• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1741-1744
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• 2005

In this paper, we proposed an adaptive skill element based on error signal. We assume that human progress their skills of actions based on errors, then an inverse dynamic of human motion have to changes. Human controller consists from feedback element (FB) and feed forward element (FF) and their elements cooperate to control actions. Under the assumption, we vary the connection of FF and FB by error signal. We propose the index function for change of a skill parameter. From results of the numerical simulations for the varying skill parameter with index function, we consider that the position error given by our vision changes the skill element and we confirm that the position error is the one of the estimate function for the improvement in our skill.

• Journal of Navigation and Port Research
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• v.42 no.3
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• pp.159-166
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• 2018

The identification of behavioral errors by seafarers that have caused marine accidents may provide important clues for the reduction or prevention of marine accidents. The purpose of this study is to identify the behavioral errors of seafarers by the type of marine accident using the theory of Skill-, Rule-, and Knowledge-Based Behavior (SRKBB). In order to identify behavioral errors, we collected the information related to 1,744 cases of maritime accidents over a 9 year period (2008 ~ 2016). The behavior errors of the seafarers who caused the marine accidents were classified as SBBE (Skill-Based Behavioral Error), RBBE (Rule-Based Behavioral Error), and KBBE (Knowledge-Based Behavioral Error). After analyzing the frequency of behavioral errors according to the type of marine accident, results showed SBBE had the highest frequency of errors, followed by RBBE. Additionally, the frequency of occurrence of accidents such as stranding, overturning, and sinking was high in KBBE. This study showed it is possible to identify behavioral errors of seafarers according to the type of marine accidents.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.21-31
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• 2020

There are two to three helicopter accidents every year in Korea, representing 5.7 deaths per 100,000 flights. In this study, an analysis was conducted on helicopter accidents that occurred in Korea from 2005 to 2017. The accident analysis was based on the aircraft accident and incident report published by the Aircraft and Railway Accident Investigation Board. This Research analyzed the characteristics of accidents occurring in Korea caused by human error by pilots. Accident analysis was done by classifying the organization, flight mission, aircraft class, flight stage, accident cause, etc. Pilot's huan error was classified as Skill-based error, decision error and perceptual error in accordance with the HFACS taxonomy. The accidents caused by pilot's human error were classified into five categories: powerlines collision, loss of control, fuel exhaustion, unstable approach to reservoir, and elimination of tail rotor.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.169-177
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• 2011

The aim of this study is to review previous studies on human errors in the service delivery processes. Service industry is sharply growing in the advanced countries. Many people are looking for something to contribute to the service industry. Although there are many research topics related to service domain that human factors and ergonomics specialists can do contribute, a few researchers are studying such topics. This paper indicated how previous researches on human factors and human errors have addressed the service domain, in order to prompt human factor study on the service domain. A variety of sources were inspected for literature reviews, including books and journals of managements, medicine, psychology, consumer behavior as well as human factor and ergonomics. The characteristics of human errors in the service domain were investigated. Human error studies in several service sectors were summarized such as medical service, automotive service operation, travel agent service and call center service. Until now, human factors community was not much interested in human errors in service domain. However, there is much space to contribute to service domain; human error identification, human error analysis and control of human error. The research of human error in service domain can provide clues to improve service quality. This paper helps to guide to identify human error of service domain and to design service systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.320-327
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• 2019

The purpose of this paper is to compare seafarers' behavior according to traffic conditions of a road and an onshore locations. Behaviors are classified into three categories: Skill-, Rule- and knowledge-based mode. Experimental data were collected using the questionnaires for navigators, working in a merchant ship. To compare the behaviors, we used the four analysis method; the degree of frequency, reliability test, correlation and linear regression. As a result of the study, it was found that Skill-based behavior shows more higher in the road traffic than the maritime traffic, and rule-based behavior shows more higher in the maritime traffic than the road traffic. Also, the behavior in the navigation situation showed statistical significance. Especially, in the case of Rule-based behavior, a high correlation between road and maritime was found. This study can be expected to apply to complementary system utilization between error management system of onshore and maritime traffic.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.259-268
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• 2017

Formal Safety Assessment (FSA) has been mostly implemented on the hardware aspects of vessels. Although there are guidelines regarding human error FSAs, there have not been many assessments in such areas. To this end, this study seeks to use precedent studies for the safe operation of DP vessels, conducting an FSA regarding human error of DP LOP (Loss of Position) incidents. For this, the study referred to precedent studies for the frequency of DP LOP incidents caused by human errors, adding the severity of LOP incidents, and then applying them to the Bayesian network. As a result, the study was able to confirm that among DP LOP incidents caused by human errors, the drive-off from skill-based errors was 74.3% and the drive-off from unsafe supervision was 50.5%. Based on such results, RCOs (Risk Control Options) were devised through a brainstorming session with experts coming up with proposals including providing mandatory DPO training, installing DP simulator on the vessels, drawing up measures to understanding the procedures for safe operation of DP vessels. Moreover, it was found that mandatory DPO training is reasonable in terms of cost benefits and that while installing a DP simulator is not suitable in terms of cost benefits, it can significantly reduce risks when operating DP vessels.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3628-3638
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• 2023

This paper uses 135 Licensed Operator Event Reports (LOER) from Chinese nuclear plants to analyze how safety culture affects unsafe behaviors in nuclear power plants. On the basis of a modified human factors analysis and classification system (HFACS) framework, structural equation model (SEM) is used to explore the relationship between latent variables at various levels. Correlation tests such as chi-square test are used to analyze the path from safety culture to unsafe behaviors. The role of latent error is clarified. The results show that the ratio of latent errors to active errors is 3.4:1. The key path linking safety culture weaknesses to unsafe behaviors is Organizational Processes → Inadequate Supervision → Physical/Technical Environment → Skill-based Errors. The most influential factors on the latent variables at each level in the HFACS framework are Organizational Processes, Inadequate Supervision, Physical Environment, and Skill-based Errors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.515-523
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• 2015

This study reviewed 612 DP LOP(Loss of Position) incident reports which submitted to IMCA from 2001~2010 and identified 103 human error caused incidents and classified it through HFACS. And, this study analysis of conditional probability of human error on DP LOP incidents through application of bayesian network. As a result, all 103 human error related DP LOP incidents were caused by unsafe acts, and among unsafe acts 70 incidents(68.0 %) were related to skill based error which are the largest proportion of human error causes. Among skill based error, 60(58.3%) incidents were involved inadvertent use of controls and 8(7.8%) incidents were involved omitted step in procedure. Also, 21(20.8%) incidents were involved improper maneuver because of decision error. Also this study identified that unsafe supervision(68%) is effected as the largest latent causes of unsafe acts through application to bayesian network. As a results, it is identified that combined analysis of HFACS and bayesian network are useful tool for human error analysis. Based on these results, this study suggest 9 recommendations such as polices, interpersonal interaction, training etc. to prevent and mitigate human errors during DP operations.

• Journal of the Korean Society of Safety
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• v.24 no.3
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• pp.71-78
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• 2009

During a learning process, a human being is assumed to experience knowledge-based behaviors, rule-based behaviors, and skill-based behaviors sequentially if Rasmussen was right. If any psycho-physiological symptom to those different levels can be obtained, it can be useful as a measure whether a human being is fully trained and has gotten a skill in his work. Therefore, this study aimed to draw relationships between human performance measures and psycho-physiological measures while committing a computer-simulated pointing task by utilizing the power spectrum technique of EEG data, especially with the ratio of relative beta-to-alpha band power. The result showed that, during correct responses, the ratio came to stabilize as all the performance data went stable. However, response time was not a simple linear function of task difficulty level only, but a joint function of task characteristics as well as behavior levels. Comparing relative band power ratios from errors and correct responses, activated states of one's brain could be explained, and characteristics of the task could understood. To tell that of pointing task, correlations around C3, C4, P3, P4 and 01, 02 area were significant and high in correct response cases whereas most correlation coefficients went down in error cases standing for imbalance of psycho-motor functions. Though task difficulty was the only one factor that could influence on relative band power ratio with statistical significance, it should be comprehended to mean a different way of expression indicating task characteristics since at least error-some situation could be explained with the help of relative band power ratio that absolute band power failed.