• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1145-1152
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• 2011

This study was conducted to estimate genetic effects on economically important traits for genetic improvement in Hanwoo by using the real-time ultrasound measurements for longissimus dorsi muscle area (LMA), backfat thickness (BFT), and marbling score (Marb). The phenotypic data were obtained from 1,648 pedigreed cows, and general linear models were applied to test the effects of age, region, and body condition socre. The cows between 50 and 60 months of age had the greatest scores for LMA and BFT, and Marb (P<0.05). The cows in region C had the greatest scores for body condition socre, LMA and BFT, while in region J Marb was the lowest (P<0.05). There was positive relation with LMA, BFT, and Marb according to increase body condition socre. Heritabilities for LMA, BFT, and Marb were estimated as 0.136, 0.351, and 0.236, respectively. These results would provide primary information for the efficient implementation of genetic improvement schemes in Hanwoo.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.4
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• pp.52-65
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• 1984

In general precise estimation of hourly of daily distribution of the long-term run-off should be very important in a design of source of irrigation. However, there have not been a satisfying method for forecasting of stationar'y long-term run-off in Korea. Solving this problem, this study introduces unit-hydrograph method frequently used in short-term run-off analysis into the long-term run-off analysis, of which model basin was selected to be Sumgin-river catchment area. In the estimation of effective rainfall, conventional method neglects the Soil moisture condition of catchment area, but in this study, the initial discharge (qb) occurred just before rising phase of the hydrograph was selected as the index of a basin soil moisture condition and then introduced as 3rd variable in the analysis of the reationship between cumulative rainfall and cumulative loss of rainfall, which built a new type of separation method of effective rainfall. In next step, in order to normalize significant potential error included in hydrological data, especially in vast catchment area, Snyder's correlation method was applied. A key to solution in this study is multiple correlation method or multiple regressional analysis, which is primarily based on the method of least squres and which is solved by the form of systems of linear equations. And for verification of the change of characteristics of unit hydrograph according to the variation of a various kind of hydrological charateristics (for example, precipitation, tree cover, soil condition, etc),seasonal unit hydrograph models of dry season(autumn, winter), semi-dry season (spring), rainy season (summer) were made respectively. The results obtained in this study were summarized as follows; 1.During the test period of 1966-1971, effective rainfall was estimated for the total 114 run-off hydrograph. From this estimation results, relative error of estimation to the ovservation value was 6%, -which is mush smaller than 12% of the error of conventional method. 2.During the test period, daily distribution of long-term run-off discharge was estimated by the unit hydrograph model. From this estimation results, relative error of estimation by the application of standard unit hydrograph model was 12%. When estimating by each seasonal unit bydrograph model, the relative error was 14% during dry season 10% during semi-dry season and 7% during rainy season, which is much smaller than 37% of conventional method. Summing up the analysis results obtained above, it is convinced that qb-index method of this study for the estimation of effective rainfall be preciser than any other method developed before. Because even recently no method has been developed for the estimation of daily distribution of long-term run-off dicharge, therefore estimation value by unit hydrograph model was only compared with that due to kaziyama method which estimates monthly run-off discharge. However this method due to this study turns out to have high accuracy. If specially mentioned from the results of this study, there is no need to use each seasonal unit hydrograph model separately except the case of semi-dry season. The author hopes to analyze the latter case in future sudies.

• Journal of Preventive Medicine and Public Health
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• v.39 no.4
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• pp.302-308
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• 2006

Objectives: This study aims to examine if a garbage dumping site has real and negative influence on the quality of life (QOL) for the nearby residents. The net effects of the residential distance from the garbage dumping site and from the garbage truck route were investigated for five domains of the QOL. Methods: Two hundred fifty seven Shin-dong Myeon residents, Chun-cheon Si, participated in a self-administrated survey. The Shin-dong Myeon garbage dumping site began operating in 1996. ANCOV A with generalized linear models and multiple regression analysis were performed. Results: Descriptive analyses show that a residence nearby a garbage dumping site is negatively associated with the physical and environmental domains of the QOL. The residential distance from the garbage truck route does not exert any significant effect on various domains of QOL, except for the environmental domain. On the multivariate analysis, the residents living near the garbage dumping site tended to have a significantly negative QOL in the physical and environmental domains. However, the distance from the garbage truck route did not show a significant nor substantial effect on the QOL. The demographic and socioeconomic control variables are associated with a number of the QOL domains, and their patterns are consistent with the general expectations. Conclusions: The results indicated that a garbage dumping site is considered to be an environmental hazard among the nearby residents according to the lower scores on the physical and environmental domains of the QOL. The findings from this study provide comprehensive understanding on the residents' QOL, and they may help politicians and policy makers make decisions for appropriate interventions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.93-100
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• 2008

The parameters of lens such as focal length, focus, and aperture stop changes while shooting the scenes with zoom lens. Especially, zooming action dramatically changes the geometry of lens system that causes significant change of lens model. We investigated how the lens model changes while zooming in general shooting condition. Each parameters of lens model was estimated and checked whether they can be modeled well in the condition of auto-controlling focus, aperture and vibration reduction. In order to do this, calibration images were taken, modeled in different fecal length setting. And changing patterns of models were inspected to find out if there is some elements that have some particular pattern in changing with respect to focal length. The result showed us that although we didn't control the focus and aperture setting, there's specific changing patterns in radial and do-centering distortion. Especially, the strong linear correlation was found between coefficient of $r^2$ and focal length. It is expected that many parts of distortion can be eliminated without additional self calibration even if zoom operation is done when shooting the scenes if we know its fecal length and model of this coefficient.

• Journal of Nutrition and Health
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• v.46 no.5
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• pp.410-417
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• 2013

Caloric restriction is recognized as one of the best treatment options for obesity, and is associated with changes in body composition. The purpose of this study was to determine the influence of age in caloric restriction in overweight and obese women. In this caloric restriction study, nutrient intake of 61 women was evaluated using food records written by subjects for three days. Body composition and metabolic risk factors were assessed before and after caloric restriction. Blood levels of lipids, glucose, leptin, and adiponectin were measured. Visceral fat and subcutaneous fat were evaluated using bioimpedance analysis. General linear models (GLM) identified the independent effects of age after co-varying baseline weight and difference of energy intake. Weight, fat mass, visceral fat, subcutaneous fat, and blood pressure showed a significant decrease by caloric restriction of 452 kcal/day. The percent changes in weight, visceral fat, and subcutaneous fat were -4.5%, -12.0%, and -8.2%, respectively, after caloric restriction. The percent changes of weight, visceral fat, and subcutaneous fat showed an independent association with age co-varying baseline weight and difference of energy intake. Decreased change in percent of leptin by caloric restriction also showed an association with age. Changes in body composition and leptin by caloric restriction showed an independent association with age. This may indicate greater difficulty in achievement of change of body composition as well as greater obesity-related metabolic risk with aging. Therefore, caloric restriction considering age should be recommended for effective dietary treatment in overweight or obese women.

• Journal of Environmental Health Sciences
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• v.49 no.1
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• pp.37-47
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• 2023

Background: Paraben is a widely used substance with a preservative effect found in various materials such as food, medicine, personal care products, and cosmetics. Objectives: This study was conducted to identify the level of urinary paraben concentrations (i.e., methyl-, ethyl-, and propyl-) among Korean adults and to explore the factors related with the exposure levels. Methods: We analyzed the third period (2015~2017) of the Korean National Environmental Health Survey (KoNEHS). R statistical software (version 4.1.1) was used to estimate representative values for the whole population with weight variables to reflect sampling design. Whether urinary concentrations tended to increase as the level of paraben exposure-related characteristics increased was tested and P_trend was calculated using general linear models. Results: Urinary concentrations of all three parabens (i.e., methyl-, ethyl- and propyl-) were higher in women than in men (P_trend<0.0001, 0.008, and <0.0001), and the values of methylparaben and propylparaben tended to increase as the age of subjects increased (P_trend<0.0001, and <0.0001). Urinary concentrations of methylparaben and propylparaben were associated with intensity of exercise (P_trend<0.001, and 0.004), and that of propylparaben was higher in non-smokers (P_trend=0.01). In terms of paraben exposure-related variables, urinary concentrations of parabens (i.e., methyl-, ethyl- and propyl-) increased as the daily average frequency of teeth-brushing (P_trend<0.0001, 0.03 and 0.0001), the frequency of use of hair products (P_trend=0.005, 0.05 and 0.04), the frequency of use of makeup products (P_trend<0.001, 0.001 and <0.001), and the frequency of use of antibacterial products (P_trend=0.005, 0.02 and 0.02) increased. Conclusions: In our study, urinary concentrations of all three parabens are associated with gender, teethbrushing, hair products, make-up products, and antibacterial products. Methyl- and proyl-parabens were associated with age and intensity of exercise, and propyl-paraben was associated with smoking.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Nutrition and Health
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• v.52 no.2
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• pp.206-216
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• 2019

Purpose: Management of the metabolic risk factors in diabetes patients is essential for preventing or delaying diabetic complications. This study compared the levels of the metabolic risk factors in diabetes patients according to the income levels, and examined the secular trends in recent decades. Methods: The data from the Korea National Health and Nutrition Examination Survey 1998 ~ 2014 were used. The diabetes patients were divided into three groups based on their household income levels. General information was obtained through self-administered questionnaires, and the blood biomarkers and blood pressure data were obtained from a health examination. Multivariable linear regression models were used to compare the metabolic biomarker levels according to the household income levels, adjusting for potential confounding factors. Results: The fasting blood glucose, hemoglobin A1c, and blood lipid (total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglyceride) levels were similar in the three groups. During the survey period of 16 years, the blood pressure showed a significant decreasing trend with time in all groups (p < 0.001). In contrast, the fasting blood glucose (p = 0.004), total cholesterol (p < 0.001), and LDL-cholesterol levels (p = 0.007) decreased significantly, and the HDL-cholesterol level (p < 0.001) increased significantly in the highest-income groups. In the lowest-income group, the fasting blood glucose (p = 0.02), total cholesterol (p < 0.001), and triglyceride (p = 0.003) levels showed a significant decreasing trend over time. On the other hand, the middle-income group showed no significant change in any of the metabolic risk factors except for blood pressure. Conclusion: The level of management of metabolic risk factors according to the income level of Korean diabetes patients was similar. On the other hand, the highest- and lowest-income groups showed positive trends of management of these factors during 16 years of observation, whereas the middle-income group did not show any improvement.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of agriculture & life science
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• v.50 no.5
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• pp.173-182
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• 2016

This study was aimed to identify the phenotypic relationships between calving interval and lactation curve parameters in Korean Holstein cow. The data of 36,505 lactation records was obtained from the Dairy Herd Improvement program run by Dairy Cattle Improvemnet Center of National Agricultural Federation of Korea. All lactation records were collectied from the multiparous cows calving between 2011 to 2013. The estimated lactation curves were drawn using Wood model based on actual milk yield records, and NLIN Procedure of SAS program (ver. 9.2). General linear multivariate models for calving interval, 305-d milk yield, lactation parameters(A, b, c), persistency, peak day, and peak yield included fixed effects of calving year-season (spring, summer, fall and winter) and parity(2, 3 and 4). For calving interval, 305-d milk yield, lactation parameters(A, b, c), persistency, peak day and peak yield, all two fixed effect(calving year-season, parity) were significant(p<0.05). The estimated lactation functions using Wood model for 2, 3, and 4 parity were yt=24.66t0.175e-0.00302t, yt=24.69t0.192e-0.00334t, and yt=24.22t0.200e-0.00341t, respectively. Phenotypic correlation (partial residual correlation) between calving interval and 305-d milk yield, A, b, c, persistency, peak day, and peak yield were 0.093, -0.014, 0.028, -0.046, 0.099, 0.085, and 0.052, respectively. To conclude, if calving interval increase then ascent to peak, persistency, peak day and peak yield are increase, and descent after peak is decrease. So, total 305-d milk yield is increase.