人因评价的定量化研究

人因评价是安全评价中的重要组成部分，在结合层次分析法和综合加权法的基础上，建立了人因评价的量化模型。     

溶济萃取法处理含硫酸及硫酸盐的废水

采用溶剂萃取法处理含硫酸及硫酸盐的工业废水，主产优质农用硫酸钾，副产氯化铵和氮钾复合肥，整个工艺过程基本无三废排放，实现了对该废水的综合有效治理。     

入侵检测的1类支持向量机模型

计算机网络尤其是互联网的迅速发展与普及 ,使得信息安全已经成为一个全球瞩目的重要研究课题。随着攻击技术的不断进步与更新 ,迫切需要一种有效的入侵检测技术来保护信息系统的安全。由于几乎所有的攻击与滥用都被记录在系统的网络数据中 ,因而可以基于计算机系统的网络数据构造入侵检测系统。在对网络数据进行深刻的分析和研究的基础上 ,提出了入侵检测的 1类支持向量机模型。第一 ,构造适于异常点检测的1类支持向量机模型 ;第二利用抽象化的网络数据对该模型进行训练以确定其中各个参数的值。实验表明 ,该方法是行之有效的     

自然爆炸灾害的危害及其预防方法探讨

本文对两种自然爆炸灾害——天体对地球的撞击和空间碎片对航天器的撞击进行了分析，指出了这种自然灾害发生的概率及危害特性，探讨了预防灾害的可能方案。     

废水中甲酸萃取回收的研究

以ＺＹＭ混合溶剂为萃取剂，以含４．５％的甲酸的废水进行萃取试验，结果表明，ＺＹＭ具有良好的热稳定性和再生性，对废水中的甲酸有较高的萃取率。采用本萃取技术，不但具有显著的环境效益，而且还可回收甲酸，获得较好的经济效益。     

炼油污水深度处理回用工艺实验研究

试验工艺流程的方案选定,充分吸收了各炼油厂进行的污水深度处理的成功试验经验,以原臭氧生物活性炭工艺单元为基础,提出了以混凝气浮与臭氧生物活性炭串联工艺为核心的总体工艺流程,以降低工程投资及处理成本,提高污水回用的经济效益;同时,指出试验过程中所存在的问题及其对策。因此,开展炼油污水深度处理回用工艺试验研究,必将为炼油污水深度处理提供强有力的技术支撑,可作为相关污水回用处理工艺选择的参考。     

一种基于图像内容过滤的有线电视网信息审计系统

如何实现广播电视网节目内容的自动审计已成为目前广播电视网网络安全所面临的问题。笔者首先分析了目前有线电视网节目内容的审计,大多基于人工,不仅费时费力,且与先进的现代电视技术极不相匹配,接着对图像内容过滤的关键技术进行了分析,并用反差、能量、熵、相关4个特征量表示纹理特征,在此基础上用交互的动态规划法来进行图像对象分割然后利用相似度描述两个特征量的相似程度,最后以对黄色内容识别为实例,通过提取图像的纹理特征与定义好的特征库相匹配,监控包含不良人体图像信息的视频,实现对有线电视网节目内容的自动审计。     

Occurrence and dominance of Cylindrospermopsis raciborskii and dissolved cylindrospermopsin in urban reservoirs used for drinking water supply,South China

The tropical cyanobacterium Cylindrospermopsis raciborskii is of particular concern for its invasive characteristics and production of the toxin cylindrospermopsin (CYN). The present study represents the first attempt to determine the distribution of C. raciborskii and CYN in tropical China. The presence of C. raciborskii and CYN, as well as the composition of phytoplankton, was determined from a total of 86 samples from 25 urban reservoirs for drinking water supply in Dongguan City of South China. The presence of C. raciborskii was observed in 21 of the 25 reservoirs and confirmed that this species has been widely distributed in the investigated reservoirs. C. raciborskii accounted for between 0.1 and 90.3 % of the total phytoplankton biomass and contributed to the majority of the phytoplankton in some reservoirs such as Tangkengbian and Xiagongyan. Its biomass was negatively correlated with NO₃ ^?-N concentration and Secchi depth. Dissolved CYN was detected in more than one-half of the reservoirs with concentrations up to 8.25 μg L^?1, and it positively correlated with C. raciborskii biomass. Dissolved microcystins (MCs) were detected in 12 of the 25 reservoirs with a maximum concentration 1.99 μg L^?1. Our data strongly suggest that C. raciborskii and CYN could be important health hazards in urban reservoirs of South China and that more data are needed for further assessment.     

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.