• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.71-85
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• 2021

Representative domestic start-up support organizations include the Business Incubator(BI), Korea Institute of Startup & Entrepreneurship Development(KISED), Techno Park(TP), and Center of Creative Economy Innovation(CCEI), and there are about 260 Business incubator nationwide. The Business incubator is operated by universities, research institutes, and private foundations or associations. The organization consists of the center director and the incubating professionals (hereinafter referred to as "manager"), etc., and performs tasks such as center operation management and incubation support services for tenant companies. Until now, research on the operation of Business Incubator has been mainly focused on the performance of tenant companies. Studies on whether the manager's competency characteristics directly or indirectly affect the performance of the tenant companies through psychological mediators such as self-efficacy and organizational commitment were very scarce. The purpose of this study is to explore various factors influencing organizational commitment and job performance by the competence characteristics of Business incubator managers, and to explain the causal relationship among those factors. In particular, the difference in perception was investigated by a manager's survey that influences organizational commitment and work performance at the Business incubator. Through this, we intend to present practical implications for the role of managers in the operation of Business incubators. This study is an exploratory study, and the subject of the study was a survey of about 600 managers working at Business incubator nationwide, of which 116 responses were analyzed. Data analysis included descriptive statistics, exploratory factor analysis, and reliability. Structural equation model analysis was performed for hypothesis tests. As a result of the analysis, it was found that the cognitive characteristics of the Business incubator manager, communication, and situational response as the behavioral characteristics had a positive effect on the manager's self-efficacy, and the behavioral characteristics had a greater effect on the self-efficacy. It was also found that the manager's cognitive and behavioral characteristics, and self-efficacy had a positive effect on organizational commitment and work performance. In particular, a manager's self-efficacy has a positive effect on organizational commitment and work performance. This result showed that the manager's competency characteristics increase the manager's self-efficacy as a mediating factor rather than directly affecting organizational commitment and work performance. This study explains that the manager's competency characteristics are transferred to organizational commitment and work performance. The results of the study are expected to reflect the job standard of the National Competency Standards (NCS) and basic vocational competency to the job competency of managers, and it also provides a guideline for the effective business incubator operation in terms of human resource management. In practice, it is expected that the results of the study can reflect the vocational basic skills of the Business Incubator manager's job competency in the National Competency Standards(NCS) section, and suggest directions for the operation of the Business Incubator and the manager's education and training.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.4
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• pp.342-352
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• 2020

Objectives: The characteristics of research workers are different from those working in the manufacturing industry. Furthermore, the reagents used change according to the research due to the characteristics of the laboratory, and the amounts used vary. In addition, since the working time changes almost every day, it is difficult to adjust the time according to exposure standards. There are also difficulties in setting standards as in the manufacturing industry since laboratory environments and the types of experiments performed are all different. For these reasons, the measurement of the working environment of research workers is not realistically carried out within the legal framework, there is a concern that the accuracy of measurement results may be degraded, and there are difficulties in securing data. The exposure evaluation based on an eight-hour time-weighted average used for measuring the working environment to be studied in this study may not be appropriate, but it was judged and consequently applied as the most suitable method among the recognized test methods. Methods: The investigation of the use of chemical substances in the research laboratory, which is the subject of this study, was conducted in the order of carrying out work environment measurement, sample analysis, and result analysis. In the case of the use of chemical substances, after organizing the substances to be measured in the working environment, the research workers were asked to write down the status, frequency, and period of use. Work environment measurement and sample analysis were conducted by a recognized test method, and the results were compared with the exposure standards (TWA: time weighted average value) for chemical substances and physical factors. Results: For the substances subject to work environment measurement, the department of chemical engineering was the most exposed, followed by the department of chemistry. This can lead to exposure to a variety of chemicals in departmental laboratories that primarily deal with chemicals, including acetone, hydrogen peroxide, nitric acid, sodium hydroxide, and normal hexane. Hydrogen chloride was measured higher than the average level of domestic work environment measurements. This can suggest that researchers in research activities should also be managed within the work environment measurement system. As a result of a comparison between the professional science and technology service industry and the education service industry, which are the most similar business types to university research laboratories among the domestic work environment measurements provided by the Korea Safety and Health Agency, acetone, dichloromethane, hydrogen peroxide, sodium hydroxide, nitric acid, normal hexane, and hydrogen chloride are items that appear higher than the average level. This can also be expressed as a basis for supporting management within the work environment measurement system. Conclusions: In the case of research activity workers' work environment measurement and management, specific details can be presented as follows. When changing projects and research, work environment measurement is carried out, and work environment measurement targets and methods are determined by the measurement and analysis method determined by the Ministry of Employment and Labor. The measurement results and exposure standards apply exposure standards for chemical substances and physical factors by the Ministry of Employment and Labor. Implementation costs include safety management expenses and submission of improvement plans when exposure standards are exceeded. The results of this study were presented only for the measurement of the working environment among the minimum health management measures for research workers, but it is necessary to prepare a system to improve the level of safety and health.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.67-79
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• 2020

This study analyzed the start-up education curriculum and start-up education programs of seven universities in the U.S. to find out what courses are provided, what various programs exist, and what the characteristics of start-up education in each university are. California State University, San Bernardino / University of California, Irvine / Drexel University / Oklahoma State University / Florida State University / San Diego State University / University of Southern California where entrepreneurship education based on the Entrepreneurship Degree Course is being established based on the Entrepreneurship Center of seven universities in the United States, which is not well introduced in Korea. This study examined how the start-up education courses and start-up support systems at seven universities in the U.S. are progressing at the undergraduate, MBA, master's and doctoral levels, and comparative levels. Through the case studies of the universities presented, the primary analysis was carried out to explore the various characteristics of American university start-up education. The implications of start-up education at American universities in this study are as follows. First, in order for universities to take the initiative in providing start-up education, they should be organized to suit the course of start-up education suitable for the characteristics of universities and introduce support programs. Second, it is necessary to establish an independent center within domestic universities to be operated autonomously. Third, the start-up education of universities should include building university-industry partnerships, operating entrepreneurship degree courses and collaboration between departments of universities. Fourth, the independent center should lead the active participation of alumni and local start-ups and start-up-related programs should be operated based on this. Fifth, Differentiated programs for each university's characteristics should be introduced and applied to universities. Although case studies have limitations that cannot be generalized, they can provide a useful framework. Therefore, it is necessary to design a systematic start-up education that reflects the correct design direction and characteristics of each university.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.95-114
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• 2020

This paper, a meta-analysis of the effect of the start-up support policy on the start-up performance was conducted to examine the effect of the start-up support policy on the start-up performance of beneficiary companies and to provide theoretical and practical implications to support organizations and practitioners. To this end, 35 papers containing the correlation coefficient, which is a positive statistical value, were selected from the previous studies in academic journals and dissertations published in Korea from 2007 to 2020. In the preceding study of the start-up support policy, the independent variables include funding, education support, facility/equipment support, network support, mentoring support, consulting support, marketing support, management support, technical support, manpower support, and finance as a dependent variable. The effect size of the impact on aptitude and non-financial performance was reviewed. The pattern of the effect size was presented as a forest plot for easy visual understanding, and outliers were verified through sensitivity analysis for small-study-effect data with publication convenience. As a result of analyzing the effect size of the government-supported policy, it was verified that the effect size was generally medium or higher, affecting the entrepreneurial performance. Among the independent variables, the factor that has the greatest effect on startup performance is manpower support, followed by technical support, marketing support, management support, facility/equipment support, education support, mentoring support, funding, network support, and consulting support. It was analyzed that the effect size was large in order. As the 「Small and Medium Business Startup Support Act」 was recently reorganized from the manufacturing industry to digital transformation and smartization on October 8, 2020, the start-up support policy should consider the start-up stage and verify the priorities to organize the budget.

• 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.

• Korean Journal of Plant Resources
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• v.34 no.1
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• pp.23-30
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• 2021

Hemistepta lyrata Bunge (HL) has been used as a folk remedy to treat cancer, inflammation, bleeding, hemorrhoids and fever, and leaves and young shoots have been used as famine food. Nevertheless, the biological activities and underlying mechanisms of the anti-inflammatory effects remain unclear. In this study, it was undertaken to explore the functions of the aerial part of HL as a suppressor of inflammation by using RAW 264.7 cells. As immune response parameters, the productions of as nitric oxide (NO) and prostaglandin E2 (PGE2), cytokines such tumor necrotic factor (TNF)-α and interleukin (IL)-6 were evaluated. Although the release of TNF-α remained unchanged in HL-treated RAW 264.7 cells, the productions of NO, PGE2 and IL-6 were significantly increased at concentrations with no cytotoxicity. Furthermore, HL significantly attenuated the mitogen-activated protein kinases (MAPK) pathway including decreasing the phosphorylation of the extracellular signal-regulated kinase (ERK1/2) and p38 mitogen-activated protein kinases. Collectively, this study provides evidence that HL inhibits the production of major pro-inflammatory molecules in LPS-stimulated RAW 264.7 cells via suppression of ERK and P38 MAPK signaling pathways. These findings suggest that the beneficial therapeutic effects of HL may be attributed partly to its ability to modulate immune functions in macrophages.

• Korean Journal of Plant Resources
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• v.34 no.1
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• pp.64-72
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• 2021

This study aimed to identify regions with a suitable growth environment for Ligusticum chuanxing Hort. and use basic data to identify appropriate cultivation and stable production strategies. Four main areas of cultivation were selected and the relationship between growth characteristics (aboveground and underground parts) and weather and soil environment was analyzed. Overall growth was found to be significantly higher in Pyeongchang. Atmospheric and soil temperatures showed a significant negative correlation with overall height from the ground, stem diameter, and growth characteristics of the underground part; leaf length and width were positively correlated. As insolation increased, the growth characteristics, excluding leaf size, showed a positive correlation. Soil characteristics such as organic matter (OM), N, P, and K showed negative correlations with the overall height of the upper part and growth characteristics of the underground part, including stem diameter. Analysis of roots indicated that OM, N, P, and K were essential and were absorbed through the soil. The OM, N, P, and K values in the Pyeongchang area, which showed the optimal growth, were lower than those in other areas. It is believed that these results can be used to select cultivation sites for L. chuanxing and establish cultivation technology in future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.1
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• pp.18-28
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• 2021

The growth period and productivity of cropping system of winter wheat-rice, winter wheat-bean and winter wheat-grain corn for 4 years from 2015 to 2018 were compared at the experimental field of National Institute of Crop Science in Miryang city. The harvest period of winter wheat was in mid-June, and summer crops were sown (transplanted) in late June. In transplanting of rice in late June, there was no difficulty in securing the heading of panicle and the yield of rice, but there was a lot of trouble in sowing wheat in proper time because the harvest time of rice was delayed to early November due to late maturity of rice, particularly in the mid-late maturing cultivar. There was no problem in soybean planting after winter wheat because the proper period of soybean planting is late-June. In addition, there was no problem in winter wheat sowng after soybean because the maturity period of soybean was mid-October. Selection of grain maize in double cropping with winter wheat in terms of growing periods, was desirable because grain maize had the fastest maturity among summer crops. In double cropping of winter wheat-summer crops, wheats combined with soybean and grain maize showed stable yields during three years, but there was a risk of yield declines in the wheat combined with rice in heavy rainfall year. It was possible to secure high yields in three summer crops as yields of rice, soybean, and corn were 600, 350, and 800 kg/10a, respectively. Summer crops with medium maturity was recommended because of no significant difference in yield between medium maturity and medium-late maturity cultivar. Soil physical properties were improved in soils cultivated with soybean and grain maize. Therefore, It was thought that double cropping systems of winter wheat with soybean and grain maize were superior to that of winter wheat with rice in terms of connecting period between winter wheat - summer crops and improvement of soil physical properties, and total income, particularly in soybean.

• 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.