• Pediatric Infection and Vaccine
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• v.7 no.2
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• pp.225-232
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• 2000

Purpose : The use antimicrobial agents is one of the important strategies for the treatment and prophylaxis of microbial infections. But injudicious abuse and misuse of antimicrobial agents is problem to add an extra weight on medical fee, increase of resistant bacteria and side effects according to the antibiotic use. This study was performed to establish the pertinent use of antimicrobial agent in Chonbuk National University Hospital(CNUH). Characteristics of antibiotics use was analysis by reviewing the medical records of patients admitted to CNUH during the period of May 1998. Methods : One thousand eight hundred and thirty three patients were enrolled in this study(medical division 1,014 cases, surgical division 819 cases). Medical records were retrospectively reviewed to classify the rate of antibiotics use, name of antibiotics used, appropriateness of antibiotics use. Results : The overall rate of antibiotic usage in CNUH was 67.2%(1,231/1,833), showing higher rate in surgical division(89.6%) compare to that of medical division(49.0%). Among 1,231 patients to whom antimicrobial agents were given, only 125(10.2%) were treated with single antimicrobial agents. 311(25.3%) were treated with two antimicrobial agents, and 795(64.5%) patients received 3 or more antibiotics. ${\beta}$-lactams(56.4%) were most frequently used followed by aminoglycosides(35.3%), the others(4.9%) and quinolons(3.4%). Amoxicillin-clavulanate was the mostly commonly used antibiotics followed by amoxicillin and unasyn. Prophylactic use of antibiotics was carried in seven hundred six patients(57.4%), mostly in surgical division, which can be considered somewhat inappropriate in the initiation time and duration of antibiotic use. Conclusion : Importance of monotherapy and appropriate prophylactic antibiotic use should be emphasized. Strategies of antibiotics use, such as restriction of drug use, continuous monitoring system, flow sheet system should be considered to reduce antibiotics use and establish the appropriate use of antibiotics as well as inhibiting the occurrence of resistant strains.

• Journal of Korean Society of Forest Science
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• v.85 no.1
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• pp.1-14
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• 1996

The object of this study was to examine the effects of air pollution on forest vegetation structure in the vinicity of Sasang industrial complex in Korea. Forest vegetation structure was investigated at 19 sample plots surrounding industrial complex and at one site away from industrial complex as a control. The results obtained were as follows; 1. For analysis of vegetation structure, upperstory of forests was mostly consisted of Pinus thunbergii, and partly of Alnus firma and Robinia pseudoacacia. In midstory, major components were Pinus thunbergii, Robinia pseudoacacia, Rhus trichocarpa, Rhus chinensis and Styrax japonica, In lower story, Pinus thunbergii was a minor component, while Robinia pseudoacacia, Quercus serrata, Rhus trichocarpa. and Rhododendron yedoense var. poukhanense which were known to be resistant to air pollution were found in large number. Especially, importance percentage of Robinia pseudoacacia was high, while that of Rhododendron mucronulatum was low in surrounding industrial complex. 2. For woody plants, number of species, species diversity and similarity index in industrial complex, were not significantly different from those in control plot. 3. For herbs, Oplismenus undulatifolius appeared in large number in most plots. The $SDR_3$ of Miscanthus sinensis, Calamagrostis arundinacea, Paederia scandens, Spodiopogon cotulifer and Carex humilis were high, but that of Aster scaber, Saussurea seoulensis, Solidago virgaaurea var. asiatica and Prunella vulgaris var. lilacina were low in the vicinity of industrial complex. 4. Number of herb species decreased to below 10 species at surrounding industrial complex as compared to 20 species in the control plot. In addition species diversity, and similarity index in the industrial complex were lower than those in control plot. It may be concluded that Pinus thunbergii forests in industrial complex consists of tree species resistant to air pollution, and that composition of woody vegetation in industrial complex was not much different from control plot, while composition of herbs was already quite different between the two plots. Forest vegetation structure, therefore, may change with time due to air pollution in the industrial complex.

• Journal of vocational education research
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• v.37 no.6
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• pp.1-15
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• 2018

The objective of this study is to provide the basic data for the efficient operation of industry-academia partnership apprenticeship school, by analyzing the interest in the relevant policy, targeting the interested parties of school and corporation as the two main subjects operating the industry-academia partnership apprenticeship school. Using the Concerns-Based Adoption Model(CBAM) used for understanding the interested parties' interest in the adoption of a certain new changing. In the results of analysis, first, currently, the operating subjects of industry-academia partnership apprenticeship school showed the similar interest with the pattern of nonusers. In other words, currently, based on the curiosity about the relevant policy, they are interested in which roles they should perform for the successful operation. Second, when dividing the operating subjects of industry-academia partnership apprenticeship school into school parties and corporate parties, the results of examining the differences in the interest of each subject are as follows. First, in the stages except for the Stage 0(indifference), the interest of school parties was relatively higher than the one of corporate parties. It might be because the school's role is bigger in the operation of industry-academia partnership apprenticeship school, contrary to the advanced countries. In other words, in case of school parties, the overall and general understanding of the relevant policy is premised, so that their interest of each stage is higher than the one of corporate parties. Especially, the Stage 5(cooperative interest) showed the biggest differences. As the cooperation between industry and academia is the success factor of the relevant policy, it would be necessary to implant the concrete measures for industry-academia cooperation in school parties, and also to implant the importance of industry-academia cooperation in corporate parties. Next, both operating subjects showed the lowest intensity in the Stage 4(consequential interest). It means that the operating subjects' interest in the evaluation of apprenticeship students is relatively low.

• The Journal of Engineering Geology
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• v.32 no.3
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• pp.411-420
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• 2022

Recently, research using remote sensing has been active in various fields such as environment, science, and society. The results of research using remote sensing are not only numerical results, but also play an important role in solving and preventing social and scientific problems. The purpose of this thesis is to tell the correlation between the data provided and each data by using remote sensing technology for the tidal flat environment. The purpose of this study is to obtain high-resolution data using artificial satellites during remote sensing to find out information on tidal flat currents. Tidal flats created by erosion, sedimentation, low tide, and high tide contain information about the tidal flat slope and information about the ecosystem. Therefore, it can be considered as one of the very important studies to analyze the overall tidal flow channel. This paper creates a DEM (Digital Elevation Model) through TanDEM-X, and DEM is used as the most basic data to create a tidal channel. The research area is a tidal flat located in the middle of the west coast of Ganghwado tidal flat. By analyzing the tidal channel created, various information such as the slope direction of Ganghwado tidal flat and the shape of the tidal channel can be grasped. It is expected that the results of this study will increase the importance and necessity of using DEM data for tidal flat research in the future, and that high-quality results can be obtained.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.553-565
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• 2022

Awareness of the ecological value and importance of protected areas has increased as climate change accelerates, and there is a need for research on ecosystem services provided by nature. The natural park, which is a representative protected area in Korea, has a system of national parks, provincial parks, and county parks. National parks are managed systematically by the Korea National Park Service, but local governments manage provincial parks and county parks. There may be the same hierarchical differences in naturalness (habitat quality) depending on the hierarchy of the natural parks, but it has not been verified. To identify differences, we examined 22 mountain-type natural parks using habitat quality using the INVEST model developed by Stanford University. The analysis of the habitat quality, regardless of the type and area of the natural park, showed that it was higher in the order of Taebaeksan National Park (0.89), Juwangsan National Park (0.87), Woongseokbong County Park (0.86), and Gayasan National Park (0.85). The larger the area, the higher the value of habitat quality. A comparison of natural parks with similar areas showed that the habitat quality of national parks was higher than that of provincial parks and parks. On the other hand, the average habitat quality of county parks was 0.83±0.02, which was 0.05 higher than that of provincial parks at 0.78±0.03. Furthermore, the higher the proportion of forest areas within the natural park, the higher the habitat quality. The results confirmed that the naturalness of natural parks was independent of their hierarchy and that there are differences in naturalness depending on land use, land coverage, and park management.

• 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.

• Journal of Hospice and Palliative Care
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• v.9 no.2
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• pp.67-76
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• 2006

Purpose: The purpose of this study was to develop education program for physicians who work at hospice palliative care settings in Korea, to practice abridged education program extracted from the full contents of the proposed education, and to improve the quality of hospice palliative care service. Methods: To develop the education program, questionnaire for hospice education need assessment (total 79 items) was distributed to 125 organizations practicing hospice service via mail and the data was collected from 1 Sep. to 10 Oct. 2004. Another questionnaire for hospice education importance assessment was asked to the palliative specialists from Sep. 23 to 17 Oct. 2004. Based on the analysis of the questionnaires, and reviewing various references and actual hospice palliative education programs of other countries, the education programs were developed. Results: Ore-day-Hospice education 2004 was conducted based on the suggested education program, and it was practiced four times on a national basis (2 times in Seoul, and once in Busan and Gwangju, respectively). 47 physicians attended the education program. The education program lasted about 7 hours, comprising 5 hours of common lectures for all attendants regardless of their professions and 2 hours of specific seminar for physicians only. Attendants positively responded to the contents of the education program. But they pointed out that the program should be offered on weekday and it should be more in-depth and more discussion based lesson. Conclusion: The suggested education program was not fully conducted yet. After practicing the abridged education program, more in-depth and discussion oriented rather than lecture-based education were suggested. It may be argued that the proposed education, which requires much longer period education, should also reflect the evaluation of the 1-day education program to successfully implement the proposed education program.

• Korean Journal of Agricultural Science
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• v.10 no.2
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• pp.324-333
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• 1983

Modeling of longterm runoff is theoritically based on waterbalance analysis. Simplified equation of water balance with rainfall, evapotranspiration and soil moisture storage could be formulated into regression model with variables of rainfall, pan evaporation and previous-month streamflow. The hydrologic response of water shed could be represented lumpedly, qualitatively and deductively by regression coefficients of water-balance regression model. Characteristics of regression modeling of water-balance were summarized as follows; 1. Regression coefficient $b_1$ represents the rate of direct runoff component of precipitation. The bigger the drainage area, the less $b_1$ value. This means that there are more losses of interception, surface detension and transmission in the downstream watershed. 2. Regression coefficient $b_2$ represents the rate of baseflow due to changes of soil moisture storage. The bigger the drainage area and the milder the watershed slope, the bigger b, value. This means that there are more storage capacity of watershed in mild downstream watershed. 3. Regression coefficient $b_3$ represents the rate of watershed evaporation. This depends on the s oil type, soil coverage and soil moisture status. The bigger the drainage area, the bigger $b_3$ value. This means that there are more watershed evaporation loss since more storage of surface and subsurface water would be in down stream watershed. 4. It was possible to explain the seasonal variation of streamflow reasonably through regress ion coefficients. 5. Percentages of beta coefficients what is a relative measure of the importance of rainfall, evaporation and soil moisture storage to month streamflow are approximately 89%, 9% and 11% respectively.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.81-96
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• 2020

This study aims to identify implications for the role of home economics in consumer education in middle schools focusing on building consumer competency. To this end, the content in middle school textbooks of home economics and other subjects, written according to the 2015 revised curriculum, were analyzed. This study examined consumer education content based on the consumer competency measurement index developed by the Korean Consumer Agency, and reviewed different foci presented by subjects. This study also investigated how the knowledge, attitude and practice, which are components of consumer competency, are presented. The major findings of this study can be summarized as follows: First, consumer competency content, presented in textbooks of home economics and other subjects, were comprised of citizenship competency(65.3%), transactional competency(27%), and financial competency(7.7%). Second, in terms of content on the consumer's citizenship competency, little attention was paid to consumer rights, revealing an imbalance between responsibilities and rights. Third, despite its importance, the "utilization of information and communications technology" in transaction competency, and "consumer participation" in citizenship competency are insufficiently covered in the home economics. Fourth, social studies was the subject that most extensively covered the content of consumer competency. In terms of scope, home economics dealt with most of the sub-fields. Fifth, even when the same content of consumer competency was covered, it was presented differently by subject. Sixth, there was a lack of connection between components of consumer competency-knowledge, attitude, and practice, with a disproportionately high emphasis on knowledge. In conclusion, this study concluded that consumer education content of middle school subjects is insufficient to enhance consumer competency.