• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of agricultural medicine and community health
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• v.26 no.2
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• pp.133-146
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• 2001

The purpose of this study was to investigate the treatment status and its related factors of the newly detected rural hypertensives through community health promotion program. A questionnaire survey and blood pressure measurement were performed to 6,977 residents of a rural area, and 282 hypertensives detected by blood pressure measurement were selected as subjects of the study. The study employed the health belief model as a hypothetical model. The major results of this study were as follows: The proportion of person experienced treatment among hypertensives was 12.0%. Treatment experience rate was significantly related with age and educational level(p<0.01). That is, if they were older, lower educational level, the treatment experience rate was higher. The major reasons of no treatment were 'they had not hypertensive symptoms ' (45.6%), 'their blood pressure was not high so much that they received treatment ' (43.2%). The chief facilities for treatment were public health institutions(57.9%) such as health center and health subcenter, and hospital/ clinics(29.8%). The treatment experience rate was higher when they had higher perceived severity for hypertension, lower perceived barrier to treatment, although statistically not significant. Treatment experience rate was significantly related with cues to action and health education experience(p<0.05). That is, if they had hypertension related symptoms such as headache previously, patients suffered from hypertension complication and health education experience for hypertension, the treatment experience rate was higher. In multiple logistic regression analysis for treatment experience, having a cerebrovascular patient in their acquaintance and the experience of health education for hypertension were significant variables. On consideration of above findings, it would to be essential to provide knowledge about hypertension and its treatment, and severity of hypertension complications through health education.

• Journal of dental hygiene science
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• v.9 no.1
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• pp.99-108
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• 2009

The purpose of this study was to investigate the effect of oral health education practice and schoolteacher's self-efficacy on oral health attitude. The data of 217 dental hygienists was subjected to path analysis using AMOS 16.0. Oral health knowledge, attitude, self-efficacy and oral health education practice of schoolteacher were measurement variables of three path models. The goodness of fitness of Knowledge-Attitude-Practice model and Knowledge-Attitude-Self efficacy -Practice model were acceptable. The regression weights of two models were statistically significant. Oral health education practice of schoolteacher gave impact on oral health attitude by mediation of self-efficacy of schoolteacher. Self-efficacy of schoolteacher was a important determinant of oral health education practice. Oral health attitude and practice were supposed to be mutual determinants of health behavior models.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.1
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• pp.23-32
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• 1994

To determine the apparent equilibrium constants, K$_{ad,app}$, for the adsorption reactions of trace metals on amorphous iron oxyhydroxide (AIO) in the Taebag coal mine area, time-adsorption and pH-adsorption experiments were performed for a selected bottom sediment mainly comprised of AIO from the study area. The results from the adsorption experiments indicate that most of the trace metals, except Pb, achieve equilibrium states with AIO and thus, the calculated K$_{ad,app}$ may represent the true apparent equilibrium constants. K$_{ad,app}$ and the stoichiometric coefficients of proton, x, of the adsorption reactions between the trace metals and AIO were respectively calculated from the intercepts and slopes of the regression lines of log($\Gamma$/ ［M］$_{aq}$)against pH provided by pH-adsorption experiments. The calculated K$_{ad,app}$ this study has the values of the range from 10$^{－4.5}$ to 10$^{2.75}$ , which is much different from the reported values by other investigators for simple experimental systems. K$_{ad,app}$ of this study is more or less close but not exactly pertinent to the estimated values for the other natural systems. It indicates that K$_{ad,app}$ for the adsorption reactions in the aquatic system in the study area is unique and thus should be determined befor the adsorption modelling. The calculated x of this study has the values of the range from -0.3 to 0.7, which is also much different from what most geochemists generally accept. The discrepancy in x may be due to the competition among different kinds of ionic species on the adsorption site or simulataneous occurrence of different kinds of adsorption reactions. The results from this study should help construct an appropriate adsorption model for the aquatic systems polluted by the coal mine drainage in the Taebag area. With the constructed model, one can describe the concentration variations of trace metals due to the adsorption in the system, which is an essential part of the investigation on the water quality affected by coal mine drainage in the Taebag coal field.

• Journal of the korean academy of Pediatric Dentistry
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• v.34 no.2
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• pp.215-221
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• 2007

The aim of this study was to test whether metric measurements of crown length, root length and apex width during tooth development could be a better basis for correlation with age than the classical methods based on subjective estimations of various stages of tooth development. Panoramic radiographs of 120 children, aged 7 to 9 years, were collected from the department of the pediatric dentistry of Chonnam National University Hospital, Korea. The methods of Mornstad was used to estimate age. The structures measured were crown length root length and apex width in panoramic radiographic. The results were as follows : 1. In the boys, it showed higher correlation between lower 2nd molar crown length, lower 1st molar root length or lower 1st permolar apical width and age. In the girls, it showed higher correlation between lower 2nd premolar crown length, lower 2nd molar root length or lower 1st molar apical width and age. 2. With the aid of a multiple regression model, a linear relationship between some of these distances and age was shown. Boy(months) = 43.958 + lower 2nd molar crown length ${\times}$ 4.392 + lower 1st molar root length ${\times}$ 2.255 - lower 1st permolar apical width ${\times}$ 2.046, Girl(months) = 75.213 + lower 2nd premolar crown length ${\times}$ 3.910 lower 2nd molar root length ${\times}$ 2.280 - lower 1st molar apical width ${\times}$ 6.217 Age was estimated in boys and girls using the mathematic model ; the mean difference between chronological and estimated ages was $-2.1{\pm}6.8$ months for boys and $6.1{\pm}6.2$ months for girls. Therefore, it seems to be more accurate and easier than the earlier methods.

• Korea journal of population studies
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• v.26 no.1
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• pp.31-57
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• 2003

This study is intended to examine (l)whether the value of son-for example, old age security and succession of family lineage- causing son preference in the traditional society can be explained at the individual level, (2)whether women without son in the son preference country continue her childbearing until having at least one son or give up the desire of having a son at a certain level. To accomplish these purposes, the 1974 Korean National Fertility Survey data are analyzed by the quadratic hazard models controlling unobserved heterogeneity. Unlike ordinary regression model, even omitted variables that affect hazard rates and are uncorrelated with the included independent variables can distort the parameter estimates in the hazard model. Therefore the nonparametric maximum likelihood estimator(NPMLE) of a mixing distribution developed by Heckman and Singer is used to control unobserved heterogeneity. Based on the statistical result in this study, the value of son causing son preference is determined at the societal level, not at the individual level. And Korean women without a son did not continue endlessly childbearing during child bearing ages until having a son. In general, they gave up the desire having a son when she had born six daughters continuously. Thus, 30-40 years ago, the number of daughters that women without a son giving up the desire of son was six, which is about the level of total fertility rate during 1960s. In these days, we can often see many women who have only two or three daughters and do not any son. This means that the level of giving up the desire of son, which is one factor representing the strength of son preference, becomes lower. If the strength of son preference did not become much weaker, then the fertility rates in Korea could not reach the below replacement level.

• Korean Journal of Social Welfare
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• v.57 no.3
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• pp.51-72
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• 2005

The purpose of this article is to empirically testify three hypotheses on the relation between married women's employment and the allocation of unpaid domestic work within households - i.e., adaptive partnership (AP), dual burden (DB) and lagged adaptation (LA) models. The AP hypothesis assumes that, when wives are employed, husbands spend more time doing housework in order to compensate for their wives' increased responsibility. The DB model, by contrast, indicates that, even if married women are employed, their burden on domestic work does not decrease. In this case, therefore, the dual burden of married women can be expected. Between these two opposite views, the third, alternative hypothesis has been suggested recently. The LA model argues that the behaviours of households are adaptive to the changing environments but over a period of many years and even across generations. The article has analysed the total work time as well as unpaid domestic work time to testify these three hypotheses, utilising 1999 Time Use Survey data of the National Statistical Office. The research results can be summarised as follows. First, married working women worked 100 minutes more than their male spouses. Second, the average domestic work time of married men, 23-25 minutes per day, was no more than 5-10% of that of women. Third, the effects of age and women's employment were not statistically significant in multiple regression models, which means that the DB hypothesis explains the situation of married working women in Korea. Based on these findings, the article suggested the expansion of the public social service system to mitigate the dual burden of married working women, the introduction of compensatory credit for caring work, and the directions of further empirical research using the time use survey data.

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.414-420
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• 2020

This study was carried out to investigate the growth characteristics of standard chrysanthemum 'Baekma', such as fresh weight, dry weight, and leaf area and to develop prediction models for the production greenhouse based on the growth parameters and climatic elements. Sigmoid regressions models for the prediction of growth parameters in terms of dry weight and leaf area were analyzed according to the number of the day after transplanting and the accumulate temperature during this experimental period. The relative growth rate (RGR) of the chrysanthemum was 0.084 g·g^-1·d^-1 on average during the period.The dry weight and leaf area of 'Beakma' increased exponentially according to the number of day after transplanting and the accumulated temperature, in the case of dry weight increased by an average of 39.1% until 63 days (accumulated temperature of 1601℃), after that dry weight increased by an average of 7.4% before harvest. The leaf area increased by an average of 63.3% until the 28th day after transplanting, and by an average of 6.5% until the 84th day before flower bud differentiation occurred, and increased by an average of 10.6% before harvest. This experiment can be used as a useful data for establishing a cultivation management system and a planned year-round production system for standard chrysanthemum "Baekma". To make a more precise growth prediction model, it will need to be corrected and verified based on various weather data including accumulated irradiation.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.3
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• pp.175-189
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• 2020

While there have been many previous studies showing that an entrepreneur's personal characteristics have a significant impact on his intention to start a business, there was relatively little research on the inherent mechanisms for this. Recent researches show that entrepreneur's personal characteristics affect the entrepreneurial intention through entrepreneurial attitude and perceived behavioral control, rather than directly. This study carried out empirical research on 233 Chinese university students on what personal characteristics affect the entrepreneurial intention of Chinese university students, who are actively engaged in start-up activities recently. Based on the theory of planned behavior, we set entrepreneurial attitude and perceived behavioral control as important variables that shape the entrepreneurial intention and formed a model and hypotheses that personal characteristics of a potential entrepreneur(leadership, planning, innovation, sociality) affect the entrepreneurial intention through these two variables. We verified these hypotheses by regression analysis and structural equation model. The analysis confirmed that for Chinese university students the entrepreneurial attitude and perceived behavioral control were important antecedent variables that shape the entrepreneurial intention. It was also shown that leadership and innovation have a positive influence on the entrepreneurial attitude, while leadership and planning raise the level of perceived behavioral control. As a result, leadership forms the entrepreneurial intention through the entrepreneurial attitude and perceived behavior control, and innovation affects the entrepreneurial intention through the entrepreneurial attitude, while planning affects the entrepreneurial intention through perceived behavior control. Therefore, entrepreneurship education that emphasizes leadership, innovation and planning is required for Chinese college students as a potential entrepreneur. These three factors could also be important personal characteristics when choosing a potential entrepreneur.