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关键词： 分类   危险材料  

ISBN: (纸本)9787122049049

摘要： 本书以危险化学品安全为目标，以安全性评价为基础，系统阐述了与危险化学品及包装安全直接相关的分类鉴定技术、包装和标识技术、安全性评估评价技术、测试技术与方法等关键性技术和方法。同时，基于全球化学品统一分类标签制度（GHS）原理，重点论述了危险化学品物理危害、健康危害、环境危害的安全性评价试验方法，包装设计与制造技术……

关键词： 细菌检验   医院感染   外源性感染   病原微生物污染   院内感染   医院环境   外部条件   实验室   检验室   内源   疾病   传播   病人  

摘要： 医院是病人密集的场所,医院环境最容易被病原微生物污染,从而为疾病的传播提供外部条件,导致院内感染.根据感染 来源不同,一般分为内源和外源性感染,其中,外源性感染近年来有上升的趋势,为此,很多医院成立院感科,但无相应单独的 实验室,因此,细菌检验室在这方面发挥重要作用:

关键词： HYPERSPECTRAL IMAGERY   LAND   DESIGN   MODEL   AREA  

摘要： This paper presents a comprehensive knowledge-based similarity classifier that uses remote sensing images and other auxiliary data to map spatial heterogeneity, for stratifying sample units distributed at the geographical landscape in order to improve the precision of the estimate of interest. Our method emphasises the decrease of bias so as to produce the high-quality stratifying frame. For this purpose, the method takes some necessary measures such as use of auxiliary variables including spectral bands, physical and socioeconomic data to help cluster analysis, correlation analysis between auxiliary variables and the goal variable to remove irrelevant data and consideration of spatial correlation in cluster analysis through the density-based unsupervised learning etc. Furthermore, considering the time-consuming characteristic of clustering huge spatiotemporal datasets, the method uses non-parametric supervised learning to induce rules for clustered classes. The rules could be efficiently used to group pixels into different classes of similarity. Then in the method, the pixel-level similarity image was vectorised into polygons with different group labels, thus producing the vector map of geospatial heterogeneity as an easy-to-use stratification frame. Last, to have an accurate estimation of the goal variable, our method re-divided sample units while the units covered by different strata and considered the effect of the sample size in the estimation algorithm. In the survey case of the cultivated land area, the proposed method achieves higher accuracy and a better coefficient of relative efficiency (RE) of stratification with its estimate closer to the observed value in comparison with other stratification strategies, e.g., k-means, SOM and those similar to eco-regions. Our method has potential practical merits as a good stratification strategy can increase the precision and considerably save the cost of sampling for many large regions, such as those in China, to be

关键词： methods: data analysis   methods: statistical   surveys   quasars: general   DIGITAL-SKY-SURVEY   SUPPORT VECTOR MACHINES   CALIBRATION   SELECTION   LIBRARY   TREE  

摘要： We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier (DSC), a supervised classifier currently based on support vector machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification, because identification of a pure quasar sample is necessary to define the Gaia astrometric reference frame. By varying a posterior probability threshold in DSC, we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars ( upper limit on contamination of 1 in 40 000) with a completeness of 65 per cent at magnitudes of G = 18.5, and 50 per cent at G = 20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously 99 per cent with a contamination of 0.7 per cent. Including parallax and proper motion in the classifier barely changes the results. We further show that not accounting for class priors in the target population leads to serious misclassifications and poor predictions for sample completeness and contamination. We discuss how a classification model prior may, or may not, be influenced by the class distribution in the training data. Our method controls this prior and so allows a single model to be applied to any target population without having to tune the training data and retrain the model.

关键词： class imbalance   classification   Gaia   machine learning   quasars  

摘要： We have developed a method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier, a supervised classifier currently based on Support Vector Machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification (partly because a pure quasar sample is necessary to define the Gaia astrometric reference frame). By varying a posterior probability threshold in DSC (Pt) we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars (upper limit on contamination of 1 in 40 000) with a completeness of 65% at magnitudes of G = 18.5, and 50% at G = 20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously more than 99% with a contamination of 0.7%. Including parallax and proper motion in the classifier barely changes the results. Not accounting for class priors leads to serious misclassifications and poor predictions for sample completeness and contamination. Our method controls the prior and so allows a single model to be applied to any target population without having to tune the training data and retrain the model. [ABSTRACT FROM AUTHOR]

关键词： 衣着   检验   命案   作用  

摘要： 在命案侦查中,衣着服饰因具有普遍存在性、个体差异性、外在表露性、相对稳定性、良好反映性和易于承载性等特点,使得衣着检验在分析研究命案的诸多方面发挥着极其重要的作用。

关键词： 检验科   微生物感染   控制  

摘要： 检验科担负着全医院微生物检测的任务,在防止院内交叉感染发生的方面起着非常重要的作用。因此检验科要对细菌室所用的物品进行严格的消毒,防止因废物处理不当而引起医院感染事件的发生,对医院的高危病房进行重点的、不定期的检测,定期发布细菌耐药性监测结果,对医院购进的一次性医疗用品都要进行微生物检测,为感染科和各临床科室提供信息,有效地降低或杜绝医院感染的发生。

关键词： 利率   时滞   有效性  

摘要： 1996年以后,我国央行开始逐渐放松对利率的管制,随着利率市场化的逐步推进,特别是近几年来,央行加大了利率政策工具的使用频率及力度。那么利率是否真正地发挥了货币政策在各经济环节的传导功能是人们一直争论的问题,就利率政策而言,央行应在正确认识时滞问题基础上保持政策的稳定性,避免由价格效应的不一致性而频繁改变货币政策。文章将运用1996～2007年的月度数据,考察不同经济周期下的利率发挥作用的时间及有效性。

关键词： 检验   分析   质量控制  

摘要： 检验是利用各种检测方法对各类标本进行正确的分析,为临床诊断和治疗提供准确的实验数据.

关键词： 知识资本   高技术产业   人力资本   知识产权   实证分析  

摘要： 高技术产业是知识高度密集、技术高度密集和人力资本高度密集的产业,知识资本是高技术产业的核心要素。以我国高技术产业发展为背景,运用我国省际数据就知识资本对高技术产业发展作用问题进行的实证研究结果表明:物质资本、人力资本和知识产权资本均对我国高技术产业产出具有显著的影响。人力资本对我国高技术产业的产出弹性比较高,知识产权资本对我国高技术产业的产出影响还很小。由此,促进人力资本投资和高技术产业人力资本的形成与积累,加快实施自主创新战略,推进知识产权的资本化,是当前提高我国高技术产业发展水平必须着力解决的关键问题。