Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

The effect of different data structures,sample sizes on model fit measures

In this study, our aim was to investigate the changes of different data structures and different sample sizes on the structural equation modeling and the influence of these factors on the model fit measures. Examining the created structural equation modeling under different data structures and sample sizes, the evaluation of model fit measures were performed with a simulation study. As a result of the simulation study, optimization and negative variance estimation problems have been encountered depending on the sample size and changing correlations. It was observed that these problems disappeared either by increasing the sample size or the correlations between the variables in factor. For upcoming studies, the choice of RMSEA and IFI model fit measures can be suggested in all sample sizes and the correlation values for data sets are ensured the multivariate normal distribution assumption.     

Human Agency in Disaster Planning: A Systems Approach

Current approaches to risk management place insufficient emphasis on the system knowledge available to the assessor, particularly in respect of the dynamic behavior of the system under threat, the role of human agents (HAs), and the knowledge available to those agents. In this article, we address the second of these issues. We are concerned with a class of systems containing HAs playing a variety of roles as significant system elements—as decisionmakers, cognitive agents, or implementers—that is, human activity systems. Within this family of HAS, we focus on safety and mission‐critical systems, referring to this subclass as critical human activity systems (CHASs). Identification of the role and contribution of these human elements to a system is a nontrivial problem whether in an engineering context, or, as is the case here, in a wider social and public context. Frequently, they are treated as standing apart from the system in design or policy terms. Regardless of the process of policy definition followed, analysis of the risk and threats to such a CHAS requires a holistic approach, since the effect of undesirable, uninformed, or erroneous actions on the part of the human elements is both potentially significant to the system output and inextricably bound together with the nonhuman elements of the system. We present a procedure for identifying the potential threats and risks emerging from the roles and activity of those HAs, using the 2014 flooding in southwestern England and the Thames Valley as a contemporary example.     

Association of educational level and child sex ratio in rural and urban India

Utilizing data from the Census of India, this study compared child sex ratio in rural and urban regions of India and analyzed whether the child sex ratio was associated with mother’s education level. The child sex ratios in the rural and urban regions throughout India were analyzed using the two-sample and paired Student’s t-test. Further, the Chi-square test for trend in binomial proportions was used to assess the association between child sex ratios and mother’s education levels in rural and urban areas. Analysis of the data showed that there was a significant difference between the child sex ratios in rural areas versus urban areas. In addition, the Chi-square test for trend showed that there was a significant association of the child sex ratio and the educational levels of their mothers. This trend occurred in both rural and urban areas.     

竹木家具设计原则和造型方法

探讨了竹木家具设计的原则和造型方法,提出了适合新型竹木家具的人体工效学原则、可持续发展原则、人性化设计原则、本地化设计原则和手工艺与现代科技相结合的设计原则,以及借鉴、置换、重构和移植的新型竹木家具造型方法。     

基于NURBS方法的转子表面造型技术

采用双三次NURBS方法对某型号转子进行几何造型,对造型过程中出现的曲面延伸、求交和裁剪等问题进行了研究.根据叶片的形状特征,以曲线的几何形式为基础,提出了一种简单实用的曲线曲面延伸方法,实现了切矢量连续的叶片型面的延伸.对于两相交面分别为自由曲面和解析曲面的求交问题,提出了一种简化的跟踪算法,实现了转子叶片型面和圆台面的准确求交和裁剪,从而实现转子精确的几何造型.     

对素描教学的认识与思考

素描是造型艺术的基础，是基础课的重要组成部分，这个技术训练要有相应科学的教学方法，使技法和理论有机地融合在一起。     

Remedial Policies in Radiologically-Contaminated Forests: Environmental Consequences and Risk Assessment

As a result of the Chernobyl nuclear power plant accident in 1986, large forested areas in Europe were contaminated by radionuclides. Extensive societal pressure has been exerted to decrease the radiation dose to the population and to the environment. Thus, in making abatement and remediation policy decisions not only economic costs, but also human and environmental risk assessment are desired. Forest remediation by organic layer removal, one of the most promising cleanup policies, is considered in this paper. Ecological risk assessment requires evaluation of the radionuclide distribution in forests. The FORESTPATH model^(1,2) is used for predicting the radionuclide fate in forest compartments after deposition as well as for evaluating the application of the remedial policy. Time of intervention and radionuclide deposition profile was predicted as being crucial for the remediation efficiency. Risk assessment conducted for a critical group of forest users in Belarus shows that consumption of forest products (berries and mushrooms) leads to about 0.004% risk of a fatal cancer. Cost-benefit analysis for forest cleanup suggests that complete removal of organic layer is too expensive for application in Belarus.     

Theoretic and empirical data-inclusive process characterization

Summary.  In process characterization the quality of information that is obtained depends directly on the quality of process model. The current quality revolution is now providing a strong stimulus for rethinking and re-evaluating many statistical ideas. Among these are the role of theoretic knowledge and data in statistical inference and some issues in theoretic–empirical modelling. With this concern the paper takes a broad, pragmatic view of statistical inference to include all aspects of model formulation. The estimation of model parameters traditionally assumes that a model has a prespecified known form and takes no account of possible uncertainty regarding model structure. But in practice model structural uncertainty is a fact of life and is likely to be more serious than other sources of uncertainty which have received far more attention. This is true whether the model is specified on subject-matter grounds or when a model is formulated, fitted and checked on the same data set in an iterative interactive way. For that reason novel modelling techniques have been fashioned for reducing model uncertainty. Using available knowledge for theoretic model elaboration the techniques that have been created approximate the exact unknown process model concurrently by accessible theoretic and polynomial empirical functions. The paper examines the effects of uncertainty for hybrid theoretic–empirical models and, for reducing uncertainty, additive and multiplicative methods of model formulation are fashioned. Such modelling techniques have been successfully applied to perfect a steady flow model for an air gauge sensor. Validation of the models elaborated has revealed that the multiplicative modelling approach allows us to attain a satisfactory model with small discrepancy from empirical evidence.