• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.589-597
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• 2020

The purpose of this study was to verify the acne care improvement effects of natural cosmetics with distilled bamboo vinegar contents and develop the materials for acne cosmetics. For the research subjects, 20 teenage boys and girls were selected and based on random number table, 10 subjects were assigned in the control group that used natural cosmetics (foam cleanser, toner, facial pack) and 10 subjects were assigned in the experimental group that used natural cosmetics with distilled bamboo vinegar contents (foam cleanser, toner, facial pack). The natural cosmetics was used for 12 weeks, and Mark-·Vu facial analysis system was used to measure the sebum, pore size, and redness before using the natural cosmetics, 6 weeks after using the natural cosmetics, and 12 weeks after using the natural cosmetics. For the collected data, SPSS v. 21.0 statistics package program was used for the analysis, and the results are as follows. First, it is a safe natural cosmetics based on the results of the patch test to confirm the skin safety of the natural cosmetics. Second, homogeneity was secured based on the results of the test of homogeneity for the sebum, pore size, and redness of the control group and experimental group. Third, in the verification of acne skin improvement effects of natural cosmetics with distilled bamboo vinegar content, the experimental group had higher reduction rate of changes in the sebum, pore size, and redness on the forehead and right cheek compared to the control group. Therefore, it was identified that the natural cosmetics with distilled bamboo liquid content is safe for the skin and effective for reducing the sebum, pore size, and redness for acne skin. For this reason, it is anticipated for distilled bamboo vinegar to be used in the cosmetics industry.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.64-79
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• 2023

This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.397-408
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• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.

• Journal of Korean Dental Science
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• v.16 no.2
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• pp.128-148
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• 2023

Dementia is an umbrella term that describes the loss of thinking, memory, attention, logical reasoning, and other mental abilities to the extent that it interferes with the activities of daily living. More than 50 million individuals worldwide live with dementia, which is expected to increase to 131 million by 2050. Recent research has shown that poor oral health increases the risk of dementia, while oral health declines with cognitive decline. In this narrative review, the literature was based on the "hypothesis" that dementia and oral health have a close relationship, and appropriate oral health and occlusal rehabilitation treatment can improve the quality of life of patients with dementia and prevent progression. We conducted a literature search in PubMed and Google Scholar databases, using the search terms "dementia," "major neurocognitive disorder," "dentition," "occlusion," "tooth loss," "dental prosthesis," "dental implant," and "occlusal rehabilitation" in the title field over the past 30 years. A total of 131 studies that scientifically addressed dementia, oral health, and/or oral rehabilitation were included. In a meta-analysis, the random effect model demonstrated significant tooth loss increasing the dementia risk 3.64-fold (pooled odds ratio=3.64, 95% confidence interval [2.50~5.32], P-value=0.0348). Tooth loss can be an important indicator of cognitive function decline. As the number of missing teeth increases, the risk of dementia increases. Loss of teeth can lead to a decrease in the ascending information to the brain and reduced masticatory ability, cerebral blood flow, and psychological atrophy. Oral microbiome dysbiosis and migration of key bacterial species to the brain can also cause dementia. Additionally, inflammation in the oral cavity affects the inflammatory response of the brain and the complete body. Conversely, proper oral hygiene management, the placement of dental implants or prostheses to replace lost teeth, and the restoration of masticatory function can inhibit symptom progression in patients with dementia. Therefore, improving oral health can prevent dementia progression and improve the quality of life of patients.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Journal of Preventive Medicine and Public Health
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• v.22 no.1 s.25
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• pp.29-44
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• 1989

A household survey was conducted to determine the utilization rate of medical facilities and to identify the factors related with the utilization in the South District of Taegu from July 3 to July 15, 1988. Study population included 1,723 family members of 431 households which were selected by one-stage simple cluster random sampling. Well trained medical college students interviewed mainly housewives with a structurized questionnaire. Morbidity rate of acute illness during the 2-week period was 101 per 1,000 persons and it was highest in the age group of 9 years below. The rate for chronic illness was 77 per 1,000 persons, increasing with age, low income and medicaid benefit. During the 2-week period, 689 of 1,000 persons utilized the medical facilities. Of the facilities, most number, 294, used hospital and clinic, and the order ran as pharmacy, health center, and herb medical clinic. The utilization rate was higher in the female, 70-year and older group, medicaid group, the lowest income class and self-employed group than other groups. The average number of visits among users of medical facilities during the 2-week period was 3.25. those who visited medical facilities most frequently were females, the 70-year and older group, the lowest income class and blue collar worker group. During one-year period, admission rate of 1,000 persons was 27.6 and that of female was 38.9, higher than that of male. the eldest group had the highest admission rate. Admission rate of medical insurance beneficiaries was twice or higher than non-beneficiaries. The higher the family monthly income, the more frequently they admitted. During one-year period, average admission days of the persons hospitalized were 22.5 days and males were hospitalized longer than females. The groups which were hospitalized longest were those between the ages of 40 and 49, medical insurance beneficiaries, the lowest income group and unemployed group. During one-year period, average admission days of 1,000 persons were 560 days and those of female were 661 days, more than those of male. The guoups which had the longest admission days were those above 70 years of age, the lowest income and unemployed groups. The medical insurance beneficiaries were three times or longer than non-beneficiaries. In logistic regression analysis of utilization of physician significant independent variables were the 9-year and younger group(+), the 70-year and older group(+), acute illness episode(+), chronic illness episode(+), medical insurance beneficiary(+) and white collar workers(-). Acute and chronic illness episode(+), and medical insurance for government employees and private school teacher(-) were significant variables in analysis of utilization of pharmacy. In multiple regression analysis of the number of physician visits, siginificant variables were acute illnes episode(+), chronic illness episode(+), industrial, occupational and regional medical insurance beneficiary(+), white collar workers(-). Acute and chronic illness episode(+), and medical insurance beneficiary(-) were significant variables in analysis of the number of pharmacy visits. In logistic regression analysis of admission event, significant independent variables were the 9-year and younger group(+), the 70-year and older group(+) , chronic illness episode(+), and medical insurance beneficiary(+).

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.1-19
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• 2007

1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.