• (The)Study of the Eastern Classic
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• no.70
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• pp.91-117
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• 2018

This paper examines the persuasive style(論說類) proses of Myeonggog(明谷) Choi, seokjeong(崔錫鼎, 1646~1715). He is a disciple of Namguman(南九萬) and Parksechae(朴世采), and is a man who played an active part by political soron(少論) leader in the middle of the Joseon Dynasty. It is also a central figure that links the genealogy of the late Joseon Dynasty, which leads to Namguman(南九萬)-Choiseokjeong(崔錫鼎)-Chotaeeok(趙泰億). He wrote total 14 persuasive style prose. The time of creation is from around 1671 until the end of life. In this paper, the preoses to be analyzed are Sunukron(荀彧論), Bujadaegaron(夫子待賈論) and Muneongyebyeon(文言系辭辨). The reverse idea that reverses the existing discussion is outstanding, and the work which is unique in composition is Sunukron(荀彧論). Bujadaegaron(夫子待賈論) is a work that uses the ryubi(類比) to increase persuasiveness and converts the existing perspective. Muneongyebyeon(文言系辭辨) is a work that attempted to harmonize in the formality of vocabulary, sentence and composition while showing the logical perfection to dismiss the counter-argument's prerequisite. For example, Muneongyebyeon(文言系辭辨) consists of a total of five paragraphs in aspect of composition, each paragraph arranged in good order. In addition, this work presented sequential arguments, used the incremental method which emphasizes the importance of arguments as it moves backward.

• The Journal of Korean Philosophical History
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• no.23
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• pp.7-65
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• 2008

The object of this essay is to apply the Leadership Theory, current interest in Asian Philosophy, to Korean appliance. This is to associate contemporary Leadership Theory with Chosun Confucianism in order to discover the Korean Leadership Prototype, and seek the possibility of applying it for modern usage. The essay uses two analysis models. The tools used for the methodology consists of the personal characteristics of the leader as one axis and ruling out the roles in order to develop the discussion as the other axis. First axis is the process of the leader setting the identity and strengthening the ability to successfully deploy his/her leadership. The second axis is comprised of four specific fields where the leadership is deployed. The four sectors are Self Sector, Relationship Sector, Team Sector and Community Sector. Core values of each sector have been set up and specific competences have been presented. In the Self Sector, $zh{\grave{i}}x{\bar{i}}n$(治心) and $ch{\acute{i}}j{\grave{i}}ng$(持敬) have been set as core values and $l{\grave{i}}zh{\grave{i}}$(立志) and $sh{\acute{i}}x{\bar{i}}n$(實心) as their competences. In the Relationship Sector and Team Sector, circumstances(時宜) and $sh{\acute{i}}sh{\grave{i}}g{\bar{e}}ngzh{\bar{a}}ng$(實事更張) were set as core values, accordingly. Lastly for the Community sector, the core value, 'Ideal Leader and the Visions of and Ideal Community', was conceptualized as '$m{\grave{ui}}m{\acute{i}}nzh{\grave{i}}zh{\grave{i}}$(牧民至治)'. The leadership is then expanded from the Self Sector to the final stage through its processes. Through this research, it can be found out that the Korean Leadership Model is not rigid to just cover a specific point in time or situation, but embraces many contemporary leadership concepts, thus having the characteristics of a comprehensive leadership theory.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.4
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• pp.49-57
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• 2020

Traditional landscape is a cultural asset left by Seonhyeon to modern society, and it can not only understand the landscape culture of ancient tradition but also provides / provided a new creative material for modern landscape designs / designed. However, it is well known that Korea and China have a relationship between the development and exchange of landscaping in a global background, the succession of traditional landscape architecture culture in a global background covers many dimensions, including protection, development and innovation, and that "traditional and modern" and "regionally and internationality" should be harmonized with each other. This study uses traditional Korean and Chinese landscaping buildings as research subjects to extract and organize related data through various channels, including basic literature research that understands the history and culture of the two countries. I interpreted the cultural backgrounds of the two countries by dividing them into religious ideas, traditional culture, and natural views, and highlighted the history of development and the relationship between the two countries. Based on this, it analyzed the differences created by traditional landscaping between Korea and China, and also specifically analyzed the "creation of righteous army" and "the law of righteous army." In particular, this study sought to inherit and innovate traditional landscape culture for the internationalization of "One Belt, One Road" based on the characteristics of Korea and China's landscape through a comparative analysis of the construction elements and methods of Yihwawon of the Ming and Qing periods and Gyeongbokgung Palace of the Joseon Dynasty on the theoretical background of landscaping and the significance of landscaping. The direction for the development and exchange with landscaping between the two countries was presented in line with the development trend of Korea-China landscaping in the global environment. In the future, the development of landscaping between the two countries is expected to be key to international cooperation in traditional culture, creative combination of local characteristics, creation of a harmonious landscape architecture environment, and co-prosperity of various cultures.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.11-28
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• 2021

Due to its size and complex characteristics, it is not often to newly create a large park within an existing urban area. Also, there has been a lack of research on the planting design methodologies for a large park. This study aims to elucidate how ecological ideas can be applied to planting practice from a designer's perspective, and eventually suggest a planting design framework in the actual case, the Central Park in the City of Gwangju. This framework consists of spatial structure of planting area in order to connect and unite the separated green patches, to adapt to the changes of existing vegetation patterns, to maintain the visual continuity of landscape, and to organize the whole open space system. The framework can be provided for the spatial planning and planting design phase in which the landscape designer flexibly uses it with the design intentions as well as with an understanding of the physical, social, and aesthetic characteristics of the site. The significance of this approach is, first that it can maintain ecological and visual consistency of the both existing and introduced landscapes as a whole in spite of its intrinsic complexity and largeness, and second that it can help efficiently respond to the unexpected changes in the landscape. In the case study, comprehensive site analysis is conducted before developing the framework. In particular, wetlands and grasslands have been identified as potential wildlife habitat which critically determines the vegetation patterns of the green area. Accordingly, the lists of plant communities are presented along with the planting scheme for their shape, layout, and relations. The model of the plant community is developed responding to the structure of surrounding natural landscape. However, it is not designed to evolve to a specific plant community, but is rather a conceptual model of ecological potentials. Therefore, the application of the model has great flexibility by using other plant communities as an alternative as long as the characteristics of the communities are appropriate to the physical conditions. Even though this research provides valuable implications for landscape planning and design in the similar circumstances, there are several limitations to be overcome in the further research. First, there needs to be more sufficient field surveys on the wildlife habitats, which would help generate a more concrete planting model. Second, a landscape management plan should be included considering the condition of existing forest, in particular the afforested landscapes. Last, there is a lack of quantitative data for the models of some plant communities.

• Journal of Food Hygiene and Safety
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• v.36 no.3
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• pp.220-227
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• 2021

Fluoroimide is a fungicide and is also used as a pesticide for persimmons and potatoes. The established fluoroimide pesticide analysis method takes a long time to perform and uses benzene, a carcinogen. In addition, a lower limit of quantification is required due to enforcement of the Positive List System. Therefore, this study aimed to improve the analysis method for residual fluoroimide to resolve the problems associated with the current method. The analytical method was improved with reference to the increased stability of fluoroimide under acidic conditions. Fluoroimide was extracted under acidic conditions by hydrogen chloride (4 N) and acetic acid. MgSO₄ and NaCl were used with acetonitrile. C₁₈ (octadecylsilane) 500 mg and graphitized carbon black 40 mg were used in the purification process. The experiment was conducted with agricultural products (hulled rice, potato, soybean, mandarin, green pepper), and liquid chromatograph-tandem mass spectrometry was used for the instrumental analysis. Recovery of fluoroimide was 85.7-106.9% with relative standard deviations (RSDs) of less than 15.6%. This study reports an improved method for the analysis of fluoroimide that might contribute to safety by substituting the use of benzene, a harmful solvent. Furthermore, the use of QuEChERS increased the efficiency of the improved method. Finally, this research confirmed the precise limit of quantification and these results could be used to improve the analysis of other residual pesticides in agricultural products.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.206-219
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• 2021

The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.1-19
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• 2021

The purpose of this research is to improve the investment success rate for startups in the water industry for the development of the entrepreneurial environment of the Korean water industry. In this research, we identified investment determinants through prior research and stratified them, and then surveyed the investor group at the beginning of the start-up using the FGI method, and determined the order of the investment determinants of investors. At the same time, we classified 41 start-ups related to the water industry into two groups: the group that received investment and the group that did not in the early stages of the start-up. Then we investigated the understanding of the investor's investment determinants, ranked them, and compared them by using the AHP technique. Through this, this research proposes five implications. First, it is important for start-ups in the early stages to receive seed investment to revitalize investment for startups in the water industry. For this, startups need to understand investors and prepare to attract investment with the perspective of angel investors rather than the perspective of VC investors. Second, Start-ups in the water sector should consider that the characteristics of the founder are important in order to receive seed investment, and also need to define their business at the industry and market level, and provide relevant rationale to meet the expectations of investors who value industry expertise and experience, and to increase the possibility of seed investment, which is important in the early stages of a startup. Third, institutions, such as K-water(Korea Water Resources Corporation), that support water industry startups need to conduct open innovation business opportunities discovery programs linked to startups so that startups currently participating in the startup support program could have business opportunities from the business infrastructure of platform-forming companies in the water industry. In particular, such institutions should help founders develop their industrial expertise and careers by supporting this type of start-up preparation process through the participation of in-house venture founders. Fourth, when K-water uses the government start-up support fund to discover and foster founders, it should increase initial contact with seed investors, conduct more thorough verification of business plans, and develop programs that use government start-up support funds to prepare a business suitable for seed angel investors. Fifth, K-water should support seed by connecting funds for initial investment among funds operated by itself. It is also necessary to develop a program that links the company receiving the seed investment with VC investment, not angel investment in cooperation with the VC fund operation entity participating as an LP so that companies that have attracted seed investment could attract follow-up VC investment.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.25-28
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• 2021

Purpose CA 72-4 is a tumor marker that uses two monoclonal antibodies, CC49 and B72.3, to measure tumor-related glycoprotein(TAG72) in the serum. CA 72-4 is used to diagnose stomach, ovarian, and pancreatic cancers, and is known to perform high specificity for stomach cancer. The purpose of this study is to re-evaluate the reference value provided by the manufacturer through revalidation of the reference value in CA 72-4. Furthermore this study was conducted to provide useful help when making a clinical diagnosis at gastric cancer center. Materials and Methods We selected 271 patients who had been to health care center in national cancer center for the month of November 2020. The gender of the subjects was 140 males and 131 females, and the age group was from 30s to 60s. The reagent used in the study was a CA 72-4 IRMA KIT (ISOTOPES, Hungary) and the results were measured using a Dream Gamma-10 gamma counter (Shinjin medics, Korea). Results Statistical analysis of the results of this study used Hoffmann's method and Bayesian's method, which are primarily used in setting reference value. As a result of measuring CA 72-4 of 271 patients, the mean value was 4.54 U/mL and the median value was 3.30 U/mL. 24 people who deviated from 3SD were excluded from the measured value, the mean calculated after that was 3.53 U/mL, median was 3.00 U/mL and SD was 1.89. The reference value calculated based on this results was set to 7.31 U/mL. Conclusion The reference value provided by the manufacturer is less than 4 U/mL. It is slightly different from the value calculated in this study, 7.31 U/mL, so it seems necessary to reset the reference value according to the laboratory environment. Currently, we are receiving inquiries about the reference value from the center for gastric cancer at National Cancer Center. If additional research is carried out along with this study, it will be possible to set more accurate reference value.