• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1696-1707
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• 2019

This paper conducts a qualitative policy analysis of current challenges to safety culture and security culture in Southeast Asia and emerging best practices in Northeast Asia that are aimed at strengthening both cultures. It analyses lessons, including strengths and limitations, that can be derived from Northeast Asian states, given the long history of nuclear energy in South Korea, China and Japan. It identifies and examines best practices from Northeast Asia's Nuclear Security Centres of Excellence in terms of boosting nuclear security culture and their relevance for Southeast Asia. The paper accentuates the important role of the State in adopting policy and regulatory frameworks and in institutionalising nuclear education and training programmes to deepen the safety-security cultures. Best practices in and challenges to developing a nuclear safety culture and a security culture in East Asia are examined using three frameworks of analysis (i) a comprehensive nuclear policy framework; (ii) a proactive and independent regulatory body; and (iii) holistic nuclear education and training programmes. The paper argues that Southeast Asian states interested in harnessing nuclear energy and/or utilising radioactive sources for non-power applications must develop a comprehensive policy framework on developing safety and security cultures, a proactive regulatory body, and holistic nuclear training programmes that cover both technical and human factors. Such measures are crucial in order to mitigate human errors that may lead to radiological accidents and nuclear security crises. Key lessons from Japan, South Korea and China such as best practices and challenges can inform policy recommendations for Southeast Asia in enhancing safety-security cultures.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.469-476
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• 2020

Modeling and Simulation (M&S) systems which deal with situational complexity often require human involvement due to the high-level decision-making that is necessary for ship movement, navigation, control center management, shipping company logistics, meteorological system information, and maritime transportation GIS. In order to properly simulate maritime traffic, it is necessary to accurately model the human decision-making process of the ship officer, including aspects of the ship officer's behavioral tendencies, personal navigation experience, and pattern of voyage errors, as this is the most accurate way in which to reproduce and predict realistic maritime traffic conditions. In this paper, which looks at agent-based maritime traffic simulation, we created a basic survey in order to conduct behavior analysis on ship operators' collision avoidance strategies. Using the information gathered throughout the survey, we developed an agent-based navigational behavior model which attempts to capture the behavioral patterns of a ship officer during an instance of ship collision. These results could be used in the future in further developments for more advanced maritime traffic simulation.

• Safety and Health at Work
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• v.12 no.4
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• pp.496-504
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• 2021

Background: With the increasing demand for industrial robots and the "noncontact" trend, it is an appropriate point in time to examine whether risk assessments conducted for robot operations are performed effectively to identify and eliminate the risks of injury or harm to operators. This study discusses why robot accidents resulting in harm to operators occur repetitively despite implementing control measures and proposes corrective actions for risk assessments. Methods: This study collected 369 operator-injured robot accidents in Korea over the last decade and reconstructed them into the mechanism of injury, work being undertaken, and bodily location of the injury. Then, through the techniques of Systematic Cause Analysis Technique (SCAT) and Root Cause Analysis (RCA), this study analyzed the root and direct causes of robot accidents that had occurred. Causes identified included physical hazards and complex combinations of hazards, such as psychological, organizational, and systematic errors. The requirements of risk assessments regarding robot operations were examined, and three case studies of robot-involved tasks were investigated. The three assessments presented were: camera module processing, electrical discharge machining, and a panel-flipping robot installation. Results: After conducting RCA and comparing the three assessments, it was found that two-thirds of injury-occurring from robot accidents, causative factors included psychological and personal traits of robot operators. However, there were no evaluations of the identifications of personal aspects in the three assessment cases. Conclusion: Therefore, it was concluded that personal factors of operators, which had been overlooked in risk assessments so far, need to be included in future risk assessments on robot operations.

• Smart Media Journal
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• v.12 no.7
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• pp.59-67
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• 2023

Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.

• Journal of The Geomorphological Association of Korea
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• v.17 no.4
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• pp.41-52
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• 2010

Coastal lagoons(Ssangho, Gapyeongri wetland, Gunggaeho and Yeomgaeho) distribute densely around Osan-ri, Yangyang-gun. While Ssangho with the representative lagoon group in the East Coast has maintained the lagoon conditions of water surface since it was formed during the Climax of transgression, the others were formed at the swale areas of sand beach. They vary considerably in area reduction rates and position variations during the 20th century, and the causes examined can be divided into natural, human and other factors. They result in the lagoon aggradation stage by geomorphic development, reclamation due to rapid industrialization and urban development during the 20th century, and lacks of understanding on values of small coastal lagoon or errors in mapping and lags of survey techniques. Therefore, the plans for lagoon restorations should be proceeded by the individual properties of lagoons. The restorations of Ssangho are recommended preferentially and it is desirable to restore to the lagoon conditions of 1920s when the influences of human were minimum.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.371-380
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• 2023

Currently, as construction projects in Korea are becoming larger and more complex, the hazard rate of the construction industry is steadily increasing, contrary to other industries. This can be seen as an indication that the safety technology and safety consciousness of construction workers are insufficient compared to the improved construction technology. In addition, due to the characteristics of the construction industry based on manpower, most accidents appear in conventional forms such as fall and trip due to human errors. Therefore, analyzing the relationship between the characteristics of human resources and accidents and establishing detailed safety plans is an essential part of reducing construction accidents. In this study, a correlation analysis was conducted using 62,805 cases of construction accident cases over 3 years to derive the characteristics of accident occurrence focusing on the age of workers. As a result of the analysis, the relationship between the age of workers and the frequency and severity of accidents for each accident type was derived, focusing on the top 10 accident types.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.528-535
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• 2022

Although the domestic aviation industry has made rapid progress with the development of aircraft manufacturing and transportation technologies, aviation safety accidents continue to occur. The supervisory agency classifies hazards and risks based on risk-based aviation safety data, identifies safety trends for each air transportation operator, and conducts pre-inspections to prevent event and accidents. However, the human classification of data described in natural language format results in different results depending on knowledge, experience, and propensity, and it takes a considerable amount of time to understand and classify the meaning of the content. Therefore, in this journal, the fine-tuned KoBERT model was machine-learned over 5,000 data to predict the classification value of new data, showing 79.2% accuracy. In addition, some of the same result prediction and failed data for similar events were errors caused by human.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.17 no.2
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• pp.131-140
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• 2006

Objectives : This study was conducted to investigate the deficits of executive function in children with ADHD, Asperger's Disorder(AD), and teaming disorder (LD), and to identify the differential characteristics of executive function deficits among three groups. Methods : The clinical group consisted of 46 children between the ages of 7 and 15 (16 ADHD, 16 LD, 14 AD). Neuropsychological tests for measuring cognitive function, attention and executive function were individually administered to children, and their performance scores were calculated based on the age norm for each test. Results : There was no significant difference in FSIQ, VIQ, and PIQ among the three groups. However, the AD group tended to show higher scores on the subtests of Information, Vocabulary and Digit Span, and lower score on Comprehension subtest than the ADHD and LD groups, while the LD group tended to show the lowest scores on the Information and Vocabulary subtests. On ADS, the ADHD group showed the highest omission and commission errors. All groups showed poor performances belonging to below 25 percentile ranks on executive function tests when compared to the age norms of normative group. The number of completed category on WCST was the smallest in the ADHD group, while the working memory score was the lowest in the LD group. Conclusion : These results suggest that ADHD, LD, and AD children have executive function deficit in common. However, the specific deficit areas in executive function are different for each group.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.211-220
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• 2019

It helps to wisely abstain from errors of the a priori subjective emotions related to human emotions, and orders emotions to make rational choices. These emotional happiness of human and moral sensitivities work directly or indirectly in rational choice of rational thought and reason. Abraham would have been troubled by the divine mandate to sacrifice a son who was only one, and a son who had been healed. Was his reason reasonable at this time? In rational reason, it can be said that the act of dedicating his son is an appropriate act, but is it possible in the human mind? Aristoteles also called human virtue virtue in good for human beings. Because happiness is also a mental activity, we have to know a certain degree about the mind. This ψυχή(psyche, spirit) spirit is an irrational element that is invisible but an intervention in rational principles. Also C. G. Jung states that all human beings have four dynamic psychological functions that are not visible, and that the mind is driven by these four functional dimensions. This means that the elements of S, Sensing, N, Intuition, T, Thinking, and Feeling are combined. David Hume also emphasized the principle of empathy, asserting that morality can not be derived from reason, and Max Ferdinand Scheler, before grasping the visual characteristics of a person, has already captured the whole feeling of the person, And that the value given to this feeling is the value, and that the function of emotion that is elevated to the perceived object by grasping the value through this process and the value is always preceded by the reason. Emmanuel Levinas states that emotional emotions of love are ahead of reason and that emotions precede human reasoning and rationality is the inability of emotional control that we need rational thought and rational and wise action as reason of control and temperance. As part of human emotional education, in the 7th curriculum, Bloom's cognitive, perceptive, and behavioral domain, which is a person with integrated thinking, is trying to be a moral practitioner. It focuses on how to act according to the direction of emotions for virtuous acts and how to develop emotions for emotions on behalf of vicious acts. We can design the possibility and direction of cultivating human emotions and emotional happiness and happy sensitivities by the principle of strengthening virtue and the principle of elimination of ill feeling.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.