党的意识形态建设面临的挑战及应对措施

在新的世纪,国际国内环境及党自身发生的深刻变化给党的意识形态建设带来了严峻挑战。面对挑战,中国共产党必须审时度势,积极应对:在坚持主流意识形态的基础上,增强意识形态的包容性与灵活性;把意识形态建设与民族精神培育统一起来;建立起符合时代特点和要求的现代思想教育体系,提高党的意识形态灌输的有效性;遏制党内腐败,重塑廉洁形象,增强党的意识形态的说服力;顺应时代改革潮流,充分吸纳世界文明思想精华。     

基于向量夹角余弦的组合预测模型的性质研究

基于向量夹角余弦的组合预测是一种相关性的组合预测模型,它是研究组合预测方法的一个新途经.针对基于向量夹角余弦准则下组合预测模型,研究它的基本结构特征.首先提出新的优性组合预测、预测方法优超、冗余度等概念.然后探讨了非劣性组合预测、优性组合预测以及冗余预测方法的存在性,并给出冗余信息的判定定理.最后进行实例分析,表明该方法有较大的实际应用价值.     

人力资源个体价值计量方法——当期实现价值系数法

由于人力资源自身具有复杂性、不确定性的特点,使得人力资源价值难以计量。而准确的计量人力资源价值,尤其是人力资源的个体价值是人力资源会计能否实施的关键因素。针对这个问题,本文在分析前人成果的基础上提出了人力资源当期实现价值系数法计量模型。并通过实例验证了计量模型的实用性。     

Moment‐Independent Sensitivity Analysis Using Copula

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment‐independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment‐independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the “curse of dimensionality.” At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.     

Semi-polynomial copulas

In this paper, we characterise a family of bivariate copulas whose sections between the main diagonal and the border of the unit square are polynomial, generalising several families of copulas, including those with quadratic and cubic sections. We also study a measure of association and the tail dependence for this class, illustrating our results with several examples.     

Influence measures in blocked designs of experiments with correlated errors

Diagnostics measures for detecting outliers in data from block designs of experiments with correlated errors are considered. Influence is often assessed by deleting suspected outlying observations. Autocorrelation of order one is considered to model correlation in each block. Cook-statistic is developed for detecting the effect of a single outlier, where results are illustrated with an example.     

An adaptive two-sample location-scale test of lepage type for symmetric distributions

For the two-sample location and scale problem we propose an adaptive test which is based on so called Lepage type tests. The well known test of Lepage (1971) is a combination of the Wilcoxon test for location alternatives and the Ansari-Bradley test for scale alternatives and it behaves well for symmetric and medium-tailed distributions. For the cae of short-, medium- and long-tailed distributions we replace the Wilcoxon test and the .Ansari-Bradley test by suitable other two-sample tests for location and scale, respectively, in oder to get higher power than the classical Lepage test for such distribotions. These tests here are called Lepage type tests. in practice, however, we generally have no clear idea about the distribution having generated our data. Thus, an adaptive test should be applied which takes the the given data set inio consideration. The proposed adaptive test is based on the concept of Hogg (1974), i.e., first, to classify the unknown symmetric distribution function with respect to a measure for tailweight and second, to apply an appropriate Lepage type test for this classified type of distribution. We compare the adaptive test with the three Lepage type tests in the adaptive scheme and with the classical Lepage test as well as with other parametric and nonparametric tests. The power comparison is carried out via Monte Carlo simulation. It is shown that the adaptive test is the best one for the broad class of distributions considered.     

基于HHM-RFRM的船舶航行风险评估方法研究

船舶航行风险是由各种风险因素交互作用产生。综合 HHM-RFRM 理论，构建船舶航行多维风险情景危险度测度模型，以风险因素耦合视角探讨船舶航行风险管理问题。在船舶航行多维风险情景危险度测度模型中结合贝叶斯定理，对船舶航行风险情景进行了定性与定量化过滤、评级。最后以大连港某从事商务活动的货船为例，验证了所提出方法的可行性。传统的风险评估方法只能评估单个风险因素对系统的影响，此评估方法克服了这一局限性，为船舶航行风险管理提供新的视角。     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.     

Machine Learning Vasicek Model Calibration with Gaussian Processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.