• Journal of Nutrition and Health
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• v.38 no.6
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• pp.445-454
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• 2005

The purpose of this study was to compare the validity of obese index among body mass index (BMI), waist to hip ratio (WHR), and waist circumference (WC) and to determine which is the best in relation to cardiovascular disease (CVD) risk in Korean elderly more than 65 ages. Data from the 1998 Korean Health and Nutrition Survey were used (n=1017). Anthropometric indices and CVD risk factors were measured, and chi-square test, analysis of variance following duncan's multiple range test, partial correlation analysis, and Receiver Operator Characteristic (ROC) curves were used in the analysis. Anthropometric values were decreased in both male and female when ages were goes up. In female elderly, it specially showed the characteristics of upper body fat and systolic blood pressure risk (p<0.05). Among life style factors the current smokers were prevalent in obese male (p<0.05), but not prevalent in female having obese or upper body fat. Also, person with upper body obesity have more exercise than that of normal group (p<0.01). Mean BMI values of the current smoker was lower than that of normal group in both sexes (p<0.01). Mean BMI value of person with other risk factors were higher than that of normal groups (p<0.05). Among 7 CVD risk factors in partial correlation analysis, WC had the highest correlation coefficient in 5 in male, whereas BMI in 4 in female. In ROC analyses of 12 risk factors and health conditions, the largest area under curve of obese indices for risk factors were WC>WHR>BMI in male and BMI>WHR>WC in female. The optimal cutoff values of each index (BMI : WHR : WC) for one or more risk factors were 19.02 : 0.84 : 71.3 in male and 19.04 : 0.88 : 85.6 in female. In conclusion, Most Korean elderly showed non-obese and abdominal obesity likewise other Asians. Also CVD risk factors were prevalent in Korean elderly within normal limits of obese indices. Therefore the upper body fat indices reflected in the aged whose muscle mass is replaced by fat must be used as an indicator of CVD risk together with BMI. Although WHR was the worst index based on partial correlation analysis and so located between BMI and WC in ROC curve analysis in both sexes, it need to be use with WC to screen the cardiovascular risk group.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Wind and Structures
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• v.23 no.6
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• pp.559-575
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• 2016

In order to investigate the influence of different blade positions on aerodynamic load and wind loads and load-effects of large scale wind turbine tower under the halt state, we take a certain 3 MW large scale horizontal axis three-blade wind turbine as the example for analysis. First of all, numerical simulation was conducted for wind turbine flow field and aerodynamic characteristics under different halt states (8 calculating conditions in total) based on LES (large eddy simulation) method. The influence of different halt states on the average and fluctuating wind pressure coefficients of turbine tower surface, total lift force and resistance coefficient, circular flow and wake flow characteristics was compared and analysed. Then on this basis, the time-domain analysis of wind loads and load-effects was performed for the wind turbine tower structure under different halt states by making use of the finite element method. The main conclusions of this paper are as follows: The halt positions of wind blade could have a big impact on tower circular flow and aerodynamic distribution, in which Condition 5 is the most unfavourable while Condition 1 is the most beneficial condition. The wind loads and load-effects of disturbed region of tower is obviously affected by different halt positions of wind blades, especially the large fluctuating displacement mean square deviation at both windward and leeward sides, among which the maximum response occurs in $350^{\circ}$ to the tower top under Condition 8; the maximum bending moment of tower bottom occurs in $330^{\circ}$ under Condition 2. The extreme displacement of blade top all exceeds 2.5 m under Condition 5, and the maximum value of windward displacement response for the tip of Blade 3 under Condition 8 could reach 3.35 m. All these results indicate that the influence of halt positions of different blades should be taken into consideration carefully when making wind-resistance design for large scale wind turbine tower.

• Journal of Plant Biology
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• v.13 no.1
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• pp.33-46
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• 1970

Pinus densiflora stands are common secondary forest communities on infertile soils in Korea. The stands are results of long severe past biotic pressure such as cutting, burning and grazing. These could be regarded as biotic climax in Korea. Because of their prevalent occurrence, relatively simple species and age composition, and their domestic economic importance, study of their distributional patterns may give some basic knowledge for better utilization of land resources in Korea. To detect distributional patterns and interspecific associations ten pine stands, each of which was homogenious with respect to topography and physiognomy, were subjectively selected from pine stands in Kyunggi Province near Seoul in 1969 and were made object of this study. Four contiguous systematic samples of count for trees, shrubs and seedlings from belt transects were collected from homogeneous areas within ten natural pine stands. The belt transect was 64m or 128m in length, and 1m, 2m or 4m in width. Basic units within the transect ranged from 64 to 256. The data from the contiguous transects were analysed in terms of multiple split-plot experiment. Departure from randomness of stem distribution, i.e., pattern, was tested in terms of variance mean ratio. For the detection of association between species, correlation coefficient was calculated for different block sizes. The values of ${\gamma}$ were tested by the usual t-test. Fine trees within one of the stands showed significant regular distribution through out the blocks. Within other eight stands pines were randomly distributed at basic unit with 4$\times$4m, 2$\times$2m, 2$\times$1m and 1$\times$1m. One significantly clumped distribution at basic unit 2$\times$2m, however, was observed from one of the pine stands. These randomly distributed groups were themselves significantly regularly distributed throughout the blocks for four pine stands. For the other four pine stands, in addition to the random distribution at the basie unit(the primary random group), randomly distributed groups with 32m dimension(the secondary random groups) were also observed. Both the primary and the secondary random groups were significantly regularly distributed at the rest of blocks. Pine seedlings were not distributed randomly thoughout the blocks. Within three of the ten stands they were contagiously distributed. Important shrub species underneath pines such as Querus serrata, Q. acutissima, Leapedeza intermedia, Rhododendron Yedoense var. poukhanenae, Juniperus utilis, Rhododendron mucronulatum var. ciliatum shnwed consistently similar distributional pattern with the pine at each stand. The shrub species pairs; Rhododendron Yedoense var. poukhanenae/Quercus serrata, Rhododendron mucronulatum var. ciliatum/Lespedeza intermedia were significantly negatively associated from 1m to 4m dimensional block sizes but became significantly positively associated from 8m sized blocks on. On the other hand the shrub species pairs; Lespedeza intermedia/Robinia Pseudoacacia, and Lespedeza bicolor var, japonica/Lespedeza intermedia were also significnalty negatively associated from 1m to 8m sized blocks but became significantly positively associated from 16m sized blocks on. The associational pattern between Rhododendron mucronul tun var. poukhanenae and Lespedeza intermedia was not consistent throughout the stands. In some stands negative associations were observed throughout the blocks except NS 32. From these observatons micro-edaphic variation within the pine stands seems not to be great enough to cause distributinal difference of pine trees within the ten pine stands. Among each species and pine seedings, however, the edaphic variation within the pine stands may be great enought to cause distributional variation.

• Journal of Korean Public Health Nursing
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• v.19 no.1
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• pp.41-52
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• 2005

This study was designed to provide a base for nursing intervention to help apheresis blood-donors to perform health promotion behavior effectively by surveying their health promotion behavior and by analyzing the critical factors. The study subjects were 468 participants in platelet donation at a university hospital apheresis unit in Seoul. The data for this study were collected between May and June. 2002. by questionnaire. Data were analyzed by t-test, ANOVA. Scheffe test, Pearson correlation coefficient. and stepwise multiple regression. The results were as follows. 1. The degree of performance of health promotion behavior of the subjects was a total average score of $152.9\pm21.5$ points and a mean score of 2.7 points. The highest score was 'I have a good relationship with others' in the factor of self-actualization and interpersonal support. The lowest score was 'I have my blood pressure checked regularly' in the factor of health responsibility. 2. Considering the classification according to the subjects' general characteristics. the health promotion behavior score was significantly higher for soldiers than high school students, for religious believers than atheists. and for high class economic status than mid and low class economic status. Also the health promotion behavior score was higher for those who had made more than five blood donations than those who had made zero or one donation. and for those who had made more than four blood donations than for those who had made less than four blood donations in the previous times of apheresis blood donation. The score was also higher for those not having a relationship with recipient than those having a relationship. 3. The self-efficacy related to donation. general self-efficacy and self-esteem had a significant correlation with the performance in health promotion behavior. 4. The critical factors that influenced the health promotion behavior were explained by $35.6\%$ of the general self-efficacy and by $40.2\%$ of the total of self-efficacy related to donation, and previous times of apheresis blood donation. The health promotion behavior score of apheresis blood-donors differed according to job, religion, economic status, previous times of whole blood donation, previous times of apheresis blood donation, and relationship with recipient. The health promotion behavior and self-efficacy related to donation, general self-efficacy, and self-esteem showed significant positive correlation with one another. The general self-efficacy, self-efficacy related to donation, and previous times of apheresis blood donation appeared to be the significant predictive factors of health promotion behavior. Therefore, from these study results, it is necessary to establish more effective and organized nursing intervention strategies for the health promotion behavior of apheresis blood-donors.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Journal of Yeungnam Medical Science
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• v.9 no.1
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• pp.29-43
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• 1992

A case-control study was conducted to investigate the association between the risk of cancer and selenium concentration in blood and toenails. Seventy three patients and two hundreds eighty three controls were, selected at the Yeungnam University Hospital between May and September in 1991. The selected cases were patients who had been hospitalized for stomach or colon cancer at the Depertment of General Surgery. The controls were people who visited to check physical examination at the Automated Mediscreening Center. The selenium concentration in whole blood and toenails were measured by atomic absorption spectrophotometer equipped with graphite furnace atomizer. The following information was ascertained for all cancer patients and controls : sex, age, body mass index, blood pressure, total serum cholesterol, and history of smoking and drinking. The mean selenium concentration in blood and toenail for all cancer patients were $143.6{\pm}10.8{\mu}g/l$ and $1.04{\pm}0.62{\mu}g/g$ and for the controls, $167.0{\pm}14.5{\mu}g/l$ and $1.15{\pm}0.55{\mu}g/g$, respectively. The difference in blood and toenail selenium concentrations of the two cancer sites was not statistically significant. Metastasis did not influence the concentration of selenium in blood and toenails. In the multiple logistic regression analysis, the blood selenium concentration($_aOR$: 0.888, 95% CI : 0.860-0.918), age, BMI and total serum cholesterol were significant variables for risk of cancer, but the selelenium concentration in toenail was not shown to be a significant variable in this regression analysis. The coefficient for blood selenium concentration adjusted for age, sex, diastolic blood pressure, total serum cholesterol, body mass index and smoking was -0.1184(p<0.01). These findings suggest that low selenium concentration is associated with gastrointestinal cancers. Further epidemiologic studies including important variables such as other antioxidant micronutrients will be necessary.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• Journal of Bio-Environment Control
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• v.16 no.3
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• pp.210-216
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• 2007

A study was conducted to find mechanism and spray characteristics of a mini-sprinkler with downward spray to develop a new design type to be able to prevent drop water. The experiments were executed in a plastic greenhouse to minimize the effect of the wind. Data was collected at five different operation pressures and at 4 different raiser heights. Spray characteristics of the sprinkler such as effective radius, effective area, mean application depth, absolute maximum application depth, effective maximum application depth and coefficient of variation were determined. In order to analyze the mechanism and packing supporter of sprinkler, the numerical simulation using ABAQUS was performed. The optimum pressure for preventing drop water was determined.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.