• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1420-1427
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• 2023

Seismic risk has received increased attention since the 2011 Fukushima accident in Japan. The seismic risk of a nuclear power plant is evaluated via seismic probabilistic safety assessment (PSA), for which several methods are available. Recently, the discrete approach has become widely used. This approximates the seismic risk by discretizing the ground motion level interval into a small number of subintervals with the expectation of providing a conservative result. The present study examines the effect of the number of subintervals upon the results of seismic risk quantification. It is demonstrated that a small number of subintervals may lead to either an underestimation or overestimation of the seismic risk depending on the ground motion level. The present paper also provides a method for finding the boundaries between overestimation and underestimation regions, and illustrates the effect of the number of subintervals upon the seismic risk evaluation with an example. By providing a method for determining the effect of a small number of subintervals upon the results of seismic risk quantification, the present study will assist seismic PSA analysts to determine the appropriate number of subintervals and to better understand seismic risk quantification.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.141-146
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• 2024

Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

• Nutrition Research and Practice
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• v.8 no.2
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• pp.213-219
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• 2014

BACKGROUND/OBJECTIVES: There is little information on the association between weight misperception and eating behavior in Korean adolescents. Therefore, we investigated the association of food intake habits and dieting method and disturbed eating behavior (DEB) in relation to weight misperception. SUBJECTS/METHODS: Data was collected by using a nationwide online panel survey from 6,943 adolescents enrolled in middle/high school. DEB was measured with the Eating Attitudes Test (EAT-26) and those who scored ${\geq}20$ on the EAT-26 were considered to have eating disorder. Logistic regressions were conducted to examine the association between weight misperception based on self-reported weight status and dieting method and eating behaviors. RESULTS: The proportion of weight underestimation was 23.5% and that of overestimation was 24.0%. Weight overestimating girls were more likely to engage in various unhealthy dieting practices (OR = 1.69 for fasting; OR = 1.88 for laxative or diuretic use; OR = 2.05 for self-induced vomiting after meals; P < 0.05). Moreover, there was a strong association between overestimation and undesirable eating behaviors, especially among girls, e.g.: having breakfast (OR = 0.85), high consumption of fast foods (OR = 1.28) and regular sodas (OR = 1.39), but not among boys. In both genders, weight overestimation appears to be a major risk factor for DEB (OR = 1.34 for boys and OR = 1.41 for girls; P < 0.05). CONSLUSIONS: Weight overestimation is associated with unhealthy weight control practices and eating behaviors. We particularly found a significant association between weight overestimation and DEB among nationwide Korean adolescents.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.139-148
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• 2022

We attempted to determine how adolescents' general characteristics, appearance stress, and anxiety affect adolescents' body image distortion using data from the 16th Korea Youth Risk Behavior Survey. We confirmed Body image distortion in 38.2% of the subjects, and the results of underestimated body image in 19.9% and overestimation in 18.3%. Appearance stress and anxiety were found to have an effect in both underestimate and overestimate groups. We confirmed that demographic characteristics such as gender, economic level, and academic level influence different aspects in the underestimation and overestimation groups. Therefore, we suggested that comprehensive evaluation by subdividing the subjective perception of adolescents' weight into cases of overestimation and underestimation will be an important factor in determining mental health and weight control behavior in the future.

• Architectural research
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• v.21 no.2
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• pp.49-57
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• 2019

Risk assessment during pre-construction phase is important due to the uncertainty of the risks that may exist in projects. Risk checklist is a method to systematically classify and organize the risks that have been experienced in the past, and to identify the risk factors that may be present in the future projects. In addition, risk value assessment based on checklists plays a key role in risk management, and various risk assessment researches have been conducted to carry out this systematically. However, previous approaches have limitations in common, this is because risk values are evaluated individually in risk checklists, which ignore interdependencies among risk factors and neglect the emergence of co-occurrence of risks. Hence, when multiple risk factors cooccur, they cannot be far off from the conventional method of summing the total risk value to establish the risk response strategy. Most of risk factors are interdependent and may have multiple effects if occurred than expected. In particular, specific cause can be overlapped if multiple risks co-occur, and this may result in overestimation of the risk response for the future project. Thus, the objective of this research is to propose a model to help decision makers to quantify the risk value reflecting the interdependency during the identification phase using existing risk checklist that is currently being practiced in actual construction projects. The proposed model will provide the guideline to support the prediction and identification of the interdependency of risks in practice. In addition, the better understanding and prediction of the exceeding risk response by co-occurring risks during the risk identification phase for decision makers.

• Architectural research
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• v.15 no.3
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• pp.151-158
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• 2013

Offshore oil and gas process plants are exposed to hazardous accidents such as explosion and fire, so that the structural components should resist such accidental loads. Given the possibilities of thousands of different scenarios for the occurrence of an accidental hazard, the best way to predict a reasonable size of a specific accidental load would be the employment of a probabilistic approach. Having the fact that a specific procedure for probabilistic accidental hazard analysis has not yet been established especially for explosion and fire hazards, it is widely accepted that engineers usually take simple and conservative figures in assuming uncertainties inherent in the procedure, resulting either in underestimation or more likely in overestimation in the topside structural design for offshore plants. The variation in the results of a probabilistic approach is determined by the assumptions accepted in the procedures of explosion probability computation, explosion analysis, and structural analysis. A design overpressure load for a sample offshore plant is determined according to the proposed probabilistic approach in this study. CFD analysis results using a Flame Acceleration Simulator, FLACS_v9.1, are utilized to create an overpressure hazard curve. Moreover, the negative impulse and frequency contents of a blast wave are considerably influencing structural responses, but those are completely ignored in a widely used triangular form of blast wave. An idealistic blast wave profile deploying both negative and positive pulses is proposed in this study. A topside process module and piperack with blast wall are 3D FE modeled for structural analysis using LS-DYNA. Three different types of blast wave profiles are applied, two of typical triangular forms having different impulse and the proposed load profile. In conclusion, it is found that a typical triangular blast load leads to overestimation in structural design.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.33-55
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• 2007

The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

• The Journal of Korean Society for School & Community Health Education
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• v.22 no.4
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• pp.49-60
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• 2021

Objectives: Laboratories have various latent physical, chemical, biological, and ergonomical factors according to the diversification and fusion of research and development activities. This study aims to investigate the chemical exposure concentrations of college laboratories and evaluate their health risks, and use them as basic data to promote the health of college students. Methods: The sampling and analysis of harmful chemicals in the air in laboratories were performed using Method 1500 of the U.S. National Institute for Occupational Safety and Health (NIOSH)의 Method 1500. The harmful chemicals in the laboratories were divided into carcinogenic and non-carcinogenic chemicals. Risk assessment was performed using the cancer risk (CR) for carcinogenic chemicals and using the hazard index (HI) for non-carcinogenic chemicals. Results: The harmful chemicals in college laboratories consisted of acetone, diethyl ether, methylene chloride, n-hexane, ethyl acetate, chloroform, tetrahydrofuran, toluene, and xylenes. They showed the highest concentrations in laboratories A (acetone 0.001~2.34ppm), B (chloroform 0.95~6.35ppm), C (diethyl ether 0.08~8.68ppm), and D (acetone 0.07~14.96ppm). The risk assessment result for non-carcinogenic chemicals showed that the HI of methylene chloride was 2.052 for men and 2.333 for women, the HI of N-hexane was 4.442 for men and 5.05 for women. Thus, the HI values were higher than 1. The risk of carcinogenic chemicals is determined by an excess cancer risk (ECR) value of 1.0×10^-5, which means that one in 100,000 people has a cancer risk. The ECRs of chloroform exceeded 1.0×10^-5 for both men and women, indicating the possibility of cancer risk. Conclusion: College laboratories showed the possibility of non-carcinogenic health risks for methylene chloride, n-hexane, tetrahydrofuran (THF), toluene, and xylenes, and carcinogenic health risks for chloroform, methylene chloride. However, this study used the maximum values of measurements to determine the worst case, and assumed that the subjects were exposed to the corresponding concentrations continuously for 8 hours per day for 300 days per year. In consideration of the nature of laboratory environment in which people are intermittently exposed, rather than continuously, to the chemicals, the results of this study has an element of overestimation.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.144-156
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• 2018

Level 3 Probabilistic Safety Assessment (PSA) is performed for the risk assessment that calculates radioactive material dispersion to the environment. This risk assessment is performed with a tool of MELCOR Accident Consequence Code System (MACCS2 or WinMACCS). For the off-site consequence analysis of multi-unit nuclear power plant (NPP) accident, the single location (Center Of Mass, COM) method has been usually adopted with the assumption that all the NPPs in the nuclear site are located at the same COM point. It was well known that this COM calculation can lead to underestimated or overestimated radionuclide concentration. In order to overcome this underestimation or overestimation of radionuclide concentrations in the COM method, Multiple Location (ML) method was developed in this study. The radionuclide concentrations for the individual NPPs are separately calculated, and they are summed at every location in the nuclear site by the post-processing of radionuclide concentrations that is based on two-dimensional Gaussian Plume equations. In order to demonstrate the efficiency of the ML method, radionuclide concentrations were calculated for the six-unit NPP site, radionuclide concentrations of the ML method were compared with those by COM method. This comparison was performed for conditions of constant weather, yearly weather in Korea, and four seasons, and the results were discussed. This new ML method (1) improves accuracy of radionuclide concentrations when multi-unit NPP accident occurs, (2) calculates realistic atmospheric dispersion of radionuclides under various weather conditions, and finally (3) supports off-site emergency plan optimization. It is recommended that this new method be applied to the risk assessment of multi-unit NPP accident. This new method drastically improves the accuracy of radionuclide concentrations at the locations adjacent to or very close to NPPs. This ML method has a great strength over the COM method when people live near nuclear site, since it provides accurate radionuclide concentrations or radiation doses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.