• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.4
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• pp.501-509
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• 2012

The dietary intake of whole grains is known to reduce the incidence of chronic diseases such as obesity, diabetes, cardiovascular disease, and cancer. In our previous study, hog millet (HM, $Panicum$ $miliaceum$ L.) water extract showed the highest anti-lipogenic activity among nine cereal types in 3T3-L1 cells. In this study, the effect of hog millet water extract on hepatic steatosis and lipid metabolism in mice fed a high fat diet was investigated. Mice were fed a normal-fat diet (ND), high-fat diet (HFD) or HFD containing 1% or 2% (w/w) HM for 7 weeks. Body weight and food intake were monitored during the study period. Insulin resistance by homeostasis model assessment (HOMA-IR), fasting lipid profile, hepatic fatty acid metabolism-related gene expression determined, and intraperitoneal glucose tolerance test (IGTT) were performed at the study's end. The results indicated that 1% and 2% HM diets effectively decreased liver weights, blood TG and T-cholesterol levels (p<0.05), while the HDL-cholesterol level was increased (p<0.05) compared to HFD-induced steatotsis mice. Hepatic lipogenic-related gene ($PPAR{\alpha}$, L-FABP, and SCD1) expressions decreased, whereas lipolysis- related gene (CPT1) expression increased in animals fed the 2% PME diet (p<0.05). In addition, mice fed 1% or 2% HM diet had markedly decreased IGTT and HOMA-IR, compared to the those of the HFD-induced hepatic steatosis control group (p<0.05). These results indicated that HM inhibited hepatic lipid accumulation by regulating fatty acid metabolism, and suggested that HM is useful in the chemoprevention or treatment of high fat-induced hepatic steatosis and hepatic steatosis-related disorders including hyperlipidemia, glucose sensitivity, and insulin resistance.

• Journal of dental hygiene science
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• v.16 no.1
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• pp.53-61
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• 2016

Eating supports to gain energy and nutrition and improves quality of life. Ageing affects the food intake ability due to loss of natural teeth and the progressive muscle degeneration. Our objective was to investigate how the food intake ability (FIA) and the remaining teeth could influence on oral health related quality of life in the elderly. This study was performed with 503 elderly subjects living in Daejeon, Korea. The questionnaire with the FIA with 30 Korean food and Oral Health Impact Profile 14 (OHIP-14) and oral examination were surveyed. The five groups according to cluster analysis of FIA had the different numbers of remaining teeth and functional posterior teeth with opposing teeth or prosthesis significantly: group 1, $21.78{\pm}8.27$ and $2.80{\pm}2.63$; group 2, $16.75{\pm}7.87$ and $2.16{\pm}2.44$; group 3, $14.68{\pm}9.77$ and $1.73{\pm}2.30$; group 4, $9.93{\pm}8.13$ and $0.78{\pm}1.68$; group 5, $10.18{\pm}8.37$ and $0.51{\pm}1.22$. The more foods the subjects could masticate, the better oral health related quality of life they had. The medium FIA, soft FIA and the number of remaining teeth could explain 46% of OHIP-14, but hard FIA could not in the multiple regression model. We suggested to develop the oral health program for the elderly to be able to eat the food with medium physical property at least be helpful to improve oral health related quality of life.

• Korean Journal of Medicinal Crop Science
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• v.16 no.4
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• pp.225-230
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• 2008

Diabetes mellitus is the fifth leading cause of death among Koreans. Control of hyperglycemia and dyslipidemia is strongly correlated with decrease in risks for cardiovascular diseases, the most common and fatal diabetic complication. The effects of chronic feeding of a mixture of Chinese herbs on blood lipid profile were measured in an animal model of type 2 diabetes mellitus, db/db mice (C57BL/Ks). The Chinese herb mixture was composed of Panax ginseng C. A. Meyer,Astragalus membranaceus, Glycyrrhiza uralensis, Lycium chinense, Morus, Pueraria thunbergiana, Prunella vulgaris var. lilacina, Acanthopanax sessiliflorus, Schizandra chinensis, Scutellaria baicalensis, Dioscorea batatas, Polygonatum doratumvar. pluriflorum, Paeonia lactiflora, and Rehmannia glutinosa in a ratio of 1 : 0.7 : 0.4 : 0.7 :0.4 : 0.7 : 1.1 : 0.9 : 0.4 : 0.4 : 0.7 :0.7 : 0.9 : 0.9. Methanol extract of the Chinese herb mixture was tested for the inhibitory activity against yeast ${\alpha}$-glucosidase in vitro. The Chinese herb mixture extract inhibited ${\alpha}$-glucosidase by 25.2% at the concentration of 0.5mg/mL. Four weekold male db/db mice (n = 14) were fed AIN-93G semipurified diet or diet containing 10% powder of the Chinese herb mixture for 6 weeks after 1 week of adaptation period. Body weight (39.5 ${\pm}$ 1.6 g) and food intake (4.3 ${\pm}$ 0.6 g/day) of the Chinese herb group were not significantly different from those of the control group (40.4 ${\pm}$ 2.6 g and 4.5 ${\pm}$ 0.6 g/day). Consumption of Chinese herb mixture significantly decreased plasma glucose level (442.5 ${\pm}$ 36.0mg/dL) compared with the control group (489.8 ${\pm}$ 34.6 mg/dL, p < 0.05). Plasma cholesterol level (159.2 ${\pm}$ 18.4 mg/dL) of the Chinese herb group was significantly lower than that of the control group (185.4 ${\pm}$ 13.7 mg/dL, p < 0.05). Blood glycated hemoglobin (6.3 ${\pm}$ 0.8%) and plasma triglyceride levels (99.4 ${\pm}$ 15.0mg/dL) of the Chinese herb group were not significantly different from those of the control group (6.7 ${\pm}$ 0.7% and 108.8 ${\pm}$ 11.0mg/dL). Thus, the Chinese herb mixture could be useful in the treatment of diabetes and cardiovascular complications of diabetes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Journal of Nutrition and Health
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• v.52 no.1
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• pp.6-16
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• 2019

Purpose: Dyslipidemia is a major risk factor for cardiovascular disease. Pine needles (Pinus densiflora seib et Zucc) are a traditional medicine used to treat dyslipidemia in clinical settings. This study examined the potential effects of sulgidduk, a Korean traditional rice cake containing pine needle juice to protect against dyslipidemia induced by a high-fat/sugidduk diet in a rat model. Methods: Twenty one male Sprague-Dawley rats were divided randomly into three groups: normal control (NC), Sulgidduk diet (SD), Sulgidduk diet containing pine needle juice (PSD). The blood lipid levels, production of lipid peroxide in the plasma and liver, total cholesterol and triglyceride in the liver and feces, antioxidant enzyme activities in plasma and erythrocytes were measured to assess the effects of PSD on dyslipidemia. Results: A high-fat/Sulgidduk diet induced dyslipidemia, which was characterized by significantly altered lipid profiles in the plasma and liver. The food intake was similar in the three groups, but weight gain and food efficiency ratio (FER) were reduced significantly in the PSD group compared to those in the SD group. The level of total cholesterol, LDL-cholesterol and TBARS in the plasma showed tendencies to decrease in the PSD group compared to those in the SD group. The levels of high-fat/Sulgidduk diet-induced sterol regulatory element-binding protein 2 (SREBP2) gene expression were reduced significantly in the PSD group. The supplementation of PSD reduced the hepatic triglyceride and total cholesterol levels significantly, and enhanced the fecal excretion of triglyceride and hepatic antioxidant enzyme activities compared to the SD group. Conclusion: These results suggest that the addition of 0.4% pine needle juice to Sulgidduk may be an alternative snack to control dyslipidemia.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.