• Journal of Nutrition and Health
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• v.56 no.6
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• pp.683-701
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• 2023

Purpose: The purpose of the study was to analyze the status of dietary behavior and nutrition intakes according to the gender and the level of physical activity of adolescents. Methods: Data from 659 adolescents aged 13 to 18 years who participated in the Korea National Health and Nutrition Examination Survey (2017-2018) were analyzed. Collected data were analyzed using complex sampling data analysis with SPSS v. 27.0. Results: The adolescents were categorized into three groups based on their physical activity as follows: The first group with high physical activity (8.9%), a second group with normal physical activity (29.7%), and a third group without physical activity (61.4%). Boys showed significantly higher physical activity than the girls. Adolescents with high physical activity had a significantly lower body mass index than adolescents without physical activity, but their meal regularity, subjective health status, and recognition of body image were significantly higher. In terms of biochemical factors, adolescents with high physical activity had lower triglycerides and cholesterol than adolescents without physical activity, while hemoglobin and hematocrit were significantly higher. In addition, the intakes of energy, carbohydrates, proteins, fat, vitamin B₁, niacin, calcium, phosphorus, sodium, potassium, iron increased significantly as adolescents' physical activity increased. Conclusion: The physical activity of adolescents had a positive effect on dietary behavior, lifestyle, and nutritional factors. Therefore, it is necessary to increase participation in physical classes in schools and develop various programs considering the level of physical activity among adolescents.

• The Korean Journal of Archival Studies
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• no.78
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• pp.197-249
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• 2023

This paper focus on the demand for broadcast and video archive contents by users outside broadcasters as the archive openness and sharing projects of terrestrial broadcasters have become more active in recent years. In the process of creating works using broadcasters' released video footage, the study examined the criteria by which video footage is selected and the methods and processes utilized for editing. To this end, the study analyzed the the case of the 5.18 footage video sharing project 〈May Story(Owol-Iyagi)〉 contest organized by KBS in 2022, in which KBS released its footage about the May 18 Democratic Uprising and invited external users to create new content using them. Analyzing the works that were selected as the winners of the contest, the research conducts in-depth interviews with the creators of each work. As a result, the following points are identified. Among the submitted works, many works deal with the direct or indirect experience of the May 18 Democratic Uprising and focus on the impact of this historical event on individuals and our current society. The study also examined the ways in which broadcasters' footage is used in secondary works. We found ways to use video as a means to share historical events, or to present video as evidence or metaphor. It is found that the need for broadcasters to provide a wider range of public video materials such as the May 18 Democratic Uprising, describing more metadata including copyright information before releasing selected footage, ensuring high-definition and high-fidelity videos that can be used for editing, and strengthening streaming or downloading functions for user friendliness. Through this, the study explores the future direction of broadcasters' video data openness and sharing business, and confirms that broadcasters' archival projects can be an alternative to fulfill public responsibilities such as strengthening social integration between regions, generations, and classes through moving images.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.435-445
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• 2023

The aim of this study was to explore the effects of vinegar extract from seed of common buckwheat (Fagopyrum esculentum Moench) and seed of tartary buckwheat (F. tataricum Gaertner) on acute ethanol-induced hangover in Sprague-Dawley rats. Vinegar extract from buckwheat is rich choline, quercetin and its glycoside, rutin known as flavonoid antioxidants. The test extract containing buckwheat was proven to alleviate hangovers through a significant reduction in the concentration of alcohol and acetaldehyde in the context of an alcohol-induced hangover model. Hepatic alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) activities were significantly higher in buckwheat vinegar-treated rats than in ethanol-treated rats. Moreover, tartary buckwheat vinegar upregulated antioxidant enzyme such as superoxide dismutase and Catalase activities in liver tissues. These results suggest that buckwheat vinegar extract could alleviate ethanol-induced hangover symptoms by elevating activities related to hepatic ethanol-metabolizing enzymes against ethanol induced metabolites, and in particular, tartary buckwheat should be further developed to be a novel anti-hangover material.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.455-468
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• 2023

We aimed to assess the potential growth-promoting effects of buckwheat sprout on intestinal bacteria and their anti-inflammation effects in a cellular model of intestinal inflammation. The growth of Bifidobacterium longum ssp. infantis BT1 was enhanced with the addition of the sprout extract of tartary buckwheat. Further, in the inflammatory model cells cultured with Raw 264.7 cells were treated with buckwheat sprout including each 10 probiotics before the addition of lipopolysaccharide (LPS) to induce inflammation in Raw 264.7 cells. Buckwheat sprout in both Bifidobacterium longum ssp. infantis BT1 and Lacticaseibacillus paracasei LPC5 significantly reduced the production of NO and PGE₂. The above results indicate that buckwheat sprout extract which contains with various physiologically active substances such as rutin, quercetin, and choline is effective in suppressing NO and PGE₂ production, which are inflammation-related indicators. The present study suggests that buckwheat sprout could induce positive effects on the intestinal beneficial bacteria and in anti-inflammation.

• Journal of Life Science
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• v.33 no.11
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• pp.887-896
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• 2023

The inflammatory response have been considered as one of important targets for cancer treatment because they play a key role during all steps of tumor development including initiation, promotion, malignant conversion and progression. To investigate the anti-inflammatory response during anti-tumor activity of an aqueous extracts of Ecklonia cava (AEC), alterations on the distribution of mast cells and the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), nuclear factor (NF)-κB, inflammasome compositional protein and inflammatory cytokines were examined in CT26 colon tumor-bearing BALB/cKorl syngeneic mice after administrating AEC for five weeks. After treatment of AEC, total weight of tumor and necrotic region of tumor section were significantly decreased compared to vehicle treated group. The number of infiltered mast cells was higher in AEC treated group than vehicle treated group, while the expression levels of COX-2 and iNOS were decreased in AEC treated group. Also, similar decrease pattern were detected in the expression levels of NF-κB, NLR family pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and caspase-1 (Cas-1) after AEC treatment although the decrease rate was varied. Furthermore, the mRNA expressions of three inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-1α (IL-1α) and interleukin-6 (IL-6) were remarkably decreased in AEC treated group compared to vehicle treated group. These results suggest that inhibition of inflammatory response may be tightly associated with anti-tumor activity of AEC in CT26 colon tumor-bearing BALB/cKorl syngeneic mice.

• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.54-70
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• 2023

Surveys and studies on cultural assets using LiDAR measurement are already active overseas. Recently, awareness of the advantages and availability of LiDAR measurement has increased in Korea, and cases of using it for surveys of cultural assets are gradually increasing. However, it is usually restricted to surveys of mountain fortresses and is not actively used for surveys of ancient tombs yet. Therefore, this study intends to emphasize the need to secure fundamental data from LiDAR measurement for the era from the Three Kingdoms to Unified Silla in which recovery, maintenance, etc., in addition to the actual surveys, are unfulfilled due to the sites being mainly distributed in mountainous areas. For this, LiDAR measurement was executed for the area of Jangsan Ancient Tombs and Chunghyo-dong Ancient Tombs in Seoak-dong, Gyeongju, to review the distribution and geographical conditions of ancient tombs. As a result, in the Jangsan Ancient Tombs, in which a precision archaeological (measurement) survey was already executed, detailed geographic information and distribution conditions could be additionally identified, which could not be known only with the layout indicated by the topographic map of the existing report. Also, in the Chunghyo-dong Ancient Tombs, in which an additional survey was not conducted after 10 tombs were found during the Japanese colonial period, the location of the ancient tombs initially excavated was accurately identified, and the status and additional information was acquired, such as on the conditions of ancient tombs not surveyed. Such information may also be used as fundamental data for the preservation and maintenance of future ancient tombs in addition to the survey and study of the ancient tombs themselves. LiDAR measurement is most effective for identifying the condition of ancient tombs in mountainous areas where observation is difficult or access is limited due to the forest zone. It may be executed before on-site surveys, such as archaeological surveys, to secure data with high availability as prior surveys or pre-surveys. Therefore, it is necessary to secure fundamental data from LiDAR measurement in future surveys of ancient tombs and to establish a survey and maintenance/utilization plan based on this. To establish survey/study and preservation/maintenance measures for ancient tombs located in mountainous areas, a precision archaeological survey is currently executed to draw up a distribution chart of ancient tombs. If LiDAR measurement data is secured before this and used, a more effective and accurate distribution chart can be drawn up, and the actual conditions can be identified. Also, most omissions or errors in information can be prevented in on-site surveys of large regions. Therefore, it is necessary to accumulate fundamental data by actively using LiDAR measurement in future surveys of ancient tombs.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.502-514
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• 2023

This study was conducted to understand the long-term changes in soil physiochemical properties and seedling growth in Larix kaempferi (larch) stands planted in clear-cut larch and Pinus rigida (pine) forest soils over an 11-year period after reforestation. Two-year-old bare-root larch seedlings were planted in 2009-2010 at a density of 3,000 seedlings ha^-1 in clear-cut areas that harvested larch (Chuncheon and Gimcheon) and pine (Wonju and Gapyeong) stands. We analyzed the physiochemical properties of the mineral soils sampled at 0-20 cm soil depths in the planting year, and the 3^rd, 7^thand 11^th years after planting, and we measured seedling height and root collar diameter in those years. We found significant differences in soil silt and clay content, total carbon and nitrogen concentration, available phosphorus, and cation exchangeable capacity between the two stands; however, seedling growth did not differ. The mineral soil was more fertile in Gimcheon than in the other plantations, while early seedling growth was greatest in Gapyeong. The seedling height and diameter at 11 years after planting were largest in Wonju (1,028 tree ha^-1) and Chuncheon (1,359 tree ha^-1) due to decreases in stand density after tending the young trees. The soil properties in all plantations were similar 11 years after larch planting. In particular, the high sand content and high available phosphorus levels (caused by soil disturbance during clear-cutting and planting) showed marked decreases, potentially due to soil organic matter input and nutrient uptake, respectively. Thus, early reforestation after clear-cutting could limit nutrient leaching and contribute to soil stabilization. These results provide useful information for nutrient management of larch plantations.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.