• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.320-329
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• 2023

Cadmium (Cd), a heavy metal found in the aquatic environment, accumulates in organisms through the food chain. In the study, we investigated the survival rates, measurement of body Cd levels, and expression analysis of the stress response genes (Heat shock protein 70: HSP70 and Heat shock protein 60: HSP60) and antioxidant enzyme Glutathione S-Transferases (GST) on benthic oligochaete worm Tubifex tubifex exposed three concentrations of Cd, to analyze the bioaccumulation and changes of stress gene expressions to exposure toxicity of the Cd-spiked sediment. Survival rates of T. tubifex exposed to the Cdspiked sediment were 93% at 0.4 mg kg^-1 Cd, 96% at 1.87 mg kg^-1 Cd, and 93% at 6.09 mg kg^-1 Cd for 10 days. Cd concentration in the body of T. tubifex was higher than that in the sediment. After Cd exposures for 10 days, the body Cd levels were 18.4 mg kg^-1, 13.06 mg kg^-1, and 79.11 mg kg^-1 at exposed three concentrations of Cd, respectively. Upregulation of HSP70 gene expression was observed at all concentrations of exposed Cd as a time-dependent manner, whereas transcriptional expression of the HSP60 gene increased as a timedependent manner in T. tubifex exposed to the relative high concentration (6.09 mg kg^-1) of Cd. However, GST gene expression increased on day 1 at all concentrations after Cd exposures, and then downregulated until 10 days. These results indicate to ecotoxicological and molecular effects in benthic oligochaete worm T. tubifex to Cd-spiked sediment and provide the basic information for the utilization of environmental toxicity assessment using the T. tubifex as a aquatic pollution indicator species.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.714-729
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• 2023

Purpose: Since the coronavirus pandemic, the number of obese people has increased, and accelerated aging has been reported, particularly among young population. Therefore, this study analyzed the dietary habits of university students according to their risk of obesity to provide data for improving their eating habits. Methods: Ninety students at Daegu Catholic University were surveyed for their eating habits and photo-enhanced meal intake. The obesity risk was categorized as normal if the body mass index (BMI) and percent body fat (PBF) were normal, at-risk if both indicated overweight or obese, obesity in BMI alone were analyzed as BMI group and those with obesity in percent body fat alone were analyzed as PBF group. Results: There were 23 (25.5%) in the normal group, 10 (11.1%) in the BMI group, 24 (26.7%) in the PBF group and 33 (36.7%) in the at-risk group. The dietary survey showed that the risk groups had lower consumption frequencies of vegetables (p < 0.05) than the normal group, had less sleep time (p < 0.05) and higher frequency of fast food consumption (p < 0.001). The intake of vegetables was significantly higher in the normal group than in the risk group (p < 0.05). In terms of the daily nutrient intake, there was no significant difference in energy intake according to the obesity risk, but the intakes of dietary fiber (p < 0.01), vitamin A (p < 0.01), vitamin C (p < 0.01) were higher in the normal group than in the risk groups. Conclusion: Therefore, it is important to consider the BMI and percent body fat together to diagnose obesity and provide nutrition education and counseling.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.697-714
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• 2023

The Tracksite of Cretaceous Dinosaurs and Pterosaurs in Jeongchon, Jinju was discovered in late 2017 during the construction of the Ppuri industry complex. This site is a natural heritage site with a high paleontological value, as it preserves fossils of various types of dinosaurs, pterosaurs, and animal traces at a dense concentration. In this study, we surveyed that physical weathering such as joint, crack, scaling, exfoliation, and fragmentation occurred through field research in the fossil site, and conducted basic research on conservation science to reduce the damage. To this end, among the eight levels identified after excavation, the rocks of Level 3, which yielded a large number of theropod footprint fossils, and Level 4, which yielded pterosaur footprint fossils, were analyzed for material characteristics and evaluation of the effectiveness of consolidation and adhesion. This results showed that the rocks in the Level 3 stratum were dark gray siltstone and the rocks in the Level 4 stratum were dark gray shale, which contained a large amount of calcite and were composed of quartz, plagioclase, mica, alkali feldspar, and other clay minerals, which are likely to be damaged by rainfall under external conditions. As a result of conducting an artificial weathering experiment by dividing the probationary sample into four groups: untreated, consolidation treatment, anti-swelling treatment, and adhesive treatment, the consolidation and the swelling inhibitor showed an effect immediately after treatment, but did not show a blocking effect under a freezing-thawing environment. The adhesive showed that the adhesive effect was maintained even under freezing-thawing conditions. In order to preserve the fossil sites at Jeongchon in the future, in addition to temporary measures to block the inflow of moisture, practical measures such as the construction of protective facilities should be prepared.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.132-158
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• 2023

The five-story and seven-story stone pagodas at Cheongnyangsaji temple site in Gongju are located under the Sambulbong peak of Gyeryongsan mountain, and are known to have been built of the middle in Goryeo dynasty. As the two pagodas in which two types of Baekje stone pagoda coexist in one era, their historical and academic value are recognized. The seven-story pagoda was overturned by robbery in 1944, and as a result, the five-story pagoda was tilted. Although the two pagodas were restored in 1961, structural instability was continuously raised. In this study, measurement data accumulated from May 2021 to March 2022, and seasonal characteristics were reviewed, and the micro behavior of pagodas were analyzed according to temperature and precipitation during the same period. As a result, the micro thermoelastic behavior was repeated according to the daily temperature change in all sensors, and both the slope and the displacement showed microscale behavior. In the inclinometer, moisture containing the surface and inside of the stones repeated expansion and contraction due to temperature change, showing the micro movements. In particular, the upper part of the five-story pagoda moved up to 3.89° to the northwest, and the seven-story pagoda tilted up to 0.078° to the northeast. The maximum displacements were recorded as 0.127 and 0.149 mm in the five-story and the seven-story pagoda, respectively. These values tended to return to the original position at the end of the measurement, but did not recover completely, indicating a state requiring precise monitoring. The result obtained through the study can be used as basic data for the stable conservation of the two stone pagodas. Based on the behavioral characteristics considering various environmental factors should be analyzed, and the preventive conservation through the maintenance of measurement system built this time should be continued.

• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.94-108
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• 2023

Onyanghaenggung Palace(temporary palace at Onyang) is an important cultural heritage that can substantially confirm the king's onhaeng(溫行) base on literature records such as <Ongungyeonggoedae(溫宮靈槐臺)>, <Oncheonhaenggungdo(溫泉行宮圖)> of 『Ongungsasil(溫宮事實)』『, Younggoedaegi(靈槐臺記)』and cultural property such as Yeonggoedae(靈槐臺) and Shinjeong Monument(神井碑). As the Onyang Tourist Hotel is located in the presumed site of the Onyanghaenggung Palace, even the identity of the Onyanghaenggung Palace site is being threatened without restoration efforts. The purpose of this study is to estimate the location of Onyanghaenggung Palace based on <Oncheonhaenggungdo> before the damages during the Japanese colonial period. To achieve these purposes, records related to Onhaeng during successive kings' terms in the Joseon Dynasty are first reviewed, before changes in the architecture of Onyanghaenggung Palace that took place in the Joseon Dynasty and damage suffered during the Japanese colonial period are summarized, and finally <Oncheonhaenggungdo>, <Eupji>, <Ancient Maps>, <Jijeokwondo> are reviewed. Based on these processes, the location of Onyanghaenggung Palace is estimated by comparing the current Onyang Tourist Hotel and the surrounding area. The results of this study are as follows. First, if the 1,758 cheok(尺) of 「Onyanggun eupji」 and 「Hoseo eupji」 are converted in Jucheok(周尺), the scope of Onyanghaenggung Palace is close to the inner circumference of the site(垈) in Jijeokwondo(1914). Second, the streamlet leading to Oncheoncheon(溫泉川) from the southern side of Onyanggwan(溫陽館), the hot spring hole in use of <Distribution Map of Hot Spring(溫泉分布見取圖)>(1925, 1928), and considering the relationship of the inner east gate(內東門), Bigak(碑閣), Sinjeong(神井) of <Oncheonhaenggungdo>, the building of Hermann Gustav Theodor Sander and the Copyright Commission's Onyang Hot Springs photograph can be estimated as the Onyanghaenggung Palace Hot-spring, namely Tangsil(湯室). Third, in the process of developing to amusement park, the transfer and relocation of the Yeonggaedae site(a governmentowned property) was requested by Gyeongnam Railway Company, but Chungcheongnam-do denied transfer and relocation of the Yeonggaedae because of the importance in the history of Onyang Hot Springs, so the government-owned Yeonggaedae Monument site were permanently preserved at the current location together with the hoe tree(Sophora japonica L.). Also, Yeonggoedae in <Tourists Attractions around Gyeongnam Railway in Joseon (朝鮮京南鐵道沿線名所交通図絵)> (1929) is shown to exist in its current location, and it can be seen that the Shinjeong Monument Pavilion was moved to the front of Shinjeonggwan (神井館). Based on the circumference of Onyanghaenggung Palace, the location of Onyanghaenggung Palace Hot Spring (Tangsil) and Yeonggaedae Monument Pavilion, changes in roads and lots of land during the Japanese colonial period and the modern period, as well as the location of Onyanghaenggung Palace and other major buildings, can be estimated to extend to the current Shimin-ro and Onyang Hot Spring Market.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1605-1613
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• 2023

The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R² and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Korean Journal of Culture and Social Issue
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• v.10 no.1
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• pp.1-30
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• 2004

Study 1 composed of three experiments examined differences in person perception between computer-mediated (or CMC) and face-to-face (or FTF) communications. In Experiment 1, each of 17 groups of 4-5 discussed a donation entrance system through CMC and a week later a college-based university system through FTF communication mode for half an hour. Then members of a given group rated each other along with self-ratings on five personality traits. Results indicated that in FTF than CMC condition, ratings of others were more positive and also self-peer agreement and meta-accuracy were larger in spite of no large difference in inter-judge agreement between two communication modes. In Experiment 2, 17 groups of 4 in each of the CMC and FTF condition discussed a college-based university system for an hour. Then group members rated each other on another five trait dimensions. Although ratings of others were more positive in FTF than CMC condition, there no systematic differences in two types of agreement and meta-accuracy between the two communication modes. In Experiment 3, 17 groups of 4 in each of the CMC and FTF condition discussed a donation entrance system for an hour and then group members rated each other on five trait dimensions different from those used in Experiment 1 and 2. The findings replicated Experiment 1. Study 2 examined gender differences in person perception in CMC. Fifteen dyads for each of the man-man, man-woman, and man-woman conditions communicated for an half hour in CMC and then rated each other along with self ratings on 25 personality trait dimensions. Results indicated that participants rated their partners more negatively for extorversion, agreeableness and culture factors, which was due mainly to woman's negative evaluations for their male partners. Also, self-peer agreement was the largest in the man-man communication condition. These findings were discussed in relation to differences between CMC and FTF communication modes.