Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.5
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pp.1-14
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2021
Innovation and Scale-up of Start-up companies are becoming important national tasks. In the past, it was spread the start-up policy paradigm such as 'Start-up America', 'Start-up Chile', 'Start-up Britain' to overcome the recession globally. However as the economic recovery has become more visible recently in advanced economies, it is shifting from a start-up support policy to a scale-up oriented policy paradigm such as 'Scale-up America', Scale-up UK', 'Scale-up Denmark'. It is necessary to enter the scale-up phase beyond the start-up phase to increase the number of high-quality jobs and to continue economic growth. Therefore, it is necessary to grow the start-up into a strong medium-sized company and to lay the foundation for survival. Therefore, the purpose of this study is to consider the antecedent factors that influence the scale-up aspiration for the start-up firm to grow into a scale-up company, and empirically identifies the differences between the stages of economic development and entrepreneurs in the country. In order to accomplish the purpose, this study predicted scale-up by aspiration which is a predictor of scale-up behavior because it is difficult to achieve visible growth in a short period of time due to the characteristics of start-up companies. In order to empirically explore these relationships, the data were collected from nascent entrepreneurs who have less than 3.5 years of the Adult Population Survey(APS) among the subjects surveyed by the Global Entrepreneurship Monitor(GEM) and the national economic development stage are divided into Innovation-driven, Efficiency-driven, Factor-driven type economies. For the test hypotheses, this study adopted the multi-level model analysis for comparison between national economic development stages and using the R 3.5.0 program. The results of this study are as follows. There is difference between the national economic development and the entrepreneur in the relationship between innovation orientation of entrepreneurs and scale-up aspirations. As the economy of the country develops, the innovation activity of the entrepreneur becomes more active. Since start-ups are heavily influenced by entrepreneurs, there is a difference in the degree of aspiration depending on how innovative an entrepreneur is in the same environment. In terms of the relationship between innovation orientation and scale-up aspiration, the fear of failure was found to differ between national economic development and entrepreneurs. The fear of failure differ from country to country, and this is one of the important factors affecting entrepreneurial activities. It is expected that the factors influencing the growth of the start-up companies which are identified through the results of these studies, will be used to create a suitable scale-up ecosystem according to the national economic development stage.
In general, stormwater flows to the road surface, especially in urban areas, and it is discharged through the drainage grate inlets on roads. The appropriate evaluation of the road drainage capacity is essential not only in the design of roads and inlets but also in the design of sewer systems. However, the method of road surface flow analysis that reflects the topographical and hydraulic conditions might not be fully developed. Therefore, the enhanced method of road surface flow analysis should be presented by investigating the existing analysis method such as the flow analysis module (uniform; varied) and the flow travel time (critical; fixed). In this study, the algorithm based on varied and uniform flow analysis was developed to analyze the flow pattern of road surface. The numerical analysis applied the uniform and varied flow analysis module and travel time as parameters were conducted to estimate the characteristics of rainfall-runoff in various road conditions using the developed algorithm. The width of the road (two-lane (6 m)) and the slope of the road (longitudinal slope of road 1 - 10%, transverse slope of road 2%, and transverse slope of gutter 2 - 10%) was considered. In addition, the flow of the road surface is collected from the gutter along the road slope and drained through the gutter in the downstream part, and the width of the gutter was selected to be 0.5 m. The simulation results were revealed that the runoff characteristics were affected by the road slope conditions, and it was found that the varied flow analysis module adequately reflected the gutter flow which is changed along the downstream caused by collecting of road surface flow at the gutter. The varied flow analysis module simulated 11.80% longer flow travel time on average (max. 23.66%) and 4.73% larger total road surface discharge on average (max. 9.50%) than the uniform flow analysis module. In order to accurately estimate the amount of runoff from the road, it was appropriate to perform flow analysis by applying the critical duration and the varied flow analysis module. The developed algorithm was expected to be able to be used in the design of road drainage because it was accurately simulated the runoff characteristics on the road surface.
This study was conducted to evaluate the possibility of applying phytoremediation technology by investigating soil and native plants in waste coal landfills exposed to heavy metal contamination for a long period of time. The ability of native plants to accumulate heavy metals using greenhouse cultivation experiments was alse evaluated. Plants were investigated at an abandoned coal mine in Hwajeolyeong, Jeongseon, Gangwon-do. Two species of native plants (Carex breviculmis. R. B. and Salix koriyanagi Kimura ex Goerz.) located in the study area and three Korean native plants (Artemisia japonica Thunb. Hemerocallis hakuunensis Nakai., and Saussurea pulchella (Fisch.) Fisch.) were cultivated in a greenhouse for 12 weeks in artificially contaminated soil. Soils contaminated with arsenic and lead were generated with arsenic concentration gradients of 25, 62.5, 125, and 250 mg kg-1 and lead concentration gradients of 200, 500, 1000, and 2000 mg kg-1, respectively. Results showed that none of the five plants could survive at high arsenic concentration treatment (125 and 250 mg kg-1) and some plants died in 2000 mg kg-1 lead concentration treatment soil. The plant translocation factor (TF) was highest in H. hakuunensis in arsenic treatments, and A. japonica in lead treatments, respectively. The bioaccumulation factor (BF) of plants was more than 1 in all species in arsenic treatment, whereas it was highest in H. hakuunensis. BF for all species was less than 1 in lead treatment. Particularly, in 2000 mg kg-1 concentration lead treatment, A. japonica accumulated more than 1000 mg kg-1 lead and was expected to be a lead hyperaccumulator. In conclusion, A. japonica and H. hakuunensis were excellent in the accumulation of arsenic heavy metals, and S. koriyanagi was excellent in lead accumulation ability. Therefore, the above mentioned three plants are considered to be strong contenders for application of the phytoremediation technology.
This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.
This study analyzed the case of elderly care cluster in Gwangjin-gu to explore the possibilities of social economy as a provider of community-based social services. Community-based means the approach by which community organizations build a voluntary and collaborative network to enhance collective problem-solving abilities. Therefore, it is very likely that the social economy that emphasizes people, labor, community, and democratic principles can contribute to community-based social services. This study analyzed social economic network by using four characteristics of social economy suggested by OECD community economy and employment program as an analysis framework. The results of this study are as follows: First, it is found that social economy would hardly supply community-based social services through network cooperation because of a large variation in community identity, investment to new product, and labor protection. Second, community users are not the consumers of the social economy and the products of the social economy stay in market products only for the organizations in social economy. In order to create good services that meet the needs of residents, community development approaches are required at the same time. The importance of community space where local residents and social economy meet is derived. Third, public support such as purchasing support has weakened the ecosystem of social economy by making the distinction between public economy and social economy more obscure. On the other hand, public investment in community infrastructure is an indirect aid to social economy to communicate with residents and to promote good supply and consumption. In the end, community-based social services need a platform where the social economy and the people meet. This type of public investment can create the ecosystem of the social economy.
Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.
The sugar beet cyst nematode (SBCN), Heterodera schachtii first detected in Taebaek, Gangwon-do in 2011, is one of the major plant parasitic nematodes that cause economic damage to the Chinese cabbage in highland regions. In addition, the distribution of clover cyst nematode (CCN), H. trifolii was confirmed in the highland Chinese cabbage cultivated regions in 2017. In order to investigate the spread of cyst nematodes, this study has been conducted since 2013 in the highland Chinese cabbage cultivation area. In addition, in 2017, the Real-Time PCR technique with the species-specific primer was used to investigate those two cyst nematodes and the soybean cyst nematode (SCN), H. glycines which is known for its distribution in Korea, focusing on the main production regions of highland Chinese cabbage cultivation. The number of infected fields in the Chinese cabbage plantation in highland increased every year to confirm distribution in Taebaek, Samcheok, Jeongseon and Gangneung in 2017, and the cumulative number of infection fields reached 245 by 2017. Of the 41 possible cyst nematode samples for PCR analysis, 61% were CCN, only 9.8% of the SBCN and 29.3% of the SCN were identified. Therefore, some of the previously known SBCN or CCN discoveries are likely to have been infected with SCN. It is believed that the CCN needs to be controlled in the future as CCN have been found to be dominant species in the highland Chinese cabbage plantation regions.
Korean Journal of Agricultural and Forest Meteorology
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v.21
no.3
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pp.135-145
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2019
Analysis of a long cycle or a trend of time series data based on a long-term observation would require comparability between data observed in the past and the present. In the present study, we proposed an approach to ensure the compatibility among the instruments used for the long-term observation, which would allow to secure continuity of the data. An open-path gas analyzer (Model LI-7500, LI-COR, Inc., USA) has been used for eddy covariance flux measurement in the Gwangneung deciduous forest for more than 10 years. The open-path gas analyzer was replaced by an enclosed-path gas analyzer (Model EC155, Campbell Scientific, Inc., USA) in July 2015. Before completely replacing the gas analyzer, the carbon dioxide ($CO_2$) and latent heat fluxes were collected using both gas analyzers simultaneously during a five-month period from August to December in 2015. It was found that the $CO_2$ fluxes were not significantly different between the gas analyzers under the condition that the daily mean temperature was higher than $0^{\circ}C$. However, the $CO_2$ flux measured by the open-path gas analyzer was negatively biased (from positive sign, i.e., carbon source, to 0 or negative sign, i.e., carbon neutral or sink) due to the instrument surface heating under the condition that the daily mean temperature was lower than $0^{\circ}C$. Despite applying the frequency response correction associated with tube attenuation of water vapor, the latent heat flux measured by the enclosed-path gas analyzer was on average 9% smaller than that measured by the open-path gas analyzer, which resulted in >20% difference of the sums over the study period. These results indicated that application of the additional air density correction would be needed due to the instrument heat and analysis of the long-term observational flux data would be facilitated by understanding the underestimation tendency of latent heat flux measurements by an enclosed-path gas analyzer.
Kim, Kwang Soo;Yoo, Byoung Hyun;Hyun, Shinwoo;Kang, DaeGyoon
Korean Journal of Agricultural and Forest Meteorology
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v.21
no.3
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pp.175-186
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2019
Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.
Kim, Chul-Gyum;Lee, Jeongwoo;Lee, Jeong Eun;Kim, Nam Won;Kim, Hyeonjun
Journal of Korea Water Resources Association
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v.54
no.9
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pp.731-745
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2021
In this study, the monthly temperature of the Han River basin was predicted by statistical multiple regression models that use global climate indices and weather data of the target region as predictors. The optimal predictors were selected through teleconnection analysis between the monthly temperature and the preceding patterns of each climate index, and forecast models capable of predicting up to 12 months in advance were constructed by combining the selected predictors and cross-validating the past period. Fore each target month, 1000 optimized models were derived and forecast ranges were presented. As a result of analyzing the predictability of monthly temperature from January 1992 to December 2020, PBIAS was -1.4 to -0.7%, RSR was 0.15 to 0.16, NSE was 0.98, and r was 0.99, indicating a high goodness-of-fit. The probability of each monthly observation being included in the forecast range was about 64.4% on average, and by month, the predictability was relatively high in September, December, February, and January, and low in April, August, and March. The predicted range and median were in good agreement with the observations, except for some periods when temperature was dramatically lower or higher than in normal years. The quantitative temperature forecast information derived from this study will be useful not only for forecasting changes in temperature in the future period (1 to 12 months in advance), but also in predicting changes in the hydro-ecological environment, including evapotranspiration highly correlated with temperature.
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