• Korean journal of applied entomology
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• v.59 no.1
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• pp.55-64
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• 2020

Smart greenhouses are primarily used for growing fruits and vegetables, such as sweet peppers, tomatoes, strawberries. Although the number of smart greenhouses has been increasing exponentially, no studies have been performed to evaluate the state of smart greenhouses in Korea. Therefore, this study was conducted to determine current state of smart greenhouses with regard to greenhouse specifications, crop growing methods, pests, and user satisfaction in Korea. Contact information for smart greenhouses was provided by the officials of local agricultural research and extension services. This survey was conducted by visiting each greenhouse. Results showed that approximately 50% of surveyed smart greenhouses were between 3,300 ㎡ and 6,600 ㎡. The most frequently chosen method for pest control was chemical pesticides (97.1%). Powdery mildew and gray mold comprised 54.4% and 33.8% of the crop diseases, respectively. All tomato greenhouse farmers considered whiteflies the most problematic pest. In contrast, 76.5% and 70.6% of sweet pepper farmers believed thrips and aphids posed significant threats, respectively. The mean satisfaction score was 7.5 out of 10 points, with 10 being "extremely satisfied". These results will aid in decision making with respect to the management of current smart greenhouses and the design of future smart farms in Korea.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.242-261
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• 2012

Early stages of technology valuation have been often overlooked or under-represented. The early stage technologies are even riskier due to their inadequacy of commercial development and market applicability. More than 95% of patents fail to earn any revenues so that the majority of patents were valueless. Technology transfers from laboratories at universities and research institutes to industrial firms have increased to acquire value from invented technologies. Technology transfer, a process of transferring discoveries and innovations resulted from research to commercial sectors, typically comprises several steps: disclosing the discoveries and innovations, i.e., intellectual property (IP), evaluating the IP's economic prospects, securing a patent, copyright or trademark for the IP, commercializing the technology through licensing, forming a joint venture, or selling. At each of those stages in the research and development of technology, the value of technology would play a very important role of making decision on the movement toward the next step, however, the financial value of technology is not easy to determine due to a great amount of uncertainty in the course of research and development, and commercialization. This paper refers to technology embodied as devices, equipment, software or processes primarily developed at public research institutions such as universities. Sometimes it is also as the result of externally financed projects contracted with industry. Nearly always technology developed at public research entities results in laboratory prototypes. When it is required to define the technology transfer contract terms for the license of the university patrimonial rights to external funding companies or other interested parties, a question arises: what is the monetary value? In this paper, we present a method for technology valuation based on the identification of specific value points related to its development. The final technology value must be within previously defined value limits. This paper consists of the review of issues related to technology transfer and commercialization, the identification of characteristics of technologies in the early stage of technology development, the formulation of framework of methods to value the early stage technologies, and the conclusion and implication of the previous review.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.8
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• pp.1088-1096
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• 2006

The purpose of this study was to identify the service encounter blueprint by types of restaurants in order to manage moment of truth when customers who visit a restaurant encounter services. The service encounter blueprint gives an overall picture of the service provision to visualize an entire service process and its integrated structure. The blueprint is used for service process analysis technique. The random samples of 15 customers were observed by types of restaurants and the records were collected for three-days' observation. Interviews were performed by 3 managers, 3 service encounter employees, 3 cashiers, 3 cooks and 10 customers by types of restaurants. After drawing the first service blueprint, it was revised by the interview with the 3 managers and 6 service encounter employees. In this paper, restaurant service processes are reviewed and analyzed. By use of service blueprint, the processes are analyzed to find a fail point, customer wait, employee decision. As a result of making a blueprint of service encounter by types of restaurant, blueprints of fine-dining restaurants and family restaurants were similar, while fast-food restaurants showed a little difference. In particular, difference was indicated in a point where interaction of service encounter occurred. Difference was indicated depending on types of restaurants. Therefore, the efforts to improve this problem were needed. The blueprint is a map or flowchart (called a process chart in manufacturing) of all transactions constituting the service delivery process. The results showed that service encounter blueprint can be used to improve the service process in the restaurant's encounter.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.438-453
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• 2009

Attracting advanced foreign enterprises into the less-developed regions has gained increasing importance as a regional development strategy in Korea. This study critically examines the foreign-direct investment-led regional development strategy of Wales, United Kingdom. Despite a high FDI inflow in manufacturing, the Welsh regional economy has suffered from specialization in low-skilled assembly with limited R&D activities, insufficient linkage with local domestic suppliers, and violent fluctuation in local employment in response to changes within the global business environment. This tendency shows that the foreign-invested companies have neither locally embedded themselves enough nor created the external agglomeration economies in the region. At the same time, the Welsh local government's excessive dependence on financial incentives packages to induce multinationals, rather than effort to create regional innovative capacity, has resulted in a sizable fiscal loss, an abused local planning process, and subordination of the local government's major administrative decision-making on foreign investors. The Welsh FDI case suggests that an effective FDI attraction policy should include inter-regional cooperation and coordination in the inward investment attraction procedure, a comprehensive land use planning process, and state-level concrete governance on FDI.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.173-185
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• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.

• Korean small business review
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• v.41 no.3
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• pp.49-75
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• 2019

Market instability offers opportunities as well as the need for careful innovation strategies and learning for a company's survival. Companies that find new opportunities decide to carry out innovation and decide on the size of their investments by considering their position in the market they are aiming for and the intensity of competition. This study was conducted to check whether obstacles to innovation face by SMEs in the manufacturing sector vary depending on the stage of corporate growth and to identify the impact of the government support system on the decision-making process on the performance of innovation. According to the analysis, there were differences in obstacles to innovation depending on the stage of corporate growth. It was found that more innovative SMEs are, more obstacles they face, and to overcome such obstacles, they try to access government support systems more. In addition, the use of a government support system eliminated obstacles to innovation, and the positive and significant effects of investing in innovation were identified. This study is meaningful in that it explicitly approached these hypotheses by applying a multistage model to the process of innovation carried out by SMEs in the manufacturing sector.

• Tuberculosis and Respiratory Diseases
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• v.43 no.4
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• pp.558-570
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• 1996

Background : The detection of Collapsible airways has important therapeutic implications in chronic airway disease and bronchial asthma. The distinction of a purely collapsible airways disease from that of asthma is important because the treatment of the dormer may include the use of pursed lip breathing or nasal positive pressure ventilation whereas in the latter, pharmacologic approaches are used. One form of irreversible airflow limitation is collapsible airways, which has been shown to be a Component of asthma or to emphysema, it can be assessed by the volume difference between what exits the lung as determined by a spirometer and the volume compressed as measured by the plethysmography. Method : To investigate whether volume difference between slow and forced vital Capacity(SVC-FVC) by spirometry may be used as a surrogate index of airway collapse, we examined pulmonary function parameters before and after bronchodilator agent inhalation by spirometry and body plethysmography in 20 cases of patients with evidence of airflow limitation(chronic obstructive pulmonary disease 12 cases, stable bronchial asthma 7 cases, combined chronic obstructive pulmonary disease with asthma 1 case) and 20 cases of normal subjects without evidence of airflow limitation referred to the Pusan National University Hospital pulmonary function laboratory from January 1995 to July 1995 prospectively. Results : 1) Average and standard deviation of age, height, weight of patients with airflow limitation was $58.3{\pm}7.24$(yr), $166{\pm}8.0$(cm), $59.0{\pm}9.9$(kg) and those of normal subjects was $56.3{\pm}12.47$(yr), $165.9{\pm}6.9$(cm), $64.4{\pm}10.4$(kg), respectively. The differences of physical characteristics of both group were not significant statistically and male to female ratio was 14:6 in both groups. 2) The difference between slow vital capacity and forced vital capacity was $395{\pm}317ml$ in patients group and $154{\pm}176ml$ in normal group and there was statistically significance between two groups(p<0.05). Sensitivity and specificity were most higher when the cut-off value was 208ml. 3) After bronchodilator inhalation, reversible airway obstructions were shown in 16 cases of patients group, 7 cases of control group(p<0.05) by spirometry or body plethysmography d the differences of slow vital capacity and forced vital capacity in bronchodilator response group and nonresponse group were $300.4{\pm}306ml$, $144.7{\pm}180ml$ and this difference was statistically significant. 4) The difference between slow vital capacity and forced vital capacity before bronchodilator inhalation was correlated with airway resistance before bronchodilator(r=0.307 p=0.05), and the difference between slow vital capacity and forced vital capacity after bronchodilator was correlated with difference between slow vital capacity and forced vital capacity(r=0.559 p=0.0002), thoracic gas volume(r=0.488 p=0.002) before bronchodilator and airway resistance(r=0.583 p=0.0001), thoracic gas volume(r=0.375 p=0.0170) after bronchodilator, respectively. 5) The difference between slow vital capacity and forced vital capacity in smokers and nonsmokers was $257.5{\pm}303ml$, $277.5{\pm}276ml$, respectively and this difference did not reach statistical significance(p>0.05). Conclusion : The difference between slow vital capacity and forced vital capacity by spirometry may be useful for the detection of collapsible airway and may help decision making of therapeutic plans.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Korean journal of applied entomology
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• v.49 no.3
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• pp.219-226
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• 2010

This paper presents the occurrence and damage characteristics of the rice leaf-folder populations in the paddy fields of Dangsu-dong, Suwon from 2004 to 2007, and also reports the insecticide response of rice leaf-folder populations, which were collected from 2005 to 2006 in Korea and Vietnam. Laboratory measurements of the head capsule width and body length data enabled the identification of the rice leaf-folder larva stages collected in the field. The rice leaf-folder population in Suwon from 2004 to 2007 has a clear pattern consisting of two different group: the low and high density years. During the low density years (2004 and 2006), only one adult peak was noted in late August, with the damaged-hill percent less than 10% in late July, and the damaged-leaf percent around 2% in September. In contrast, during the high density years (2005 and 2007), two adult peaks were noted in early August and mid-September, with the damaged-hill percent was around 30% in late July, and the damaged-leaf percent 15 to 30% in September, which was beyond the economic injury level of rice leaf-folder. High correlations existed between the occurrence of rice leaf-folder in late July and early August and damages to rice during September. Based on these results, we suggest that the information on the rice leaf-folder population monitored by the adult density or damaged-hill percent in late July and early August would be very useful for predicting the damages later in the season for aiding in decision-making for timely control. In addition, the regional populations of rice leaf-folder showed the similar responses to the insecticides tested: high susceptibility to IGRs (tebufenozide and methoxyfenozide) and organophosphates (chlorpyrifos-methyl, pyridaphenthion), but relatively low to cartap.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.277-307
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• 2016

Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.