Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

基于最优分割理论的酸雨监控点位的分类研究

Fisher最优分割法是用离差平方和来表示同类样本之间的差异程度,通过简便的计算步骤和作图,确定最优分类数,使同类样本间的差异最小,各类别样本间的差异最大,并用F检验法检验最优分类数的合理性。文章根据Fisher最优分割法的理论内涵,研究其应用于酸雨环境监测优化布点的可行性。以漳州市沿海区域监测点为研究实例,用Fisher最优分割法确定最优的分类情况和最优的优化布点方案。结果表明,原布设的9个监测点用Fisher最优分割法优化为3个典型点位,可客观地反映漳州市酸雨控制区的整体污染状况和污染趋势,该方法理论内涵直观、计算简便、重复性好,对环境质量监测有重要的意义。     

Food-exchange by foragers in the hive – a means of communication among honey bees?

Dancing and trophallactic behaviour of forager honey bees, Apis mellifera ligustica >Spinola, that returned from an automatic feeder with a regulated flow rate of 50% weight-to-weight sucrose solution (range: 0.76–7.65 μl/min) were studied in an observation hive. Behavioural parameters of dancing, such as probability, duration and dance tempo, increased with the nectar flow rate, though with very different response curves among bees. For trophallaxis (i.e. mouth-to-mouth exchange of food), the frequency of giving-contacts and the transfer rate of the nectar increased with the nectar flow rate. After unloading, foragers often approached other nest mates and begged for food before returning to the food source. This behaviour was less frequent at higher nectar flow rates. These results show that the profitability of a food source in terms of nectar flow rate had a quantitative representation in the hive through quantitative changes in trophallactic and dancing behaviour. The role of trophallaxis as a communication channel during recruitment is discussed. Received: 14 January 1995/Accepted after revision: 14 August 1995     

THE IMPORTANCE OF ACCURATE CURVE NUMBERS IN THE ESTIMATION OF STORM RUNOFF1

ABSTRACT: Storm runoff as calculated by the runoff curve number method is shown to be of varying sensitivity to both input rainfall and curve number. Using an assumed input error of 10%, a runoff error chart is given. Up to about 9 inches of rainfall, runoff is more sensitive to curve number than to rainfall. The importance of accurate curve number selection in this range is stressed.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

A taxonomy of performance influencing factors for human reliability analysis of emergency tasks

This paper introduces the process for, and the result of, the selection of performance influencing factors (PIFs) for the use in human reliability analysis (HRA) of emergency tasks in nuclear power plants. The approach taken in this study largely consists of three steps. First, a full-set PIF system is constructed from the collection and review of existing PIF taxonomies. Secondly, PIF candidates are selected from the full-set PIF system, considering the major characteristics of emergency situations and the basic criteria of PIF for use in HRA. Finally, a set of PIFs is established by structuring representative PIFs and their detailed subitems from the candidates. As a result, a set of PIFs comprised of the 11 representative PIFs and 39 subitems was developed.     

Importance of incorporation of personal communication devices in evacuation simulators

The importance of the incorporation of personal communication devices in emergency evacuation simulators will be discussed. Four case studies are examined to identify usage statistics and human behavior when using the devices in an emergency. The case studies are: 9/11 World Trade Center Attacks, London train bombings, Virginia Tech shooting and United Flight #93. The case studies’ findings are implemented into the Vacate evacuation simulator, which uses particle swarm optimization to mimic human pedestrian behavior. The physical actions of using a device, as well as the reaction to the information transmitted during usage, are examined. Findings show that the effects of the personal communication devices can affect individuals that are close to the user of the device, as well as those not in the local vicinity of the user. These effects, combined with the rapid mainstream acceptance of communication technologies, justify the implementation of personal communication devices into evacuation simulators.     

基于熵权-HDT的航空器维修人误概率确定

人误是造成民用航空维修差错的主要因素。为确定不同情境下人误发生概率,结合某维修基地具体情况,采用熵权法确定主要的影响因子,并基于全决策树法分析主要影响因子对航空器维修人误概率的影响程度。计算结果显示,该维修基地人因可靠性的主要影响因子包括航空器维修人员的安全态度、技能、沟通、工作环境、压力以及工段长领导能力。根据各主要影响因子的不同品质描述等级组合,确定该情境下航空器维修人员的人误概率。鉴于该维修基地人因可靠性影响最明显的因子是"沟通",提出信息及时交流、明确沟通重要性等解决措施。     

基于HERA-JANUS模型的空管人误认知分析

空管人误分类分析是空管人误研究的基础。为了对管制员人误进行系统的分类研究,结合空管业务知识和认知心理学理论,对欧洲航空安全局和美国联邦航空局合作开发的HERA-JANUS模型的工作原理和流程进行较详细地分析。运用该方法模型,对我国一起空管不安全事件案例进行分析后得到3个由管制员所产生的人误差错,并对这3个人误差错分别从人误类型、人误认知、相关因素3方面进行详尽的分析研究,最后得出该不安全事件的21项人误结果。结果表明,HERA-JANUS模型能较全面地从深层次分析管制员的人误,其分类形式也便于开展空管人误统计。     

飞行员人因可靠性定量预测

为有效预测飞行员的人因可靠性,以保障飞行安全,基于认知可靠性与失误分析法(CREAM)的扩展法,建立飞行员人因可靠性定量预测模型。依据飞行员的任务特点,调整认知行为及认知功能。通过优化共同绩效条件(CPC)因子水平等级,并增加新的因子,改进CPC因子依赖规则,用于修正因子的初始评估结果,解决扩展法未考虑因子间关系的问题,从而完成模型的建立。利用回看分析法验证模型的有效性,采用所建立的模型和扩展法分别对已发生的飞行案例进行预测,并与实际发生结果对比分析。结果表明,与扩展法相比,采用飞行员定量预测模型得到的预测结果与案例发生结果所反映的控制模式更为匹配。