• 한국컴퓨터정보학회논문지
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• 제18권7호
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• pp.57-67
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• 2013

본 연구는 운용성 향상을 위하여 효율적이고, 체계적인 인적 요소 분석 방법을 제안한다. 시스템 개발의 출발점인 사용자의 요구사항 생성 및 관리, 설계반영에 중점을 두고 이를 활용할 수 있는 방법론을 제시함으로써 운용성 향상을 구현하기 위함이다. 이러한 목적을 달성하기 위하여 본 연구에서는 사례연구로 인에이블링 시스템 운용환경 설계를 위한 인적 요소 요구사항 아키텍처방법을 제시하고, 이를 기반으로 하여 인에이블링 시스템 인적요소 데이터베이스를 분석하고 구축하는 작업을 수행하였다. 최근 들어, 인에블링 시스템에 관한 인적 요소분석 및 설계반영의 필요성이 증대되고 있다. 인간공학 표준 및 가이드에서 제시하는 방법들을 정리하고, 분석하여 인에이블링 시스템 운용환경설계 검토를 수행하였다. 본 연구의 인에이블링 시스템 운용 환경 설계를 위한 인적요소 분석방법론을 통하여 체계 데이터베이스를 구축하고, 다양한 분야의 체계 개발에 활용될 수 있을 것으로 기대한다.

• 품질경영학회지
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• 제23권3호
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• pp.69-83
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• 1995

In a large number of literature on of inspection tasks, one of the most consistent findings is the existence of large and consistent differences among inspectors. It is possible that the individual difference is described by the difference of cognitive skills, because cognitive skills are required more than manual skills in inspection tasks. Therefore, a set of cognitive factors in human information processing may underly human performance in inspection tasks. In this study, a cognitive skill was described as the relative importance of the cognitive factors involved. A hierarchical task analysis and a fuzzy hierarchical analysis were used to represent how the importance of cognitive factors contribute to inspection performance. An experiment was conducted using the computer simulations of PCB inspection tasks. The results revealed that the subject group with better performance showed the importance weights of cognitive factors in the following rank; (attention, perception, judgement, classification, recognition)<(detection)$\ll$(memory). The results of the experiment can serve as a selection criterion for efficient inspection performance and the information of skilled learning for an inspection training program. The usefullness of a hierarchical task analysis and a fuzzy hierarchical task analysis for the analysis of cognitive tasks are also confirmed.

• 한국항해항만학회지
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• 제32권4호
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• pp.279-285
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• 2008

We have proposed modeling methods of mariners' standard behavior for collision avoidance by analyzing mariners' recognition process in a previous study. As a subsequent study, the aim of this study is to build a model of mariners' execution process which is one of six processes in the condition of collision avoidance. In this study, thus, the structure of mariners' information processing on the process of taking avoiding actions is described and the relation between mariners' behavior and necessary factors in the process is analyzed. And then we have built a model of mariners' standard behavior for execution process based on the characteristics of mariners in ship-handling, which are obtained from the international collaborative research on human factors. It is tried to define the contents of execution process based on the standard behavior of mariners for collision avoidance and to formulate information processing of mariners.

• Nuclear Engineering and Technology
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• 제45권2호
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• pp.151-164
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• 2013

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available - from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., "easy" vs. "somewhat difficult"), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented.

• 한국안전학회지
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• 제21권3호
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• pp.137-142
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• 2006

Quantification of error possibility, in an HRA process, should be performed so that the result of the qualitative analysis can be utilized in other areas in conjunction with overall safety estimation results. And also, the quantification is an essential process to analyze the error possibility in detail and to obtain countermeasures for the errors through screening procedures. In previous studies for the quantification of error possibility, nominal values were assigned by the experts' judgements and utilized as corresponding probabilities. The values assigned by experts' experiences and judgements, however, require verifications on their reliability. In this study, the validity of new error possibility values in new MCR design was verified by using the Onisawa's model which utilizes fuzzy linguistic values to estimate human error probabilities. With the model of error probabilities are represented as analyst's estimations and natural language expression instead of numerical values. As results, the experts' estimation values about error probabilities are well agreed to the existing error probability estimation model. Thus, it was concluded that the occurrence probabilities of errors derived from the human error analysis process can be assessed by nominal values suggested in the previous studies. It is also expected that our analysis method can supplement the conventional HRA method because the nominal values are based on the consideration of various influencing factors such as PSFs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.219-222
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• 2004

There are several factors that disturb an Ultra-Wideband (UWB) radio propagation in an indoor environment such as path loss, shadowing and multipath fading. These factors directly affect the quality of the received signal. In this paper, we investigated the influence of the human body shadowing on UWB propagation based on measured wireless channel in an anechoic chamber. The characteristics of the UWB channel including the transmitter and the receiver antenna effects are acquired over the frequency bandwidth of 3${\sim}$11 GHz. The major factors such as the power delay profile (PDP), the angular power distribution (APD), the pulse distortion and the RMS delay spread caused by the human body shadowing are presented.

• Nuclear Engineering and Technology
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• 제41권10호
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• pp.1361-1374
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• 2009

Due to the need of data for a Human Reliability Analysis (HRA), a number of data collection efforts have been undertaken in several different organizations. As a part of this effort, a human error analysis that focused on a set of simulator records on a Steam Generator Tube Rupture (SGTR) scenario was performed by using the Human Event Repository and Analysis (HERA) system. This paper summarizes the process and results of the HERA analysis, including discussions about the usability of the HERA system for a human error analysis of simulator data. Five simulated records of an SGTR scenario were analyzed with the HERA analysis process in order to scrutinize the causes and mechanisms of the human related events. From this study, the authors confirmed that the HERA was a serviceable system that can analyze human performance qualitatively from simulator data. It was possible to identify the human related events in the simulator data that affected the system safety not only negatively but also positively. It was also possible to scrutinize the Performance Shaping Factors (PSFs) and the relevant contributory factors with regard to each identified human event.

• 산업경영시스템학회지
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• 제23권54호
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• pp.167-177
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• 2000

The problem of system reliability is very important issue in the nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and quality loss. This paper therefore proposes a normalized scoring model by the qualitative factors order to evaluate the robust reliability of nuclear power plants under uncertainty. Especially, the qualitative factors including risk, functional, human error, and quality function factors for the robust justification has been also introduced. Finally, the analytical reliability and safety assessment model developed in this paper can be used in the real nuclear power plant.

• 한국멀티미디어학회논문지
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• 제21권4호
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• pp.478-484
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• 2018

The choice of the motion features influences the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of the human body, environment and video camera. So the accuracy of action recognition is restricted. On the bases of studying the representation and recognition of human actions, and giving fully consideration to the advantages and disadvantages of different features, the Dense Trajectories(DT) algorithm is a very classic algorithm in the field of behavior recognition feature extraction, but there are some defects in the use of optical flow images. In this paper, we will use the improved Dense Trajectories(iDT) algorithm to optimize and extract the optical flow features in the movement of human action, then we will combined with Support Vector Machine methods to identify human behavior, and use the image in the KTH database for training and testing.

• Safety and Health at Work
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• 제8권3호
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• pp.267-275
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• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.