AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

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。     

对重大危险源安全预警系统的探讨

阐述了安全预警技术和重大危险源安全预警系统的建立.重大危险源安全预警系统的建立,将对实现重大危险源安全监察工作信息化、科学化、现代化起到积极的推动作用.     

基于系统动力学模型的影剧院人员疏散策略

随着社会的发展,人们对生命的重视程度日益增强,大型公共场所临灾情况下人员疏散问题的研究也越来越有实际意义.分析以往影剧院火灾事故可以发现,不正确的疏散逃生行为所引起的通道堵塞,是导致人员大量伤亡的一个主要原因.根据系统动力学原理,应用STELLA系统软件,建立了基于粗网络模型的人员疏散模型.以影剧院发生火灾为例,分析了采取不同疏散策略所产生的避难效果差异,找出了最佳的疏散策略.所提研究方法和建立的模型,对于合理设计疏散路线和优化建筑物的出口与通道结构具有一定的实用价值.     

City hazardous gas monitoring network

In our today's societies, many dangerous chemicals are produced and transported. Due to the vast use of chemicals, more chemical accidents are taking place with huge losses. In this study a city hazardous gas monitoring network was designed to detect the dispersion of toxic and combustible gases in the primary stages. The network could cover hazardous chemical facilities, important hazardous chemical routes, warehouses and special locations which may be the targets of terrorist attacks. The network is consisted of several local networks and a central control panel complex. Each local network has a local control panel in the center and many detectors and sounders around it at distances less than 3000 m that communicate with the local control panels wirelessly. In each location there are two types of gas detectors, toxic and combustible, and a sounder which are equipped with a wireless, radio frequency modem allowing the units to communicate readings and other information on a real-time basis with a remotely located local control panel. High sensitive Photo Ionization Detectors, PIDs, are used to provide fast and low-level on-site screening for chemicals contamination. Combustible gas detectors are the second choice to sense the combustible gas and verify the readings of PIDs in this regard. The central panel consists of several connected control panels work uniquely helping a computer set and the appropriate software and communicate with local control panels via telephone lines. All of the network components are shown on the monitor of central panel with special symbols by geographical information system program. The system is fully addressable so that the high level detection of a detector produces a blinking color double-circle around its symbol in GIS plan. In case of high level gas detection, a team of experts who are fully equipped with different portable detectors depart to the site to test the field to identify the chemicals. All readings of detectors are saved in a data bank and then analyzed to find any chemicals spills and leakages. The network was simulated by a special program so that the components of local networks and the central panel are shown in separate windows. By clicking on one detector on environmental window the formerly designed responses will be activated in central panel window.     

大学生沉溺网络透析及防范措施

因沉溺网上聊天、交友、玩游戏、看色情而影响大学生学习、生活、身体健康,以致诱发犯罪的问题如洪水猛兽席卷而来.防止大学生沉溺网络,走向犯罪是当前社会、学校、家庭不容忽视的问题.立法、执法、管理、教育应形成合力.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

MODELING LIGHT ATTENUATION,SECCHI DISK,AND EFFECTS OF TRIPTON IN SENACA RIVER,NEW YORK,USA1

The development, testing, and application of a probabilistic model framework for the light attenuation coefficient for downwelling irradiance (K_d) and Secchi disc transparency (SD) that resolves the effects of several light attenuating constituents, including phytoplankton and nonliving particles (tripton), is documented. The model is consistent with optical theory, partitioning the magnitudes of the light attenuating processes of absorption and scattering according to the contributions of attenuating constituents as simple summations. The probabilistic framework accommodates variations in the character and concentrations of these constituents and ambient conditions during measurements, and recognizes a linear relationship between the magnitudes of absorption and scattering by tripton. The model is tested and applied for a 21 km reach of the Seneca River, New York, that features optical gradients caused by an intervening hypereutrophic lake and dam, and a severe infestation of the exotic zebra mussel. The model is applied to resolve the roles of phytoplankton and tripton in regulating measured longitudinal patterns of SD along the study reach of the river and increases in SD since the zebra mussel invasion, and to predict decreases in K_d since the invasion.     

国产多核处理器芯片TDBI技术研究

随着集成电路的功能越来越复杂,超大规模集成电路的动态老炼越来越成为一项困难的工作。传统针对超大规模集成电路的老炼多采用静态老炼方法,这种方法不能使电路内部的功能节点动作起来,无法保证老炼效果,因此能够实现电路内部所有功能模块全动态激励的TDBI技术越来越受到人们的关注。本文以国产多核处理器芯片为测试对象,为研究多核处理器芯片的TDBI方法进行了芯片老炼测试软硬件系统开发,解决了多核处理器老炼中大功率电源供电、图形存储空间不足等关键技术。     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.