• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.582-591
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• 2022

This study was conducted to eliminate Myocastor coypusMolina, 1782 (Nutria) from Jeju Special Self-Governing Province, South Korea. Habitat identification and eradication were carried out from September to November 2013, and a survey was carried out until June 2022 to check whether the eradication was successful. The habitat was identified with unmanned cameras, interviews, and literature surveys, and the capture was performed using the trapping method with food to attract nutria to the habitat area. The study area for the follow-up survey, which was set relatively wide considering nutria's home range, included wetlands and rivers within 4.0 km² of the habitat area (eradication area). As a result, nutria's habitat was confirmed only at Songdang Ranch, Songdang-ri, of Jeju Island, with traces of habitat (footprints, excrement, and burrows) confirmed in waterways and ponds within the pasture. Eight individuals were captured, including four females, three males, and one individual in too advanced a state of decay to identify the sex. The follow-up survey thoroughly investigated the habitat and its surroundings, focusing on three areas with permanent water, Seongeup Reservoir, Cheonmi Creek, and Molsuni Pond, but no signs of habitat were identified. Therefore, it is determined that nutria inhabiting Jeju Island has been completely eradicated. It is believed that the successful eradication of nutria in the Jeju Special Autonomous Region was possible due to a synergy between 1) the eradication of nutria at the beginning of the settlement phase through rapid capture after confirming the nutria habitat and 2) the delayed expansion period because of rare presence of wetlands, where water is constantly stagnant, on Jeju Island. These results imply that quickly identifying the ecological characteristics of the species and preventing disturbances before they or at the beginning of the ecological disturbance through control and eradication at the initial stage of settlement before the expansion stage is an effective measure to cope with the influx of alien species.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• The Journal of KAIRB
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• v.2 no.1
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• pp.23-31
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• 2020

Purpose: To obtain opinions from Korean Institutional Review Board (IRB) members' self-evaluation on ability to conduct fairness review of clinical trial protocol with presence of conflict of interest and from investigators and IRB members on financial conflict of interest through surveying. Methods: IRB members and researchers in 9 different hospitals were asked to answer survey questions via email. Results: Responders were 115 personnel (IRB Chair/vice 18, medical member 30, non-medical member 28, and researcher 39) from 9 centers. Compared to IRB medical members, IRB chair/vice respondents scored higher with statistically significance on 10 point scale (8.44±1.381 vs. 7.30±1.685, p=0.005) when asked to self-evaluate fairness reviewing a protocol proposed by an investigator from the same department and a protocol from the company that supports the scientific committee of responders. When reviewing a protocol proposed by a hospital director, non-medical members scored statistically significantly higher than medical-members (7.47±1.76 vs. 8.07±2.70, p=0.034). When asked about the limitation of labor fee for principal investigator on phase 3 Human clinical trials of the Investigational new drug, while the responses range was wide, 60% answered that labor cost of principal investigator should be less than 30% of total budget for clinical trials with a budget of 100 million won. 51.3% answered that there is no need to disclose the labor cost of the principal investigator in the consent form. Since every investigator can be influenced unconsciously by conflict of interest, the answer that 'responder agrees that there is need for management' was the most chosen answer (IRB member 61.8%, investigator 64.1%, multiple answers allowed). Conclusion: Considering scores on questions of fairness by IRB members were between 7.23-8.56 on scale of 0 to 10 point when IRB members were asked about reviewing a clinical trial protocol, it cannot be said with absolute certainty that there is no issue regarding fairness in the review process. Therefore, there should be more ways to safeguard fairness for these issues. There is a need that the disclosure amount of honorarium from sponsor should be lower than 100 million Korean won. Considering the results of the survey in which respondents expressed their thoughts, it is likely that more education on the concept of conflict of interest is needed.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.274-283
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• 2023

Buffer zones, an example of nature-based solutions, offer wide range of environmental, social and economic benefits due to their multifunctionality when applied to watershed areas promoting blue-green connectivity. This study evaluated the effects of buffer zone application to the water quality of Yongdam reservoir tributaries. Particularly, the challenges and improvement of the buffer zone design were identified and suggested, respectively. Water and soil samples were collected from a total of six sites in Yongdam reservoir from September 2021 to April 2022. Water quality analyses revealed that among the sites monitored, downstream of Sangjeonmyeon Galhyeonri (SG_W_D2) was found to have the highest concentration for water quality parameters turbidity, total suspended solids (TSS), chemical oxygen demand (COD), total phosphorus (TP) and total nitrogen (TN). This finding was attributed to the algal bloom observed during the sampling conducted in September and October 2021. It was found through the soil analyses that high TN and TP concentrations were also observed in all the agricultural land uses implying that nutrient accumulation in agricultural areas are high. Highest TN concentration was found in the agricultural area of Jeongcheonmyeon Wolpyeongri (JW_S_A) followed by Jucheonmyeon Sinyangri (JS_S_A) while the lowest TN concentration was found in the original soil of Sangjeonmyeon Galhyeonri (SG_S_O). Among the types of buffer zones identified in this study, Type II-A, Type II-B and Type III were found to have blue-green connectivity. However, initially, blue-green connectivity in these buffer zone types were not considered leading to poor design and poor performance. As such, improvement in the design considering blue-green network and renovation must be considered to optimize the performance of these buffer zones. The findings in this study is useful for designing buffer zones in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.730-741
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• 2023

Purpose: The 2020 Dietary Reference Intakes for Koreans (KDRIs) serves as a foundation for daily nutrient and energy recommendations aiming to enhance public health and prevent chronic diseases. They act as guidelines for maintaining proper nutrition and overall health. Using KDRIs is crucial for promoting healthier lifestyles and making informed dietary choices. Thus, this study explores the influence of a nutrition education program, based on the 2020 KDRIs, on the nutrition knowledge and dietary habits of undergraduates in Gyeongsangnam-do and Gyeonggi-do. Methods: The nutrition education program, designed with diverse instructional materials, was executed across a wide range of universities. The education group (n = 75) engaged in the program for a 6-week instructional period, while the control group (n = 53) underwent the survey without participating in the education program. Nutrition Quotient (NQ) and knowledge assessments were administered to both groups immediately before and after the instructional period. Results: Within the education group, the nutrition education program positively impacted responses to NQ practice items, including knowledge of nutrition, daily intake, and portion sizes (p < 0.05). In contrast, there were no significant differences between the before and after responses of the control group for most survey items. Post-program evaluations showed significantly higher self-assessment scores and increased satisfaction levels (p < 0.05), with the satisfaction rate for the education program using the 2020 KDRIs reaching 99.2%. Conclusion: This study has demonstrated the positive impact of an effective nutrition education program. However, there is a need for the continuous development and implementation of nutrition education programs to sustain these outcomes and further enhance the nutritional education experience.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.114-120
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• 2023

Soybean is the one of the most important crops for providing quality vegetable protein to umans and livestock. Soybean cultivars with a brown seed coat have a wide range of antioxidant benefits because of the flavonoid components. However, they also contain lectin, 7S α′ subunit, lipoxygenase, and Kunitz trypsin inhibitor (KTI) proteins that can be allergenic and digestive inhibitors and reduce processing aptitude. Genetic removal of these four proteins is necessary in soybean breeding. Therefore, this study was conducted to select a new line with brown seed coat, green cotyledon, and tetra-null genotype (lecgy1lox1lox2lox3ti) for lectin, 7S α′ subunit, lipoxygenase, and KTI proteins in the mature seed. Five germplasms were used to create breeding population. From a total of 58 F₂ plants, F₂ plants with lele genotype were selected using a DNA marker, and F₃ seeds with a brown seed coat, green cotyledon, and the absence of 7S α′ subunit protein were selected. Three lines (S1, S2, and S3) were developed. Genetic absence of lectin, 7S α′ subunit, lipoxygenase, and KTI proteins was confirmed in F₆ seeds of the three lines, which had a brown seed coat, green cotyledons, and a white hilum. The 100 seed weights of the three lines were 26.4-30.9 g, which were lower than 36 g of the check cultivar - 'Chungja#3'. The new S2 line with 30.9 g hundred seed weight can be used as a parent to improve colored soybean cultivars without antinutritional factors such as lectin, 7S α′ subunit, lipoxygenase, and KTI proteins.

• Journal of Life Science
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• v.33 no.12
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• pp.1002-1014
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• 2023

The root of Cirsium japonicum var. maackii (Maxim.) has long been used in traditional medicine to prevent the onset and progression of various diseases and has been reported to exert a wide range of physiological effects, including antioxidant activity. However, research on its effects on hepatocytes remains scarce. This study used the human hepatocellular carcinoma HepG2 cell line to investigate the antioxidant activity of ethanol extract of C. japonicum root (EECJ) on hepatocytes. Hydrogen peroxide (H₂O₂) was used to mimic oxidative stress. The results showed that EECJ significantly reverted the decrease in cell viability and suppressed the release of lactate dehydrogenase in HepG2 cells treated with H₂O₂. Moreover, an analysis of changes in cell morphology, flow cytometry, and microtubule-associated protein light chain 3 (LC3) expression showed that EECJ significantly inhibited HepG2 cell autophagy induced by H₂O₂. Furthermore, it attenuated H₂O₂-induced apoptosis and cell cycle disruption by blocking intracellular reactive oxygen species and mitochondrial superoxide production, indicating strong antioxidant activity. EECJ also restored the decreased levels of intracellular glutathione (GSH) and enhanced the expression and activity of superoxide dismutase and GSH peroxidase in H₂O₂-treated HepG2 cells. Although an analysis of the components contained in EECJ and in vivo validation using animal models are needed, these findings indicate that EECJ is a promising candidate for the prevention and treatment of oxidative stress-induced liver cell damage.