This study developed the Assessment Indicator evaluating eco-cultural value of temple forest in Korea and applied the developed Assessment Indicator to Songgwang-sa(also known as Seungbo-sachal), one of the Three Jewels Temple. Literature reviews and the draft of Assessment Indicator were drawn from brainstorming(including 2 forest therapy experts, 1 Buddhist monk expert, 1 landscape architect, 1 forest expert, and 6 researchers). After that, the Assessment Indicator drawn from the group of experts(the 1st in-depth interview: 32 people, the 2nd in-depth interview: 30 people) was verified and revised. The final Assessment Indicator, which was composed of 4 parts and 20 items, was developed. The results are as follows. The eco-cultural Assessment Indicator of temple forest was composed of 4 parts, which were Historical Cultural value, Ecological value, Recreatory Visitational value, and Educational Useful value, and 20 items and each item had 5 points. Historical Cultural value had 5 items and its total points were 25. Ecological value had 5 items and had total 25 points. Recreatory Visitational value had 6 items, 30 total points. Educational Useful value had 4 items, 20 total points. The total points of the eco-cultural Assessment Indicator were 100 points. As a result of applying the developed Assessment Indicator to the target place, Songgwang-sa in Mt. Jogye, Historical Cultural value of temple forest was calculated as 23 points(out of 25). Ecological value was 21 point(out of 25), Recreatory Visitational value, 22 points(out of 30), and Educational Useful value, 16 points(out of 20). The total points were 82(out of 100). Consequently, this study is meaningful based on the following 5 aspects. Firstly, this study challenged the development of the eco-cultural Assessment Indicator of temple forest for the first time. It is significant because the developed Assessment Indicator can be a useful resource for the eco-cultural value of temple forest. Secondly, the result showed that Educational Useful value and Recreatory Visitational value of forest temple were very low. Therefore, the supports for leisure, tour, education, and use of temple forest are needed from Korea Forest Service, Ministry of Environment, Cultural Heritage Administration and other government agencies since they acknowledge the temple forest as the best customers in Korea. Thirdly, the excellence or for eco-cultural value of temple forest needs to be extended in a national level. It is possible to make a Korean National Bran(e.g., the Therapy at the Temple) by blending temple stay, which is only in temples, and therapy, and is also possible to be a global tour industry. Fourthly, this study suggested legal definition about the necessary of legal definition for temple forest because there is no legal definition on temple forest in the current situation. When the definition of temple forest is legally arranaged, it would be a foundation for conserving eco-cultural value of temple forest, for organizing exclusively responsible departments in governmental institutions, and further for registering temple forest as World Natural Heritage. Lastly, the developed eco-cultural Assessment Indicators of temple forest from this study would be applied to "the 7 Sansa, Buddhist Mountain Monasteries in Korea(Sansa)" and the characteristics of each 7 temple are drawn. This study would be a basic data for temples' management and use with the eco-cultural Assessment Indicator of temple forest.
The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.
Classification and research trends were studied to analyze a total of 240 original articles that have been published in 34 volumes of The Korean Journal of Rural Medicine from 1976 to 1999. The results were as follows: 1. A total of 337 articles were published. Among them, 240(71.2%) articles were classified as original articles. This number has been increasing significantly over the years as the number of the articles was 13 in the 1970s, 73 in the 1980s, and 154 in the 1990s. 2. There were 10 authors in the original articles and 55(22.9%) of them were written by 3 of them. There were five research institutions involved in the articles, and 106(44.2%) of the articles were done by one research group. 3. In the original articles. 24(10.0%) were noted to be done using research funds, and only 6(2.5%) were written in English. 4. In the view of the research styles of the original articles, 115(47.9%) used analytical study, 92(38.3%) used technical study, 21(9.2%) used experimental study, and 6(2.5%) used case reports. In the 1970s, 13(100.0%) articles used technical study, and in the 1980s, 47(64.4%) used technical studies and 19(26.0%) used analytical studies. However, in the 1990s, 96(62.8%) articles used analytical studies and 32(20.9%) used technical studies. The statistical methods most commonly used in the articles were technical statistics, the
Medical services are a fundamental and essential service in all urban areas. The location and accessibility of medical service facilities and institutions are critical to the diagnosis, control and prevention of illness and disease. The purpose of this paper is to present the results of a study on the location of medical facilities in Kwangju and the utilization of these facilities by the inhabitants. The following information is a summary of the findings: (1) Korea, like many countries, is now witnessing an increase in the age of its population as a result of higher living standards and better medical services. Korea is also experiencing a rapid increase in health care costs. To ensure easy access to medical consultation, diagnosis and treatment by individuals, the hierarchical efficient location of medical facilities, low medical costs, equalized medical services, preventive medical care is important. (2) In Korea, the quality of medical services has improved significantly as evident by the increased number of medical facilities and medical personnel. However, there is still a need for not only quantitative improvements but also for a more equitable distribution of and location of medical services. (3) There are 503 medical facilities in Kwangju each with a need to service 2,556 people. This is below the national average of 1,498 inhabitants per facility. The higher locational quotient and satisfactory population per medical facility showed at the civic center. On the other hand, problem regions such as the traditional residential area in Buk-Gu, Moo-deung mountain area and the outer areas of west Kwangju still maintain rural characteristics. (4) In the study area there are 86 general medicine clinics which provide basic medical services. i. e. one clinic per every 14,949 residents. As a basic service, its higher locational quotient showed in the residential area. The lower population concentration per clinic was found in the civic center and in the former town center, Songjeong-dong. In recently build residential areas and in the civic center, the lack of general medicine clinics is not a serious medical services issue because of the surplus of medical specialists in Korea. People are inclined to seek a consultation with a specialist in specific fields rather than consult a general practitioner. As a result of this phenomenon, there are 81 internal medicine facilities. Of these, 32.1% provide services to people who are not referred by a primary care physician but who self-diagnose then choose a medical facility specializing in what they believe to be their health problem. Areas in the city, called dongs, without any internal facilities make up 50% of the total 101 dongs. (5) There are 78 surgical facilities within the area, and there is little difference at the locational appearance from internal medicine facilities. There are also 71 pediatric health clinics for people under 15 years of age in this area, represents one clinic per 5,063 people. On the quantitative aspect, this is a positive situation. Accessibility is the most important facility choice factor, so it should be evenly located in proportion to demander distribution. However, 61% of 102 dongs have no pediatric clinics because of the uneven location. (6) There are 43 obstetrical and gynecological clinics in Kwangju, and the number of residents being served per clinic is 15,063. These services need to be given regularly so it should increase the numbers. There are 37 ENT clinics in the study area with the lower concentration in Dong-gu (32.4%) making no locational differences by dong. There are 23 dermatology clinics with the largest concentration in Dong-Gu. There are 17 ophthalmic clinics concentrated in the residential area because of the primary function of this type of specialization. (7) The use of general medicine clinics, internal medicine clinics, pediatric clinics, ENT clinics by the inhabitants indicate a trend toward primary or routine medical services. Obstetrics and gynecology clinics are used on a regular basis. In choosing a general medicine clinic, internal medicine clinic, pediatric clinic, and a ENT clinic, accessibility is the key factor while choice of a general hospital, surgery clinic, or an obstetrics and gynecology clinic, thes faith and trust in the medical practitioner is the priority consideration. (8) I considered the efficient use of medical facilities in the aspect of locational and management and suggest the following: First, primary care facilities should be evenly distributed in every area. In Kwangju, the number of medical facilities is the lowest among the six largest cities in Korea. Moreover, they are concentrated in Dong-gu and in newly developed areas. The desired number of medical facilities should be within 30 minutes of each person's home. For regional development there is a need to develop a plan to balance, for example, taxes and funds supporting personnel, equipment and facilities. Secondly, medical services should be co-ordinated to ensure consistent, appropriate, quality services. Primary medical facilities should take charge of out-patient activities, and every effort should be made to standardize and equalize equipment and facility resources and to ensure ongoing development and training in the primary services field. A few specialty medical facilities and general hospitals should establish a priority service for incurable and terminally ill patients. (9) The management scheme for the inhabitants' efficient use of medical service is as follows: The first task is to efficiently manage medical facilities and related services. Higher quality of medical services can be accomplished within the rapidly changing medical environment. A network of social, administrative and medical organizations within an area should be established to promote information gathering and sharing strategies to better assist the community. Statistics and trends on the rate or occurrence of diseases, births, deaths, medical and environment conditions of the poor or estranged people should be maintained and monitored. The second task is to increase resources in the area of disease prevention and health promotion. Currently the focus is on the treatment and care of individuals with illness or disease. A strong emphasis should also be placed on promoting prevention of illness and injury within the community through not only public health offices but also via medical service facilities. Home medical care should be established and medical testing centers should be located as an ordinary service level. Also, reduced medical costs for the physically handicapped, cardiac patients, and mentally ill or handicapped patients should be considered.