• Journal of Korean Medicine for Obesity Research
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• v.21 no.2
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• pp.69-79
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• 2021

Objectives: This study aimed to compare the anti-obesity effects of raw and pickled garlic in vitro in 3T3-L1 preadipocytes. Methods: The pickled garlic samples comprised the following: garlic aged in vinegar (VG), garlic aged in soy sauce, and vinegar (1:1, v/v) (PG) and raw garlic (RG) as control. Hexane, butanol, and distilled water were used to prepare the fractions. The pancreatic lipase inhibitory activity was used as a measure of anti-obesity effects of the extracts. The lipid droplet accumulation and triglyceride content in the 3T3-L1 cells were measured using Oil red O staining and triglyceride assay kits, respectively. The adipogenesis related protein expression levels were analyzed using the kits and the western blot method. Results: The pancreatic lipase inhibitory activity of the garlic extracts (VG, PG, RG) was the highest in the butanol fraction, and the inhibitory effect was the highest in RG, followed by PG and VG. All garlic butanol extracts suppressed triglyceride accumulation in differentiated adipocytes (P<0.05) through the activation of cyclic adenosine monophosphate (AMP), AMP-activated protein kinase, carnitine palmitoyl transferase-1, and the inhibition of fatty acid synthase. Raw garlic extracts significantly inhibited the expression of proteins involved in adipogenesis as compared to pickled garlic. Conclusions: Raw garlic has the potential to be an effective natural material for reducing obesity compared to pickled garlic with vinegar or soy sauce.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• Applied Microscopy
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• v.52
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• pp.5.1-5.10
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• 2022

The use of Pipelines for long-distance transportation of crude oil, natural gas and similar applications is increasing and has pivotal importance in recent times. High specific strength plays a crucial role in improving transport efficiency through increased pressure and improved laying efficiency through reduced diameter and weight of line pipes. TRIP-based high-strength and high-ductility alloys comprise a mixture of ferrite, bainite, and retained austenite that provide excellent mechanical properties such as dimensional stability, fatigue strength, and impact toughness. This study performs microstructure analysis using both Nital etching and LePera etching methods. At the time of Nital etching, it is difficult to distinctly observe second phase. However, using LePera etching conditions it is possible to distinctly measure the M/A phase and ferrite matrix. The fraction measurement was done using OM and SEM images which give similar results for the average volume fraction of the phases. Although it is possible to distinguish the M/A phase from the SEM image of the sample subjected to LePera etching. However, using Nital etching is nearly impossible. Nital etching is good at specific phase analysis than LePera etching when using SEM images.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.215-223
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• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• Journal of Korea Trade
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• v.26 no.4
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• pp.83-97
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• 2022

Purpose - In this paper, we, taking South Korea's foreign direct investment in RCEP partners as an example, will examine its investment efficiency in these countries and analyze the main influencing factors, making suggestions for further liberalizing and facilitating its investment in and even for promoting its trade and economic cooperation with them. Design/methodology - In this study, we look at the panel data of South Korea and the other 13 RCEP countries (Brunei excluded) from 2000 to 2019 and apply the stochastic frontier analysis to measure its foreign direct investment efficiency and explore the influencing factors in RCEP countries. We examine the investment potential of South Korea in these places. Findings - We find that South Korea's average investment efficiency in RCEP countries reached 0.62, indicating large investment potential. We also find that its investment efficiency in RCEP partners was heterogeneous. Our study reveals that South Korea's foreign direct investment is significantly positively correlated with the market size and population of the two countries, as well as with whether the host country has a coastline and rich natural resources, while negatively with geographic distance. It shows that free trade agreements, economic freedom, and regulatory quality play significant roles in improving investment efficiency. Originality/value - Through theoretical and empirical analysis, we deal with the efficiency and influencing factors of South Korea's direct investment in RCEP partners, proposing new drivers for facilitating its trade and investment in these countries and comprehensively evaluating the efficiency and revealing the trend of its FDI in these countries. In this paper, we put forward a solid theoretical basis for empirical analysis of the future economic and trade development between South Korea and its RCEP partners and give objective insights for further improving its foreign direct investment efficiency and tapping its investment potential.

• Advances in concrete construction
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• v.14 no.3
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• pp.185-194
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• 2022

For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R² metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.313-313
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• 2022

The Smilacis chinae Radix refers to the root of Smilax chinae L distributed in mountain and filed of Korea, and it is a vine shrub in the Lilaceae family, called Berchemia berchemiaefolia, and is referred to as Smilacis chinae Radix in it's a natural medicine name. Antibacterial, inflammatory, and antioxidant activity were studied in Smilacis chinae Radix. In this study, biological activities such as antioxidant (DPPH, ABTs, TPC), cytotoxicity, wrinkle improvement, and whitening improvement to increase the utilization value of Smilacis chinae Radix and identify the botanical value. Therefore, we tried to explore the applicability of Smilacis chinae Radix as a functional cosmetic material. Smilacis chinae Radix (SCR) was dried and extracted with ethanol. In order to measure the biological activity of the SCR, antioxidant activity, inhibition activities of collagenase, tyrosinase and cell viability were measured. The DPPH (1,1-diphenyl-2-picryl hydrazyl) radical scavenging activity in the extract with a concentration of 400㎍/mL is 91.22% ± 0.41%%. ABTs (2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid) radical scavenging activity in the extract with a concentration of 400㎍/mL is 99.60% ± 0.03%. Total polyphenol contents (TPC) are 0.203 ± 0.05 mg GAE/mg Ext when SCR was lmg/mL. And the Cell viability for HaCaT derived human keratinocyte and Raw264.7, a mouse-derived macrophage was determined using the MTT assay. When cell was treated with 100㎍/mL of SCR, HaCaT cell showed cell viability of 78.09 ± 0.1% and Raw264.7 cell showed cell viability of 91.88 ± 0.42%. From the above results, we have shown the possibility that the CSR have antioxidant ability, inhibition activity of collagenase and tyrosinase and cell safety ability which can be useful in a functional cosmetic material.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.108-108
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• 2022

In this study, multispectral images of wheat according to soil water state were collected, compared, and analyzed to measure the physiological response of crops to environmental stress at the individual level. CMS-V multi-spectral camera(Silios Technologies) was used for image acquisition. The camera lens consists of eight spectral bands between 550nm and 830nm. Light Reflective information collected in each band sensor and stored in digital values, and it is converted into a reflectance for calculating the vegetation index and used. According to the camera manual, the NDVI(Normalized Difference vegetation index) value was calculated using 628 nm and 752 nm bands. Image measurement was conducted under natural light conditions, and reflectance standards(Labsphere) were captured with plants for reflectance calculation. The wheat variety used Gosomil, and the wheat grown in the field was transplanted into a pot after heading date and measured. Three treatments were performed so that the soil volumetric water content of the pot was 13~17%, 20~23%, and 25%, and the growth response of wheat according to each treatment was compared using the NDVI value. In the first measurement after port transplantation, the difference in NDVI value according to treatment was not significant, but in the subsequent measurement, the NDVI value of the treatment with a water content of 13 to 17% was lowest and was the highest at 20 to 23%. The NDVI values decreased compared to the first measurement in all treatment, and the decrease was the largest at 13-17% water content and the smallest at 20-23%. Although the difference in NDVI values could be confirmed, it would be difficult to directly relate it to the water stress of plants, and further research on the response of crops to environmental stress and the analysis of multi-spectral image will be needed.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.5 no.3
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.143-155
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• 2018

The Natural Landscape Rating System was introduced in the amendment of the NATURAL ENVIRONMENT CONSERVATION ACT in 2006. For landscape preservation, the system aims to consider the effects of development projects or plans implemented in a natural landscape on skylines, scenic resources, and view corridors. Currently, a lack of consistency in standards for determining Landscape Control Points (LCP) to assess landscape impact lowers the accuracy and reliability of the assessment results. As the perception of and the impact on a landscape varies, depending on the location of the LCP, it is necessary to establish a reasonable set of criteria to select viewpoints and avoid unreliability in the assessment due to unclear criteria. The intent of this study is to propose an objective and reasonable set of criteria for LCP selection to effectively measure the impact on the landscape from development projects that anticipate a change in the landscape and, ultimately, to suggest basic analysis methods to assess the landscape impact of development projects and to monitor the landscape in the future. Among the development projects affecting natural landscapes, as reported in the statement of the environmental impact assessment, cases of construction of a single building or other small-scale development projects were studied. Four spot development projects were analyzed in depth for their landscape impacts, in order to make recommendations for the LCP selection procedure, which aims to widen the scope of selection according to the direction of viewpoints from the target site. The existing results of analysis based on LCP have limitations because they failed to cover the viewshed of the target buildings when there are topographical changes in the surroundings. As a solution to this problem, a new viewshed analysis method has been proposed, with a focus on the development site and target buildings, rather than viewpoints, as used in past analysis.