针对不同的企业，构筑什么样的创新网络是有效的? 为了深化以往的创新网络研究，从知识架构的视角出发，聚焦于网络层次的合作伙伴配置，构建了以产业特征为情境条件，知识基宽度/深度为焦点企业特征，知识异质性/质量为创新网络节点组成特征，高创新追赶绩效为结果变量的逻辑模型。结论显示，有三种相应的架构类型能够获取高创新追赶绩效。此外，在不同的产业特征情境下，不同的企业分别可以采用相应的架构类型取得更好的绩效。以此，为后发企业构建有效创新网络提供了理论和实践的借鉴。     

从语义学到心灵哲学： 重思对阿奎那关于理智之非物质性论证的一些批评

阿奎那关于个别感觉与普遍理性表征的理论是其对理智之非物质性论证的关键部分，但这一理论受到司各特、奥卡姆及布里丹等后来者的批评。然而，这些批评其实都不能成立。阿奎那的论证并不像罗伯特·帕斯纳奥对他的诘难中所说的那样，犯了从一个表征的语义内容推出此表征之本体论属性的“内容谬误”。此外，由布里丹本人的评论可以看出，布里丹实际上不得不接受他所批评的阿奎那论证所蕴含的主要内容。     

Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials

In situations where the structure of one of the variables of a contingency table is ordered recent theory involving the augmentation of singular vectors and orthogonal polynomials has shown to be applicable for performing symmetric and non-symmetric correspondence analysis. Such an approach has the advantage of allowing the user to identify the source of variation between the categories in terms of components that reflect linear, quadratic and higher-order trends. The purpose of this paper is to focus on the study of two asymmetrically related variables cross-classified to form a two-way contingency table where only one of the variables has an ordinal structure.     

基于VoiceXML的图书馆IVR系统设计研究

文章对基于VoiceXML的IVR系统的关键技术、系统架构模型进行了分析,并对高校图书馆IVR系统的主要功能做以描述,最后对部分代码进行了举例说明。     

Cumulative correspondence analysis using orthogonal polynomials

Taguchi's statistic has long been known to be a more appropriate measure of association of the dependence for ordinal variables compared to the Pearson chi-squared statistic. Therefore, there is some advantage in using Taguchi's statistic in the correspondence analysis context when a two-way contingency table consists at least of an ordinal categorical variable. The aim of this paper, considering the contingency table with two ordinal categorical variables, is to show a decomposition of Taguchi's index into linear, quadratic and higher-order components. This decomposition has been developed using Emerson's orthogonal polynomials. Moreover, two case studies to explain the methodology have been analyzed.     

SoC软硬件协同技术的FPGA芯片测试新方法

针对传统的基于纯硬件平台的FPGA芯片测试方法所存在的种种问题,提出并验证了一种基于软硬件协同技术的FPGA芯片测试方法。该方法引入了软件的灵活性与可观测性等软件技术优势,具有存储深度大、可测I/O管脚数目多、自动完成配置下载(不需人工干预)和自动定位FPGA中的错误等优点,提高了FPGA的测试速度和可靠性,并降低了测试成本,与传统的自动测试仪(ATE)相比有较高的性价比。采用软硬件协同方式针对Xilinx4010的I/O单元进行了测试,实现了对FPGA芯片的自动反复配置、测试和错误定位。     

英语政治新闻的语篇体裁结构潜势研究

英语政治新闻的语篇体裁结构潜势创造了对英语政治新闻语篇体裁进行描述的元语言。英语政治新闻的语境配置可以描述为新闻记者通过媒介向潜在读者报道新近发生的政治事件；英语政治新闻的语篇体裁结构潜势包含标题、电头、导语、主要事件、背景信息、影响、结果或后果和评论等成分，其中标题、电头、导语和主要事件是必要成分．在结构潜势程式中出现的顺序是固定的，背景信息、影响、结果或后果和评论是可选性成分，其位置可根据需要随意变换。必要成分及其顺序决定了语篇的语篇体裁，可选性成分决定了属于同一个语篇体裁的语篇变异现象。     

Skew-normal alpha-power model

In this paper, authors study properties and inference for the newly introduced skew-normal alpha-power model, generalizing both, the power-normal and skew-normal models. Inference is approached via maximum likelihood. Fisher information matrix is derived and shown to be nonsingular at the whole parametric space. Special emphasis is placed on the special case of the power–skew-normal model. Studies with real data illustrate the fact that the model can be very useful in applications, being able to overfit less general models entertained in the literature.