• Journal of Preventive Medicine and Public Health
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• v.57 no.4
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• pp.399-406
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• 2024

Objectives: This study developed a causal relationship model of herb use from observational data and analyzed the direct and indirect effects of herb use on health according to the model. Methods: A cross-sectional study was conducted with 400 participants aged 26-59 years, selected through multistage random sampling. The instruments used for data collection included demographic information, herb use, health literacy (HL), perceived social support, societal values, and attitudes toward herb use. The conceptual model, hypothesized based on prior evidence, was tested using confirmatory factor analysis through structural equation modeling. Path coefficients were estimated using the maximum likelihood method. Results: The final model utilized empirical data, which showed that perceived social support had the most significant impact on herb use. This was followed by HL, positive attitudes toward herbal remedies, and societal values, with coefficients of 0.31, 0.18, and 0.16, respectively. When analyzing variables that indirectly affected herb use, it was clear that positive attitudes, perceived social support, and societal values significantly influenced herb use through HL, with influence coefficients of 0.08, 0.16, and 0.04, respectively. Together, these variables accounted for 68% of the variance in herb use. Conclusions: The findings from this study can be utilized to develop and implement strategies that guide the use of herbal products, ultimately aiming to improve human health.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.2
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• pp.19-29
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• 2024

Objective : Pattern identification in Korean Medicine is a core value, leading to a quantitative and qualitative increase in related studies. This study aims to identify trends in newly published research and discuss pattern identification. Method : We reviewed studies from 2015 to 2023 using the Oriental Medicine Advanced Searching Integrated System provided by the Korea Institute of Oriental Medicine. The keywords used were: pattern identification, cold-heat, deficiency-excess, exterior-interior, yin-yang, phlegm-retained fluid, static blood, qi-blood, qi deficiency, blood deficiency, yin deficiency, yang deficiency, and four-constitution. Results : A total of 150 studies met the inclusion criteria. These comprised 84 observational studies, including case reports, 2 experimental studies, and 64 literature reviews. Most studies were published in the Korean Journal of Oriental Physiology and Pathology. On average, 17.1 studies were published annually, although the number of studies has decreased over the years. Network analysis revealed that the main keyword in titles was pattern identification (n=122), followed by study (n=68) and patients (n=34). Conclusion : These findings highlight trends in studies related to pattern identification, with a focus on its standardization. Considering the limitations of pattern identification, a shift towards a disease-centered approach is recommended.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.31-38
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• 1990

The power water flowed out from the multipurpose darn influences the ecosystem approximately because of the low water temperature. An appropriate counter measure to the rising water temperature is needed for growing crops especially when the temperature is below 18˚C in the source of the irrigation water This observational study is practiced in Yong-Doo water warming canal and pond in the down stream of Choong-Ju multipurpose dam and is practiced for analyse and compare the rising effects in actural water temperature by actual measurement with the rising effects of planned water temperatuer by the basic theoritical method and for the help to present the direction in plan establishment through investigate the results afterwards. The results are as follows. 1.The degree of the rise of the water temperature can be decided by $\theta$x=$\theta$o +K L--v.h (T-$\theta$˚)Then, K values of a factor representing the characteristics of the water warming canal were 0.00002043 for the type I. and 0.0000173 for the type II. respectively. 2.A variation of water temperature which produced by the difference effective temperature and water temperature in the water warming canal was $\theta$x1 = 16.5 + 15.9(1-e -0.00018x), $\theta$x2 =18.8 + 8.4( 1-e -0.000298x)for the type I. and $\theta$x, = 19.6 + 12.8 ( 1-e -0.00041x) for the type II. 3.It was shown that the effects of the rise of water temperature for the type I. water warming canal were greater than that of type II. as a resultes of broadening the surface of the canal compared with the depth of water, coloring the surface of water canal and installing the resistance block. 4.In case of the type I. water warming canal, the equation between the air temperature and the degree of the rise of water temprature could be made ;Y= 0.4134X + 7.728 In addition, in case of the type II. water warming canal, the correlation was very low. 5.A monthly variation of the water temperature in the water warming canal was the highest in August during the irrigation period and the water temperature rose with the air temperature until August. However, it was blunted after then. 6.A rising degree of water temperature of the practical value in the water warming pond was higher than that of the theoritical equation by 69% for the type I. and 57% for the type II. Accordingly, it was possible to acquire the result near the practical value.$\theta$w-$\theta$o=[1-exp{ -h(1+2$\psi$) . X($\theta$w-$\theta$0)XC Here, C values are 1.69 for the type I. and 1.57 for the type II. 7.It was shown that the effect of the rise of water temperature was favorable when the thermal absorption was to be good by coloring the surface of the water warming pond and removing the bottom osmosis. 8.By enlarging the surface of water in comparison with the depth, and by having dead area of water in the water warming pond, this structure in the water warming pond is helpful for the rise of water temperature.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.97-105
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• 2005

In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.647-660
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• 2020

The objectives of this study are to develop a framework for selecting multi-GCMs considering Asia monsoon characteristics and assess it's applicability. 12 climate variables related to monsoon climates are selected for GCM selection. The framework for selecting multi-GCMs includes the evaluation matrix of GCM performance based on their capability to simulate historical climate features. The climatological patterns of 12 variables derived from individual GCM over the summer monsoon season during the past period (1976-2005) and they are compared against observations to evaluate GCM performance. For objective evaluation, a rigorous scoring rule is implemented by comparing the GCM performance based on the results of statistics between historical simulation derived from individual GCM and observations. Finally, appropriate 5 GCMs (NorESM1-M, bcc-csm1-m, CNRM-CM5, CMCC-CMS, and CanESM2) are selected in consideration of the ranking of GCM and precipitation performance of each GCM. The selected 5 GCMs are compared with the historical observations in terms of monsoon season and monthly mean to validate their applicability. The 5 GCMs well capture the observational climate characteristics of Asia for the 12 climate variables also they reduce the bias between the entire GCM simulations and the observational data. This study demonstrates that it is necessary to consider various climate variables for GCM selection and, the method introduced in this study can be used to select more reliable climate change scenarios for climate change assessment in the Asia region.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2E
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• pp.20-25
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• 1994

The major drawback to the Code Excited Linear Prediction(CELP) type vocoders is their large computational requirements. In this paper, a simple method is proposed to reduce the pitch searching time in the pitch filter almost without degradation of quality. Bease upon the observational regularity of the correlation function of speech, the searching range can be restricted to the positive side in pitch search. This is done by skipping the negative side with the width which is estimated from the previous positive envelope. In addition to that, the maximum number of available lags can be limited by the threshold, $L_T$, which is set on 58 empirically. So, only the limited numbers of lags are considered in pitch search, which is less than a half of that of the full search method. By using the proposed method in pitch search, its required computations are greatly reduced. Experimental result shows 51% time reduction almost without lowering the speech quality in segmental SNR measure.

• Journal of Korean Society of Forest Science
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• v.21 no.1
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• pp.47-51
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• 1974

In order to prove the similarity relationships between the basic species of oak through Electronic Data Processing System(EDPS) and numerical analysis, The analized species and datas were selected from the list of morphological observation in the thesis of T.B. Lee, 1961, "Phytogenetic study of the subgenus Lepidobalanus of the genus Quercus in Korea", and were coded by categories shown in Table 1. The value in the list were transformed into hundred percentage to standardize the observational value by each code into dimensionless. The similarity index between species were computed through formula of non-metric coefficient, $N_{jk}=\sum\limits_{i=1}^{n}\(\frac{{\mid}x_{ij}-x_{ik}{\mid}}{x_{ij}+x_{ik}}\)$, using the UNiVAC-1106, at National Computer Center. Quercus aliena, by analysis result, is most similar to Q. mongolica with the similarity index, 71.6 and Q. dentata is most far apart from Q. serrata in the relationship with index, 121.4. The above thesis of Professor, T. Lee, are closely similar with the result of this research study. But, their similar relationship are proved in quantity through numerical method in our research study. In addition, The relationships among Q. mongolica, Q. aliena and Q. serrata are found to be very similar, but Q. dentata to be enough far in similarity to other species by dendrogram shown at Fig. 1. The numerical classification through EDPS is found to be suitable method also applicable to the plant taxonomy.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.5
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• pp.284-291
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• 2016

A standard typhoon, which results in extreme wind speeds having various return period, can be reconstructed by combination of typhoon parameter informations(Kang et al., 2016). The aim of this study is to present a kind of surge-frequency analysis method by numerical simulation of a standard typhoon at Yeonggwang. MIKE21 was adopted as a numerical model and was proved to simulate the surge phenomena of the typhoon BOLAVEN(1215) well at several sites of the Western Coast. The simulation results with change of typhoon track which reflects typhoon-surge characteristics of the Western Coast show to have something in common with the observational results. This method is considered to be very efficient method on the point of simulating only one typhoon, while existing methods need to simulate a lot of typhoons.