• Journal of Life Science
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• v.28 no.12
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• pp.1406-1415
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• 2018

Based on the antioxidative effects in organic solvent fractions obtained from the main methanolic extract of Houttuynia cordata Thunb, the cytoprotective effects by oxidative-stress were here analyzed. Regarding the antioxidant activity of organic solvent fractions, the electron-donating ability of DPPH increased in a dose-dependent manner, and $ED_{50}$ exhibited the highest concentration at $175{\mu}g/ml$ in the Hc-EtOAc fraction. The cell viability of Hc-EtOAc fractions on $H_2O_2$-induced HaCaT cell death ($IC_{50}$) increased in a concentration-dependent manner and a visible cell survival rate of 74% was observed at a concentration of $100{\mu}g/ml$. Meanwhile, the gene expression patterns in HaCaT cells treated with $100{\mu}g/ml$ of the Hc-EtOAc fraction for 6 and 24 hr were identified with microarray analysis. The genes involved in signal transduction, cell division, antioxidant activity, and epithelial cell proliferation were found to be 2-fold up-regulated genes in HaCaT cells following the Hc-EtOAc fraction treatment. Especially, proinflammatory cytokines (IL1B, TNF, and IL6) were identified as involved in antioxidant activity based on the expression patterns of the HaCaT cells, and pathway analysis indicated that TLR4 might be considered an upstream regulator of these genes. In order to verify the activity of IL1B, TNF, and IL6, qRT-PCR showed that the expression increased more than 2 times in HaCaT cells treated with at least $100{\mu}g/ml$ of the Hc-EtOAc fraction. The activity of the upstream regulator TLR4 protein was also increased by the Hc-EtOAc fraction. As a result, the antioxidative activity of the Hc-EtOAc fraction is predicted to pass from TLR4 through cytokines such as IL1B, TNF, and IL6.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.268-276
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• 2021

As wireless communication devices become more common, interests in how to control the electromagnetic waves generated from the devices are increasing. One of the most commonly used electromagnetic wave control materials is magnetic one, but due to the features that make the product heavy and thick when applied to the product, it is difficult to use them in curved electronic devices. Therefore, a polymer flexible meta electronic device has been presented to sort out the problem, which is thin and can have various curvatures. However, it requires an additional evaluation of curvature reliability. In this study, we developed a method to predict electromagnetic wave control characteristics through the resistance/length of the conductive ink line patterns of polymer flexible meta electronic devices, which is inversely proportional to the electromagnetic wave control characteristics. As the radius of curvature decreased, the resistance/length increased, and there was little variations with the duration times of curvature. We also found that both permanent and recoverable changes along with the removal of curvature were occurred when the curvature was applied, and that the cause of these changes was newly created vertical cracks in the conductive ink line pattern due to the tensile stress applied by applying curvature.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.41-54
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• 2021

It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.334-346
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• 2022

There is a lack of knowledge and information on the understanding and application of the Process Safety Management (PSM) system, recognized as a major cause of industrial accidents in small-and medium-sized workplaces. Hence, it is necessary to prepare a protocol to secure the practical and continuous levels of implementation for PSM and eliminate human errors through tracking management. However, insufficient research has been conducted on this. Therefore, this study investigated and analyzed the various violations in the administrative measures, based on the regulations announced by the Ministry of Employment and Labor, in approximately 200 small-and medium-sized PSM workplaces with fewer than 300 employees across in korea. This study intended to contribute to the prevention of major industrial accidents by developing a facility maintenance web program that removed human errors in small-and medium-sized workplaces. The major results are summarized as follows. First, It accessed the web via a QR code on a smart device to check the equipment's specification search function, cause of failure, and photos for the convenience of accessing the program, which made it possible to make requests for the it inspection and maintenance in real time. Second, it linked the identification of the targets to be changed, risk assessment, worker training, and pre-operation inspection with the program, which allowed the administrator to track all the procedures from start to finish. Third, it made it possible to predict the life of the equipment and verify its reliability based on the data accumulated through the registration of the pictures for improvements, repairs, time required, cost, etc. after the work was completed. It is suggested that these research results will be helpful in the practical and systematic operation of small-and medium-sized PSM workplaces. In addition, it can be utilized in a useful manner for the development and dissemination of a facility maintenance web program when establishing future smart factories in small-and medium-sized PSM workplaces under the direction of the government.

• Journal of Korean Living Environment System
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• v.16 no.2
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• pp.89-100
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• 2009

The present study was designed to observe the thermal dynamics of core and skin temperatures during sub-maximal treadmill exercise; to investigate the effect of regional body cooling during short rest after the treadmill exercise on the thermal dynamics. Three conditions (No cooling, Head/Hand cooling, Leg cooling) were simulated in a climatic chamber at 24±1℃ and 50±5%RH. Subjects performed two bouts of treadmill exercise at a rate of 80%HR_max followed by rest. Body cooling with a hood, long gloves, and a blanket that circulated water set at 15℃ was assigned during two bouts of rest. The results showed that (1) rectal temperature (T_re) did not show significant difference between three conditions; (2) Skin temperatures had specific features, depending on body regions. In particular, the initial fall phenomena of skin temperatures at the onset of exercise were noteworthy in the chest, thigh, calf, and finger tip. Of these, the most significant initial fall was found in finger temperature (T_fing). (3) During the period of the initial fall in skin temperatures, T_re gradually increased. (4) The magnitude of the fall of T_fing at the onset of 2^nd running was on average 4.8, 5.1 and 3.4℃ for Control, HH cooling, and Leg cooling, respectively (p<0.05). The initial drop of T_fing at the onset of running was maintained for an average of 8.1, 7.9 and 6.3 minutes for Control, HH cooling, and Leg cooling, with no significant differences. In conclusion, the initial fall phenomena at the onset of treadmill exercise reflected non-thermal factors, as opposed to internal thermal status. The magnitude of the initial fall in T_fing was affected by legs cooling. Therefore, the initial fall phenomenon should be considered when interpreting the thermal status of the shell during heavy works/exercises that assigned with intermittent regional body cooling.

• Atmosphere
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• v.32 no.1
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• pp.61-70
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• 2022

This study evaluates the economic values for the several first precipitation events during Changma period. The selected three years are 2015, 2019, and 2020, where average precipitation amounts across the 58 Korean stations are 12.8, 20.1 and 13.3 mm, respectively. The four categories are used to assess the values including air quality improvement, water resource acquisition/accumulation, drought mitigation, and forest fire prevention/recovery. Economic values for these three years are estimated 50~150 billion won. Among the four factors considered, the effect of air quality improvement is most highly valued, amounting to 70 to 90% of the total economic values. Wet decomposition of air pollution (PM₁₀, NO₂, CO, and SO₂) is the primary reason. The next valuable element is water resource acquisition, which is estimated 9~15 billion won. Effects of drought mitigation and fire prevention are deemed relatively small. This study is the first to estimate the value of the precipitation events during Changma onset. An analysis for more Changma years will be performed to achieve a more reliable estimate.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.225-232
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• 2024

This study focuses on the determination of the fracture mode in composite laminates using deep learning. With the increase in the use of laminated composites in numerous engineering applications, the insurance of their integrity and performance is of paramount importance. However, owing to the complex nature of these materials, the identification of fracture modes is often a tedious and time-consuming task that requires critical domain knowledge. Therefore, to alleviate these issues, this study aims to utilize modern artificial intelligence technology to automate the fractographic analysis of laminated composites. To accomplish this goal, scanning electron microscopy (SEM) images of fractured tensile test specimens are obtained from laminated composites to showcase various fracture modes. These SEM images are then categorized based on numerous fracture modes, including fiber breakage, fiber pull-out, mix-mode fracture, matrix brittle fracture, and matrix ductile fracture. Next, the collective data for all classes are divided into train, test, and validation datasets. Two state-of-the-art, deep learning-based pre-trained models, namely, DenseNet and GoogleNet, are trained to learn the discriminative features for each fracture mode. The DenseNet models shows training and testing accuracies of 94.01% and 75.49%, respectively, whereas those of the GoogleNet model are 84.55% and 54.48%, respectively. The trained deep learning models are then validated on unseen validation datasets. This validation demonstrates that the DenseNet model, owing to its deeper architecture, can extract high-quality features, resulting in 84.44% validation accuracy. This value is 36.84% higher than that of the GoogleNet model. Hence, these results affirm that the DenseNet model is effective in performing fractographic analyses of laminated composites by predicting fracture modes with high precision.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.151-163
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• 2024

This study sought to confirm the impact of analytical methods and behavioral economic theory factors on decision-making when making chartering decisions in the dry bulk shipping market. This study on chartering decision-making model was began to verify why shipping companies do not make rational decision-making and behavior based on analytical methods such as freight prediction and process of alternative selection in the same market situation. To understand the chartering decision-making model, it is necessary to study the impact of behavioral economic theory such as heuristics, loss aversion, and herding behavior on chartering decision-making. Through AHP analysis, the importance of the method factors relied upon in chartering decision-making. The dependence of the top factors in chartering decision-making was in the following order: market factors, heuristics, internal factors, herding behavior, and loss aversion. Market factors, heuristics, and internal factors. As for detailed factors, spot freight index and empirical intuition were confirmed as the most important factors relied on when making decisions. It was confirmed that empirical intuition is more important than internal analysis, which is an analytical method. This study can be said to be meaningful in that it academically researched and proved the bounded rationality of humans, which cannot be fully rational, and sometimes relies on experience or psychological tendencies, by applying it to the chartering decision-making model in the dry bulk shipping market. It also suggests that in the dry bulk shipping market, which is uncertain and has a high risk of loss due to decision-making, the experience and insight of decision makers have a very important impact on the performance and business profits of the operation part of shipping companies. Even though chartering are a decision-making field that requires judgment and intuition based on heuristics, decision-makers need to be aware of this decision-making model in order to reduce repeated mistakes of deciding contrary to market situation. It also suggests that there is a need to internally research analytical methods and procedures that can complement heuristics such as empirical intuition.