• (The)Study of the Eastern Classic
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• no.50
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• pp.179-209
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• 2013

This study takes as its text "Yangarok", the record written by Mukjae Lee Mun Geon (1494-1567) about his grandson rearing and examines the conflicts between the grandfather and the grandson. The reason it is focused on the conflicts between the grandfather and the grandson particularly among many aspects of Yangarok is that the paper notices the dual feelings of love and hatred lying in the mind of Mukjae, the subject of the narrative. Because the record of grandson rearing plainly reflects the dual elements of the grandfather, love and hatred, expectation and disappointment, and hope and resignation, it shows the acute conflicts between the two persons well. At the time of the grandson's birth, Mukjae went through a gloomy period both in family and socially. He had to taste tremendous frustration in the status as an exile pushed back from the center of the political world, and his only son was handicapped, so he could not expect his caring after that. Spending each day in such frustration, he faced the birth of his grandson just like a miracle. However, the excitedness and expectation he had in the beginning of the child raising were turned into disappointment and complaining as time went by. His change lets us think about the distance between love and hatred existing in human relations. This study analyzes Yangarok but is focused on the conflicts between the grandfather and the grandson for further discussion, so it attempts to understand Yangarok from a different perspective. First of all, Chapter 2 of this article notices the fact that cause results in effect and examines the ultimate factors raising grandfather-grandson conflicts. Next, Chapter 3 considers the concrete aspects of grandfather-grandson conflicts. Based on the above examination on the causes and aspects of the conflicts, Chapter 4 focuses on the value that Yangarok has as the material for introspection and lays the ground to think about the messages that this record implies for contemporaries.

• Journal of the Korean Applied Science and Technology
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• v.38 no.3
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• pp.771-785
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• 2021

This study was performed to provide detailed and comprehensive information on inflammation-related blood indicators, joint range of motion, pain scale, and psychological indicators by patient characteristics by performing a 12-week home-based exercise program for ankylosing spondylitis patients. For the purpose of this study, 10 patients with ankylosing spondylitis were selected by age (30s vs. 40s vs. 50s), gender (male vs. female), and duration (less than 5 years vs. 5 years or more). The home-based exercise program was a combination of aerobic exercise and Pilates-based resistance exercise, and was performed 4 times a week for 12 weeks at an intensity of 50-70% of maximal heart rate (MHR). As a result, after 12 weeks of home-based exercise intervention, the blood C-reactive protein (CRP) concentration of patients with ankylosing spondylitis decreased (-35.6%, p=.002), and the blood inflammation level was improved, and each joint (hip, lumbar, cervical) improved mobility (p<.05). In addition, the bath ankylosing spondylitis disease activity index (BASDAI) was decreased by -67% (p=.001) and the visual analogue scale (VAS) was decreased by -64.8% (p=.001), stiffness and pain has been alleviated. In particular, as the degree of depression decreased by -65.5% (p=.001) and the degree of anxiety by -55.2% (p=.003), 12 weeks of home-based exercise improved not only physical changes but also psychological factors. On the other hand, there was no difference in exercise effect according to age, gender, and disease duration in ankylosing spondylitis patients (p>.05). These results suggest that the 12-week home-based exercise applied in this study can be an effective exercise program that can be universally used for ankylosing spondylitis patients regardless of patient characteristics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.147-159
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• 2021

After the 2020 Corona 19 pandemic, consumers' online consumption is increasing rapidly, and non-store online retail channels are showing high growth. In particular, social media is gaining its status as a social media market where direct transactions take place in the means of promoting companies' brands and products. In this study, changes in consumer behavior after the Corona 19 pandemic are different in choosing online shopping media such as existing online shopping malls and SNS markets that can be classified into open social media and closed social media when purchasing agri-food online. We tried to find out what type of product is preferred in the selection of agri-food products. For this study, demographic characteristics of consumers, perceived risk of consumers, and dietary lifestyle were set as independent variables to investigate the effect on online shopping media type and product selection. The summary of the empirical analysis results is as follows. When consumers purchase agri-food online, there are significant differences in demographic characteristics, consumer perception risks, and detailed factors of dietary lifestyle in selecting shopping channels such as online shopping malls, open social media, and closed social media. Appeared to be. The consumers who choose the open SNS market are higher in men than in women, with lower household income, and higher in consumers seeking health and taste. Consumers who choose the closed SNS market were analyzed as consumers who live in rural areas and have a high degree of risk perception for delivery. Consumers who choose existing online shopping malls have high educational background, high personal income, and high consumers seeking taste and economy. Through this study, we tried to provide practical assistance by providing a basis for judgment to farmers who have difficulty in selecting an online shopping medium suitable for their product characteristics. As a shopping channel for agri-food, social media is not a simple promotional channel, but a direct transaction. It can be differentiated from existing studies in that it is approached as a market that arises.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.3
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• pp.19-34
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• 2022

This study was conducted to provide basic data that can be used when establishing Net Zero policies and implementation plans for non-urban settlements by quantitatively analyzing the Net Zero contribution to green infrastructure in rural areas corresponding to non-urban settlements. The main purpose is to first, systematize green infrastructure in rural areas, secondly derive basic units for each element of green infrastructure, and thirdly quantify and present the impact on Net Zero in Korea using these. In this study, CVR(Content Validity Ration) analysis was performed to verify the adequacy of green infrastructure elements in rural areas derived through research and analysis of previous studies, is as follows. First, Hubs of Green infrastructure in rural area include village forests, wetlands, farm land, and smart farms with a CVR value of .500 or higher. And Links of Green infrastructure in rural area include streams, village green areas, and LID (rainwater recycling). Second, the basic unit for each green infrastructure element was presented by classifying it into minimum, maximum, and median values using the results of previous studies so that it could be used for spatial planning and design for Net Zero. Third, when Green infrastructure in rural areas is applied to non-urban settlements in Korea, it is analyzed that it has the effect of indirectly reducing CO₂ by at least 70.76 million tons and up to 141.16 million tons. This is 3.4 to 6.7 times the amount of CO₂ emission from the agricultural sector in 2019, and it can be seen that the contribution to Net Zero is very high. It is expected to greatly contribute to the transformation of the ecosystem. This study quantitatively presented the carbon-neutral contribution to settlements located in non-urban areas, and by deriving the carbon reduction unit for each element of green infrastructure in rural areas, it can be used in spatial planning and design for carbon-neutral at the village level. It has significance as a basic research. In particular, the basic unit of carbon reduction for each green infrastructure factors will be usable for Net Zero policy at the village level, presenting a quantitative target when establishing a plan, and checking whether or not it has been achieved. In addition, based on this, it will be possible to expand and apply Net Zero at regional and city units such as cities, counties, and districts.

• Korean Journal of Food Science and Technology
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• v.53 no.4
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• pp.399-407
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• 2021

Wrinkle formation and dryness are the most well-known symptoms of skin aging. This study investigated skin anti-aging and moisturizing effects of Mugunghwa (Hibiscus syriacus L.), the national flower of Korea. The effect of H. syriacus L. flower extract was examined in skin cells originating from humans in vitro and in hairless mice exposed to UVB in vivo. The in vivo study results showed that skin hydration-related factors such as involucrin, filaggrin, HAS1, HYAL1, and matrix metalloproteinase-I (a primary skin photoaging factor) were regulated by H. syriacus L. Additionally, epidermal thickness and collagen disruption, which resulted in wrinkle formation and skin dryness, were ameliorated by oral administration of H. syriacus L. These results indicate that H. syriacus L. flowers can play important roles in preventing aging and promoting skin moisturizing.

• Land and Housing Review
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• v.14 no.1
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• pp.47-66
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• 2023

This study reviews prior studies on the residential environment characteristics, residential satisfaction, residential ownership consciousness and housing movement of MZ generation and analyze the structural equation models using the 2020 Korea Housing Survey data. Using 14 residential characteristics based on three classifications, we explore the effects on residential satisfaction, residential ownership consciousness, and housing movement. The empirical results are summarized as follows. First, based on factor analysis with Varimax of principal component analysis, parking facility items were excluded from the analysis by hindering validity, and as a result, KMO was 0.925 and Bartlett's test result showed a significant probability of less than 0.01. This indicates that the factor analysis model was suitable. Second, the results of the structural equation analysis for the MZ generation show that the surrounding environment, which is a potential variable of the residential environment characteristics, was statistically significant, but the accessibility and convenience were not statistically significant. Third, we find that the higher the satisfaction with the accessibility of commercial facilities, the more significant the sense of housing ownership appears. This suggests that the younger generation such as the MZ generation has a stronger desire for consumption. Fourth, the overall housing satisfaction of the MZ generation was significant for housing movement, but not for housing ownership. Compared to the industrialized generation, the baby boom generation, and the X generation, MZ generation shows distinct factors for housing satisfaction, housing ownership, and housing movement. Therefore, the residential environment characteristics of the residential survey should be improved and supplemented following the trend of the times. In addition, the government and local governments should prioritize actively participating in the housing market that suits the environment and characteristics of the target generation. Finally, our study provides implications regarding the need for housing-related research on how differ in special temporal situations such as COVID-19 in the future.

• Journal of Life Science
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• v.32 no.11
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• pp.872-881
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• 2022

In this study, we optimized the composition of the indole-3-acetic acid (IAA) production medium using response surface methodology on Pantoea agglomerans SRCM 119864 isolated from soil. IAA-producing P. aglomerans SRCM 119864 was identified by 16S rRNA gene sequencing. There are 11 intermediate components known to affect IAA production, hence the effect of each component on IAA production was investigated using a Plackett-Burman design (PBD). Based on the PBD, sucrose, tryptone, and sodium chloride were selected as the main factors that enhanced the IAA production at optimal L-tryptophan concentration. The predicted maximum IAA production (64.34 mg/l) was obtained for a concentration of sucrose of 13.38 g/l, of tryptone of 18.34 g/l, of sodium chloride of 9.71 g/l, and of L-tryptophan of 6.25 g/l using a the hybrid design experimental model. In the experiment, the nutrient broth medium supplemented with 0.1% L-tryptophan as the basal medium produced 45.24 mg/l of IAA, whereas the optimized medium produced 65.40 mg/l of IAA, resulting in a 44.56% increase in efficiency. It was confirmed that the IAA production of the designed optimal composition medium was very similar to the predicted IAA production. The statistical significance and suitability of the experimental model were verified through analysis of variance (ANOVA). Therefore, in this study, we determined the optimal growth medium concentration for the maximum production of IAA, which can contribute to sustainable agriculture and increase crop yield.

• Journal of Life Science
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• v.32 no.6
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• pp.447-454
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• 2022

In this study, we confirmed the effect of HK shiitake mushroom mycelium (HKSMM) on immune enhancement in Balb/c mice. Experimental animals were divided into five groups: negative control (NC), positive control (PC; 1,000 mg/100 g; AHCC), T1 (500 mg/100 g; HKSMM), T2 (1,000 mg/100 g; HKSMM), and T3 (2,000 mg/100 g; HKSMM), and dissection was performed at four and six weeks. COX-2 and iNOS concentrations were significantly lower in the six-week experimental group than in the control group, and the NO results were also similar. Results of the confirmation of the factors related to the NF-κB (p-p65 and p-IκBα) and MAPK (pERK, pJNK, and p38) signaling pathways revealed that the HKSMM-fed experimental group significantly decreased compared with the control group. A comparative analysis of the number and size of white pulp in the spleen tissue showed that those of the experimental group were significantly higher than those of the control group in a concentration-dependent manner. These results suggest that HKSMM has both immune-enhancing and anti-inflammatory effects in Balb/c mice, indicating that it can be used as a health functional food ingredient.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.477-490
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• 2022

Serious Accident Punishment Act(SAPA) went into effect as of Jan. 27, 2022. The subject of study was the worker of the nuclear medicine department and the investigation was aimed at identifying the present situation of their understanding on the issue in the here and now, which can be utilized as basic research for further study. The survey was conducted on 51 people of the worker in the nuclear medicine department. The general factors were classified by their gender, the scale of the hospitals, the period of career, and the detailed occupational categories. The conclusion was drawn, including 1 missing data in gender and 2 in the type of occupation. The targeted hospitals were tertiary hospital, university hospital, and general hospital which have nuclear medicine department in. The period of subjects' career was categorized by less than 3 years, 3 to 5 years, 5 to 10 years, and more than 10 years. The specific occupation was classified by in-vivo radiological technologist, radiation safety manager and others. The amount of pressure that the job entails was highest in the category of general hospital, the period of 3 to 5 years of job experience, and radiation safety manager each. The system of the code was well constructed in the category of general hospital, the period of less than 3-year career, and radiation safety manager, as they responded. The blood transmissible disease had the largest number of outbreak of accidents related to the serious industrial accident. In addition, the radiopharmaceutical dosing error had the highest number of outbreak of accidents related to the serious civil accident. Therefore, we need to improve SAPA, facility inspection, security of budget, security of professional manpower. It will help the stable use of radiation and ensure patient safety.