基于Soft Fuzzy ARTMAP算法的地铁隧洞光纤光栅传感火灾识别研究*

为解决传统火灾报警系统在应对地铁火灾报警时存在的即时性差、灵敏度及智能化水平低等问题,基于Fuzzy ARTMAP网络,结合Yu范数相似度准则与软竞争学习机制,提出1种软竞争学习Fuzzy ARTMAP算法,弥补传统Fuzzy ARTMAP网络胜者为王规则导致的区域重叠而产生误判的不足;结合地铁光纤光栅传感网络数据,将该算法应用于地铁火灾识别。结果表明:与传统的Fuzzy ARTMAP相比,该算法可快速有效地识别地铁火灾趋势,为地铁火灾识别系统研究提供理论支持。     

Ambient monitoring of asbestos in selected Italian living areas

This paper presents the results of an intensive monitoring activity of the particulate, fall-out and soil of selected living areas in Italy with the aim to detect the asbestos concentration in air and subsequent risk of exposure for the population in ambient living environments, and to assess the nature of the other mineral phases composing the particulate matrix. Some areas were sorted out because of the presence of asbestos containing materials on site whereas others were used as blank spots in the attempt to detect the background environmental concentration of asbestos in air. Because the concentration of asbestos in ambient environments is presumably very low, and it is well known that conventional low–medium flow sampling systems with filters of small diameter (25 mm) may collect only a very small fraction of particulate over a short period, for the first time here, an intense monitoring activity was conducted with a high flow sampling system. The high flow system requires the use of large cellulose filters with the advantage that, increasing the amount of collected dust, the probability to collect asbestos fibers increases. Both the protocol of monitoring and analysis are novel and prompted by the need to increase the sensitivity towards the small number of expected fibers. With this goal, the collection of fall-out samples (the particulate falling into a collector filled with distilled water during the monitoring shift) and soil samples was also accomplished. The analytical protocol of the matrix particulate included preliminary X-ray powder diffraction (XRPD), optical microscopy and quantitative electron microscopy (SEM and TEM). Correlations with climatic trends and PM10 concentration data were also attempted.The surprising outcome of this work is that, despite the nature of the investigated site, the amount of dispersed asbestos fibers is very low and invariably lower than the theoretical method detection limits of the SEM and TEM techniques for identification and counting of asbestos fibers. The results are compared to the literature data worldwide and an updated model for asbestos fibers dispersion in ambient environments is proposed.     

Measurement Of Nutrients In Green House Soil With Laser Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) has been applied for the determination of nutrients in the green house soil samples. We determined appropriate spectral signatures of vital nutrients and calibrated the method to measure the nutrients in a naturally fertilized plot, cultivated with tomato and cucumber plants. From the calibration curves we predicted the concentrations of important nutrients such as Ca, K, P, Mg, Fe, S, Ni and Ba in the soil. Our measurements proved that the LIBS method rapidly and efficiently measures soil nutrients with excellent detection limits of 12, 9, 7, 9, 7, 10, 8 and 12~mg/kg for Ca, K, P, Mg, Fe, S, Ni and Ba respectively with a precision of 2%, The unique features of LIBS for rapid sample analysis demonstrated by this study suggests that this method offers promise for precision measurements of soil nutrients as compared to conventional methods in short span of time.     

Method for identifying errors in chemical process development and design base on accidents knowledge

It has been claimed that the high accident rate in the chemical process industry is due to poor dissemination of accident knowledge that affects directly the level of learning from accidents. In response to this situation, this paper utilized past accident knowledge as a basis to develop a safety oriented design tool whereby the accident information were directly disseminated into plant design. The method was developed based on our previous accident analysis of design error in which the common design errors were ranked in accordance to their frequency and its origins during normal plant design project. Based on the design error ranking and its origin at a specific design phases, a method for design error detection is proposed. The method is expected to be able to identify the possible design error and its causes throughout chemical process development and design. The main objective is to trigger safe design thinking at the specific design phases so that appropriate action for risk reduction could be timely implemented. The Bhopal and BP Texas tragedies are used as case studies to test and verify the method. The proposed method can detect up to 74% of design errors.     

Mechanistic understanding of human–wildlife conflict through a novel application of dynamic occupancy models

Crop and livestock depredation by wildlife is a primary driver of human–wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08–0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human–wildlife interactions.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

离子色谱法同时测定水中的甲酸、乙酸、丙烯酸和氯乙酸

建立了离子色谱电导同时检测水中甲酸、乙酸、丙烯酸和氯乙酸的方法,当采用1.0mL/min、1mmol/L KOH淋洗液梯度洗脱时可达到样品中甲酸、乙酸、丙烯酸和氯乙酸分离分析的目的;乙酸、甲酸、丙烯酸和氯乙酸的线性范围分别为0.01～10.0、0.01～20.0、0.01～20.0和0.01～20.0mg/L,检出限分...     

某企业工业X射线探伤机环境影响评价

以某企业的工业X射线探伤机为例讨论了固定式探伤的环境影响评价过程,分析了探伤机项目对周围环境的影响,评价结果表明,该企业探伤室的屏蔽防护符合有关标准要求,对放射性职业工作人员和周围公众人员的年有效剂量分别低于相应的剂量约束值。     

地震灾区河谷滑坡检测的遥感分析——以北川县滑坡为例

震区滑坡易堵塞河道形成高危型堰塞湖,一旦坝堤溃决,将释放巨大能量,造成严重的地震次生水灾。本文利用多源遥感数据,旨在研究一种检测河道滑坡的快速有效的方法,迅速判断出滑坡位置,为救援减灾提供重要信息。首先,对于灾前CBERS-02B星CCD数据,通过归一化水体指数(NDWI)来提取灾前水体信息主要为河道;由于灾后震区天气状况恶劣,故采用Radarsat-1SAR数据。利用水体在SAR影像上的特性,经过多次试验后使用阈值法来提取河道范围。再对两幅影像提取结果中的河道区域进行交集运算,检测出河道范围内的变化部分。通过上述方法提取的河道信息较为模糊、零散,这些模糊、零散并非都由滑坡堵塞河道造成,而是受噪声影响,在此对河道交集影像做膨胀处理,达到突出滑坡信息的目的,进而得以提取河道真实堵塞范围。最后进行人机交互判读,提取滑坡区域。实验以四川省北川县滑坡灾害为例,证明了本文方法的高效性与可靠性。