基于RSA的电子商务信息加密技术研究

21世纪是网络信息时代,电子商务的迅猛发展和普及打破了人们传统的经营和消费理念,网上消费已成为一种新的消费形式,但随之而来的便是电子商务赖以生存和发展的安全问题。文章主要通过对电子商务安全隐患的分析,论证了数据加密技术在电子商务安全中的作用,重点探讨了RSA公钥加密算法,并通过实例对其加密原理、计算复杂性等安全性问题作了详尽的分析和阐述。     

供应链风险产生根源的理论分析

根据现有文献研究成果,结合实际调研分析,将供应链风险因素整理归纳为系统风险、供应风险、物流风险、信息风险、财务风险、管理风险、需求风险和环境风险。每种风险因素并非独立存在,而是相互影响、互为根源。其非线性叠加结果将会放大供应链整体风险水平。因此,必须认识到其存在的风险,只有在明确各种风险产生根源的基础上,才能恰当地制定、选择和采取有效措施,规避风险,确保供应链整体绩效稳步提高。     

海伍德对政治学核心概念的独到分析与诠释——《政治学核心概念》评介

《政治学核心概念》是一部在国外政治学界有广泛影响的著作。在这部著作中,海伍德强调了政治概念的特殊重要性并对此进行了独到的解释;探讨了政治概念在实际应用中存在的特殊问题并进行了有深度的分析;对"规范性概念"和"描述性概念"进行了富有启发意义的区分与阐释。该书不仅展现了作者在政治概念界定与诠释上的学术专长与独到之处,也体现了作者在政治学知识再现与传播上尽量贴近读者与学生的教师情结与风范。     

Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

Robust testing with generalized partial linear models for longitudinal data

By approximating the nonparametric component using a regression spline in generalized partial linear models (GPLM), robust generalized estimating equations (GEE), involving bounded score function and leverage-based weighting function, can be used to estimate the regression parameters in GPLM robustly for longitudinal data or clustered data. In this paper, score test statistics are proposed for testing the regression parameters with robustness, and their asymptotic distributions under the null hypothesis and a class of local alternative hypotheses are studied. The proposed score tests reply on the estimation of a smaller model without the testing parameters involved, and perform well in the simulation studies and real data analysis conducted in this paper.     

中国上市公司财务预警实证研究

在对国外公司财务预警经典研究成果进行回顾和总结的基础上,运用多元判别分析方法（MDA）和逐步判别分析（Stepdisc）等方法逐层推进构造预测模型,以经济实用为选择标准,最终建立一个预测准确率最高、变量最少的适合中国实际情况的财务危机预测模型。     

再论企业自知识能力及其管理

根据先前的研究 ,从企业核心能力的角度阐述了自知识能力的本质特征 ,即动态的特征、宽泛的特征、深层次的特征。分析了扼杀企业自知识能力的因素 ,包括企业文化因素、组织结构设计因素、分析性思维因素、策略性决策因素、激励性体系因素等五个方面。在此基础上提出了提升企业自知识能力的对策。     

Backfitting Random Varying-Coefficient Models with Time-Dependent Smoothing Covariates

Abstract.  In this paper, we propose a random varying-coefficient model for longitudinal data. This model is different from the standard varying-coefficient model in the sense that the time-varying coefficients are assumed to be subject-specific, and can be considered as realizations of stochastic processes. This modelling strategy allows us to employ powerful mixed-effects modelling techniques to efficiently incorporate the within-subject and between-subject variations in the estimators of time-varying coefficients. Thus, the subject-specific feature of longitudinal data is effectively considered in the proposed model. A backfitting algorithm is proposed to estimate the coefficient functions. Simulation studies show that the proposed estimation methods are more efficient in finite-sample performance compared with the standard local least squares method. An application to an AIDS clinical study is presented to illustrate the proposed methodologies.     

施工企业危机管理及其经济分析

危机管理的目的是为了避免和减少危机的损害,是一场"防御性的战斗",也是一项系统工程。论文结合竞争激烈的施工企业市场实际,从施工企业危机管理入手,阐述了施工企业危机管理目前的共性内容,并通过分析对危机管理的重要意义、危机管理效果和经济效果的衡量等问题,进一步通过施工企业危机管理的经济分析对危机管理投入、所得的界定,研究了危机管理投入的量化及归一化,以及危机管理所得的量化及归一化问题,得出单位投入所带来的整体稳定态势,其值越大表明危机管理越有效。可为施工企业开展此项工作提供一定的理论指导。     

Quantifying uncertainty in the biospheric carbon flux for England and Wales

Summary.  A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO₂) concentrations in the atmosphere. Vegetation can extract CO₂ through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 10¹² g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.