• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.2 s.51
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• pp.169-177
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• 2005

The propensity to purchase babies' cosmetics is investigated and analysed for this research. The synopsis of this research paper is as follows. The first, the $68\%$ of all respondents do not how a manufacturer or brand name in the reality of variously emerging domestic and import cosmetics for babies. The second, in case of a child haying a fair, sensitive skin or atopy (atopic dermatitis), the respondents are careful in choosing babies cosmetics but in case of a child having a normal skin the older a child grows from a stage of a new-born, a baby and an infant to a primary-school child, the older its mother is, the more respondents use adults' cosmetics in common rather than use cosmetics only for babies. $7.6\%$ of respondents do not use babies' cosmetirs at ail. Especially, in using bathing goods such as a shampoo or a body cleanser, they frequently use adults' cosmetics in common. The third, the qualify is taken into the utmost consideration in purchasing babies' cosmetics. The Quality of imports is trusted and preferred better than that of domestic goods. The cost of purchasing babies cosmetics is less than 10,000 Won. consumers recognize that the price or cosmetics is rather high. The last, the improvement or babies cosmetics is 'the safety of goods', answered by $56.5\%$ of respondents. The respondents are generally not satisfied with babies' cosmetics. So, a baby's skin is threatened by a newly-built house syndrome, the increase of atopic dermatitis, etc., caused by an environmental pollutions, a change of diet and a change of residential life. Under these actual conditions, babies' cosmetics which can protect a delicate and sensitive skin of a baby should be developed immediately. Consumers should have a correct choice with precise recognition and information on a baby's skin and cosmetics and continually use the efficacious and excellent babies' cosmetics to prevent a baby from a skin irritation, and need to show a keen interest in a healthy skin of a baby.

• Tuberculosis and Respiratory Diseases
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• v.61 no.1
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• pp.34-40
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• 2006

Background: Extubation failure was associated with poor prognosis and high hospital mortality. Cuff leak test (CLT) has been proposed as a relatively simple method for detecting laryngeal obstruction that predispose toward postextubation stridor (PES) and reintubation. We examined the risk factors of extubation failure and evaluated the usefulness and limitation of CLT for predicting PES and reintubation. Methods: Thirty-four consecutive patients intubated more than 24 hours were examined. The subjects were evaluated daily for extubation readiness, and CLT was performed prior to extubation. Several parameters in the extubation success and failure group were compared. The accuracy and limitation of CLT were evaluated after choosing the thresholds values of the cuff leak volume (CLV) and percentage (CLP). Results: Of the 34 patients studied, 6 (17.6%) developed extubation failure and 3 (8.8%) were accompanied by PES. The patients who had extubation failure were more likely to have a longer duration of intubation and more severe illness. The patients who developed PES had a smaller cuff leak than the others: according to the CLV ($22.5{\pm}23.8$ vs $233.3{\pm}147.1ml$, p=0.020) or CLP ($6.2{\pm}7.3$ vs $44.3{\pm}24.7%$, p=0.013). The best cut off values for the CLV and CLP were 50ml and 14.7%, respectively. The sensitivity, negative predictive value, and specificity of CLT were relatively high, but the positive predictive value was low. Conclusion: The likelihood of developing extubation failure increases with increasing severity of illness and duration of intubation. A low CLV or CLP (<50ml or 14.7%) is useful in identifying patients at risk of PES, but the CLT is not an absolute predictor and should not be used an indicator for delaying extubation.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.183-192
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• 2004

Even in Korea the number of steel structure buildings that allow internal space and easy change of their layouts in accordance with the purpose of buildings and box-type steel bridges constructed with thick plates with thickness in a rage just from a few $\beta$AE to \$100\beta$AE is increasing these days and therefore, domestic fabrication and processing technology of members for steel structures is being improved at a pace faster than in the past to meet the growing requirements of consumers for high reliability on quality control on the related steel structures. However, most domestic fabricators os steel structures who are turning out their steel products in accordance with the designs prepared by engineering companies in their respective works for the sake of cost cut more than anything else, hesitating to introduce any advanced new technology into themselves. In the case of the steel structure design application for small and mid-size buildings in particular, it is quite meaningful not only for those who are involved in steel structure business, but also for the people working at construction work fields to review the result of the study on the connections of steel structure members deigned to obtain superb quality of steel structures within short period for steel fabrication and erection at fields in economical ways, as there is a glowing tendency seeking standardization of connection of steel structure members as well as whole structure together with the development on design of construction system of buildings including their exterior and interior decoration materials, manufacture of the related members and fabrication technique structure. This paper has been prepared with the aim to review the peculiar characteristics of buildings constructed with the main frames of steel structures and actual cases of the change made ing the connections between steel structure columns and between columns and girder members in order to reduce the work period necessary for fabrication and erection of steel structures at the maximum as well as the some examples of steel structures fabricated through automatic welding by robots for box-type columns in addition to the description of the problems found in the course of fabricating those steel structures, suggesting possible counter-measures to solve them.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.181-188
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• 2022

Objectives: The prevalence of diabetes mellitus was approximately 16% in populations of over age 30 years, and deaths from diabetes mellitus became the sixth most prevalent cause of death by disease. To assess the relationship between HbA1c and heavy metal level in blood and urine, targeted residents were evaluated in a vast steel industrial complex. Methods: We selected 414 subjects for analysis after applying the following exclusion criterion: 18 persons with diabetes mellitus. They took part in a questionnaire survey and underwent blood and urinary assessments. HbA1c and lead (Pb) level were measured in blood and, cadmium (Cd), inorganic arsenic (iAs) and mercury (Hg) were evaluated in urine. Two subgroups were divided by HbA1c 6.5%. Each subgroup was divided by 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th and 90th percentile levels of biological exposure index of the heavy metals for logistic regression. Results: Odd ratios have a tendency to increase as they go from the 90th to the 10th percentile of cadmium. However, lead, arsenic and mercury did not have significant relationships with HbA1c. In correction of age, region, gender and smoking history, a higher distribution in the subgroup with cadmium above 0.8318 ㎍/g creatinine (30th percentile) was demonstrated in the subgroup with HbA1c levels above the 6.5%, with an odds ratio of 5.26 (95% C.I. ; 1.44~19.17). Conclusion: This study found a significant correlation between urinary levels of cadmium and HbA1c in correction of several factors. It is meaningful that this outcome may be used as a basis for a study to establish the acceptable limit of urinary cadmium in Korea.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Korean Journal of Culture and Social Issue
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• v.22 no.4
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• pp.595-622
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• 2016

This study aims to understand the process of family reunion of the ex-offenders. To this end, Korea Rehabilitation Agency under Ministry of Justice and Healthy Family Support Center conducted intensive interviews with ex-offenders, their families and with 8 counselors who are in charge of ex-offenders and their families' residential, psychological, and educational support. The data collected through the interviews were analyzed by Consensus Qualitative Research(COR). The followings are the results: the counselors found out that most of ex-offenders had experienced unhappy childhood which was lack of healthy relationship with their parents. Secondly, counselors noticed a common feature among the families of ex-offenders. The common feature was that they keep the fact that one of their parents was imprisoned to their children as a secret. Thirdly, through the data analysis, counselors could understand various factors that affect reunion of ex-offenders' families: the factors that helped successful reunion were ex-offenders' sense of responsibility, open and healthy communication among family members, and mutual understanding of being a good family member, whereas, irresponsible dependance to other family members, denier and avoidance from the family members against ex-offenders, and lost sense of being a family member were the factors that discouraged the reunion. It turned out that the kinds of crime that ex-offenders committed also affected family reunion. The processes of reunion were easier for those who served their time with fraud, embezzlement, whereas, it was much more challenging for those who served their time with rape, violence, or murder. Fourthly, counselors learned that "relaxation" is the key factor in the process of reunion of ex-offenders' families. They also emphasized that there should be thorough monitoring process before the intervention in the reunion process. This study contributes in terms of finding healthy ways of intervention with ex-offenders' families and developing programs that help ex-offenders to recover their relationship with their family.

• Knowledge Management Research
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• v.24 no.1
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• pp.245-271
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• 2023

The change to the data economy requires a new analysis beyond ordinary research in the management field. Data matching refers to a technique or processing method that combines data sets collected from different samples with the same population. In this study, statistical matching was performed using random hotdeck and Mahalanobis distance functions using 2020 Survey of Korea Venture Firms and 2020 Korea Innovation Survey datas. Among the variables used for statistical matching simulation, the industry and the number of workers were set to be completely consistent, and region, business power, listed market, and sales were set as common variables. Simulation verification was confirmed by mean test and kernel density. As a result of the analysis, it was confirmed that statistical matching was appropriate because there was a difference in the average test, but a similar pattern was shown in the kernel density. This result attempted to expand the spectrum of the research method by experimenting with a data matching research methodology that has not been sufficiently attempted in the management field, and suggests implications in terms of data utilization and diversity.