• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.2
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• pp.174-179
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• 2007

This study was carried out to investigate the effect of Gastrodiae elata Blume fractions on systolic blood pressure and serum lipid profiles in spontaneously hypertensive rats (SHR/NCrj) fed high fat diet. Twenty-four males SHR weighing approximately 160 g were randomly divided into four groups; A (low molecule, GR-1), B (polysaccharide, GR-2), C (protein, GR-3) fractions of G. elata Blume, respectively, and D (high fat diet as control). After orally tube feeding the fractions of G. elata Blume, there were no differences in final body weights among the treatment groups. Diet intake was somewhat high in the control group (D), but there were no significant differences in feed efficiency ratios. In terms of serum lipid profiles, total-cholesterol level was statistically higher in the control group (D) than in G. elata Blume fraction groups (p<0.05). Triglyceride levels of low molecule (A) and polysaccharide (B) groups were lower by 16% and 11%, respectively than that of the control group (D). HDL-cholesterol level was remarkably higher (p<0.05), whereas LDL-cholesterol level was significantly lower (by 25%) in the group B as compared to the control group (D). Atherogenic index (AI) of G. elata Blume fraction groups were significantly lower than in the control group (p<0.05). Reference blood pressure (RBP) showed an average of $180\sim190mmHg$ at 8 weeks old after 3 weeks on feeding high fat diet. Compared with RBP, final blood pressure of treatment groups (35 days after feeding the fractions of G. elata Blume gractions) were decreased by 1.7% (A), 5.5% (B) and 3.6% (C), respectively, but the control group (D) contrarily showed an increase of 2.6%. Especially, final systolic blood pressure of the polysaccharide group (B) was lower by 22 mmHg than that of the control group (D). From these findings, it can be suggested that polysaccharide fraction may improve blood serum lipids and should be considered as effective in lowering of blood pressure.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.7
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• pp.849-858
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• 2007

This study was intended to collect the baseline information on health status, nutrient intakes and dietary self-efficacy according to the obesity levels of male workers. Nutrient intakes of 224 male workers were assessed by 24 hr recall method; also, dietary attitude and dietary self-efficacy were investigated by self-administerd questionnaires. Biochemical characteristics such as blood pressure (SBP, DBP), total cholesterol(TC), hemoglobin (Hb), blood glucose (BG), SGOT, SGPT and ${\gamma}-GTP$ were assessed. Subjects were divided into normal, overweight and obese groups by body mass index (BMI). The health status was analyzed as normal group, health concerned group and disease suspected group. Weight, percent ideal body weight (PIBW), BMI and body circumference (waist, hip) and waist-hip ratio were high in the order of obese group, overweight group and normal group. Body fat mass was high also in the order of obese, overweight and normal group. Blood pressure (SBP, DBP) was the highest in obese group. SGOT, SGPT, ${\gamma}-GTP$ were higher in the obese group than normal and overweight groups. It was Proven that the percentage of those evaluated as low nutrient intakes were 71% for Ca, 50.9% for Zn, 70.5% for vitamin B2, 56.3% for vitamin C and 81.3% for folic acid. The dietary attitude scores were high according to the dietary self-efficacy. The age was positively correlated with dietary attitude, and the dietary attitude was positively correlated with dietary self-efficacy and total energy intakes. Dietary attitude showed the greatest total causal effect in relation to dietary self-efficacy. The results of this study showed some health problems and nutritional problems, indicating the need for nutritional management for male workers.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.3
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• pp.319-332
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• 2009

The present study was performed to analyze the life style and eating behavior of stroke patients and to find the risk factors related to stroke incidence in Daegu and Gyeongbuk Province, Korea. The case subjects (n=100) were selected from newly diagnosed stroke patients at Kyungpook National University Hospital. The control subjects (n=150) were selected from community inhabitants who did not have stroke history and were sex and age-matched with the case subjects. The survey was conducted by individual interviews using questionnaires on the general characteristics, life-style, eating behavior, food intake frequency and food preference. The high body mass index, preexisting diseases such as diabetes and hypertension, stroke family history, smoking, overeating habit and high preference for sweet, greasy and meat foods appeared to be the risk factors for stroke incidence. On the other hand, the results suggest that life style of regular exercise and nonsmoking, food habits of green tea drinking and enough chewing, preference for Korean meal type, high intake frequency for legumes, vegetables, mushrooms, seaweeds, fishes and shell fishes, soy milk and green tea might be the protective factors for the stroke. Therefore, maintenance of healthy weight, the prevention and management of the deteriorative chronic diseases, change of life style and improvement of eating behaviors are considered to be important for stroke prevention.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.788-818
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• 2009

Renewable energy refers to solar energy, biomass energy, hydrogen energy, wind power, fuel cell, coal liquefaction and vaporization, marine energy, waste energy, and liquidity fuel made out of byproduct of geothermal heat, hydrogen and coal; it excludes energy based on coal, oil, nuclear energy and natural gas. Developed countries have recognized the importance of these energies and thus have set the mid to long term plans to develop and commercialize the technology and supported them with drastic political and financial measures. Considering the growing recognition to the field, it is necessary to analysis up-to-now achievement of the government's related projects, in the standards of type of renewable energy, management of sectional goals, and its commercialization. Korean government is chiefly following suit the USA and British policies of developing and distributing renewable energy. However, unlike Japan which is in the lead role in solar rays industry, it still lacks in state-directed support, participation of enterprises and social recognition. The research regarding renewable energy has mainly examinedthe state of supply of each technology and suitability of specific region for applying the technology. The evaluation shows that the research has been focused on supply and demand of renewable as well as general energy and solution for the enhancement of supply capacity in certain area. However, in-depth study for commercialization and the increase of capacity in industry followed by development of the technology is still inadequate. 'Cost-benefit model for each energy source' is used in analysis of technology development of renewable energy and quantitative and macro economical effects of its commercialization in order to foresee following expand in related industries and increase in added value. First, Investment on the renewable energy technology development is in direct proportion both to the product and growth, but product shows slightly higher index under the same amount of R&D investment than growth. It indicates that advance in technology greatly influences the final product, the energy growth. Moreover, while R&D investment on renewable energy product as well as the government funds included in the investment have proportionate influence on the renewable energy growth, private investment in the total amount invested has reciprocal influence. This statistic shows that research and development is mainly driven by government funds rather than private investment. Finally, while R&D investment on renewable energy growth affects proportionately, government funds and private investment shows no direct relations, which indicates that the effects of research and development on renewable energy do not affect government funds or private investment. All of the results signify that although it is important to have government policy in technology development and commercialization, private investment and active participation of enterprises are the key to the success in the industry.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.53-57
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• 2009

Heavy metal pollution may be one of the most serious challenges confront crop production and human health. Therefore, the selection of heavy metal tolerance cultivars which adapted to the contaminated fields will introduced a suitable solution for management this critical environmental risk. The objectives of this research is to assess human health risk using geochemical analyses and exposure assessment of heavy metals in rice cultivars. Risk for inhabitants in the closed mine area was comparatively assessed for As, Cd, Cu and Pb in 10 rice varieties as a major exposure pathway. The average daily dose (ADD) of each heavy metal was estimated by analyzing the exposure pathways to rice and soil. For the non-carcinogenic risk characterization, Hazard Quotient (HQ) and Hazard Index (HI) were calculated using toxicity indices provided by US-EPA IRIS. The different rice varieties revealed a wide range of HI values from 23.6 to 34.3, indicating that all rice varieties have a high potential toxic risk. The DA rice variety showed the lowest HI value while the TB rice variety the highest. The probabilities of cancer risk for As via rice consumption were varied with rice varieties ranging from 2.0E-03 to 3.5E-03 which exceeded the regulatory acceptable risk of 1 in 10,000 set by US-EPA. The DA rice variety also showed the lowest value while the TB rice variety gave the highest value. Our results indicate that risk assessment can be contribute to screen the pollution safe rice cultivars in paddy fields affected by the mining activity.

• Journal of Bio-Environment Control
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• v.28 no.1
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• pp.66-77
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• 2019

The present study investigated pine trees, which forms a major plantation species in Korea, with the objective of improving the survival rate of pine trees after planting. Growth responses and characteristics were assessed by controlling the level of fertilizer application, which is a basic controlling the growth of pine seedlings, to identify the optimal fertilization treatment. Pine tree seedlings were grown in 104 containers and were examined 8 weeks after planting. Stem height and were measured at 4-week intervals. In terms of fertilization treatment for 1-0 pine seedlings, the treatment group with gradually-increasing fertilizer concentration ($500{\rightarrow}1000{\rightarrow}1000{\rightarrow}1000mg{\cdot}L^{-1}$) had the biggest increase in stem height and diameter at the root. The survey results indicated that the increased concentration treatment group and the gradually-increasing concentration treatment group had more growth compared with that in the fixed concentration treatment group. The gradually-increasing concentration treatment group ($500{\rightarrow}1000{\rightarrow}1000{\rightarrow}1000mg{\cdot}L^{-1}$) had the highest total dry matter production. Nine weeks after fertilization, the tips of the pine leaves turned yellow in the fixed concentration treatment group ($3000mg{\cdot}L^{-1}$). The same phenomenon was observed in the treatment group in which the concentration was increased to $2000mg{\cdot}L^{-1}$, and in the gradually-increasing concentration treatment group, when the concentration was raised up to $2000mg{\cdot}L^{-1}$. We concluded that the optimal fertilization conditions for producing healthy pine 1-0 seedlings involve fertilizing once a week with Multifeed 19 at $500mg{\cdot}L^{-1}$ during the seedling period, Multifeed 19 at $1000mg{\cdot}L^{-1}$ during the rapid growth period, and Multifeed 32 at $1000mg{\cdot}L^{-1}$ during the maturation period.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.152-168
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• 2019

The element arsenic, which is abundant in the Earth's crust, is used for various industrial purposes including materials for disease treatment and household goods. Various human activities, such as the disposal of soil waste, metal mining and smelting, and combustion of fossil fuels, have caused the pollution of the environment with arsenic. Recently, guidelines for arsenic in rice have been adopted by the Korean ministry of food and drug safety to prevent health risks based on rice consumption. Because of the exposure to arsenic and its accumulation in the human body through various channels, such as air inhalation, skin contact, ingestion of drinking water, and food consumption, integrated multimedia risk assessment is required to adopt appropriate risk management policies. Therefore, integrated human health risk assessment was carried out in this study using integrated exposure assessment based on multimedia (e.g., air, water, and soil) and multi-route (e.g., oral, inhalation, and dermal) scenarios. The results show that oral uptake via drinking water is the most common pathway of arsenic into the human body, accounting for 57%-96% of the total arsenic exposure. Among various age groups, the highest exposures to arsenic were observed in infants because the body weight of infants is low and the surface areas of infant bodies are large. Based on the results of the exposure assessment, the cancer and non-cancer risks were calculated. The cancer risk for CTE and RME is in the range of 2.3E-05 to 6.7E-05 and thus is negligible because it does not exceed the cancer probability of 1.0E-04 for all age groups. On the other hand, the cancer risk for RME varies from 6.4E-05 to 1.8E-04 and from 1.3E-04 to 1.8E-04 for infants and preschool children, exceeding the excess cancer risk of 1.0E-04. The non-cancer risks range from 5.4E-02 to 1.9E-01 and from 1.5E-01 to 6.8E-01, respectively. They do not exceed the hazard index 1 for all scenarios and all ages.