• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.397-416
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• 2024

This study assessed the hydrogeological properties of the deep geological environment to develop safety criteria for the natural barriers used in the deep geological disposal of high-level radioactive waste in Korea. The assessment focused on the distribution and trends of hydraulic conductivity and permeability properties appropriate for the domestic geological environment, using various in-situ hydraulic test data collected for groundwater development and management. To develop a depth-hydrogeological property relationship model suitable for domestic conditions, the study reviewed various international research examples and applied a representative model that explains the trends of hydraulic conductivity and permeability with depth. The development of the model suitable for Korea involved applying ensemble regression analysis to account for the uncertainty of various factors in the collected data. The results confirmed that existing international depth-hydrogeological property relationship models adequately describe the characteristics of the domestic geological environment. Considering the preferred hydrogeological criteria suggested by countries like Sweden, Germany, and Canada, there is a high likelihood that a suitable geological environment exists in Korea. Additionally, the application of hydrogeological criteria indicative of low-permeability environments showed that suitable conditions for disposal construction increase at depths greater than 300 m, where the influence of fractures on groundwater flow might be minimal at depths exceeding 500 m. This research can serve as foundational information for establishing hydrogeological safety standards for natural barriers in Korea according to international regulatory guidelines.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.73-97
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• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Journal of Distribution Science
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• v.9 no.1
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• pp.17-27
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• 2011

As the world becomes more globalized, business competition becomes fiercer, while consumers' needs for less expensive quality products are on the increase. Business operations make an effort to secure a competitive edge in costs and services, and the logistics industry, that is, the industry operating the storing and transporting of goods, once thought to be an expense, begins to be considered as the third cash cow, a source of new income. Logistics centers are central to storage, loading and unloading of deliveries, packaging operations, and dispensing goods' information. As hubs for various deliveries, they also serve as a core infrastructure to smoothly coordinate manufacturing and selling, using varied information and operation systems. Logistics centers are increasingly on the rise as centers of business supply activities, growing beyond their previous role of primarily storing goods. They are no longer just facilities; they have become logistics strongholds that encompass various features from demand forecast to the regulation of supply, manufacturing, and sales by realizing SCM, taking into account marketability and the operation of service and products. However, despite these changes in logistics operations, some centers have been unable to shed their past roles as warehouses. For the continuous development of logistics centers, various measures would be needed, including a revision of current supporting policies, formulating effective management plans, and establishing systematic standards for founding, managing, and controlling logistics centers. To this end, the research explored previous studies on the use and effectiveness of logistics centers. From a theoretical perspective, an evaluation of the overall introduction, purposes, and transitions in the use of logistics centers found issues to ponder and suggested measures to promote and further advance logistics centers. First, a fact-finding survey to establish demand forecast and standardization is needed. As logistics newspapers predicted that after 2012 supply would exceed demand, causing rents to fall, the business environment for logistics centers has faltered. However, since there is a shortage of fact-finding surveys regarding actual demand for domestic logistic centers, it is hard to predict what the future holds for this industry. Accordingly, the first priority should be to get to the essence of the current market situation by conducting accurate domestic and international fact-finding surveys. Based on those, management and evaluation indicators should be developed to build the foundation for the consistent advancement of logistics centers. Second, many policies for logistics centers should be revised or developed. Above all, a guideline for fair trade between a shipper and a commercial logistics center should be enacted. Since there are no standards for fair trade between them, rampant unfair trades according to market practices have brought chaos to market orders, and now the logistics industry is confronting its own difficulties. Therefore, unfair trade cases that currently plague logistics centers should be gathered by the industry and fair trade guidelines should be established and implemented. In addition, restrictive employment regulations for foreign workers should be eased, and logistics centers should be charged industry rates for the use of electricity. Third, various measures should be taken to improve the management environment. First, we need to find out how to activate value-added logistics. Because the traditional purpose of logistics centers was storage and loading/unloading of goods, their profitability had a limit, and the need arose to find a new angle to create a value added service. Logistic centers have been perceived as support for a company's storage, manufacturing, and sales needs, not as creators of profits. The center's role in the company's economics has been lowering costs. However, as the logistics' management environment spiraled, along with its storage purpose, developing a new feature of profit creation should be a desirable goal, and to achieve that, value added logistics should be promoted. Logistics centers can also be improved through cost estimation. In the meantime, they have achieved some strides in facility development but have still fallen behind in others, particularly in management functioning. Lax management has been rampant because the industry has not developed a concept of cost estimation. The centers have since made an effort toward unification, standardization, and informatization while realizing cost reductions by establishing systems for effective management, but it has been hard to produce profits. Thus, there is an urgent need to estimate costs by determining a basic cost range for each division of work at logistics centers. This undertaking can be the first step to improving the ineffective aspects of how they operate. Ongoing research and constant efforts have been made to improve the level of effectiveness in the manufacturing industry, but studies on resource management in logistics centers are hardly enough. Thus, a plan to calculate the optimal level of resources necessary to operate a logistics center should be developed and implemented in management behavior, for example, by standardizing the hours of operation. If logistics centers, shippers, related trade groups, academic figures, and other experts could launch a committee to work with the government and maintain an ongoing relationship, the constraint and cooperation among members would help lead to coherent development plans for logistics centers. If the government continues its efforts to provide financial support, nurture professional workers, and maintain safety management, we can anticipate the continuous advancement of logistics centers.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• The Korean Journal of Air & Space Law and Policy
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• v.24 no.2
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• pp.139-161
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• 2009

The idea of establishing an International Court of Air and Space Law (hereinafter referred to ICASL) is only my academic and practical opinion as first proposal in the global community. The establishment of the International Court of Air and Space Law can promote the speed and promote fairness of the trial in air and space law cases. The creation of an ICASL would lead to strengthening of the international cooperation deemed essential by the global community towards joint settlement in the transnational air and space cases, claims and would act as a catalyst for the efforts and solution on aircraft, satellite and space shuttle's accidents and cases and all manpower, information, trial and lawsuit to be centrally managed in an independent fashion to the benefit of global community. The aircraft, satellite and spacecraft's accidents attributes to the particular and different features between the road, railway and maritime's accidents. These aircraft, satellite and spacecraft's accidents have incurred many disputes between the victims and the air and space carriers in deciding on the limited or unlimited liability for compensation and the appraisal of damages caused by the aircraft's accidents, terror attack, satellite, space shuttle's accidents and space debris. This International Court of Air and Space Law could hear any claim growing out of both international air and space crash accidents and transnational accidents in which plaintiffs and defendants are from different nations. This alternative would eliminate the lack of uniformity of decisions under the air and space conventions, protocols and agreements. In addition, national courts would no longer have to apply their own choice of law analysis in choosing the applicable liability limits or un-limit for cases that do not fall under the air and space system. Thus, creation of an International Court of Air and Space Law would eliminate any disparity of damage awards among similarly situated passengers and shippers in nonmembers of air and space conventions, protocols, agreements and cases. Furthermore, I would like to explain the main items of the abovementioned Draft for the Convention or Statute of the International Court of Air and Space Law framed in comparison with the Statute of the International Court of Justice, the Statue of the International Tribunal for the Law of the Sea and the Statute of the International Criminal Court. First of all, in order to create the International Court of Air and Space Law, it is necessary for us to legislate a Draft for the Convention on the Establishment of the International Court of Air and Space Law. This Draft for the Convention must include the elected method of judges, term, duty and competence of judge, chambers, jurisdiction, hearing and judgment of the ICASL. The members of the Court shall be elected by the General Assembly and Council of the ICAO and by the General Assembly and Legal Committee of the UNCOPUOS from a list of persons nominated by the national groups in the six continent (the North American, South American, African, Oceania and Asian Continent) and two international organization such as ICAO and UNCOPUOS. The members of the Court shall be elected for nine years and may be re-elected as one time. However, I would like to propose a creation an International Court of Air and Space Law in extending jurisdiction to the International Court of Justice at the Hague to in order to decide the air and space convention‘s cases. My personal opinion is that if an International Court on Air and Space Law will be created in future, it will be settled quickly and reasonably the difficulty and complicated disputes, cases or lawsuit between the wrongdoer and victims and the injured person caused by aircraft, satellite, spacecraft's accidents or hijacker and terrorists etc. on account of deciding the standard of judgment by judges of that’s court. It is indeed a great necessary and desirable for us to make a new Draft for the Convention on a creation of the International Court of Air and Space Law to handle international air and space crash litigation. I shall propose to make a new brief Draft for the Convention on the Creation of an International Court of Air and Space Law in the near future.

• Journal of the Korean Society of School Health
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• v.2 no.1
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• pp.58-90
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• 1989

This study was attempted to contribute to the development of school health by providing the basic data about the distribution basis and distribution aspect of teachers holding additional school health that are in charge of school health business in parimary schools, middle schools and high schools without any nurse-teacher. This study analyzed literatures about the history, related laws, organization and professional manpower of school health. The emphasis was set on the distribution basis of theachers holding additional school health. The results of this study are as following: 1. The school health of the world dates to the late 18th century in Europe where was free supplying with food for poor children. The school health of Korea orginated from smallpox vaccination which was executed with appearance of modern schools in the late 19th century. 2. The related laws of school health began as a part of Education Law with was constituted in 1949. By the School Health Law constituted in 1967 and the enforcement ordinance of School Health made firm the legal basis of school health. 3. The administrative organs of school health are the Ministry of Education in center and each Board of Education in cities and provinces. For the first time in 1979, the department of school health was established in the organization of the Ministry of Education. And at about the same time of establishment of the department of school health, health section was established in the department of social physical-training in locality. 4. In the manpower of school health which was presented in the related statute of school health, there are the ward chief of education, the superintendent of educational affair, of cities and districts, the mayors, the governors of provinces, the school managers, the principals, the school doctors, the school pharmacists, and the nurse-teachers, including teachers holding additional school health as the practical manpower of school health. 5. In order to get some information on distribution aspect of teachers additional school health, this study made up a questionnaire from August 3 to August 11, 1988. The subjects of this study were 212 leachers who took part in the yearly training for teachers holding additional school health from Kyunggi province, Chungbuk province and Jeonbuk province. The results of the questionnaire are as following: 1. The distribution percentages of teachers holding additional school health according to each Board of Education wich schools are subject to, are as following:70.1% (Kyunggi), 76.5% (Chungbuk), and 81.4% (Jeonbuk). There was a significant difference. The distribution percentages of teachers holding additional school health according to the school levels of 3 provinces are as following: 74.1% (Primary schools), 77.8% (Middle schools), 76.7% (High schools). There were little significant differences. 2. The distribution according to the general characteristics of the subject schools: There were 64.2 percent of primary schools and 35.8 percent of middle schools among 212 schools. 91. 5 percent of schools were located in districts. Public schools formed 55.7% and then national schools were higher in percentage than private schools. 58.5 percent of schools had 1-9 classes, 64.6 percent of schools had 101-500 students, and 90 percents of schools had 1-20 teachers. In considering student sex, the coed school showed the high distribution percentage (Primary schools : 100%, Middle schools: 81.6%). 3. The distribution according to the characteristics of teachers holding additional school health: 93.3 percent of teachers were female, and more than 60 percent of teachers were 20-29 years old. As the age got higher, the percentage became lower. There were little significant differences by marital status. In considering their educational status, 86.8 percent of teachers in primary schools were from teacher's colleges, and 64.5 percent of teachers in middle schools were from education colleges. In considering teaching career, 46.7 percent of teachers had teaching career of less than 2 years. 73.6 percent of teachers had held additional school health for less than one year. More than 80 percent of teachers had participated in the training one time or twice. More than 70 percent of teachers had 1-2 additional jobs except for the school health business. The motivation to hold additional school health is most caused by mandatory order, which accounts for more than 80.0 percent. In considering interesting degree concerning school health, lukewarm answer is the highest of 62.7 percent, followed by affirmative answer of 23.6 percent. In considering their contentment degree respecting additional school health job, "discontent or very discontent"is the highest of 47.6 percent. As a descontent reason of additional school health job, overwork is the highest factor of 37.9 percent. Among addiitional school health job, the most difficult affair is nursing service to be 34.0 percent, followed by health education of 31.6 percent. It testify the need of professional. The source of knowledge about school health has been acquired from masscommunication or private health experience, which account for as much as 56.1 percent. It shows seriousness of lack of professionalism. With regard to neccessity of school health experts, 95.8 percent represents absolute need. With above consideration of study results, I propose as follows : 1. I propose that the authorities concerned unify and improve statute respecting current school health which has not been steadfastly supporting school health business by ambiguity of expression and dualization. 2. I propose that the authorities concerned give the school manager, school staffs and parents of students educational chance with which they can acknowledge the importance of school health and in which they can participate as well as set up alternative policy plan to be albe to vitalize school health committee. 3. I propose that administrative organization practicable to taking totally charge of school health business is established within the Ministry of Education. 4. I propose that the authorities concerned back up and cooperate in an attempt by make school health better and desirable toward development by way of appointing qualitied health teachers on the basis of legally regular teacher staffs.