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     

我国证券市场体制性缺陷与投资风险分析

与国民经济长期高增长相背离,证券市场出现了深幅下跌,投资者承受了巨大的投资风险,究其原因,体制性缺陷是重要因素之一。笔者认为,我国证券市场的体制性缺陷主要表现在市场经济环境不够完备、法律法规体系不十分健全、监管体制不力、证券市场的功能定位扭曲、股权分置问题久拖难决等方面。目前该体制性缺陷是导致我国证券市场长期下跌的重要原因,也给证券投资者带来了巨大的投资风险。只有加快改革、完善法律和监管体制,我国证券市场才能具有投资价值并健康发展。     

房屋结构损伤及安全性评估实例分析

随着我国部分房屋建筑使用年限接近设计期限,或者说结构进入老化阶段,结构的健康状况和安全性评估逐步引起人们的关注。现代测试技术和计算机信息处理方法的结合,结构工程损伤检测方法、技术的规范化和科学化,基于时域和频域分析的结构参数辨识理论和技术、人工智能技术和专家系统也开始应用于结构健康监测和评估。简要评述了结构损伤检测方法进展和理论分析方法,并结合某体育场馆的结构安全性评估为实例,从结构设计、材料强度检测和实际结构状态进行全面检测和分析,并对其健康状况和安全性进行评估。     

石油天然气钻探过程中硫化氢的监测

石油天然气钻探过程中硫化氢的准确监测是确保钻井安全的条件。在介绍硫化氢气体的性质、危害的基础上具体阐述了现场常用硫化氢监测方法。对现行井场硫化氢监测问题进行了探讨，提出了硫化氢监测应从监测地面气体向监测地层流延伸，硫化氢报警内容应多样化的建议。     

室内有毒易爆气体的检测

随着城市生活水平的提高,室内装修装饰日益普及.各种新材料的引入,使得室内的各种有害气体总量日益增加.长期生活在这样的环境下,会对人体健康产生极为不利的影响.居民生活用煤气,在给人们生活带来便利的同时,作为一种可燃性、有毒气体,也具有极强的危害性.因此,研制一种能检测多种有害气体的实用仪器,具有很大的应用价值.本仪器为便携式多功能仪器,采用可充电电池供电,可以检测ppb的挥发性气体,显示气体浓度值,也可检测煤气,并具有声光报警功能.     

Landscape trajectory of natural boreal forest loss as an impediment to green infrastructure

Loss of natural forests by forest clearcutting has been identified as a critical conservation challenge worldwide. This study addressed forest fragmentation and loss in the context of the establishment of a functional green infrastructure as a spatiotemporally connected landscape-scale network of habitats enhancing biodiversity, favorable conservation status, and ecosystem services. Through retrospective analysis of satellite images, we assessed a 50- to 60-year spatiotemporal clearcutting impact trajectory on natural and near-natural boreal forests across a sizable and representative region from the Gulf of Bothnia to the Scandinavian Mountain Range in northern Fennoscandia. This period broadly covers the whole forest clearcutting period; thus, our approach and results can be applied to comprehensive impact assessment of industrial forest management. The entire study region covers close to 46,000 km² of forest-dominated landscape in a late phase of transition from a natural or near-natural to a land-use modified state. We found a substantial loss of intact forest, in particular of large, contiguous areas, a spatial polarization of remaining forest on regional scale where the inland has been more severely affected than the mountain and coastal zones, and a pronounced impact on interior forest core areas. Salient results were a decrease in area of the largest intact forest patch from 225,853 to 68,714 ha in the mountain zone and from 257,715 to 38,668 ha in the foothills zone, a decrease from 75% to 38% intact forest in the inland zones, a decrease in largest patch core area (assessed by considering 100-m patch edge disturbance) from 6114 to 351 ha in the coastal zone, and a geographic imbalance in protected forest with an evident predominance in the mountain zone. These results demonstrate profound disturbance of configuration of the natural forest landscape and disrupted connectivity, which challenges the establishment of functional green infrastructure. Our approach supports the identification of forests for expanded protection and conservation-oriented forest landscape restoration.     

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.     

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。