Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Bayesian updating of atmospheric dispersion after a nuclear accident

Summary.  We consider a Bayesian forecasting system to predict the dispersal of contamination on a large scale grid in the event of an accidental release of radioactivity. The statistical model is built on a physical model for atmospheric dispersion and transport called MATCH. Our spatiotemporal model is a dynamic linear model where the state parameters are the (essentially, deterministic) predictions of MATCH; the distributions of these are updated sequentially in the light of monitoring data. One of the distinguishing features of the model is that the number of these parameters is very large (typically several hundreds of thousands) and we discuss practical issues arising in its implementation as a realtime model. Our procedures have been checked against a variational approach which is used widely in the atmospheric sciences. The results of the model are applied to test data from a tracer experiment.     

Physiologically Based Liver Modeling and Risk Assessment

Because of the inherent complexity of biological systems, there is often a choice between a number of apparently equally applicable physiologically based models to describe uptake and metabolism processes in toxicology or risk assessment. These models may fit the particular data sets of interest equally well, but may give quite different parameter estimates or predictions under different (extrapolated) conditions. Such competing models can be discriminated by a number of methods, including potential refutation by means of strategic experiments, and their ability to suitably incorporate all relevant physiological processes. For illustration, three currently used models for steady-state hepatic elimination--the venous equilibration model, the parallel tube model, and the distributed sinusoidal perfusion model--are reviewed and compared with particular reference to their application in the area of risk assessment. The ability of each of the models to describe and incorporate such physiological processes as protein binding, precursor-metabolite relations and hepatic zones of elimination, capillary recruitment, capillary heterogeneity, and intrahepatic shunting is discussed. Differences between the models in hepatic parameter estimation, extrapolation to different conditions, and interspecies scaling are discussed, and criteria for choosing one model over the others are presented. In this case, the distributed model provides the most general framework for describing physiological processes taking place in the liver, and has so far not been experimentally refuted, as have the other two models. These simpler models may, however, provide useful bounds on parameter estimates and on extrapolations and risk assessments.     

Ranking Nuclear and Radiological Terrorism Scenarios: The Italian Case

A quantitative criterion for ranking the different scenarios of nuclear and radiological terrorism has been developed. The aim of the model is not to predict terroristic events but only to indicate which scenario has the higher utility from the point of view of a terroristic organization in terms of balance between factors favoring and discouraging the attack, respectively. All these factors were quantified according to a scoring system that takes into account the logarithmic relationship between perceptions and stimuli. The criterion was applied to several scenarios, each of which was modeled in a simple but not trivial way in order to estimate the expected damage in terms of probable life losses from both radiative and nonradiative effects. The outcome from the ranking method indicates that the attractive scenario appears to be the detonation of a low yield improvised nuclear device in the metropolitan area of a major city.     

内开槽螺纹波导冷腔色散特性模拟研究

根据螺纹波导中模式间的耦合方程组及冷腔色散方程进行了数值计算,分析了2个模式的相互耦合机理。基于圆柱形波导中线性极化TE11模式存在极化简并的特性,将线极化TE11脉冲作为1个探针,采用粒子模拟软件对该腔体进行了3维冷腔模拟;并将模拟结果与数值计算结果进行了比较,两者基本一致。通过计算机模拟得出了混合模式的电场等位线分布图,结合色散方程数值计算分析了内开槽螺纹几何特性变化对波导色散特性的影响规律。     

浅析凤翔泥塑对现代设计的启示

中国的民间手工艺文化一直延续着中华本元文化的特征,保持了精神和物质统一的原生状态,同时包蕴了中华民族传统的自然观和思维方式,无论是其中的思想智慧还是造物工艺都为我们的现代设计在如何继承本土文化方面打开了一个可供吸收营养和借鉴的宝库。凤翔泥塑作为一种符号现象被现代设计加以运用,不能不说是民间传统手工艺术在现代的一次回归浪潮。文章探讨的是凤翔泥塑在纹饰、色彩、造型三个方面带给现代设计的启示。     

一个四层非均匀平面光波导的色散方程

借助 W.K.B 方法,参照四层均匀平面光波导的色散方程,提出了一个适用于计算四层非均匀平面光波导传播常数的色散方程。理论分析与数值计算表明,该方程不仅适用于具有任意折射率分布的四层非均匀波导,而且计算步骤简单,精度高。在0.6～1.55μm 波长范围内,用我们的公式与严格解析公式进行计算,其结果的最大差值<±1×10~(-4)。     

基于规则的客户关系管理系统建模方法

客户关系管理系统(CRM)是提高企业核心竞争力的有力武器。以工作流和过程建模技术为基础,研究CRM系统的建模,是CRM系统的建立和顺畅运行的关键。因此,将动态过程建模的思想引入CRM系统的建模过程中,按照逐层分解的建模方式来简化系统的复杂性,并采用事件驱动的、基于扩展业务规则的方法进行CRM系统的过程建模和系统性能评价,是针对CRM系统进行建模的有效手段。通过以上方法,可以建立出全面支持CRM系统运行、监控、仿真和性能评价的过程模型。根据该方法建立的CRM系统的模型经过仿真实验和企业实际应用,证明具有良好的应用效果。