• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.221-234
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• 2020

The role of entrepreneurship has become important for the continuous growth (scale-up) of companies in a rapidly changing economic environment. However, research has focused mainly on business-oriented growth that emphasizes efficiency only. However, in the era of the fourth industrial revolution, people have become more important than corporate efficiency. In particular, there are few studies on SMEs. The purpose of this study is to investigate how the characteristics of human - centered organizational culture affects the business ecosystem and firm excellence of SMEs, and how business ecosystem and firm excellence affect the performance of corporations. Therefore, this study focuses on the empathy, enablement, empowerment, and engagement of the corporate culture characteristics of the enterprise and the effects of the independent variables on the business ecosystem and the flower excellence as the parameters and the business ecosystem and company excellence. The main research subjects are the causality analysis that examines the effects on the management performance. The results of the study are as follows. Empathy, enablement, empowerment, engagement have a significant impact on the business ecosystem. In addition, the engagement have a positive effect on firm excellence. The results of empirical studies on the causal relationship between business ecosystem, corporate competence, and company excellence and business performance show that business ecosystem has no statistically significant effect on business performance. Corporate excellence has a significant effect on business performance Respectively. In addition to the above findings, this study can suggest the following implications. First, it is an empirical study of small and medium-sized enterprises (SMEs) by utilizing people-oriented entrepreneurship in addition to existing research. Small and medium-sized enterprises (SMEs) are expected to have lower perceptions of people-oriented management than large corporations or public institutions, but the analysis shows that people-centered entrepreneurship has a significant impact on the business ecosystem. Second, the research results of the serial multiple mediating effect analysis show that the higher the atmosphere of entrepreneurship in a company, the higher the atmosphere of entrepreneurship, and the parameters of business ecosystem and company excellence in the effect of people-oriented entrepreneurship on management performance. It is that the path through which people-oriented entrepreneurship influences management performance was verified by verifying the mediating effect by inputting. Lastly, it is hoped that research on people-oriented entrepreneurship in Korea's SMEs will be activated, providing a theoretical basis for transforming SMEs' business models into innovative types.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Horticultural Science & Technology
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• v.32 no.4
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• pp.427-433
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• 2014

Trellising is an important cultural practice that affects grape quality and yield. Some grape cultivars require different trellising under different climate and soil conditions. To find suitable trellis conditions for grape cultivar 'Cheongsoo', we measured growth and fruit characteristics with three different trellis systems: curtain, Geneva double curtain (GDC), and modified T. The maximum light exposure of clusters in the curtain, GDC, modified T trellis systems was 670, 1,654, and $1,649{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. However, there was no difference in air temperature among the three trellis systems. Net $CO_2$ assimilation rate at $1,500{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ light intensity was 13.4, 13.7, and $8.7{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ in curtain, GDC, and modified T trellis systems, respectively. Trunk cross section area (TCSA) and bud burst rate were not significantly different among the three systems. Shoot number was 31.3, 47.0, and 37.0 in curtain, GDC, and modified T trellis systems, respectively. The shoot length was higher (243.9 cm) in the modified T trellis system than in the single curtain (171.1 cm) and GDC (151.5 cm) systems. Interior leaf number and leaf layer number were higher in the GDC system, in which there are two primary branches, in comparison to the modified T and curtain systems, which utilize one primary branch. Primary leaf area and lateral leaf area were significantly higher in the modified T trellis system in comparison to the GDC system. Berry weight, length and diameter, and total soluble solids were not significantly different among the three trellis systems. However, cluster weight and cluster number per tree were significantly higher in GDC. Titratable acidity was significantly lower in GDC. Collectively, our data suggest that the GDC trellis system is preferable for grape 'Cheongsoo' to maintain fruit quality and quantity in Korea.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.6 no.2
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• pp.120-128
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• 2003

Purpose: Recently, while the authors were experiencing that the epidemic period of rotaviral infection happened more in the early spring, we tried to find out how the outbreaks of rotaviral infection are changing in detail depending on the weather condition since it has something to do with the climate factors and PM10. Methods: Fourteen hundreds seventy nine patients who were proved to be positive to rotavirus were chosen among children less than 5 years old from January 1995 to June 2003. Among various climate factors, monthly average temperature, humidity, rainfall and PM10 were selected. Results: Rotaviral infection was most active in 2002 as 309 (20.9%) patients. It has been the spring that is the most active period of rotaviral infection since 2000. The temperature (RR=0.9423, CI=0.933424~0.951163), rainfall (RR=1.0024, CI=1.001523~1.003228) and PM10 (RR=1.0123, CI=1.009385~1.015248) were significantly associated with the monthly distribution of rotaviral infection. Conclusion: Through this study we determined that the epidemic period of rotaviral infection is changed to spring, which is different from the usual seasonal periods such as late fall or winter as reported in previous articles. As increased PM10 which could give serious influence to the human body, and changing pattern of climate factors such as monthly average temperature and rainfall have something to do with the rotaviral infection, we suppose that further study concerning this result is required in the aspects of epidemiology, biology and atmospheric science.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.311-324
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• 1994

The quantitative knowledge of N $O_{\gamma}$ (＝N $O_{x}$ ＋HN $O_3$＋/PAN＋N $O_3$ ＋$N_2$ $O_{5}$ ＋HN $O_2$＋N $O_3$$^{-10}$ ＋organic nitrates＋......)distribution is essential in tropospheric chemistry, especially, especially that related to understanding the processes leading to ozone production. Ambient concentrations of NO, N $O_2$, HN $O_3$ and PAN as well as total N $O_{\gamma}$ were measured during June and early July 1992 at a rural site(Candor, NC), in the central Piedmont region of NC. The measurements of N $O_{\gamma}$ species were made in an effort to provide a comprehensive understanding of nitrogen chemistry and to investigate the total nitrogen budget at the site. N $O_{\gamma}$, N $O_2$, and NO showed diurnal variations with maxima in the morning. The maximum N $O_{\gamma}$ concentration reached was 14.5 ppbv, and the maximum concentrations of NO and N $O_2$ were 5.4 and 7.8 PPbv, respectively. The mean N $O_{\gamma}$ concentration as found to be 2.88$\pm$1.58 ppbv(n=743). The mean concentrations of NO and N $O_2$, were found to be 0.15 $\pm$ 0.29 ppbv(n＝785) and 1.31 $\pm$ 0.99 ppbv(n＝769). Products of photochemical oxidants, (N <$O_{\gamma}$-N $O_{x}$ ), such as HN $O_3$ and PAN, as well as ozone showed diurnal variation with maxima in the afternoon and minima at night The fractions of individual reactive nitrogen species to total N $O_{\gamma}$ were investigated and contrasted to the results from remote marine site and rural continental sites. N $O_{x}$ was the major species to total N $O_{\gamma}$(45%). NO concentrations appeared to be nearly constant whether the Prevailing winds were from continental areas or from oceanic areas. Linear regression of $O_3$ with (N $O_{\gamma}$- N $O_{x}$ )/N $O_{\gamma}$ (i.e. percent N $O_{x}$ converted to the photochemical products of N $O_{\gamma}$) yielded ( $O_3$) ＝25.8 〔 N $O_{\gamma}$-N $O_{x}$ 〕/(N $O_{\gamma}$) ＋27, ( $r^{2}$＝0.58). The regression intercept is interpreted as the ozone back ground (intercept=27ppbv) and the slope suggests that 8.6 molecules of ozone are formed per molecule of N $O_{x}$ oxidized products (when the average N $O_{\gamma}$ concentration, about 3 ppbv at the site, is used). The N $O_{x}$ N $O_{\gamma}$ ratio was used as an indicator of the chemical age of airmasses and the ratio showed strong positive correlations with HN $O_3$( $r^{2}$=0.58), PAN ( $r^{2}$=0.46) and $O_3$( $r^{2}$=0.62). Larger N $O_{\gamma}$ and N $O_{x}$ N $O_{\gamma}$ ratio were found when winds came from continental sides. It may suggest that synoptic meteorological conditions and transport of N $O_{x}$ are important in the distribution of N $O_{\gamma}$ and its relationship with photochemical oxidants at the site.

• Journal of Korean Society of Forest Science
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• v.87 no.3
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• pp.358-365
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• 1998

To offer the basic information for sustainable production of forest resources and conservation of the global environment, change in potential natural vegetation (PNV) associated with climate change due to doubling atmospheric carbon dioxide ($2{\times}CO_2$) was estimated with the global natural vegetation mapping system based an K${\ddot{o}}$ppen scheme. The system interpolates climate data spherically to each grid cell, determines the vegetation types onto the grid cell, and produces potential vegetation map and area on the globe and continents. The climate data consist of the current, ($1{\times}CO_2$) climate prior to AD 1958 observed at some 2,000 stations and the doubling ($2{\times}CO_2$) climate estimated from Meteorological Research Institute of Japan. The vegetation zone under the $2{\times}CO_2$ climate scenario expanded mainly toward the poles due to the rise in temperature. The changed PNV area on the globe amounts to 1/3 (4.91 billion (G) ha) of the total land area (15.04 Gha). Kappa statistic for judging agreement between the patterns of vegetation distribution under $1{\times}CO_2$ climate and $2{\times}CO_2$ climates shows good agreement (0.63) for the globe as a whole. The most stable areas are desert and ice. The potential forest area (PFA) was estimated at 6.82 Gha of the land area in $2{\times}CO_2$ climate scenario. In terms of continental changes in PFA, North America and Asis are increased under the $2{\times}CO_2$ climate. However, the potential forest arms of the other continents are decreased by the climate. Europe has no change in the PFA. Especially, the expansion of desert area in Oceania would be accelerated by the $2{\times}CO_2$ climate.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Journal of Preventive Medicine and Public Health
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• v.40 no.5
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• pp.363-370
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• 2007

Objectives: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. Methods: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within $37{\sim}44$ weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for $CO,\;SO_2,\;NO_2,\;and\;PM_{10}$ concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. Results: LBW risk (by Gu, or district) was significantly increased to $1.113(95%\;CI=1.111{\sim}1.116)\;for\;CO,\;1.004(95%\;CI=1.003{\sim}1.005)\;for\;NO_2,\;1.202(95%\;CI=1.199{\sim}1.206\;for\;SO_2,\;and\;1.077(95%\;CI=1.075{\sim}1.078)\;\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was significantly increased to $1.081(95%\;CI=1.002{\sim}1.166)\;for\;CO,\;1.145(95%\;CI=1.036{\sim}1.267)\;for\;SO_2,\;and\;1.053(95%\;CI=1.002{\sim}1.108)\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was increased to $1.003(95%\;CI=0.954{\sim}1.055)\;for\;NO_2$, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. Conclusions: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition. environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.