• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.55-69
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• 2021

For the national economic development, the participation of women in the social and economic activities is crucial. The popularization of start-ups, digital transformation, and WEconomy trends have lowered the barriers to opportunities for women to start a business and provide an environment in which women can grow faster. This paper examines the significance and process of success of women entrepreneurs and the characteristics of innovation strategies and achievements by linking the recently changing business environment of a company, factors influencing the success of women entrepreneurship, and innovation activities. To this end, four companies' cases were analyzed in the fields of distribution/service and consumer products/services, which are areas of large investment among female startups. The result shows that women entrepreneurs recognize the meaning of success as creating and continuing to create a 'corporate value through establishing a trust relationship with customers' within the 'balance between personal life and work.' In terms of the business ecosystem, women entrepreneurs strive for 'business activities based on the win-win growth of consumers, producers and sellers' for success, and rather 'focus on the process with a problem-solving approach' rather than achieving performance-oriented goals. Also through excellent power of observation, flexibility, and execution power, women entrepreneurs conduct business by adapting to changing trends. In terms of innovation activities, the innovation strategy of women-led companies puts priority on 'creating the value customers want' and focuses on innovation in the 'customer-centric business model' rather than technological innovation. As such, women-led companies show several differentiated characteristics, which enable them to create corporate value and achieve sustainable growth. The barriers to challenges and opportunities for women to start a business have been lowered, and an ecosystem has been created for female startups to grow. But why are there still so few women entrepreneurs, and the answer to where we need to close these gaps is ultimately a close analysis and investigation of the field. We must present milestones for growth steps through the accumulation of case studies of women startups that have exited. In addition, women can stand as economic agents only when the policy targets are subdivided and specific approaches to child-rearing and childcare for women entrepreneurs must be taken. This paper expects to serve as basic data for follow-up studies and become the basis of research for women entrepreneurs to grow as economic agents.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.2
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• pp.127-136
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• 2022

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMY_normal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.241-247
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• 2001

Boundary line method was adopted to analyze the relationships between rice yield and meteorological conditions during rice growing period. Boundary lines of yield responses to mean temperature($T_a$) and sunshine hour( $S_{h}$) and diurnal temperature range($T_r$) were well-fitted to hyperbolic functions of f($T_a$) =$$\beta$_{0t}$(1-EXP(-$$\beta$_{1t}$ $\times$ ($T_a$) ) and f( $S_{h}$)=$$\beta$_{0t}$((1-EXP($$\beta$_{1t}$$\times$ $S_{h}$)), to quadratic function of f($T_r$) =$\beta$$_{0r}$(1-($T_r$ 1r)$^2$), respectively. to take into account to, the sterility caused by low temperature during reproductive stage, cooling degree days [$T_c$ =$\Sigma$(20-$T_a$] for 30 days before heading were calculated. Boundary lines of yield responses to $T_c$ were fitted well to exponential function of f($T_c$) )=$\beta$$_{0c}$exp(-$$\beta$_{1c}$$\times$$T_c$ ). Excluding the constants of $\beta$$_{0s}$ from the boundary line functions, formed are the relative function values in the range of 0 to 1. And these were used as yield indices of the meteorological elements which indicate the degree of influence on rice yield. Assuming that the meteorological elements act multiplicatively and independently from each other, meteorological yield index (MIY) was calculated by the geometric mean of indices for each meteorological elements. MIY in each growth period showed good linear relationship with rice yield. The MIY's during 31 to 45 days after transplanting(DAT) in vegetative stage, during 30 to 16 days before heading (DBH) in reproductive stage and during 20 days after heading (DAH) in ripening stage showed greater explainablity for yield variation in each growth stage. MIY for the whole growth period was calculated by the following three methods of geometric mean of the indices for vegetative stage (MIVG), reproductive stage (HIRG) and ripening stage (HIRS). MI $Y_{I}$ was calculated by the geometric mean of meteorological indices showing the highest determination coefficient n each growth stage of rice. That is, (equation omitted) was calculated by the geometric mean of all the MIY's for all the growth periods devided into 15 to 20 days intervals from transplanting to 40 DAH. MI $Y_{III}$ was calculated by the geometric mean of MIY's for 45 days of vegetative stage (MIV $G_{0-45}$ ), 30 days of reproductive stage (MIR $G_{30-0}$) and 40 days of ripening stage (MIR $S_{0-40}$). MI $Y_{I}$, MI $Y_{II}$ and MI $Y_{III}$ showed good linear relationships with grain yield, the coefficients of determination being 0.651, 0.670 and 0.613, respectively.and 0.613, respectively.