• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.335-344
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• 2022

This study was conducted for 4 weeks on the preparation of the science teaching/learning course plan for 109 students in 4 classes of the 2nd year intensive course at B University of Education. Pre-service elementary teachers attended a two-week field training practice after listening to a lecture on how to write a science teaching and learning course plan. Pre-service elementary teachers tried to find out about the selection of materials and the degree of connection between the course plan and the class to prepare the science teaching/learning course plan. The researcher completed the questionnaire by reviewing and deliberation on the questionnaire questions together with 4 pre-service elementary teachers. The questionnaire related to the writing of the science teaching and learning course plan consists of 8 questions. Preferred reference materials when writing the course plan, the level of interest in learning, the success or failure of the science course plan and class, the science preferred model, the evaluation method in unit time, and the science teaching and learning One's own efforts to write the course plan, the contents of this course are the science faculty. It is composed of the preparation of the learning process plan and how helpful it is to the class. The results of this study are as follows. First, it was found that elementary school pre-service elementary teachers preferred teacher guidance the most when drafting science teaching and learning curriculum plans. Second, it is recognized that the development stage is very important in the teaching and learning stage of the science department. Third, Pre-service elementary teachers believe that the science and teaching and learning process plan has a high correlation with the success of the class. Fourth, it was said that the student's level, the teacher's ability, and the appropriate lesson plan had the most influence on the class. Fifth, it was found that pre-service elementary teachers prefer the inquiry learning class model. Sixth, it was found that reports and activity papers were preferred for evaluation in 40-minute classes. Seventh, it was stated that the teaching and learning process plan is highly related to the class, so it will be studied and studied diligently. Eighth, the method of writing a science teaching and learning course plan based on the instructional design principle is interpreted as very beneficial.

• Korean Journal of Culture and Social Issue
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• v.21 no.2
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• pp.227-252
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• 2015

This study was intended to examine child abuse experience, response to child abuse, perception of the cause of child abuse, and need for counseling to prevent and eliminate child abuse among 514 day care center teachers across the country. First, 17.9% (92) of the teachers had experience of witnessing child abuse at day care centers. After such witness, the teachers mostly "paid attention to abused children and provided them with warm treatment" when they were abused by other teachers and "took no actions" when they were abused by directors of the day care centers. The biggest reason of not taking any actions was: they "had no authority to intervene in child care of other teachers" in case of child abuse by other teachers and "were afraid of responsibilities or roles that could be placed on them after reporting" in case of child abuse by day care center directors. Second, the biggest reason of child abuse by teachers was job stress followed by excessive work and mental health of teachers. Third, necessary actions when child abuse cases were found and confirmed were suspension of involved teachers and psychological evaluation for involved children and parents. Fourth, 88.9% (457) of the teachers responded that they would use an organization specialized in child abuse if such organization was built and that the organization would help them to decide on whether to report child abuse and prevention of and intervention in child abuse. They also said that such organization should be installed in the Counseling Center in the Comprehensive Child Care Support Center. Fifth, 95.3% (490) of the teachers answered professional counselors specialized in development and counseling of infants and toddlers were needed to address child abuse at day care centers. They demanded that such counselors should be able to administer psychological evaluation for young children and assess child abuse cases. Qualification of the counselors was at least college graduates who majored in psychology and child care, three to five years of experience in the field, and appropriate certificates or licenses. Finally, the teachers said that training and professional counseling about child abuse were required to prevent and eliminate child abuse at day care centers. Implications and follow-up studies were provided and suggested based on these findings.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.2
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• pp.123-135
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• 2012

Purpose: It is essential to minimize the movement of tumor due to respiratory movement at the time of respiration controlled radiotherapy of non-small cell lung cancer patient. Accordingly, this Study aims to evaluate the usefulness of restricted respiratory period by comparing and analyzing the treatment plans that apply free and restricted respiration period respectively. Materials and Methods: After having conducted training on 9 non-small cell lung cancer patients (tumor n=10) from April to December 2011 by using 'signal monitored-breathing (guided- breathing)' method for the 'free respiratory period' measured on the basis of the regular respiratory period of the patents and 'restricted respiratory period' that was intentionally reduced, total of 10 CT images for each of the respiration phases were acquired by carrying out 4D CT for treatment planning purpose by using RPM and 4-dimensional computed tomography simulator. Visual gross tumor volume (GTV) and internal target volume (ITV) that each of the observer 1 and observer 2 has set were measured and compared on the CT image of each respiratory interval. Moreover, the amplitude of movement of tumor was measured by measuring the center of mass (COM) at the phase of 0% which is the end-inspiration (EI) and at the phase of 50% which is the end-exhalation (EE). In addition, both observers established treatment plan that applied the 2 respiratory periods, and mean dose to normal lung (MDTNL) was compared and analyzed through dose-volume histogram (DVH). Moreover, normal tissue complication probability (NTCP) of the normal lung volume was compared by using dose-volume histogram analysis program (DVH analyzer v.1) and statistical analysis was performed in order to carry out quantitative evaluation of the measured data. Results: As the result of the analysis of the treatment plan that applied the 'restricted respiratory period' of the observer 1 and observer 2, there was reduction rate of 38.75% in the 3-dimensional direction movement of the tumor in comparison to the 'free respiratory period' in the case of the observer 1, while there reduction rate was 41.10% in the case of the observer 2. The results of measurement and comparison of the volumes, GTV and ITV, there was reduction rate of $14.96{\pm}9.44%$ for observer 1 and $19.86{\pm}10.62%$ for observer 2 in the case of GTV, while there was reduction rate of $8.91{\pm}5.91%$ for observer 1 and $15.52{\pm}9.01%$ for observer 2 in the case of ITV. The results of analysis and comparison of MDTNL and NTCP illustrated the reduction rate of MDTNL $3.98{\pm}5.62%$ for observer 1 and $7.62{\pm}10.29%$ for observer 2 in the case of MDTNL, while there was reduction rate of $21.70{\pm}28.27%$ for observer 1 and $37.83{\pm}49.93%$ for observer 2 in the case of NTCP. In addition, the results of analysis of correlation between the resultant values of the 2 observers, while there was significant difference between the observers for the 'free respiratory period', there was no significantly different reduction rates between the observers for 'restricted respiratory period. Conclusion: It was possible to verify the usefulness and appropriateness of 'restricted respiratory period' at the time of respiration controlled radiotherapy on non-small cell lung cancer patient as the treatment plan that applied 'restricted respiratory period' illustrated relative reduction in the evaluation factors in comparison to the 'free respiratory period.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.40-51
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• 2019

Ginseng has a unique production system that is different from those used for other crops. It is subject to the Ginseng Industry Act., requires a long-term cultivation period of 4-6 years, involves complicated cultivation characteristics whereby ginseng is not produced in a single location, and many ginseng farmers engage in mixed-farming. Therefore, to bring the production of Ginseng in line with GAP standards, it is necessary to better understand the on-site practices of Ginseng farmers according to established control points, and to provide a proper action plan for improving efficiency. Among ginseng farmers in Korea who applied for GAP certification, 77.6% obtained it, which is lower than the 94.1% of farmers who obtained certification for other products. 13.7% of the applicants were judged to be unsuitable during document review due to their use of unregistered pesticides and soil heavy metals. Another 8.7% of applicants failed to obtain certification due to inadequate management results. This is a considerably higher rate of failure than the 5.3% incompatibility of document inspection and 0.6% incompatibility of on-site inspection, which suggests that it is relatively more difficult to obtain GAP certification for ginseng farming than for other crops. Ginseng farmers were given an average of 2.65 points out of 10 essential control points and a total 72 control points, which was slightly lower than the 2.81 points obtained for other crops. In particular, ginseng farmers were given an average of 1.96 points in the evaluation of compliance with the safe use standards for pesticides, which was much lower than the average of 2.95 points for other crops. Therefore, it is necessary to train ginseng farmers to comply with the safe use of pesticides. In the other essential control points, the ginseng farmers were rated at an average of 2.33 points, lower than the 2.58 points given for other crops. Several other areas of compliance in which the ginseng farmers also rated low in comparison to other crops were found. These inclued record keeping over 1 year, record of pesticide use, pesticide storages, posts harvest storage management, hand washing before and after work, hygiene related to work clothing, training of workers safety and hygiene, and written plan of hazard management. Also, among the total 72 control points, there are 12 control points (10 required, 2 recommended) that do not apply to ginseng. Therefore, it is considered inappropriate to conduct an effective evaluation of the ginseng production process based on the existing certification standards. In conclusion, differentiated certification standards are needed to expand GAP certification for ginseng farmers, and it is also necessary to develop programs that can be implemented in a more systematic and field-oriented manner to provide the farmers with proper GAP management education.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• The Korean Journal of Emergency Medical Services
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• v.15 no.3
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• pp.31-44
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• 2011

Purpose : The purpose of emergency medical services(EMS) is to save human lives and assure the completeness of the body in emergency situations. Those who have been qualified on medical practice to perform such treatment as there is the risk of human life and possibility of major physical and mental injuries that could result from the urgency of time and invasiveness inflicted upon the body. In the emergency medical activities, 119 emergency medical technicians mainly perform the task but they are not able to perform such task independently and they are mandatory to receive medical direction. The purpose of this study is to examine the recognition and request for medical direction by 119 emergency medical technicians in order to provide basic information on the development of medical direction program suitable to the characteristics of EMS as well as for the studies on EMS for the sake of efficient operation of pre-hospital EMS. Method : Questionnaire via e-mail was conducted during July 1-31, 2010 for 675 participants who are emergency medical technicians, nurses and other emergency crews in Gyeongbuk. The effective 171 responses were used for the final analysis. In regards to the emergency medical technicians' scope of responsibilities defined in Attached Form 14, Enforcement regulations of EMS, t-test analysis was conducted by using the means and standard deviation of the level of request for medical direction on the scope of responsibilities of Level 1 & Level 2 emergency medical technicians as the scale of medical direction request. The general characteristics, experience result, the reason for necessity, emergency medical technicians & medical director request level, medical direction method, the place of work of the medical director, feedback content and improvement plan request level were analyzed through frequency and percentage. The level of experience in medical direction and necessity were analyzed through ${\chi}^2$ test. Results : In regards to the medical direction experience per qualification, the experience was the highest with 53.3% for Level 1 emergency medical technicians and 80.3% responded that experience was helpful. As for the recognition on the necessity of medical direction, 71.3% responded as "necessary" and it turned out to be the highest of 76.9% in nurses. As for the reason for responding "necessary", the reason for reducing the risk and side-effects from EMS for patients was the largest(75.4%), and the reason of EMS delay due to the request of medical direction was the highest(71.4%) for the reason for responding "not necessary". In regards to the request level of the task scope of emergency medical technicians, injection of certain amount of solution during a state of shock was the highest($3.10{\pm}.96$) for Level 1 emergency rescuers, and the endotracheal intubation was the highest($3.12{\pm}1.03$) for nurses, and the sublingual administration of nitroglycerine(NTG) during chest pain was the highest($2.62{\pm}1.02$) for Level 2 emergency medical technicians, and regulation of heartbeat using AED was the highest($2.76{\pm}.99$) for other emergency crews. For the revitalization of medical direction, the improvement in the capability of EMS(78.9%) was requested from emergency crew, and the ability to evaluate the medical state of patient was the highest(80.1%) in the level of request for medical director. The prehospital and direct medical direction was the highest(60.8%) for medical direction method, and the emergency medical facility was the highest(52.0%) for the placement of medical director, and the evaluation of appropriateness of EMS was the highest(66.1%) for the feedback content, and the reinforcement of emergency crew(emergency medical technicians) personnel was the highest(69.0%) for the improvement plan. Conclusion : The medical direction is an important policy in the prehospital EMS activity because 119 emergency medical technicians agreed the necessity of medical direction and over 80% of those who experienced medical direction said it was helpful. In addition, the simulation training program using algorithm and case study through feedback are necessary in order to enhance the technical capability of ambulance teams on the item of professional EMS with high level of request in the task scope of emergency medical technicians, and recognition of medical direction is the essence of the EMS field. In regards to revitalizing medical direction, the improvement of the task performance capability of 119 emergency medical technicians and medical directors, reinforcement of emergency medical activity personnel, assurance of trust between emergency medical technicians and the emergency physician, and search for professional operation plan of medical direction center are needed to expand the direct medical direction method for possible treatment beforehand through the participation by medical director even at the step in which emergency situation report is received.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.

• Journal of Korean Academy of Nursing
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• v.30 no.6
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• pp.1488-1502
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• 2000

This study, based on current home nursing services, aims at promoting measures for establishing a community-based home nursing system derived from the pilot home nursing demonstration project conducted by the Seoul Nurses Association. The study was based on an analysis of home nursing records from march 1993 to December 1999. The following is a summary analysis, based on individual characteristics of the patients, the organization, which recommended the service for their patients and personnel services. 1. The service has been used by many elderly people 60years of age or older(66.4%). and married people(60.9%). The average number of visits by service personnel for patients of city government was 23.5. This is 2.5 times as many visits by general patients. General patients(20.2%) had only one visit from service personnel, while 65.5% of patients of city government had 10 or more visits. Particularly, for government recommended patients, 72.7% of the patients were recommended by nurses, while only 21.9% where referred to the services by doctors. The main focus of a home nursing service was to maintain present health status (53.4%), and hospice(11.6%). Also to increase hospital-based home nursing services focused on recovery(55.9%) and maintain present health conditions (19.0%). 2. For general patients, 42.0% of patients were suffering from problems related to CVA, 11.3% from high blood pressure, and for patients referred from city, 21.2% from skeletal muscular disease. Results of home nursing services 29.4% of patients were able to recover or maintain their health status, but 48.9% of the patients died. Another main point of community-based home nursing services is medication(6.7%), other basic nursing services(6.1%), special treatment, instructions on how to use medical devices(5.9%), change of physical posture(4.6%), and training on changing physical positions(4.7%). As mentioned above there were some differences between the characteristics of patients who used the pilot home nursing service conducted by the Seoul Nurses Association and those hospital-based service users. The results are believed to be useful to support a community-based home nursing service model. Particularly, patients under medical supervision and patients recommended by government-run health clinics show a higher frequency and longer use of home nursing services compared to general patients or hospital-based home nursing service users. According to the study, nurses accounted for a large number of recommendations for home nursing services. Many patients with CVA, high blood pressure, skeletal muscular disease and bedsores used community-based home nursing services, while others used the service for minor treatments or maintaining their current health status. Based on the study, the researchers make several suggestions to establish a community- based home nursing service system. First, different ways of setting up a community-based home nursing system have to be mapped out based on the evaluation of the pilot home nursing service conducted by the Seoul Nurses Association. Secondly, a new, community-based, home health care nursing service model, and reimbursement payment system have to be developed. This is based on the outcome of the analysis, and implemented policy. Accordingly, efforts are needed to develop a community- based home nursing system with an intermediary role to promote the visiting nursing services of government-run health centers.