基于BP神经网络的受限空间火灾联合探测方法

针对航空受限空间火灾探测高误报的问题，在现有技术成果基础上对多种火灾探测方式进行研讨，并提出1种基于BP神经网络技术的飞机机身内部受限空间火灾联合探测报警方法。该方法结合现有烟雾感应、气体传感器探测等常用火灾探测技术，以红外热成像探测为辅助手段，采用神经网络实现数据融合，对模拟实验舱火灾烟雾进行联合探测，在单一火灾探测方式基础上提高了探测准确率。     

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down.A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator.     

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

Effectiveness of Scat‐Detection Dogs in Determining Species Presence in a Tropical Savanna Landscape

Abstract: Most protected areas are too small to sustain populations of wide‐ranging mammals; thus, identification and conservation of high‐quality habitat for those animals outside parks is often a high priority, particularly for regions where extensive land conversion is occurring. This is the case in the vicinity of Emas National Park, a small protected area in the Brazilian Cerrado. Over the last 40 years the native vegetation surrounding the park has been converted to agriculture, but the region still supports virtually all of the animals native to the area. We determined the effectiveness of scat‐detection dogs in detecting presence of five species of mammals threatened with extinction by habitat loss: maned wolf (Chrysocyon brachyurus), puma (Puma concolor), jaguar (Panthera onca), giant anteater (Myrmecophaga tridactyla), and giant armadillo (Priodontes maximus). The probability of scat detection varied among the five species and among survey quadrats of different size, but was consistent across team, season, and year. The probability of occurrence, determined from the presence of scat, in a randomly selected site within the study area ranged from 0.14 for jaguars, which occur primarily in the forested areas of the park, to 0.91 for maned wolves, the most widely distributed species in our study area. Most occurrences of giant armadillos in the park were in open grasslands, but in the agricultural matrix they tended to occur in riparian woodlands. At least one target species occurred in every survey quadrat, and giant armadillos, jaguars, and maned wolves were more likely to be present in quadrats located inside than outside the park. The effort required for detection of scats was highest for the two felids. We were able to detect the presence for each of five wide‐ranging species inside and outside the park and to assign occurrence probabilities to specific survey sites. Thus, scat dogs provide an effective survey tool for rare species even when accurate detection likelihoods are required. We believe the way we used scat‐detection dogs to determine the presence of species can be applied to the detection of other mammalian species in other ecosystems.     

滇西北高原湖泊剑湖演变过程及其生态环境效应分析

以滇西北高原湖泊剑湖为研究区,1974—2015年间8期遥感影像为数据源,运用遥感和地理信息系统技术,研究剑湖湖泊近40年间的时空演变过程,探析剑湖湖泊的入湖污染物及其生态环境效应变化。结果表明:近40年来剑湖湖泊面积呈现先明显减少再增加后缓慢减少的变化规律,由1974年的504.47 hm~2减至2015年的451.72 hm~2;目前剑湖水体中COD含量较低,符合地表水环境质量Ⅱ类标准;TP含量满足Ⅲ类标准;TN含量仅可满足IV类标准;剑湖入湖的主要污染源是农村生活污染和农业面源污染;随着时间的演变剑湖湖泊TN、TP污染物浓度呈上升趋势,剑湖湖泊生态系统受到极大干扰。     

原子吸收火焰法次灵敏线测定污水和电镀污泥中高含量的锌

对采用原子吸收火焰法次灵敏线测定污水和电镀污泥中高含量的锌进行了研究。试验结果表明：在锌浓度50．0～600．0mg/L之间,溶液锌含量与吸光度呈线性关系。线性回归方程为y＝0．000661x-0．0007,相关系数γ＝0．9998。方法检出限为25．0mg/L,相对标准误差（RSD）＜2．96％,加标回收率为92．5％～105％,与标准法的相对误差＜2．76％。     

由德国实验室的安全设施引发的思考

德国对实验室的安全问题相当重视,实验室内安全设施齐全,气罐使用管理严格,工作人员安全意识高,废弃物处置规范。与之相比,江苏省监测系统的实验室在安全重视程度上还存在差距,在安全设施的配备、管理及宣传等方面均有待改进。建议加强实验室安全设施建设,以德国先进经验为抓手,重点从提高安全意识、改造通风系统、规范有毒有害废弃物的处置等方面着手,切实改进实验室的安全问题,为建设现代化的实验室奠定基础。     

pH值对凯氏蒸馏法氨氮检出量的影响分析研究

土壤、肥料中的氨氮测定常用2mol·L^-1KC浸提一蒸馏法一酸滴定的方法进行测定,其中蒸馏是最关键和最重要的一个环节。以污泥堆肥样品为例,利用统计学原理,研究了汽提蒸馏过程中pH对氨氮检出量的影响。结果显示：pH值在6．5—11．0范围内与氨氮的检出系数是显著的正相关关系（相关系数r=0．9891）;回归方程在0．05的水平下是非常显著的,拟合度很好。进一步做残差和预测分析可以得出：pH值在6．5～10．0范围内,预测值和测定值的符合度更好。     

车辆高原环境模拟试验技术发展现状综述

由于高原环境对车辆性能影响的严酷性,现代车辆的高原环境适应性越来越受到重视,推动了车辆高原环境模拟试验技术的快速发展。阐述了车辆高原环境模拟试验技术的基本内涵,以及车辆高原环境适应性试验的类型、特点和试验项目等,分析了国内外高原环境模拟试验技术研究与发展概况。以某型车辆高原环境实验室为例,详细介绍了车辆高原环境实验室的结构、功能及原理。