• Journal of the korean academy of Pediatric Dentistry
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• v.32 no.3
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• pp.444-453
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• 2005

Sometimes the dentists encounter a child who can not be treated with traditional behavior management techniques (for example, reward, restraint, Tell-Show-Do, familialization). In such a case, the dentists use sedation technique. Recently, in Korea, the use of sedation by pediatric dentists is increased. But, the guideline and survey of sedation is very insufficient. Now, we need a survey of sedation practice in Korea. We carried out research on the actual condition about sedation with a questionaire to pediatric dentists in Korea. Followings are the conclusions 1. Sixty six percent of pediatric dentists use sedative agents in their practice. In this study, using sedation shows an increase as compared with the past. 2. Determinative factors of using sedation were orderly behavior management, number of visiting, guidian's opinion, amount of treatment, general condition. 3. Distribution of ages in patients sedated with agents was orderly 3 years, 4-5 years, under 2 years, 6-10 years, more than 10 years. 4. Particular sedative drugs were chloral hydrate 60-70mg/kg, hydroxyzine 10-40mg/kg(25mg/kg), and oral route was the most favorable route. 5. Observation of skin and nail color, pulse oximeter were the most frequently utillized monitoring method during sedation. 6. Only fifty six percent of pediatric dentists complete the cardiopulmonary resuscitation course.

• Journal of the HCI Society of Korea
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• v.13 no.3
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• pp.55-63
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• 2018

Most people today search for information on the Internet about the goods or services they want to purchase and then assess the replies posted by other people who have experience with those goods or services. These replies serve as an important reference point that can affect purchase decisions. Replies are divided broadly into two types: first, market normative replies about whether a person experiences satisfaction with (or more than) the price paid for goods or services (positive) or not (negative); and the second is non-market normative replies about whether the goods or service provider morally deserves the profits gained from providing them (positive) or not (negative). Previous studies on replies have focused on market normative replies (whether the food is delicious), and there have only been some studies on the effect of non-market normative replies (the owner is morally good). This research was undertaken to re-examine the effect of market normative replies identified by previous studies in a restaurant visit intention evaluation (Experiment 1), to examine the effect of non-market normative replies not investigated in previous studies (Experiment 2), and to compare the effect of market normative replies and non-market normative replies (the meta-analysis) In conclusion, restaurant visit intention was stronger when market normative replies were positive (delicious) than when they were negative (not delicious) (Experiment 1). Furthermore, restaurant visit intention was stronger when non-market normative replies were positive (the owner is moral) than when they were negative (the owner is immoral) (Experiment 2). On the other hand, it was found that restaurant visit intention was stronger when non-market normative replies were positive than when market normative replies were positive, and restaurant visit intention was weaker when non-market normative replies were negative than when market normative replies were negative. This implies that people are more likely to be affected by non-market normative replies than market normative replies. In addition, this study suggested that the mood changed more before and after checking non-market normative replies than before and after checking market normative replies, and due to this difference, people could be affected more by non-market normative replies than market normative replies.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.10-27
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• 2017

Recently, the importance of recognizing the natural environment and the need for its conservation are increasing due to rapid urbanization. Suncheon Bay, designated as Scenic Site No. 41 and one of the World's Five Greatest Coastal Wetlands, is the only tideland among the tidal flats in Korea, which has salt marsh reserves. It has high conservation value from the ecological aspect. In addition to the Suncheon Bay National Garden, it provides various benefits not only to visitors but to local residents as well in terms of economics, environmental issues, and history and cultural aspects. Two million tourists visit the site annually, which has constantly highlighted the limits of ecological capacity. The valuation of the Suncheon Bay wetland is more important for the sustainability of the Suncheon Bay wetland than for its value as a tourism resource for the activation of the local economy. This study used the Logit model, which is commonly used among probabilistic choice models, to evaluate the economic value of Suncheon Bay wetland with the contingent valuation method(CVM). Applying the conservation value of the Suncheon Bay wetland to the benefit of KRW 8,200 for 1 person and 1 day, the benefit from exploration is KRW 2,050, the management and conservation value is KRW 3,034, and the heritage value is KRW 3,116. The results of this study are that benefit from the annual exploration of Suncheon Bay wetland was KRW 44.3 in billion, the management and conservation value was KRW 6.55 in billion, and the heritage value was KRW 6.73 in billion. When converted to the number of paying visitors per year, the conservation value is about KRW 177.1 billion. This study was conducted to evaluate the use and conservation aspects of the economic value of Suncheon Bay wetland. Based on the latent value of the Suncheon Bay wetland, it provides basic data about the efficient management and policy establishment of Suncheon Bay wetland. The study is significant in that the ecological sustainability of the Suncheon bay wetland and the value of non-marketable were evaluated based on the recognition of 'benefit through exploration', 'management and conservation value' and 'value of heritage'. It can be used as policy decision data on the integrated collection of the admission fee of the Suncheon Bay wetland and Suncheon Bay National Garden.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Journal of Chest Surgery
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• v.33 no.12
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• pp.941-947
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• 2000

Background: Central nervous system complication after coronary artery bypass grafting(CABG) is one of the major prognostic determinants and the use of the cardiopulmonary bypass(CPB) may increase the incidence of this devastating complication. In this study, the outcomes after off-pump CABG were studied and compared with those following the conventional CABG using CPB. Material and Method: Among the consecutive isolated CABG's performed in SNUH during Feb. 1995 and Jun. 1999, 338 coronary artery bypass grafting were divided into two groups. 223 patients underwent CABG using the CPB(Group I), and 115 patients underwent CABG without CPB(OPCAB)(Group II). All patients enrolled in this study received extensive preoperative examinations including thorough neurologic examination before and after surgery, transcranial doppler study, carotid duplex ultrasonography, and magnetic resonance angiography if necessary. Central nervous system(CNS) complications were defined as stroke, seizure, metabolic or hypoxic encephalopathy and transient delirium after surgery. Result: There were 61 cases(27.3%) who developed postoperative CNS complication in Group I, whereas 8 cases(7.0%) of CNS complications developed postoperatively in group II(p<0.05). Statistically significant predictors of postoperative CNS complications in group I were age and the use of cardiac assist devices perioperatively. Conclusion: This study suggested that omitting the use of CPB in CABG resulted in significant decrease of the postoperative CNS complications. OPCAB should be more widely applied especially to the elderly who have preexisting cerebrovascular disease.

• Journal of Environmental Impact Assessment
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• v.28 no.5
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• pp.427-439
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• 2019

Natural environmental ecology ofthe environmental impact assessment(EIA)is very much lacking in quantitative evaluation. Thus, this study attempted to evaluate quantitative assessment for ecosystem service in the site of Eco-delta project in Busan. As a part of climate change adaptation, this study evaluated and compared with the value for carbon fixation and habitat quality using the InVEST model before and after development with three alternatives of land-use change. Carbon fixation showed 216,674.48 Mg of C (year 2000), and 203,474.25 Mg of C (year 2015)reducing about 6.1%, and in the future of year 2030 the value was dropped to 120,490.84 Mg of C which is 40% lower than year 2015. Alternative 3 of land use planning was the best in terms of carbon fixation showing 6,811.31 Mg of C. Habitat quality also changed from 0.57 (year 2000), 0.35 (year 2015), and 0.21 (year 2030) with continued degradation as development goes further. Alternative 3 also was the highest with 0.21(Alternative 1 : 0.20, Alternative 2 : 0.18). In conclusion,this study illustrated that quantitative method forland use change in the process of EIA can helpdecision making for stakeholders anddevelopers with serving the best scenario forlow impact of carbon. Also it can help better for land use plan, greenhouse gas and natural environmental assets in EIA. This study could be able to use in the environmental policy with numerical data of ecosystem and prediction. Supplemented with detailed analysis and accessibility of basic data, this method will make it possible for wide application in the ecosystem evaluation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.1-24
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• 2021

The Korean government is currently expanding the business startup incubator support program and funds for new ventures with innovative technology in order to spread the second venture boom. However, despite the fact that entrepreneurial education and mentoring that entrepreneurs should have are important parts for the sustainable growth of the startup, some companies selected for government support programs are reluctant to participate in programs such as entrepreneurship education and mentoring for the sole purpose of funding commercialization. This research addressed the effects of entrepreneurial alertness with opportunity awareness as its medium and the small business mentoring service along with the number of times the mentoring has taken place, on the corporate performances. The results of empirical research are as follow: the first one is that scanning-search and evaluation-judgment can influence a company's performance (financial, non-financial) through opportunity recognition, with the exception of association-connection, which is a sub-factor of entrepreneurial alertness. Secondly, it was found to affect a company's financial and non-financial performance through opportunity recognition for financing mentoring, technical support mentoring, and management support mentoring. Thirdly, it was found that the number of mentoring also affects the financial and non-financial performance of a company through opportunity recognition. The implications of this study are that it should be revisited that program managers consider rooms that do not violate the startup founder's strategic decision-making opportunities when designing and operating the program as entrepreneurial alertness sub-factor association-connection does not affect corporate performance through opportunity recognition. This study also emphasizes the need for customized mentoring to meet the outcome goals of each startup, as it has been empirically clarified that the mentoring provided to the startup by the government's support is important. The contribution of this research is that entrepreneurial alertness and opportunity recognition that are treated as important components in research for entrepreneurship, and the factors of mentoring and mentoring frequency that are recognized as important elements in the practical aspect of startup business are clarified theoretically and empirically as an influential factor in corporate performance. And this study also provide a rationale for the startup business support agency supplying mentoring.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.49-62
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• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Korean Journal of Environment and Ecology
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• v.33 no.4
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• pp.472-480
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• 2019

Selection of the plant material for planting to reduce fine dust should comprehensively consider the visual characteristics, such as the shape and texture of the plant leaves and form of bark, which affect the adsorption function of the plant. However, previous studies on reduction of fine dust through plants have focused on the absorption function rather than the adsorption function of plants and on foliage plants, which are indoor plants, rather than the outdoor plants. In particular, the criterion for selection of fine dust reduction species is not specific, so research on the selection criteria for plant materials for fine dust reduction in urban areas is needed. The purpose of this study is to identify the priorities of eight indicators that affect the fine dust reduction by using the fuzzy multi-criteria decision-making model (MCDM) and establish the tree selection criteria for the urban planting to reduce fine dust. For the purpose, we conducted a questionnaire survey of those who majored in fine dust-related academic fields and those with experience of researching fine dust. A result of the survey showed that the area of leaf and the tree species received the highest score as the factors that affect the fine dust reduction. They were followed by the surface roughness of leaves, tree height, growth rate, complexity of leaves, edge shape of leaves, and bark feature in that order. When selecting the species that have leaves with the coarse surface, it is better to select the trees with wooly, glossy, and waxy layers on the leaves. When considering the shape of the leaves, it is better to select the two-type or three-type leaves and palm-shaped leaves than the single-type leaves and to select the serrated leaves than the smooth edged leaves to increase the surface area for adsorbing fine dust in the air on the surface of the leaves. When considering the characteristics of the bark, it is better to select trees that have cork layers or show or are likely to show the bark loosening or cracks than to select those with lenticel or patterned barks. This study is significant in that it presents the priorities of the selection criteria of plant material based on the visual characteristics that affect the adsorption of fine dust for the planning of planting to reduce fine dust in the urban area. The results of this study can be used as basic data for the selection of trees for plantation planning in the urban area.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.