• 전기의세계
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• v.20 no.3
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• pp.8-16
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• 1971

The proper design of man-machine systems requires as much understanding of the human element as of the machine. Although the modern systems engineer can obtain a very high degree of repeatability and accuracy for the characteristics of a machine, these of the human elements are much less well known. Due to the complexity and importance of modern man-machine systems, this difficult problem has recently received increasing attention. In this paper, the dynamic characteristics of the human operator have been newly determined by impulse estimation using Pseuo-random binnary signals as a test signal and the quasi-linear human operator models used as an element of a closed-loop control system adopted from McRuer & Krendel and Bekey. Also the techniques and instruments are presented for correlating the actual characteristics of the constructed system with anticipated theoretical values. Consequently, in spite of many problems remain yet, experimental results were very satisfactory.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.984-994
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• 2020

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.474-480
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• 2007

This paper presents an application of intelligent modeling method to manual control system with human operator. Human operator as a part of controller is difficult to be modeled because of changes in individual characteristics and operation environment. So in these situation, a fuzzy model developed relying on the expert's experiences or trial and error may not be acceptable. To supplement the fuzzy model block, a neural network based modeling error compensator is incorporated. The feasibility of the present fuzzy-neural modeling scheme has been investigated for the real human based target tracking system.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.349-354
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• 1996

SACOM(Simulation Analyser with Cognitive Operator Model) is being developed at Korea Atomic Energy Research Institute to simulate human operator's cognitive characteristics during the emergency situations of nuclear power plans. An operator model with error mechanisms has been developed and combined into SACOM to simulate human operator's cognitive information process based on the Rasmussen's decision ladder model. The operational logic for five different cognitive activities (Agents), operator's attentional control (Controller), short-term memory (Blackboard), and long-term memory (Knowledge Base) have been developed and implemented on blackboard architecture. A trial simulation with a scenario for emergency operation has been performed to verify the operational logic. It was found that the operator model with error mechanisms is suitable for the simulation of operator's cognitive behavior in emergency situation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1753-1758
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• 2005

Human Adaptive Mechatronics (HAM), which is a system concept to adapt human characteristics, has been proposed. As the HAM application, this paper addresses an information emphasis scheme to alert some hazards which are undetectable by a human operator. The emphasis scheme employs cognitive psychological approach to human discrimination characteristics because excess or deficient emphasis may disturb the operation. One of advantages of teleoperation system is able to include human valuable abilities as global environment recognition, planning, prediction and so on. To implement these abilities to mechanical system is difficult because of not enough intelligence. Proposed teleoperation system is designed to progress the human abilities, and moreover, to not disturb the abilities. In this paper, we consider that the discrimination characteristics depend on window positions on GUI display and operator's individuality. Finally, the efficiency of the alert scheme is verified by some experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.140-146
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• 2009

Since the computer technology has been drastically developed and broadly employed for the design of human machine system, human system interface was somehow digitalized. Actually the operator's working environment employing the digital devices are not be fully digitalized due to its technical constraints so that it has been changed to the hybrid environment which has a combination of digital and analog elements. The hybrid environments need to study its characteristics and the guidelines for the proper design and evaluation purpose. This paper describes the human factor design elements of the console operated under hybrid environment through studying the characteristics of digital and analog environment based on the related human factor guidelines and literatures. The result of this paper implies the contribution to the evaluation of the generic human working environment which digital and analog elements are jointly used.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1759-1764
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• 2005

Human Adaptive Mechatronics(HAM) is a new concept which was proposed in our university's research project sponsored by Japanese Ministry of Education, Sports, Culture, Science and Technology(MEXT), and is defined as "intelligent mechanical systems that adapt themselves to the user's skill under various environments, assist to improve the user's skill, and assist the human-machine system to achieve best performance". In this paper, the concept and key-items of HAM are mentioned. And the control strategy to realize a HAM human-machine system is explained in the case of physical-interface system, i.e. haptic system. The proposed assist-control of a force-feedback type haptic system includes online estimation of a operator's control characteristics, and a `force assist' function implemented as a change in the support ratio according to the identified skill level. We developed a HAM-haptic device test system, executed evaluation experiments with this apparatus, and analyzed the measured data. It was confirmed that the operator's skill could be estimated and that operator's performance was enhanced by the assist-control.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1554-1560
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• 2019

Development of digital main control rooms (MCRs) has greatly changed operating environments by altering operator tasks, and thus the unique characteristics of digital MCRs should be considered in terms of human reliability analysis. Digital MCR tasks can be divided into primary tasks that directly supply control input to the plant equipment, and secondary tasks that include interface management conducted via soft controls (SCs). Operator performance regarding these secondary tasks must be evaluated since such tasks did not exist in previous analog systems. In this paper, we analyzed SC-related tasks based on simulation data, and classified the error modes of the SCs following analysis of all operational tasks. Then, we defined the factors to be considered in human reliability analysis methods regarding the SCs; such factors are mainly related to interface management and computerized operator support systems. As these support systems function to reduce the number of secondary tasks required for SC, we conducted an assessment to evaluate the efficiency of one such support system. The results of this study may facilitate the development of training programs as well as help to optimize interface design to better reflect the interface management task characteristics of digitalized MCRs.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1271-1287
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• 2022

When abnormal operating conditions occur in nuclear power plants, operators must identify the occurrence cause and implement the necessary mitigation measures. Accordingly, the operator must rapidly and accurately analyze the symptom requirements of more than 200 abnormal scenarios from the trends of many variables to perform diagnostic tasks and implement mitigation actions rapidly. However, the probability of human error increases owing to the characteristics of the diagnostic tasks performed by the operator. Researches regarding diagnostic tasks based on Artificial Intelligence (AI) have been conducted recently to reduce the likelihood of human errors; however, reliability issues due to the black box characteristics of AI have been pointed out. Hence, the application of eXplainable Artificial Intelligence (XAI), which can provide AI diagnostic evidence for operators, is considered. In conclusion, the XAI to solve the reliability problem of AI is included in the AI-based diagnostic algorithm. A reliable intelligent diagnostic assistant based on a merged diagnostic algorithm, in the form of an operator support system, is developed, and includes an interface to efficiently inform operators.