• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.287-297
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• 2012

In order to prepare for the introduction of the E-Discovery system from the United States and to cope with some causable changes of legal systems, we propose a general E-Discovery process and essential tasks of the each phase. The proposed process model is designed by the analysis of well-known projects such as EDRM, The Sedona Conference, which are advanced research for the standardization of E-Discovery task procedures and for the supply of guidelines to hands-on workers. In addition, Machine Learning Algorithms, Open-source libraries for the Information Retrieval and Distributed Processing technologies based on the Hadoop for big data are introduced and its application methods on the E-Discovery work scenario are proposed. All this information will be useful to vendors or people willing to develop the E-Discovery service solution. Also, it is very helpful to company owners willing to rebuild their business process and it enables people who are about to face a major lawsuit to handle a situation effectively.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.4
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• pp.573-583
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• 2015

Objectives: This study was carried out to evaluate the effect of noise exposure and aging on changes in hearing threshold level and the relationship between age and noise. Materials: The author selected 274 male shipyard and assembly line workers as the noise exposed group and 582 males not exposed to noise as the general population group. Data were collected from five years of consecutive annual audiometric tests performed from 2008 to 2012. Results: In the general population and noise exposed groups, there was a reverse phenomenon that hearing threshold level for 2009 was lower than that of 2008, which seemed to be due to the learning effect, but from 2010 hearing threshold level increased. In the noise exposed group, the mean hearing threshold level in the left ear was significantly higher than that for right ear. In the general population group, the older was the age, the higher was the hearing threshold level, especially at 4000 Hz. In the general population and noise exposed groups, frequency, age group and noise exposure independently affected hearing threshold level, and there was no relationship between age and noise exposure. Over all frequencies, the change of hearing threshold level was larger in the noise exposed group than in the general population group. In the noise exposed group below thirty years old, the change at 4000 Hz was remarkable. Conclusions: Age and noise exposure seem to affect hearing threshold level independently and contribute to an additive effect on hearing threshold level.

• Journal of Korean Clinical Health Science
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• v.2 no.2
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• pp.126-132
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• 2014

Purpose. Because traditional statistics approach had limitations in learning future forecasting and major factors causing occupational injuries in each industry, this paper develops a model forecasting and evaluating occupational injury rate by using a system dynamics model through the analysis of the industry injury statistics and the project for industry injury prevention. Method. The model of this paper consists of 12 total models such as a model of employees, of industrial disaster victims, of injury rate, etc.; In the analysis of firm size, it is classified and developed according to 12 groups on the basis of the number of employees, and in the analysis of industrial classification, it is done according to 10 total business fields such as manufacturing business, construction one, etc. Results. This paper suggests the methodology which forecasts industry injury rate by business field and size on the basis of developed model, and evaluates an industry injury prevention project from various angles. Conclusions. This paper deduced problem through the analysis of an industry injury by business fields and a comparative analysis of foreign cases, and analyzed to affect industry injury prevention by industry. And it also analyzed actual condition of industry injury, and did a difference in the level of safety consciousness according to the general characteristics of workers and occupational safety and health education related characteristics. In result, this paper suggests that analyzing occupational injury related factors, a safety budgetary allocation, and industry injury related factors can reduce illness costs such as employees' injury and medical care, and also assist cost for a disability.

• Tunnel and Underground Space
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• v.13 no.1
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• pp.6-19
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• 2003

This study has for its object to increase an objectivity of the observation result in the face mapping of tunnel and to suggest the reasonable support and reinforcement methods to be considered the rock properties. It was developed in this study to the tunnel stability evaluation system(Prototype NFEST) to be used fuzzy set theory and neuro-fuzzy techniques, and this system was verified according to the reliability evaluation between the 36 learning data and the inferred results. When it summarized the results; (1) 12 evaluation items and ranges were proposed to be modified basis on the RMR which are well known to the domestic workers. (2) It was shown that correlation coefficient(│R│) between $RMR_{inf}$ inferred by 12 items and $RMR_{org}$ due to arithmetic total, $RMR_{chk}$ due to subjective judgement of observer are relatively high relationship with each 0.83 and 0.79. (3) Inferred result of the total tunnel safety shows also a good relationship with $RMR_{inf}$ (│R│=0.7) and the rock weathering(│R│=0.84).

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.191-200
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• 2013

This study set out to explore the human rights sensitivity of undergraduates who were in the social welfare classes with regards to socio-demographic factors, education experiences in human rights. 251 students' data were collected and analyzed with frequency, ANOVA. Analysis revealed that students' human rights sensitivity level was 2.70(moderate) and the respondents showed high level of sensitivity in work rights of emigration workers and education rights of handicapped children. Among demographic variables, human rights sensitivity was significantly different from major and experiences of attending a social welfare ethics. The students who majored social welfare and who had attended a social welfare ethics showed high human rights sensitivity. There were differences in human rights sensitivity level according to each episode. These findings highlight that in the education of social worker as a human rights professionals it would be necessary to respect students' rights in the classes and to provide student customized human rights education. It was suggested that learning human rights dilemma cases and self reflection processes in classes would be necessary to effective human rights education.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.24 no.2
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• pp.78-82
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• 2013

Child labor is being recognized as the key issue of human rights, and the International Labor Organization and the Convention on the Rights of the Child emphasize that children are individuals with dignity and rights. Male and female child actors belong to a profession with wide public exposure and there is a potential danger of invading classes and roles not matching the developmental stage of the child. In this study, we would like to discuss international and domestic laws and future complementary measures surrounding legal and institutional issues that need to be considered for child actors. Although the basic rights for child workers are stated in the Constitution Article 32 Paragraph 5 and Labor Standards Act Articles 64 through 70, they are insufficient. Following the revised broadcasting deliberation regulations by the Korea Communication Commission and amendment of the Juvenile Protection Law, several changes are taking place in the working environment. In certain foreign places such as California, United States, the economic and educational rights of male and female child actors are being protected. Although legal and institutional frameworks for the male and female child actors are being reinforced, more consistent devices are needed. Consideration for working hours, regulations to keep up with learning while working, and preparation for physical and emotional influences are required to keep up with international changes.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.1-29
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• 2013

This paper examines the effect of trade liberalization or globalization, more broadly, on plants' growth as well as on "bi-polarization". To do so, we reviewed the possible theoretical mechanisms put forward by recent heterogeneous firm trade theories, and provided available micro-evidence from existing empirical studies on Korean manufacturing sector. Above all, the empirical evidence provided in this paper strongly suggests that globalization promoted growth of Korean manufacturing plants. Specifically, evidence suggests that exporting not only increases within-plant productivity but also promotes introduction of new products and dropping of old products. However, the empirical evidence also suggest that globalization has some downsides: widening productivity differences across plants and rising wage inequality between skilled and unskilled workers. Specifically, trade liberalization widens the initial productivity differences among plants through learning from export market participation as well as through interactions between exporting and R&D, both of which increase plants' productivity. We also show that there is only a small group of large and productive "superstar" plants engaged in both R&D and exporting activity, which can fully utilize the potential benefits from globalization. Finally, we also show evidence that trade liberalization interacts with innovation to increase the skilled-unskilled wage inequality.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.56-65
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• 2015

The purpose of this study is to find out the possibility of the healing function of art museums in modern times with the precedent studies and to explore the healing potential specifically. There have been studies on the various healing programs regarding patients with Alzheimer, learning disability, seniors, etc. The researcher approached this study in three aspects, art appreciation, space, communication as healing potential of art museums. These findings will be able to draw more social attention on art museums. Therefore, this study will provide a new perspective on the art museums to people concerned art museums. And it will make the professionals, working for company workers, students and other people suffering under the modern stress, recognize the art museums as a place to look inside in the professionals' own mind and to heal as well as a place for culture and sophistication. These findings will be able to draw more social attention on art museums.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.435-442
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• 2017

The runway visual range affected by fog and so on is one of the important indicators to determine whether aircraft can take off and land at the airport or not. In the case of airports where transportation airplanes are operated, major weather forecasts including the runway visual range for local area have been released and provided to aviation workers for recognizing that. This paper proposes a runway visual range estimation model with a deep neural network applied recently to various fields such as image processing, speech recognition, natural language processing, etc. It is developed and implemented for estimating a runway visual range of local airport with a deep neural network. It utilizes the past actual weather observation data of the applied airfield for constituting the learning of the neural network. It can show comparatively the accurate estimation result when it compares the results with the existing observation data. The proposed model can be used to generate weather information on the airfield for which no other forecasting function is available.