MS SQL SERVER复制技术在地震前兆数据集成中的应用

基于WINDOWS NT 网络操作系统的MS SQL SERVER复制环境，分析并探讨了SQL SERVER复制技术、 复制模块的参数设置及其在地震前兆数据集成中的应用。 通过实例说明了SQL SERVER复制技术在地震前兆数据集成中应用的可行性。 同时，对复制过程中常出现的事务日志空间问题进行了剖析，并提出了解决办法。 分析结果表明，应用SQL SERVER复制技术进行数据交换、 共享及应用是较为有效的，而且也是可行的。     

监测数据的审核及结果的分析与判断

本文介绍了监测数据审核的意义，从监测结果的表达、报告的完整性，采要的准确性等方面阐述了监测数据审核的要点，提出了监测结果异常数据的几种较为简便，实用的判断方法。     

气候环境试验设备温度参数数据处理方法的分析与探讨

不同的温度参数数据处理方法有不同的计算结果,本文针对检测与评定气候环境试验设备的技术性能中存在的问题,分析了三个标准(GB 11158-89、GB/T 5170.1-1995、JTM K 05-1991)的温度参数数据处理方法,比对了二组实际检测数据的计算结果,说明"绝对极值法"科学准确、简捷实用.     

一种基于改进的一致性算法数据融合技术

在重大工程结构健康监测中,随着研究对象复杂程度的提高,往往需要获得大量观测数据才能对结构进行有效的评估,因此采用多种或多个传感器进行测量已成为必然趋势。数据融合技术就是将多个传感器的测量结果进行综合处理,从而得出比单个传感器更为准确可靠的结果。本文基于一致性算法,提出一种改进的多传感器数据融合技术,该数据融合技术属于数据级融合,它克服了一致性算法中两传感器在测量精度不同时置信距离不同的缺点,并对支持矩阵进行模糊化处理,避免了人为定义阈值而产生的主观误差。文中通过算例,验证了此方法可获得较好的结果,并且能够有效地减小由于扰动因素造成的测量数据的变化。     

Location and Characterization of Emission Sources for Airborne Volatile Organic Compounds Inside a Refinery in Taiwan

This study aimed to locate VOC emission sources and characterized their emitted VOCs. To avoid interferences from vehicle exhaust, all sampling sites were positioned inside the refinery. Samples, taken with canisters, were analyzed by GC–MS according to TO-14 method. The survey period extended from Febrary 2004 to December 2004, sampling twice per season. To interpret a large number of VOC data was a rather difficult task. This study featured using ordinary application software, Excel and Surfer, instead of expensive one like GIS, to overcome it. Consolidating data into a database on Excel facilitated retrieval, statistical analysis and presentation in the form of either table or graph. The cross analysis of the data suggested that the abundant VOCs were alkanes, alkenes, aromatics and cyclic HCs. Emission sources were located by mapping the concentration distribution of these four types of VOCs in terms of contour maps on Surfer. During eight surveys, five emission sources were located and their VOCs were characterized.     

Data Sharing – a Case of Shared Databases and Community Use of On-Line GIS Support Systems

Data management is becoming increasingly simple and complex at the same time. The challenge is to effectively use the increasing number of tools available to manage increasing amounts of environmental information for purposes of data capture, analysis, display, sharing and storage. Government is no longer the main collector and provider of data. Community groups possess vast amounts of data collected through daily work of monitoring the environment in their local community. The chief concerns are data access, sharing, integrity and comparability. The capacity of groups to sustain data management is the key to making the sharing possible. The Southeast Environmental Association has been working with Environment Canada to develop a community, on-line database that will be linked to other geo-spatial data sets to allow instant access to geo-referenced data.     

LCA中清单分析数据的获得

清单分析是ＬＣＡ继目标界定后的一步重要操作,工业量极大,本文从我国具体情况出发,开发了一套获取产品ＬＣＡ清单数据的方法,介绍了通过行业污染系数获取产品的社会数据以及借助企业生产的质量流程图收集和检验企业数据的具体步骤。     

随机性混合数据评价技术的方法研究

在城市和环境规划等方案评价中,如何综合利用定性和定量信息是人们较为关注的问题。本文首先将方案评价中常见的定性信息分为三大类,并用数学式来描述各类定性信息,在此基础上,运用随机处理的方法对定性信息进行处理后与定量信息进行综合,以求得各个方案的优劣排序概率,并由此概率确定最优方案。这种方法克服了以往同类方法只能利用定性信息中的排序信息的缺点,从而使得方案评价更客观。最后,本文给出了方法应用的实例。     

Norwegian Meteorological Institute’s real-time dispersion model snap (Severe Nuclear Accident Program): Runs for ETEX and ATMES II experiments with different meteorological input

The Norwegian Meteorological Institute (DNMI) has developed and implemented for operational use a real-time dispersion model Severe Nuclear Accident Program (SNAP) with capability for predicting concentrations and depositions of the radioactive debris from large accidental releases. SNAP has been closely linked to DNMI’s operational numerical weather prediction (NWP) models.How good are these predictions? Participation in ETEX has partly answered this question. DNMI used SNAP with LAM50S giving meteorological input for these real-time dispersion calculations. LAM50S Limited Area Model with 50 km grid squareswas DNMI’s operational NWP model in 1994 when ETEX took place.In this article we report on how SNAP performed in the first of the ETEX releases in near-real-time mode, using LAM50S—and in hindcast mode for ATMES II, using “ECMWF 1995: ETEX Data set (ATMES II)”as meteorological input data. These two input data sets came from NWP models with quite different characteristics but with similar resolution in time and space.The results from these dispersion simulations matched closely. Deviations early in the simulation period shrank to insignificant differences later on. Since both input data sets were based on “weather analysis” and had similar resolution in space and time, SNAP described the dispersion of the released material very similar in these two simulations.