• Korean Journal of Environment and Ecology
• /
• v.33 no.5
• /
• pp.525-538
• /
• 2019

The purpose of this study was to analyze the habitat status and species diversity of benthic diatoms and estimate the applicability of TDI (Trophic Diatom Index) to obtain the basic data for the identification and management of created wetlands in the Nakdong River. We observed a total of 38 families and 173 species of benthic diatom during the survey period, and spring and autumn showed a similar number of species of 156 and 154, respectively. The result of the SOM (Self-Organizing Map) analysis showed that the distribution of benthic diatom was sensitive to environmental factors such as nutrient concentration and rainfall in each wetland. The cluster 1 was characterized by the survey sites of autumn mostly and consisted of points of high TDI, although the nutrients such as total phosphorus and total nitrogen were low, and the species number and abundance of diatoms were low. Conversely, cluster 4 was characterized by the survey sites of spring mostly and consisted of points of low TDI, even though total nitrogen was high. Considering that most of the created wetlands had the reduced inflow and outflow, the increased flow rate in the summer lowers nutrient values in autumn, and the species number and abundance of benthic diatom decreases due to the increase of turbidity, which reduces the light penetrations to the substrates. On the contrary, the TDI value is low in spring because the low water level causes insufficient substrate surface to the benthic diatoms, and it is too early for the establishment and development of saprophilous species. Although various studies have used TDI as an indicator for evaluating the habitat environment and water quality, it is not a good evaluation indicator in this study since the nutrient concentration in the wetlands mostly high as they have a low flow rate and are close to the stagnant area. Nevertheless, additional periodic surveys that comprehensively reflect the fact that the summer rainfall and inflow/outflow regulating function might affect the species diversity and distribution of benthic diatoms are necessary.

• The Journal of Korean Society for Radiation Therapy
• /
• v.32
• /
• pp.53-59
• /
• 2020

Purpose: The purpose of this study is to compare and analyze the difference between the MLC log file-based software (Mobius) and the conventional phantom-ionization chamber (ArcCheck) dose verification method according to the change of target volume. Material and method: Radius 0.25cm, 0.5cm, 1cm, 2cm, 3cm, 4cm, 5cm, 6cm, 7cm, 8cm, 9cm, 10cm with a Sphere-shaped target Twelve plans were created and dose verification using Mobius and ArcCheck was conducted three times each. The irradiated data were compared and analyzed using the point dose error value and the gamma passing rate (3%/3mm) as evaluation indicators. Result: Mobius point dose error values were -9.87% at a radius of 0.25cm and -4.39% at 0.5cm, and the error value was within 3% at the remaining target volume. The gamma passing rate was 95% at a radius of 9cm and 93.9% at 10cm, and a passing rate of more than 95% was shown in the remaining target volume. In ArcCheck, the average error value of the point dose was about 2% in all target volumes. The gamma passing rate also showed a pass rate of 98% or more in all target volumes. Conclusion: For small targets with a radius of 0.5cm or less or a large target with a radius of 9cm or more, considering the uncertainty of DQA based on MLC log files, phantom-ionized DQA is used in complementary ways to include point dose, gamma index, DVH, and target coverage. It is believed that it is desirable to verify the dose delivery through a comprehensive analysis.

• Journal of Nutrition and Health
• /
• v.54 no.1
• /
• pp.10-22
• /
• 2021

Purpose: Key Foods refers to foods that have a high contribution in the nutrient intake of individuals, and exert important effects on their health. This study was undertaken to identify Korean Key Foods, using data from the 7th Korea National Health and Nutrition Examination Survey (KNHNES). Methods: The data source for the extraction of Key Foods was the 24-hour dietary survey data obtained from the 7th KNHNES (2016-2018), and 21,271 subjects were evaluated. A total of 17 nutrients were selected as the key nutrients for identifying the Key Foods, including energy, carbohydrates, protein, lipid, dietary fiber, calcium, phosphorus, iron, sodium, potassium, vitamin A, thiamin, riboflavin, niacin, vitamin C, cholesterol, and sugars. The nutrient consumption approach was applied to generate a list of potential Key Foods. Foods included in 85% of the cumulative intake contribution from one or more key nutrients, were subsequently selected as Key Foods. Results: Of the 1,728 foods consumed by survey respondents, we extracted 728 Key Foods. These Key Foods explained 94% key nutrient intakes of the subjects. Based on the contribution rate to key nutrient intake, the top 10 Key Foods identified were multigrain rice (5.32%), plain white rice (4.23%), milk (3.3%), cabbage kimchi (2.82%), grilled pork belly (1.56%), apples (1.52%), fried eggs (1.49%), cereal (1.36%), instant coffee mix (1.21%), and sweet potatoes (1.12%). These 10 foods accounted for 23.93% total key nutrient intake of the survey respondents. Conclusion: Seven hundred and twenty-eight foods were extracted and identified as the 2020 Korean Key Foods. These Key Foods can be considered the priority foods to be analyzed for establishing a national nutrient database.

• Journal of Nutrition and Health
• /
• v.54 no.3
• /
• pp.277-291
• /
• 2021

Purpose: This study was undertaken to identify the alcohol drinking status of industrial workers, their health care practice, and dietary behavior, as well as their nutrient intake. Methods: In July 2019, 220 male subjects working in the Chungnam area were enrolled in the study. Their alcohol drinking status was evaluated by applying the Alcohol Use Disorder Identification-K (AUDIT-K) system. Demographic characteristics, status of health care practice, and dietary behaviors were assessed using a self-administered questionnaire; nutrient intakes were analyzed using 24-hour recalls. Data were analyzed by applying χ²-test, ANOVA, Duncan test, and Pearson's correlation analysis with SPSS v. 25.0. Results: Workers were classified by their alcohol drinking status as 'normal' (84, 38.2%), 'problem drinker' (45, 20.5%), 'alcohol dependence I' (60, 27.3%), and 'alcohol dependence II' (31, 16.0%). The alcohol drinking status showed significant differences with age (p < 0.05), monthly income (p < 0.05), smoking status (p < 0.05), and need for weight control (p < 0.05). Moreover, increased alcohol intake resulted in significantly decreased levels of health care practice and dietary behaviors (p < 0.05, p < 0.01, respectively). The energy intake was highest in the 'alcohol dependence I' group, followed by 'alcohol dependence II', 'problem drinker', and 'normal drinker' (p < 0.05). Intakes of vitamin E, vitamin C, and niacin in the 'alcohol dependence I' group were found to be higher than the other groups (p < 0.05). A negative correlation was obtained between alcohol drinking status, health care practice, and dietary behaviors, whereas a positive correlation was determined between alcohol drinking status, energy and water intakes. Conclusion: Considering these results, we conclude the necessity to consider nutritional and alcoholic education programs for improving the quality of work life of industrial workers, based on their alcohol drinking status.

• Korean Journal of Remote Sensing
• /
• v.37 no.3
• /
• pp.543-557
• /
• 2021

Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.

• Journal of the Microelectronics and Packaging Society
• /
• v.27 no.4
• /
• pp.19-24
• /
• 2020

In this work, the electrical property of Si-doped β-Ga2O3 was investigated via a post-growth annealing process. The Ga2O3 samples were annealed under air (O-rich) or N2 (O-deficient) ambient at 800~1,200℃ for 30 mins. There was no correlation between the crystalline quality and the electrical conductivity of the films within the experimental conditions explored in this work. However, it was observed the air ambient led to severe degradation of the film's electrical conductivity while N2-annealed samples exhibited improvement in both the carrier concentration and Hall mobility measured at room temperature. Interestingly, the x-ray photoemission spectroscopy (XPS) revealed that both annealing conditions resulted in higher concentration of oxygen vacancy (VO). Although it was a slight increase for the air-annealed sample, high resistivity of the film strongly suggests that VO cannot be a shallow donor in β-Ga2O3. Therefore, the enhancement of the electrical conductivity of N2-annealed samples must be originated from something other than VO. One possibility is the activation of Si. The XPS analysis of N2-annealed samples showed increasing relative peak area of Si 2p associated with SiOx with increasing annealing temperature from 800 to 1,200℃. However, it was unclear whether or not this SiOx was responsible for the improvement as the electrical conductivity quickly degraded above 1,000℃ even under N2 ambient. Furthermore, XPS suggested the concentration of Si actually increased near the surface as opposed to the shift of the binding energy of Si from its initial chemical state to SiOx state. This study illustrates the electrical changes induced by a post-growth thermal annealing process can be utilized to probe the chemical and electrical states of vacancies and dopants for better understanding of the electrical property of Si-doped β-Ga2O3.

• Journal of Food Hygiene and Safety
• /
• v.36 no.1
• /
• pp.68-76
• /
• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.1
• /
• pp.70-82
• /
• 2021

The purpose of this study is to reveal the tendency of planting design through the analysis of the planting of designer's gardens in the Suncheon Bay National Garden and to derive implications for future garden planting designs. The results of the study are as follows: First, the results of the study show that the practice of tree-based planting is still valid. Large growing trees such as 'Pinus densiflrora', 'Celtis sinensis', 'Zelkova serrata', 'Machilus thunbergii', 'Pinus strobus' overwhelmed the size of the designer's garden(150 to 390㎡). Second, the selection of trees tended to be made considering the designer's intention and the decorative effects rather than by considering the physiological and ecological conditions of the site. Third, among the herbaceous, the rate of the planting of perennials was high. Fourth, the flowering period of planted herbaceous was the most common in summer, followed by spring, fall, and winter. Fifth, the frequency color of the planted herbaceous was the most common in summer, followed by spring, fall, and winter. Fifth, in terms of flower color frequency, the most common was the yellow-series, followed by red-series, blue-series Sixth, average height herbaceous plants(20~60cm) were planted the most(47.4%). Seventh, structural plants that determined the garden's framework depended on trees, and the focal plants mainly utilized were evergreen trees, and the midrange plants were the planted herbaceous plants. The implications derived from the above findings are as follows: First, to ensure the garden's quality and sustainability, the selection of trees should be carefully considered, not considering only the artist's intention but also taking into account the physical and ecological conditions. Second, herbaceous plants can be used in various ways― the garden's focal plants, midrange plants, and ground covers, so more active herbaceous planting needs to be considered. Third, in consideration of the winter landscape, herbaceous planting using characteristics, such as fruits and stems, as well as flower colors should be considered. Fourth, blue and black color herbaceous plants have a noticeable effect even in a small amount, so it is necessary to plant them actively. Fifth, for the design of herbaceous planting, where the individual property of plants can be expressed, the design method should be considered.

• Journal of Internet Computing and Services
• /
• v.21 no.6
• /
• pp.23-31
• /
• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of Technology Innovation
• /
• v.30 no.2
• /
• pp.29-58
• /
• 2022

Startups lack resources and manpower to build internal capabilities to strengthen market competitiveness; external cooperation such as joint research and networking plays is important. In this study, we analyzed the effect of startups' industry-university cooperation on organizational learning capability and innovation performance. Empirical results demonstrate the mechanism by which government R&D investment strengthens organizational learning capability and creates innovative results by promoting cooperation between startups and universities. First, industry-university cooperation strengthened organizational learning capability. An empirical analysis shows that startups increase internal capabilities through external cooperation. Second, startups' organizational learning capability had a significant effect on innovation performance. We analyze how organizations with high learning capabilities positively develop corporate innovation performance by having a culture of discovery and sharing new ideas. Finally, industry-university cooperation had different effects on organizational learning capability and innovation performance according to the previous experiences of startup founders. In particular, small- and medium-sized (startup) businesses and individual-based experience groups positively affected the creation of organizational learning capabilities and innovation performance through industry-university cooperation. Small- and medium-sized businesses and individual founders have a relatively small cooperative network with the outside world compared to founders of large companies, universities, and research institutes; therefore, they strengthen organizational learning capabilities through cooperation with universities. This study demonstrates that government should create policy inducements for cooperation with universities to maximize the R&D performance of startups. Criticism exists that lending support to startups and universities will hinder innovation performance; nevertheless, government investment plays a role in expanding intangible resources such as accumulating technologies, fostering high-quality human resources, and strengthening innovation networks. Therefore, the government should appropriately utilize the its authority to strengthen investment strategies for startup growth.