Risk Communication in The Netherlands: The Monitored Introduction of the EC "Post-Seveso" Directive

Implementation of article 8.1 of the EC-"Seveso" Directive (82/501/EC) is now under way in many countries in Europe. In The Netherlands, the implementation of the Directive started with a carefully monitored introduction of active information provision at two sites (Dordrecht and Elst). This introduction was supported by a multidisciplinary research group. This group helped to develop the risk communication program and also played a role in the evaluation of the program. This paper describes these processes and their evaluation. We will focus on the design of the risk communication programs and the effects of the programs on knowledge and attitudes of the local target groups. This effort and its results clearly started an institutional learning process involving governmental bodies at several organizational levels (local, regional, and national), and industrial organizations (individual firms and organizations of industries). Monitoring the design, the implementation, and the effects of active information provision proves an effective means to gain experience with the implementation of the Seveso Directive and could help to facilitate further implementation.     

Innovation in education: Technological economics

Technological change and innovation are vital parts of the economy. This paper concerns one particular attempt to study both the process of innovation itself and possible means of increasing its effectiveness: Technological Economics. Barriers to innovation, intellectual and organizational, are described from the experience at the University of Stirling.     

Mapping of population density

The Bureau of the Census listing of geographical coordinates of centroids of all enumeration districts together with population counts from the U. S. 1970 Census of Population was used to contruct via computer five nationwide geographical grids of population density with sector dimensions of 0.01, 0.02, 0.04, 0.1, and 0.25 degrees of latitude and longitude. The entire population of a district was assigned to a grid sector if the coordinates of the district centroid fell within the boundaries of the sector. The sectors were then rank-ordered according to population density, and listings were made of sector population, population density, geographical location, cumulative population, area of sector, and cumulative area. The five sets of data were synthesized into single equations describing population as a function of density in one case and of area in another. From these data it was found, for example, that about 800,000 people live in 19 sectors of 0.01-degree dimensions with a population density of 100,000 people per square mile or greater (nearly all in Manhattan); about 10 million live in 183 sectors of 0.02-degree dimensions with a population density of 23,000 per square mile or greater; and about half of the total U. S. population, that is, about 100 million people, reside within about 0.6 percent of the area of the United States, that is, within 20,000 square miles.Four representative displays of population density are shown for the Northeast Corridor, including isometric views and a contour map.     

An Approach to Constructing Nested Space-Filling Designs for Multi-Fidelity Computer Experiments

Multi-fidelity computer experiments are widely used in many engineering and scientific fields. Nested space-filling designs (NSFDs) are suitable for conducting such experiments. Two classes of NSFDs are currently available. One class is based on special orthogonal arrays of strength two and the other consists of nested Latin hypercube designs. Both of them assume all factors are continuous. We propose an approach to constructing new NSFDs based on powerful (t, s)-sequences. The method is simple, easy to implement, and quite general. For continuous factors, this approach produces NSFDs with better space-filling properties than existing ones. Unlike the previous methods, this method can also construct NSFDs for categorical and mixed factors. Some illustrative examples are given. Other applications of the constructed designs are briefly discussed.     

跨国人口流动与族群认同——以东南亚的尼泊尔移民为例

通过对缅甸、泰国的尼泊尔移民的田野调查,探讨了跨国人口流动中的族群认同问题。在理论上,运用巴特的族群理论,批判了英美两国人类学传统上视社会和文化为孤立整体的思想,强调社会是一个无序的系统,并且不具备封闭性。而在方法论上,在国内首次阐述了好奇心在人类学田野调查中的重要作用,要求人类学工作者要以具体的人类行为和环境因素为基本研究对象;空间上外延、时间上后延来追溯研究对象的影响因素,同时以现存理论和模型为指导进行研究。     

A Statistical Approach to Thermal Management of Data Centers Under Steady State and System Perturbations

Temperature control for a large data center is both important and expensive. On the one hand, many of the components produce a great deal of heat, and on the other hand, many of the components require temperatures below a fairly low threshold for reliable operation. A statistical framework is proposed within which the behavior of a large cooling system can be modeled and forecast under both steady state and perturbations. This framework is based upon an extension of multivariate Gaussian autoregressive hidden Markov models (HMMs). The estimated parameters of the fitted model provide useful summaries of the overall behavior of and relationships within the cooling system. Predictions under system perturbations are useful for assessing potential changes and improvements to be made to the system. Many data centers have far more cooling capacity than necessary under sensible circumstances, thus resulting in energy inefficiencies. Using this model, predictions for system behavior after a particular component of the cooling system is shut down or reduced in cooling power can be generated. Steady-state predictions are also useful for facility monitors. System traces outside control boundaries flag a change in behavior to examine. The proposed model is fit to data from a group of air conditioners within an enterprise data center from the IT industry. The fitted model is examined, and a particular unit is found to be underutilized. Predictions generated for the system under the removal of that unit appear very reasonable. Steady-state system behavior also is predicted well.