Deciding with Thresholds: Importance Measures and Value of Information

Risk‐informed decision making is often accompanied by the specification of an acceptable level of risk. Such target level is compared against the value of a risk metric, usually computed through a probabilistic safety assessment model, to decide about the acceptability of a given design, the launch of a space mission, etc. Importance measures complement the decision process with information about the risk/safety significance of events. However, importance measures do not tell us whether the occurrence of an event can change the overarching decision. By linking value of information and importance measures for probabilistic risk assessment models, this work obtains a value‐of‐information‐based importance measure that brings together the risk metric, risk importance measures, and the risk threshold in one expression. The new importance measure does not impose additional computational burden because it can be calculated from our knowledge of the risk achievement and risk reduction worth, and complements the insights delivered by these importance measures. Several properties are discussed, including the joint decision worth of basic event groups. The application to the large loss of coolant accident sequence of the Advanced Test Reactor helps us in illustrating the risk analysis insights.     

Regression for non-Euclidean data using distance matrices

Regression methods for common data types such as measured, count and categorical variables are well understood but increasingly statisticians need ways to model relationships between variable types such as shapes, curves, trees, correlation matrices and images that do not fit into the standard framework. Data types that lie in metric spaces but not in vector spaces are difficult to use within the usual regression setting, either as the response and/or a predictor. We represent the information in these variables using distance matrices which requires only the specification of a distance function. A low-dimensional representation of such distance matrices can be obtained using methods such as multidimensional scaling. Once these variables have been represented as scores, an internal model linking the predictors and the responses can be developed using standard methods. We call scoring as the transformation from a new observation to a score, whereas backscoring is a method to represent a score as an observation in the data space. Both methods are essential for prediction and explanation. We illustrate the methodology for shape data, unregistered curve data and correlation matrices using motion capture data from an experiment to study the motion of children with cleft lip.     

Women,Poverty, and the Microenterprise: Context and Discourse

The article discusses the claims of success of microenterprise development programmes (MDPs) in poverty reduction and gender equality. It also deals with the broader theoretical and methodological issues related to the ways in which context and discourse interact in the assessment of anti‐poverty and gender equity strategies. MDPs are considered among the most viable strategies for helping women overcome poverty and promoting gender equity. However, there has been significant debate over these claims. The relationship between business ownership, poverty reduction and gender empowerment is still to be proved. The article presents the voices of women engaged in a microenterprise (ME) from a context‐informed and discourse analysis perspective, and considers the women's insights about ME as an anti‐poverty and gender empowerment strategy. The findings show a complex picture. On one hand, the new occupational status promises a tangible alternative to multiple personal, social and gender constraints. Additionally, women in the study perceived the ME as a space for self‐definition and as an outlet for expressing their oppressed identities. On the other hand, the findings seriously challenge the capacity of the MDP strategy to promote gender equity and combat poverty among low‐income women. Implications for research and policy are discussed.     

国际贸易运输法强制性体制“内在逻辑体系”的合理性

从某种意义上看,强制性体制是国际贸易运输法特别是海上货物运输法的核心和特质。在＂海商法文化＂的维度下,基于对国际贸易运输法强制性体制价值论的＂内在逻辑体系＂和运输法体系的自足性分析,运输法强制性的＂二维价值结构＂的提出具有合理性。而在＂内在逻辑体系＂范畴上,特殊主义的强制性体制价值论,特别是＂内在逻辑体系＂意义上的运输法强制性体制,在诠释运输法某些制度的应然性、理解海上运输法的自足体系以及预示运输法发展趋向等方面具有一定的功用。     

运动式执法与中国治理的困境

从决策议程对环境的回应、动员社会中的稀缺资源和实现政府间合作三个角度来分析运动式执法的必然性，运动式执法作为一种政策工具和治理模式并非总是消极的。一味地否定运动式执法，既不符合中国公共治理的现实需要，也不符合严肃的学术研究的要求。     

Cumulative correspondence analysis of ordered categorical data from industrial experiments

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a procedure to improve the ordered categorical response in a multifactor state system based on Taguchi's statistic. Users may find the proposed procedure in this paper to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determining the levels to improve process quality. A case study for optimizing the polysilicon deposition process in a very large-scale integrated circuit is provided to demonstrate the effectiveness of the proposed procedure.     

Praetor的实与名:从正名开始的罗马公法研究

古罗马的Praetor的名实问题,从翻译的角度说存在八种汉译,对Praetor官职从古罗马共和时期开始直到帝政时期的实际职掌,其最初是一种兼具行政、司法和军事职能的官职,只是到了帝政时期,Praetor才慢慢地转变为专业的司法官.因此,对Praetor一词的准确把握,应依据其在不同时期的不同职能进行,不能通译为裁判官,最好的释义是副执政官.     

A Risk Analysis Model in Concurrent Engineering Product Development

Concurrent engineering has been widely accepted as a viable strategy for companies to reduce time to market and achieve overall cost savings. This article analyzes various risks and challenges in product development under the concurrent engineering environment. A three‐dimensional early warning approach for product development risk management is proposed by integrating graphical evaluation and review technique (GERT) and failure modes and effects analysis (FMEA). Simulation models are created to solve our proposed concurrent engineering product development risk management model. Solutions lead to identification of key risk controlling points. This article demonstrates the value of our approach to risk analysis as a means to monitor various risks typical in the manufacturing sector. This article has three main contributions. First, we establish a conceptual framework to classify various risks in concurrent engineering (CE) product development (PD). Second, we propose use of existing quantitative approaches for PD risk analysis purposes: GERT, FMEA, and product database management (PDM). Based on quantitative tools, we create our approach for risk management of CE PD and discuss solutions of the models. Third, we demonstrate the value of applying our approach using data from a typical Chinese motor company.     

2009年世界民族问题热点回眸及原因与特点分析

回眸已成为历史的2009年,世界政坛波谲云诡,金融海啸继续冲击着各国经济,在此影响之下,世界民族问题热点不断.巴以之间再起战火,奥巴马新政府的战略给伊拉克局势、伊朗核问题、阿富汗和巴基斯坦局势带来新的动向,印巴关系出现新走向,南奥塞梯问题、苏丹达尔富尔和平进程、泰同南部暴力活动、塞浦路斯希土两族等问题成为2009年世界民族问题的热点.世界民族问题在多种因素的影响下涌现出新的热点和特点,值得我们对此倍加关注、认真思考、缜密分析,进而在汲取经验教训的基础上采取相应对策,为构建和谐世界尽责尽力.     

The eigenstructure of block-structured correlation matrices and its implications for principal component analysis

Block-structured correlation matrices are correlation matrices in which the p variables are subdivided into homogeneous groups, with equal correlations for variables within each group, and equal correlations between any given pair of variables from different groups. Block-structured correlation matrices arise as approximations for certain data sets’ true correlation matrices. A block structure in a correlation matrix entails a certain number of properties regarding its eigendecomposition and, therefore, a principal component analysis of the underlying data. This paper explores these properties, both from an algebraic and a geometric perspective, and discusses their robustness. Suggestions are also made regarding the choice of variables to be subjected to a principal component analysis, when in the presence of (approximately) block-structured variables.