• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.3
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• pp.421-435
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• 2017

Recently, due to the saturation of ground structures and the overpopulation of pipeline facilities requires to development of underground structures as an alternative to ground structures. Thus, mechanized tunnel construction of the shield TBM method has been increasing in order to prevent vibration and noise problems in construction of the NATM tunnel for the urban infrastructure construction. Tunnel construction plan for the tunnel line should be formed in a sharp curve to avoid building foundation and underground structures and it is inevitable to develop a shield TBM technology that suits the sharp curve tunnel construction. Therefore, this study is about the structural stability technology of the articulation jack, shield jack and skin plate for the shield TBM thrust in case of the mechanized tunnel construction that is a straight and sharp curve line. The construction case study and shield TBM operation principle are examined and analyzed by the theoretical approach. The torque of the cutter head, the thrust of the articulation jack and the shield jack, the amount of over cutting for curve is important respectively in shield TBM construction of straight and sharp curve line. In addition, it is very important to secure the stability of the skin plate structure to ensure the safety of the inside worker. This study examines the general structure and construction of the equipment, experimental simulation was carried out through numerical analysis to examine the main factors and structural stability of the skin plate structure. The structural stability of the skin plate was evaluated and optimizes the shape by comparing the loads of the articulation jack by selecting the virtual soil to be applied in a straight and sharp curve line construction. Since the present structure and operation method of the shield TBM type in domestic constructions are very similar, this study will help to develop the localized shield TBM technology for the new equipment and the vulnerability and stability review.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.22-35
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• 2021

Recently, as the climate changes rapidly and the prevalence of airborne fine particulate matter increases, the pattern of pollutants in the atmospheric environment is also changing. Therefore, the importance of studying the stability of pigments used in colored cultural properties is emerging. Hoecheong is an inorganic blue glass pigment called smalt; it is made by using cobalt as a coloring element in potash glass, and was widely used in colored cultural assets, such as murals and paintings. In this study, we collected three other hoecheong pigments to analyze their properties. The percentage of Co and K contained are different according to the manufacturer, and the smalt-3 sample has a lower cobalt content (15.1 wt.%) and higher potassium content (29.6 wt.%). After this analysis, colored specimens were prepared. Prepared specimens were exposed to ultra-violet rays, CO₂/NO₂, and NaCl, which are known to have the greatest influence on the stability of pigments. We found that factors affecting the color stability were NO₂ gas, ultra-violet rays, and water-soluble salts (NaCl). Among them, NO₂ has the most severe impact on color change of the pigments. Results of the component analysis showed that the color change depends on the potassium and cobalt content of the hoecheong pigment. Among the specimens, smalt-3 showed the most vulnerability after exposure to NO₂ gas and water-soluble salts. Pigment film stability is affected by watersoluble salts, giving rise not only to color change, but also weakening the physical properties of the film. However, there was no significant change in composition and color after exposure to CO₂ gas. In conclusion, we found that hoecheong pigments underwent color change and increased instability of the coating film when exposed to any of the atmospheric environmental factors used in this study, except for CO₂.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Korean Journal of Health Psychology
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• v.14 no.2
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• pp.277-292
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• 2009

This study investigated the responses of the autonomic nervous system of individuals with Type D personality during an acute stressful situation. Twenty-three female students of Type D personality and 23 female students with non-Type D personality. Stroop Color-Word Task was used to induce a stressful situation, heart rate variability (HRV) was used to measure the responses of the autonomic nervous system during the baseline, acute stress, recovery periods. To analyze the data, the repeated measures analysis of variance was used to compare the autonomic nervous system of the Type D group to that of the non-Type D group. Regression analysis is used to determine if the Type D scale and stress vulnerability predicted the activities of the autonomic nervous system during the baseline period. The results of this study demonstrated that the Type D group's normalized low frequency (LF norm) and ratio of low frequency to high frequency (LF/HF ratio) were higher than those for the non-Type D group, while its normalized high frequency (HF norm) was lower than that for the non-Type D group in all three periods. There were no statistically significant differences among the three periods in terms of LF norm, HF norm, and LF/HF ratio in the Type D group. The study demonstrated that the total scores of the Type DS-14 and scores of social inhibition and negative affect were independent predictors of LF norm and HF norm during the baseline. The Type D group showed increased activation of the sympathetic nervous system and/or decreased activation of the parasympathetic nervous system. These results support the hypothesis that the Type D personality is vulnerable to the stress. Also, the highly activated sympathetic and/or lowly activated parasympathetic nervous systems, which were observed in the Type D group during the baseline, indicated that the Type D individual is susceptible to psychosomatic disorders.

• Journal of Environmental Impact Assessment
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• v.23 no.5
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• pp.379-392
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• 2014

This study was performed to predict the future climate envelope of Pinus pumila, a subalpine plant and a Climate-sensitive Biological Indicator Species (CBIS) of Korea. P. pumila is distributed at Mt. seorak in South Korea. Suitable habitat were predicted under two alternative RCPscenarios (IPCC AR5). The SDM used for future prediction was a Maxent model, and the total number of environmental variables for Maxent was 8. It was found that the distribution range of P. pumila in the South Korean was $38^{\circ}7^{\prime}8^{{\prime}{\prime}}N{\sim}38^{\circ}7^{\prime}14^{{\prime}{\prime}}N$ and $128^{\circ}28^{\prime}2^{{\prime}{\prime}}E{\sim}128^{\circ}27^{\prime}38^{{\prime}{\prime}}E$ and 1,586m~1,688m in altitude. The variables that contribute the most to define the climate envelope are altitude. Climate envelope simulation accuracy was evaluated using the ROC's AUC. The P. pumila model's 5-cv AUC was found to be 0.99966. which showed that model accuracy was very high. Under both the RCP4.5 and RCP8.5 scenarios, the climate envelope for P. pumila is predicted to decrease in South Korea. According to the results of the maxent model has been applied in the current climate, suitable habitat is $790.78km^2$. The suitable habitats, are distributed in the region of over 1,400m. Further, in comparison with the suitable habitat of applying RCP4.5 and RCP8.5 suitable habitat current, reduction of area RCP8.5 was greater than RCP4.5. Thus, climate change will affect the distribution of P. pumila. Therefore, governmental measures to conserve this species will be necessary. Additionally, for CBIS vulnerability analysis and studies using sampling techniques to monitor areas based on the outcomes of this study, future study designs should incorporate the use of climatic predictions derived from multiple GCMs, especially GCMs that were not the one used in this study. Furthermore, if environmental variables directly relevant to CBIS distribution other than climate variables, such as the Bioclim parameters, are ever identified, more accurate prediction than in this study will be possible.

• Journal of agricultural medicine and community health
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• v.36 no.4
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• pp.207-217
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• 2011

Objectives: The purpose of this study is to garner useful information through a comparative analysis of health behaviors and health states between the young-old and old-old elderly in a rural Korean area. Methods: We define the young-old elderly as those 65 to 74 years of age, and the old-old as those over 70. The survey was administered in October and November of 2009 at senior citizen centers in Sangju City, Kyongsangbuk-do, South Korea. The number of subjects surveyed approximated the demographics of the aged population of the administrative district of centers of 24 eup, myeon, and dong. Results: Compared with the young-old elderly, the old-old were vulnerable to population sociological characteristics. While there were many cases of contraction of diseases, only a small percentage of old-old elderly were engaged in regular exercise. In addition, the old-old elderly lagged behind the young-old in terms of physical activity, mental and oral health, hearing, and vision. Conclusions: The vulnerability of the old-old elderly in terms of physical and mental health needs to be acknowledged as various characteristics of the elderly that appears according an age group. A variety of disease prevention and health promotion programs that focus on the health behavior and status of the young-old and old-old elderly need to be developed and put into practice.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.