• Journal of Nutrition and Health
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• v.52 no.4
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• pp.342-353
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• 2019

Purpose: The Dietary Reference Intakes for Koreans (KDRIs) suggest that the goal for the intake of sodium should be less than 2,000 mg, which is thought to be infeasible to achieve when eating the typical Korean diet. This study aimed to obtain the new intake goals for sodium with improved feasibility to achieve, and also to design optimized food intake patterns for Korean adults by performing linear programming. Methods: The data from a one day 24-hour dietary recall of the 2010 ~ 2014 Korea National Health and Nutrition Survey were used to quantify food items that Korean adults usually consumed. These food items were categorized into seven groups and 24 subgroups. The mean intakes and intake distributions of the food groups and the food subgroups were calculated for eight age (19 ~ 29, 30 ~ 49, 50 ~ 64, and over 65 years old) and gender (male and female) groups. A linear programming model was constructed to minimize the difference between the optimized intakes and the mean intakes of the food subgroups while meeting KDRIs for energy and 13 nutrients, and not exceeding the typical quantities of each of the food subgroups consumed by the respective age and gender groups. As an initial solution of the linear programming, the optimized intake of seasonings, including salt, was calculated as 0 g for all the age and gender groups when the sodium constraint was inserted not to exceed 2,000 mg. Therefore, the sodium constraint was progressively increased by 100 mg until the optimized intake of seasoning was obtained as the values closest to the $25^{th}$ percentile of the intake distribution of seasonings for the respective age and gender groups. Results: The optimized food intake patterns were mathematically obtained by performing linear programming when the sodium constraint values were 3,600 mg, 4,500 mg, 4,200 mg, 3,400 mg, 2,800 mg, 3,100 mg, 3,100 mg, and 2,500 mg for the eight age and gender groups. Conclusion: The optimized food intake patterns for Korean adults were designed by performing linear programming after increasing the sodium constraint values from 2,000 mg to 2500 ~ 4,500 mg according to the age and gender groups. The resulting patterns suggest that current diets should be modified to increase the intake of vegetables for all the groups, milk/dairy products for the female groups, and fruits for the female groups except for the females aged 50 ~ 64 years.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.548-561
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• 2018

The objectives of this study were to construct a three-dimensional (3D) hydrodynamic and water quality model (EFDC) for the river reach between the Daecheong dam and the Sejong weir, which are directly affected by Gap and Miho streams located in the middle of the Geum River, and to evaluate the trophic status and water quality improvement effect according to the flow control and pollutant load reduction scenarios. The EFDC model was calibrated with the field data including waterlevel, temperature and water quality collected from September, 2012 to April, 2013. The model showed a good agreement with the field data and adequately replicated the spatial and temporal variations of water surface elevation, temperature and water quality. Especially, it was confirmed that spatial distributions of nutrients and algae biomass have wide variation of transverse direction. Also, from the analysis of algal growth limiting factor, it was found that phosphorous loadings from Gap and Miho streams to Sejong weir induce eutrophication and algal bloom. The scenario of pollutant load reduction from Gap and Miho streams showed a significant effect on the improvement of water quality; 4.7~18.2% for Chl-a, 5.4~21.9% for TP at Cheongwon-1 site, and 4.2~ 17.3% for Chl-a and 4.7~19.4% for TP at Yeongi site. In addition, the eutrophication index value, identifying the tropic status of the river, was improved. Meanwhile, flow control of Daecheong Dam and Sejong weir showed little effect on the improvement of water quality; 1.5~2.4% for Chl-a, 2.5~ 3.8% for TP at Cheongwon-1 site, and 1.2~2.1% for Chl-a and 0.9~1.5% for TP at Yeongi site. Therefore, improvement of the water quality in Gap and Miho streams is essential and a prerequirement to meet the target water quality level of the study area.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.227-239
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• 2019

Heavy snowfall events frequently occur in the Gangwon province, and the snowfall amount significantly varies in space due to the complex terrain and topographical modulation of precipitation. Understanding the spatial characteristics of heavy snowfall and its prediction is particularly challenging during snowfall events in the easterly winds. The easterly wind produces a significantly different atmospheric condition. Hence, it brings different precipitation characteristics. In this study, we have investigated the microphysical characteristics of snowfall in the windward and leeward sides of the Taebaek mountain range in the easterly condition. The two snowfall events are selected in the easterly, and the snow particles size distributions (SSD) are observed in the four sites (two windward and two leeward sites) by the PARSIVEL distrometers. We compared the characteristic parameters of SSDs that come from leeward sites to that of windward sites. The results show that SSDs of windward sites have a relatively wide distribution with many small snow particles compared to those of leeward sites. This characteristic is clearly shown by the larger characteristic number concentration and characteristic diameter in the windward sites. Snowfall rate and ice water content of windward also are larger than those of leeward sites. The results indicate that a new generation of snowfall particles is dominant in the windward sites which is likely due to the orographic lifting. In addition, the windward sites show heavy aggregation particles by nearby zero ground temperature that is likely driven by the wet and warm condition near the ocean.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.335-341
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• 2019

In order to provide basic data for uniformization of temperature distribution in heating greenhouses, heating experiments were performed in two greenhouses with a hot water heating system. By analyzing heat transfer characteristics and improving pipes layout, measures to reduce the variation of pipe surface temperature and to improve the uniformity were derived. As a result of analyzing the temperature distributions of two different greenhouses and examining the maximum deviation and uniformity, it was found that the temperature deviation of greenhouses with a large amount of hot water flow and a short heating pipe was small and the uniformity was high. And it was confirmed that the temperature deviation was reduced and the uniformity was improved when the circulating fan was operated. The correlation between the surface temperature of the heating pipe and the indoor air temperature was a positive correlation and statistically significant(p<0.01) in both greenhouses. It was confirmed that the indoor temperature distribution in a hot water heating greenhouse was influenced by the surface temperature distribution of heating pipe, and the uniformity of indoor temperature distribution could be improved by arranging the heating pipe to minimize the temperature deviation. Analysis of the heat transfer characteristics of heating pipe showed that the temperature deviation increased as the pipe length became longer and the temperature deviation became smaller as the flow rate in pipe increased. Therefore, it was considered that the temperature distribution and the uniformity of environment in a greenhouse could be improved by arranging the heating pipe to shorten the length and controlling the flow velocity in pipe. In order to control the temperature deviation of one branch pipe within $3^{\circ}C$ in the tube rail type hot water heating system most used in domestic greenhouses, when the flow velocity in the pipe is 0.2, 0.4, 0.6, 0.8, $1.0m{\cdot}s^{-1}$, the length of a heating pipe should be limited to 40, 80, 120, 160, 200m, respectively.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.801-809
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• 2019

Existing Gamma Knife Radiosurgery(GKRS) for large lesions is often conducted in stages with volume or dose partitions. Often in case of volume division the target used to be divided into sub-volumes which are irradiated under the determined prescription dose in multi-sessions separated by a day or two, 3~6 months. For the entire course of treatment, treatment informations of the previous stages needs to be reflected to subsequent sessions on the newly mounted stereotactic frame through coordinate transformation between sessions. However, it is practically difficult to implement the previous dose distributions with existing Gamma Knife system except in the same stereotactic space. The treatment area is expanding because it is possible to perform the multistage treatment using the latest Gamma Knife Platform(GKP). The purpose of this study is to introduce the image-coregistration based on the stereotactic spaces and the strategy of multistage GKRS such as the determination of prescription dose at each stage using new GKP. Usually in image-coregistration either surgically-embedded fiducials or internal anatomical landmarks are used to determine the transformation relationship. Author compared the accuracy of coordinate transformation between multi-sessions using four or six anatomical landmarks as an example using internal anatomical landmarks. Transformation matrix between two stereotactic spaces was determined using PseudoInverse or Singular Value Decomposition to minimize the discrepancy between measured and calculated coordinates. To evaluate the transformation accuracy, the difference between measured and transformed coordinates, i.e., ${\Delta}r$, was calculated using 10 landmarks. Four or six points among 10 landmarks were used to determine the coordinate transformation, and the rest were used to evaluate the approaching method. Each of the values of ${\Delta}r$ in two approaching methods ranged from 0.6 mm to 2.4 mm, from 0.17 mm to 0.57 mm. In addition, a method of determining the prescription dose to give the same effect as the treatment of the total lesion once in case of lesion splitting was suggested. The strategy of multistage treatment in the same stereotactic space is to design the treatment for the whole lesion first, and the whole treatment design shots are divided into shots of each stage treatment to construct shots of each stage and determine the appropriate prescription dose at each stage. In conclusion, author confirmed the accuracy of prescribing dose determination as a multistage treatment strategy and found that using as many internal landmarks as possible than using small landmarks to determine coordinate transformation between multi-sessions yielded better results. In the future, the proposed multistage treatment strategy will be a great contributor to the frameless fractionated treatment of several Gamma Knife Centers.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.657-664
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• 2021

In this study, we investigated the relationships between the air quality (PM_2.5, PM₁₀, O₃) concentrations and local geographical characteristics (terrain heights, building area ratios, population density in 9 km × 9 km gridded subareas) in the Seoul metropolitan area. To analyze the terrain heights and building area ratios, we used the geographic information system data provided by the NGII (National Geographic Information Institute). Also, we used the administrative districts and population provided by KOSIS (Korean Statistical Information Service) to estimate population densities. We analyzed the PM_2.5, PM₁₀, and O₃ concentrations measured at the 146 AQMSs (air quality monitoring system) within the Seoul metropolitan area. The analysis period is from January 2010 to December 2020, and the monthly concentrations were calculated by averaging the hourly concentrations. The terrain is high in the northern and eastern parts of Gyeonggi-do and low near the west coastline. The distributions of building area ratios and population densities were similar to each other. During the analysis period, the monthly PM_2.5 and PM₁₀ concentrations at 146 AQMSs were high from January to March. The O₃ concentrations were high from April to June. The population densities were negatively correlated with PM_2.5, PM₁₀, and O₃ concentrations (weakly with PM_2.5 and PM₁₀ but strongly with O₃). On the other hand, the AQMS heights showed no significant correlation with the pollutant concentrations, implying that further studies on the relationship between terrain heights and pollutant concentrations should be accompanied.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1421-1434
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• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.