Density estimation using ranked-set sampling data

The ranked-set sampling (RSS) is applicable in practical problems where the variable of interest for an observed item is costly or time-consuming but the ranking of a set of items according to the variable can be easily done without actual measurement. In the context of RSS, the need for density estimation arises in certain statistical procedures. The density estimation also has its own interest. In this article, we develop a method for the density estimation using RSS data. We derive the properties of the resulted density estimate and compare it with its counterpart in simple random sampling (SRS). It is shown that the density estimate using RSS data provides a better estimate of the density than the usual density estimate using SRS data. The density estimate developed in this article can well serve various purposes in the context of RSS.     

人-机系统事故预防理论研究

分析人-机系统事故发生原因,剖析经典以人失误为主因的事故致因模型存在的不足,在该模型基础上增加"刺激"形成的原因,构建了改进事故致因模型。对两模型进行比较研究,指出人机工程学与防止事故的关系,提出了人机工程学防止事故的方法,并给出人机界面合理性主观评价检查表。研究及论证表明:预防人-机系统事故的本质在于有效防止人失误的发生,除安全管理措施以外,最重要的是人机工程学问题,笔者提出的基于人机工程学的人-机系统事故预防理论,对人-机系统事故的预防起到积极的指导作用。     

航空维修差错分析及其管理

航空维修差错是诱发或直接导致飞行事故最重要的原因之一 ,对维修差错进行分类和分析有助于航空安全。笔者在分析航空维修环境变化的基础上 ,基于Reason模型构建了维修差错分类与诱因分析的框架 ,并结合机务维修的实际情况 ,对框架所包括的不安全行为、不安全行为的先兆、不安全的管理及组织因素进行了初步编码。文章还简要论述了维修差错的管理技术 ,指出借助框架编制详细的差错分类与分析编码系统是发展的方向。     

复杂工业系统中班组人因失误分析

在复杂工业系统中 ,人因可靠性分析 (HRA)是预防和减少人因失误的有效方法。人在复杂工业系统中的生产活动 ,往往是由组织中班组成员集体完成的 ,完整的HRA必须充分考虑班组人误的产生。班组人误的产生有其自身的规律 ,如何合理地定义人员行为形成因子 (PSFs)是班组人因失误分析的难点 ,也是班组人因失误分析的重要手段 ,被广泛应用在核电厂 ,航空和造船工业领域的事故分析中。笔者详细分析和探讨了班组人因失误的定义、产生过程及相关的人的行为形成因子 ,以期能使大规模工业系统中的人因失误分析更加合理和完善。     

大气颗粒物“二重源解析”技术的误差分析

"二重源解析"模型计算结果的误差是采样误差、样品处理误差、化学组分分析误差、数据处理误差以及数学模型误差等所有误差的积累。提出了"二重源解析"解析结果的相对误差和标准偏差表达式,并用之计算了某市利用"二重源解析"模型计算的源贡献值的相对误差和标准偏差,还针对从源排放出来的初始态颗粒物在传输过程中发生的扬尘态变化提出了扬尘转化率的概念和计算方法。     

玻璃注射器对顶空气相色谱法分析苯系物的误差原因分析

按GB11890—89顶空气相色谱法分析苯系物时，发现重复性和分割水平样品平行性较差，经仔细分析，是由于使用普通玻璃注射器造成的。为避免此类误差，建议顶空气相色谱法分析时，使用带特氟龙顶端推杆的气密性注射器。     

SAMPLING FRAME FOR IMPROVING PEBBLE COUNT ACCURACY IN COARSE GRAVEL‐BED STREAMS1

ABSTRACT: Improved sampling techniques are needed to increase the accuracy of pebble‐count particle‐size distributions used for stream studies in gravel‐bed streams. However, pebble counts are prone to operator errors introduced through subjective particle selection, serial correlation, and inaccurate particle‐size measurements. Errors in particle‐size measurements can be minimized by using a gravel template. Operator influence on particle selection can be minimized by using a sampling frame, 60 by 60 cm, in which sampling points are identified by the cross points of thin elastic bands. Serial correlation can be minimized by adjusting the spacing between the cross points and setting it equal to the dominant large particle size (=D₉₅). In a field test in a cobble‐bed stream, the sampling frame developed in this study produced slightly coarser size distributions, particularly in the cobble range, than the traditional heel‐to‐toe walk that selects particles with a blind touch at the tip of the boot. The sampling frame produced more similar sampling results between two operators than heel‐to‐toe walks. The difference between the two sampling methods is attributed to an unbiased selection of fine and coarse particles when using the sampling frame.     

Analysis of underlying causes of investigated loss of containment incidents in Dutch Seveso plants using the Storybuilder method

In the Netherlands there are around 400 “Seveso” sites that fall under the Dutch Major Hazards Decree (BRZO) 1999. Between 2006 and 2010 the Dutch Labour Inspectorate's Directorate for Major Hazard Control completed investigations of 118 loss of containment incidents involving hazardous substances from this group. On the basis of investigation reports the incidents were entered in a tailor-made tool called Storybuilder developed for the Dutch Ministry of Social Affairs and Employment for identifying the dominant patterns of technical safety barrier failures, barrier task failures and underlying management causes associated with the resulting loss of control events. The model is a bow-tie structure with six lines of defence, three on either side of the central loss of containment event. In the first line of defence, failures in the safety barriers leading to loss of control events were primarily equipment condition failures, pre start-up and safeguarding failures and process deviations such as pressure and flow failures. These deviations, which should have been recovered while still within the safe envelope of operation, were missed primarily because of inadequate indication signals that the deviations have occurred. Through failures of subsequent lines of defence they are developing into serious incidents. Overall, task failures are principally failures to provide adequate technical safety barriers and failures to operate provided barriers appropriately. Underlying management delivery failures were mainly found in equipment specifications and provisions, procedures and competence. The competence delivery system is especially important for identifying equipment condition, equipment isolation for maintenance, pre-start-up status and process deviations. Human errors associated with operating barriers were identified in fifty per cent of cases, were mostly mistakes and feature primarily in failure to prevent deviations and subsequently recover them. Loss of control associated with loss of containment was primarily due to the containment being bypassed (72% of incidents) and less to material strength failures (28%). Transfer pipework, connections in process plant and relief valves are the most frequent release points and the dominant release material is extremely flammable. It is concluded that the analysis of a large number of incidents in Storybuilder can support the quantification of underlying causes and provide evidence of where the weak points exist in major hazard control in the prevention of major accidents.     

Arabian,Asian, western: a cross-cultural comparison of aircraft accidents from human factor perspectives

Introduction. Rates of aviation accident differ in different regions; and national culture has been implicated as a factor. This invites a discussion about the role of national culture in aviation accidents. This study makes a cross-cultural comparison between Oman, Taiwan and the USA. Method. A cross-cultural comparison was acquired using data from three studies, including this study, by applying the Human Factors Analysis and Classification System (HFACS) framework. The Taiwan study presented 523 mishaps with 1762 occurrences of human error obtained from the Republic of China Air Force. The study from the USA carried out for commercial aviation had 119 accidents with 245 instances of human error. This study carried out in Oman had a total of 40 aircraft accidents with 129 incidences. Results. Variations were found between Oman, Taiwan and the USA at the levels of organisational influence and unsafe supervision. Seven HFACS categories showed significant differences between the three countries (p?<?0.05). Conclusion. Although not given much consideration, national culture can have an impact on aviation safety. This study revealed that national culture plays a role in aircraft accidents related to human factors that cannot be disregarded.     

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.