Human error identification techniques applied to public technology: predictions compared with observed use

In this paper, we consider the use of human error identification (HEI) techniques as a possible alternative to observation studies for product evaluation. The HEI techniques used were Task Analysis for Error Identification (TAFEI) and Predictive Human Error Analysis (PHEA). The comparison was undertaken in connection with the prediction of errors in the use of a ticket vending machine. Two main findings emerged from the study. First, predictions derived from the HEI techniques compared favourably with errors observed in actual machine use. Second, the HEI techniques took far less time than direct observation to reach comparable levels of performance. Such rates suggest that these techniques can be usefully applied to the study of consumer products.     

The validation of three human reliability quantification techniques - THERP, HEART and JHEDI: part 1 - technique descriptions and validation issues

This is the first of a set of three papers reviewing the validity of three Human Reliability Assessment (HRA) techniques used in the UK to predict human performance in high risk industries. The techniques are used to determine the risks inherent in such industries due to human error, and also the benefit in terms of risk reduction by having human operators in the system. These techniques culminate in a quantitative human error probability for each error or failure identified, predicting how often errors or failed performance will occur. The major question with such an approach is whether such probabilities are accurate. This key validation question is answered in the second paper, which reports the results of a large and independent validation experiment.

Once a technique achieves some degree of predictive validity, the next question becomes whether such a technique can consistently produce valid and accurate results. This is called the reliability of the technique, and is dependent upon its consistency of usage by different assessors. Consistency can only be analysed by investigating the detailed usage of the techniques, and such an analysis is reported in the third paper in this series. The advantage of such an analysis is that it can also lead to specification of practical guidance for practitioners, and may lead to derivation of ways to improve the reliability and consistency of usage of specific HRA techniques. This first paper introduces the three techniques themselves, and reviews the major validation criteria and issues which should be considered when trying to determine if such techniques work.     

A case study of a human reliability assessment for an existing nuclear power plant

This paper concerns a Human Reliability Assessment (HRA) carried out over a period of two years as part of a Nuclear Power Plant Probabilistic Safety Assessment (PSA). The HRA involved all elements of the HRA process, from problem definition and task analysis, through error representation and quantification, to impact assessment, error reduction, quality assurance and documentation. The aim of this paper is to show the methodology of HRA as applied in a real PSA, highlighting various elements of the HRA, and how the HRA interfaced with the PSA. Comments are also given on practical aspects and impacts of the various approaches, and the usefulness of a hybrid HRA/PSA team approach.     

Learning to predict human error: issues of acceptability,reliability and validity

Human Error Identification (HEI) techniques have been used to predict human error in high risk environments for the past two decades. Despite the lack of supportive evidence for their efficacy, their popularity remains unabated. The application of these approaches is ever-increasing, to include product assessment. The authors feel that it is necessary to prove that the predictions are both reliable and valid before the approaches can be recommended with any confidence. This paper provides evidence to suggest that human error identification techniques in general, and SHERPA in particular, may be acquired with relative ease and can provide reasonable error predictions.     

An experimental study on estimating human error probability (HEP) parameters for PSA/HRA by using human model simulation

A framework of Human Error Probability (HEP) parameters, which is needed for Human Reliability Analysis (HRA) within a practice of Probabilistic Safety Assessment (PSA) of Nuclear Power Plant is first proposed. Then a laboratory experiment was conducted in order to construct a computer simulation model (human model) that describes human cognitive behaviour on detecting and diagnosing plant anomaly causes. An inter-comparison between experimental data and human model simulation was performed to estimate Human Cognitive Reliability (HCR) curves, in order to confirm the applicability of a human model for estimating these HEP parameters for PSA/HRA practice.     

An experimental study on estimating human error probability (HEP) parameters for PSA/HRA by using human model simulation

A framework of Human Error Probability (HEP) parameters, which is needed for Human Reliability Analysis (HRA) within a practice of Probabilistic Safety Assessment (PSA) of Nuclear Power Plant is first proposed. Then a laboratory experiment was conducted in order to construct a computer simulation model (human model) that describes human cognitive behaviour on detecting and diagnosing plant anomaly causes. An inter-comparison between experimental data and human model simulation was performed to estimate Human Cognitive Reliability (HCR) curves, in order to confirm the applicability of a human model for estimating these HEP parameters for PSA/HRA practice.     

Applying hierarchical task analysis to improving the patient positioning for direct lateral interbody fusion in spinal surgery

The present study brings together for the first time the techniques of hierarchical task analysis (HTA), human error identification (HEI), and business process management (BPM) to select practices that can eliminate or reduce potential errors in a surgical setting. We applied the above approaches to the improvement of the patient positioning process for lumbar spine surgery referred to as ‘direct lateral interbody fusion’ (DLIF). Observations were conducted to gain knowledge on current DLIF positioning practices, and an HTA was constructed. Potential errors associated with the practices specific to DLIF patient positioning were identified. Based on literature review and expert views alternative practices are proposed aimed at improving the DLIF patient positioning process. To our knowledge, this is the first attempt to use BPM in association with HEI/HTA for the purpose of improving the performance and safety of a surgical process – with promising results.     

基于应用视角的缓冲区溢出检测技术与工具

缓冲区溢出漏洞是危害最为广泛和严重的安全漏洞之一,彻底消除缓冲区溢出漏洞相当困难.学术界、工业界提出了众多缓冲区溢出漏洞检测技术与工具.面对众多的工具,使用者如何结合自身需求有效地选择工具,进而应用到漏洞的检测与修复、预防与保护、度量与评估等方面,是具体而实际的问题.解决这一问题,需要在各异的用户需求与多样的缓冲区溢出检测技术与工具之间建立一张条理清晰、便于用户理解和使用的映射图谱.站在使用者的立场,在概述缓冲区溢出漏洞类型与特征的基础上,从软件生命周期阶段的检测与修复、缓冲区溢出攻击阶段的预防与保护、基于认识与理解途径的度量与评估这3个应用视角,对缓冲区溢出漏洞检测技术与工具进行梳理,一定程度上在用户需求、检测技术与工具之间建立了一张映射图谱.     

Refinery-wide control loop performance assessment

This paper discusses the application of control loop performance assessment (CLPA) in a refinery setting. The CLPA algorithm has several parameters that have to be adjusted correctly to give the best results. Procedures are described for selecting these parameters which make it feasible to implement the algorithm on a refinery-wide scale. We report practical experiences with the use of the techniques.     

A Bayes-SLIM based methodology for human reliability analysis of lifting operations

Investigations have shown that human error (HE) is the most common cause of accidents involving lifting operations. So it is essential to conduct human reliability analysis (HRA) in lifting operations. The estimation of human error probabilities (HEPs) is a key to HRA. In this paper, five useful performance shaping factors (PSFs) of lifting operations were introduced and an approach to combine Bayesian methodology and the success likelihood index method (SLIM) was applied to determine the HEPs of various lifting operation errors. A numerical example was used to illustrate the application of the proposed methodology.Relevance to industryReliability analysis of crane lifting operation has traditionally been difficult without considering human error. The present study suggests that managers could use the Bayesian-SLIM methodology to conduct human reliability analysis and minimize human error in crane lifting operation.     

Applicability of human reliability assessment methods to human–computer interfaces

The UK Office of Nuclear Regulation (ONR) has undertaken a Generic Design Assessment of two nuclear power station designs for prospective construction in the UK. This assessment included a review of the Human Reliability Assessments (HRAs) submitted as part of the probabilistic safety assessments (PSAs). Both reactor designs have human–system interfaces driven by digital technology. However, the data and methods for assessing human error probability (HEP) pre-date such technology. Therefore, the ONR sought to establish whether existing HRA methods remain applicable to modern human–interface interactions and hence continue to provide a credible insight into the risk contribution from human error. An extensive literature review was undertaken to identify or derive relevant HEPs. Data have ranged from those associated with particular interface objects, plant start-ups and post-fault diagnoses. There appear to be some interesting paradoxes within the data explored in this paper. Based upon the data reviewed, it is concluded that existing human reliability assessment methods are likely to be optimistic in their estimates of HEPs where diagnosis is involved or where process control is dependent on human–computer interaction. Shortfalls in the availability of published relevant data and the scope of existing HRA methods have been identified by this work.     

Numerical solutions of nonlinear problems of continua—II. Survey of incompressibility constraints and software aspects

In Part I [Comput. Struct. 19, 865–877 (1984)], a comprehensive survey is provided for the formulation and solution techniques of finite element applications in nonlinear continuum mechanics problems. In this paper we extend the survey to cover incompressibility constraints and software aspects. Various methods of incorporating incompressibility constraints in the finite element formulation are discussed. The extension of these methods to account for nonlinear structural analysis is discussed. An emphasis is put on the numerical aspects of various techniques. In the software aspects, a discussion of various tools for solving nonlinear continuum mechanics problems is given. These are the general purpose programs, the special purpose programs, and the programming systems. A practical working practical example is outlined to aid in the assessment of various tools in view of specific problem requirements.     

A mosaic of Chu spaces and Channel Theory I: Category-theoretic concepts and tools

Chu Spaces and Channel Theory are well-established areas of investigation in the general context of category theory when applied to semantically-based information flow. In this Part I of a two-part work, we review a range of related concepts and examples showing how these methods can be applied to logic and computer science, including Formal Concept Analysis, distributed systems and ontology development. We also discuss spatial coarse-graining in relationship to information, and in this direction we establish some basic simplicial and categorical techniques which will supplement the other methods of this Part I when they are applied to characterise visual object identification and the inference of mereological (i.e. part-whole) complexity in Part II.     

浅议计算机专业课程教学中的形成性评价

计算机专业课程教学目的是让学生学会与课程相关操作与动手能力,教学目的决定了传统总结性评价教学模式对操作与动手能力评价的不足,提出将形成性评价运用到计算机专业课程教学中,把传授知识、培养能力和提高素质合为一体,促进三者协调发展。     

Human reliability analysis and optimization of manufacturing systems through Bayesian networks and human factors experiments: A case study in a flexible intermediate bulk container manufacturing plant

Human reliability analysis (HRA) and optimization in manufacturing systems are effective to reduce system failure. The purpose of this study is to examine the HRA and optimization through a Bayesian network (BN) model and human factors experiments (HFEs). This study was applied to a flexible intermediate bulk container manufacturing plant. The human physiological and psychological factors consisting of personal abilities of flexibility, coordination, memory, and attention were regarded as the only performance shaping factors in this study. With the BN model, the relationship between human factors and human errors was described qualitatively and the impact of the human factor on system failures was judged quantitatively. Then the workers’ abilities training with HFEs based on the fault diagnosis results was carried out. The total numbers of errors have been decreased by 69.06% and the system failure rate has been reduced significantly after training.     

基于几何结构失真模型的图像质量评价研究

客观图像质量评价研究的目的是设计一种和视觉感知保持一致,且适用于各种失真模型的质量评价方法. 传统的结构相似度量质量评价方法忽视了自然图像本身的特点,不能很好地评判某些失真类型图像. 本文根据人眼视觉系统(Human visual system, HVS)在感知图像质量过程中的特点,探索自然图像的本征几何结构特征, 考虑像素点的方向失真、幅度失真和方差失真,提出了一种新型的基于图像几何结构失真模型的完全参考质量评价方法. 在标准数据库上的实验结果表明,本文方法适用于所有失真模型图像数据的质量评价, 计算复杂度相对较低,得到的图像客观评价结果和主观评价方法具有更好的一致性, 能够很好地反映人眼对图像质量的主观感受.     

Comparative study on local and global strategies for confidence estimation in neural networks and extensions to improve their predictive power

The use of confidence estimation techniques on neural networks outputs plays an important role when these mathematical models are applied in many practical applications. In general, the method to provide confidence estimation is dependent on the neural network architecture, but traditionally, most popular prediction interval (PI) estimation methods are only valid under strong assumptions, which are rarely satisfied in practical real problems. In this paper, we present a comparative study of local and global strategies for PI calculations and propose novel methods in both approaches to improve the predictive power of multilayer perceptron and radial basis function neural network models when the data are heterogeneous, both in density and residual variance. We apply our methods and make comparisons in a variety of simulated and real problems.     

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications. Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.     

Influences on the use of observational methods by practitioners when identifying risk factors in physical work

Most observational methods for musculoskeletal disorder risk assessment have been developed by researchers to be applied in specific situations, and practitioners could find difficulties in their use in real-work conditions. The main objective of this study was to identify the factors which have an influence on how useful the observational techniques are perceived to be by practitioners and to what extent these factors influence their perception. A survey was conducted on practitioners regarding the problems normally encountered when implementing these methods, as well as the perceived overall utility of these techniques. The results show that practitioners place particular importance on the support the methods provide in making decisions regarding changes in work systems and how applicable they are to different types of jobs. The results of this study can serve as guide to researchers for the development of new assessment techniques that are more useful and applicable in real-work situations.     

红外模糊图像的无参考质量评价方法

图像质量评价是对图像处理算法的优劣给出合理的评估,在很多无法获取原始参考图像的应用场合中使用无参考质量评价方法。通过对红外图像结构分析得知图像所具有的不确定性往往是模糊性,而不是随机性,因此将模糊集理论中模糊熵的概念引入到红外图像质量评价中,提出一种针对红外模糊图像的无参考质量评价方法,并从算法的有效性、一致性和准确性三个方面进行比较分析。仿真实验结果表明,该方法具有计算复杂度低、运算速度快和主客观评价一致等特点,且在总体性能上优于均方误差(MSE)和峰值信噪比(PSNR)全参考图像质量评价方法。