Symmetrical design for symmetrical global sensitivity analysis of model output

Symmetrical global sensitivity analysis (SGSA) can help practitioners focusing on the symmetrical terms of inputs whose uncertainties have an impact on the model output, which allows reducing the complexity of the model. However, there remains the challenging problem of finding an efficient method to get symmetrical global sensitivity indices (SGSI) when the functional form of the symmetrical terms is unknown, including numerical and non-parametric situations. In this study, we propose a novel sampling plan, called symmetrical design, for SGSA. As a preliminary experiment for model feature extracting, such plan offers the virtue of run-size economy due to its closure respective to the given group. Using the design, we give estimation methods of SGSI as well as their asymptotic properties respectively for numerical model and non-parametrical model directly by the model outputs, and further propose a significance test for SGSI in non-parametric situation. A case study for a benchmark of GSA and a real data analysis show the effectiveness of the proposed design.     

A New Feature Selection Method for Text Categorization of Customer Reviews

With the rapid development of e-commerce, online consumer review plays an increasingly important role in consumers’ purchase decisions. Most research papers use the quantitative measures of consumer reviews for statistical analysis. Here we focus on analyzing the texts of customer reviews with text mining tools. We propose a new feature selection method called maximizing the difference. Various classification methods such as boosting, random forest and SVM are used to test the performance of the new method along with different evaluation criteria. Both simulation and empirical results show that it improves the effectiveness of the classifier over the existing methods.     

Modified linear discriminant analysis using block covariance matrix in high-dimensional data

Among many classification methods, linear discriminant analysis (LDA) is a favored tool due to its simplicity, robustness, and predictive accuracy but when the number of genes is larger than the number of observations, it cannot be applied directly because the within-class covariance matrix is singular. Also, diagonal LDA (DLDA) is a simpler model compared to LDA and has better performance in some cases. However, in reality, DLDA requires a strong assumption based on mutual independence. In this article, we propose the modified LDA (MLDA). MLDA is based on independence, but uses the information that has an effect on classification performance with the dependence structure. We suggest two approaches. One is the case of using gene rank. The other involves no use of gene rank. We found that MLDA has better performance than LDA, DLDA, or K-nearest neighborhood and is comparable with support vector machines in real data analysis and the simulation study.     

社会化网络3维用户界面设计分析与研究

为了寻找三维用户界面设计策略，在归纳2维（2D）与2．5维（2．5D）用户界面包含的内容与设计策略的基础上，从3维（3D）用户界面的交互任务、信息呈现和用户搜索行为三方面进行了分析，整合了用户需求、空间行为、空间任务，创新性地构建了面向真3D空间的“需求-任务-层次模型”，为3D用户界面的构建提供了新的思路。此外，从细节层面对3D用户界面具体设计原则进行分析，提出了“信息呈现设计矩阵”，对3D用户界面设计具有一定的指导意义。     

On the construction of optimal experimental designs: a penalty approach

Tn optimal experimental design theory there are well-known situations, in which additional constraints are implied to the design set. These constraints destroy in general the simplex structure of the set of feasible points of the design set. Thus the available iteration procedures for the unrestricted case are no longer applicable.

In this paper a penalty approach is suggested which transforms the restricted problem to the unrestricted case and allows the application of well-known algorithms such as the Fedorov-Wynn-type or the projected gradient procedure.     

长江上游地区农村产业融合发展水平测度及影响因素

以长江上游地区为例,从农业内部整合型融合、农业产业链延伸型融合、农业功能拓展型融合、先进技术对农业渗透型融合等四个层面,构建了农村产业融合发展评价指标体系,然后借助耦合协调度模型、熵值法综合评价了农村产业融合发展水平,并基于2004—2016年的面板数据,进一步对长江上游地区农村产业融合发展的影响因素进行了实证研究。研究发现:长江上游地区农村产业融合总体水平从0.2088提升为0.6116,提升了0.4028,在四种细分模式中,先进技术对农业的渗透型融合发展态势最为突出;四个省份中,四川省、重庆市农村产业融合水平较高,云南省、贵州省则相对较低;消费需求、土地流转、技术进步、基础设施、环境质量、人力资本、金融发展等因素都从不同程度作用于农村产业融合发展,各因素因为模式不同而呈现出不同的作用。     

中国价格水平的国际比较：差距及影响因素

基于世界银行2011年国际比较项目（ ICP）数据结果,分析中国价格水平的国际差距,研究其影响因素,剖析世界银行推算的中国购买力平价和价格水平指数的合理性和局限性。研究表明,中国价格总水平相对较低,但在多重因素作用下,呈大幅上升趋势,与国际的差距缩小,价格的国际竞争优势逐渐减弱。在现阶段,中国价格水平与经济发展水平大体相适应。从长期趋势看,中国价格水平继续上升的压力较大,须控制通胀预期,稳定人民币汇率,谨防价格水平上升超出经济发展水平的正常范围。     

陕西地方院校高层次人才引进策略研究?

陕西地方院校长期存在着学校知名度不高,教师收入水平低,高层次人才储备不足、引进困难和增长缓慢的不良现状。为改善这一现状,有效加强高层次人才引进工作力度,陕西地方院校应以重点学科为突破点,以实际需求为导向,牢固树立成本意识,理性制定高层次人才引进策略;应增强引才主动意识,积极学习西方发达国家引才理念,善于利用政府牵引模式下的高层次人才引进合力,全面活化高层次人才引进手段;应注重经济契约与心理契约有机结合,刚性管理与柔性管理有机结合,将团队建设纳入考核内容之中,切实加强对高层次人才的管理。     

校院二级管理下的资源配置及优化研究

基于高校各学院科研绩效评估结果,运用波士顿矩阵模型将高校二级学院分为现金牛类、明星类、问题类、瘦狗类4种类型,提出各类型学院特点。根据不同类型学院特点以及高校所面临的实际情况,将高校未来的发展分为维持模式、发展模式、补救模式。在不同的模式下,以4类学院发展基础为依据,提出高校长期发展5种战略。从案例高校全局统筹角度出发,本着学校资源分配效益最大化目标原则,选择以发展明星类、问题类战略为主的发展模式,建立各二级学院每项资源投入指标改变量模型,并对各学院人、财、物投入提出调整性数据。强调校院二级管理必须立足学院发展,依据各学院考核评价等情况进行相应的教学、科研、人事、经费资源分配,以实现二级管理资源分配相对公平、有效。     

Analysis of some ruin-related quantities in a Markov-modulated risk model

In this paper, we study the joint Laplace transform and probability generating function of some random quantities that occur in each environment state by the time of ruin in a Markov-modulated risk process. These quantities include the duration spent in each state, the number of claims and the aggregate amount of claims that occurred in each state by the time of ruin. Explicit formulae for the joint transforms, given the initial surplus, and the initial and terminal environment states, are expressed in terms of a matrix version of the scale function. Moments and covariances of these ruin-related quantities are obtained and numerical illustrations are presented. The joint transform of the duration spent in each state, the number of claims, and the aggregate amount of claims that occurred in each state by the time the surplus attains a certain level are also investigated.