• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.151-171
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• 2014

Firms today have sought management effectiveness and efficiency utilizing information technologies (IT). Numerous firms are outsourcing specific information systems functions to cope with their short of information resources or IT experts, or to reduce their capital cost. Recently, Software-as-a-Service (SaaS) as a new type of information system has become one of the powerful outsourcing alternatives. SaaS is software deployed as a hosted and accessed over the internet. It is regarded as the idea of on-demand, pay-per-use, and utility computing and is now being applied to support the core competencies of clients in areas ranging from the individual productivity area to the vertical industry and e-commerce area. In this study, therefore, we seek to quantify the value that SaaS has on business performance by examining the relationships among firm strategies, SaaS technology maturity, and business performance of SaaS providers. We begin by drawing from prior literature on SaaS, technology maturity and firm strategy. SaaS technology maturity is classified into three different phases such as application service providing (ASP), Web-native application, and Web-service application. Firm strategies are manipulated by the low-cost strategy and differentiation strategy. Finally, we considered customer acquisition as a business performance. In this sense, specific objectives of this study are as follows. First, we examine the relationships between customer acquisition performance and both low-cost strategy and differentiation strategy of SaaS providers. Secondly, we investigate the mediating and moderating effects of SaaS technology maturity on those relationships. For this purpose, study collects data from the SaaS providers, and their line of applications registered in the database in CNK (Commerce net Korea) in Korea using a questionnaire method by the professional research institution. The unit of analysis in this study is the SBUs (strategic business unit) in the software provider. A total of 199 SBUs is used for analyzing and testing our hypotheses. With regards to the measurement of firm strategy, we take three measurement items for differentiation strategy such as the application uniqueness (referring an application aims to differentiate within just one or a small number of target industry), supply channel diversification (regarding whether SaaS vendor had diversified supply chain) as well as the number of specialized expertise and take two items for low cost strategy like subscription fee and initial set-up fee. We employ a hierarchical regression analysis technique for testing moderation effects of SaaS technology maturity and follow the Baron and Kenny's procedure for determining if firm strategies affect customer acquisition through technology maturity. Empirical results revealed that, firstly, when differentiation strategy is applied to attain business performance like customer acquisition, the effects of the strategy is moderated by the technology maturity level of SaaS providers. In other words, securing higher level of SaaS technology maturity is essential for higher business performance. For instance, given that firms implement application uniqueness or a distribution channel diversification as a differentiation strategy, they can acquire more customers when their level of SaaS technology maturity is higher rather than lower. Secondly, results indicate that pursuing differentiation strategy or low cost strategy effectively works for SaaS providers' obtaining customer, which means that continuously differentiating their service from others or making their service fee (subscription fee or initial set-up fee) lower are helpful for their business success in terms of acquiring their customers. Lastly, results show that the level of SaaS technology maturity mediates the relationships between low cost strategy and customer acquisition. That is, based on our research design, customers usually perceive the real value of the low subscription fee or initial set-up fee only through the SaaS service provide by vender and, in turn, this will affect their decision making whether subscribe or not.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of agricultural medicine and community health
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• v.30 no.2
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• pp.183-204
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• 2005

Objectives: Immunization program is essential public health service under the national responsibility. One of the immunization service of national immunization program is advertising and public relation service, but research for that was rarely conducted. Therefore we conducted the survey for developing advertising strategy of immunization program in 21th century. Methods: Our study subjects were 242 health workers in immunization service department of 169 health centers and 1,193 carers who visited community health center for receiving immunization service of their children. The major questions were general characteristics of the subjects, perceived importance of immunization program, experience of advertising, knowledge and perception about immunization, and items about advertising strategy. Results: Frequently exposed materials in both health workers and carers were TV, community newspapers, and pamphlets. Health workers had high professional knowledges of immunization and carers had high perceptions for need and importance of immunization. Health workers preferred pamphlets and posters as advertising materials and carerers preferred TV and community newspapers. Both health workers and carers preferred green and yellow as advertising posters' color, active and healthy style of immunization advertising, and positive messages of campaign's slogans. Conclusions: Further researches should be conducted for precising long-term immunization advertising strategy in 21th century, and for this we need to develop advertising materials based on public needs and strategy, and evaluate the materials. The national immunization program should be activated throughout more investment of the budgets and human powers.

• Clinical and Experimental Pediatrics
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• v.51 no.2
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• pp.181-187
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• 2008

Purpose : Asthma is characterized by reversible airway obstruction and bronchial hyperresponsiveness result from airway inflammation. Fraction of nitric oxide in expired air (FeNO) has recently been investigated as a noninvasive measure of airway inflammation. FeNO has been reported to correlate with induced sputum eosinophilia and methacholine challenge test that it is represent severity of asthma. The purpose of this study was to analyze the relationship of FeNO with pulmonary function tests in patients with intermittent asthma. Methods : Eighty children included in this study were diagnosed as asthma from April through August, 2005 in Department of Pediatrics, College of Medicine, Kyunghee University. They aged from 4 to 15 years who were able to conduct spirometry and FeNO monitoring. They did not have upper respiratory tract infection and did not use an asthma controller which contain corticosteroids within 4 weeks. Pulmonary function test was done and FeNO was measured with online tidal breathing method using a chemiluminescence NO analyzer (CLD 88 sp, Eco Medics, Duernten, Switzerland). The correlations between pulmonary function test and FeNO were analyzed using Spearman correlation coefficient method. Results : The mean of FeNO of subject was 16.88 parts per billion (ppb). The mean of forced expiratory volume in 1 second ($FEV_1$) was $0.890{\pm}0.455L$ and forced vital capacity (FVC) was $1.071{\pm}0.630L$. The mean of predicted $FEV_1%$ ($FEV_1%pred$) was $98.39{\pm}34.27%$ and $FEV_1/FVC$ was $88.53{\pm}19.49$. FeNO was significantly correlate with $FEV_1$ (r=0.345, P<0.01) and FVC (r=0.244, P<0.05). FeNO did not correlate with $FEV_1%pred$ or $FEV_1/FVC$. Conclusion : The measurement of FeNO could be a useful marker in the management of childhood asthma and it is evolving to provide a complementary role alongside existing pulmonary function test. We propose that measuring technique and establishment of normal reference range are important area for future research.

• Journal of the Korean Geographical Society
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• v.30 no.1
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• pp.35-56
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• 1995

During the last two decades, Korea has achieved remarkable economic growth. In this process the nation has become urbanized and industrialized. But we have also encountered widening regional disparity, housing shortage of larger cities, transportation congestion, environmental pollution and many other problems. Rapid increasing urbanization and continuous migration toward Seoul since the late 1960s have been one of the major concerns of government. Government has sought ways to moderate the population increase in Seoul. The regulation which include new town development near Seoul and dispersion strategies of higher education and other administration and living facilities outside of Seoul havemade a great expansion of the spatial influence of Seoul city. Seoul metropolitan reaion has evolved as the most powerful center of political and economical spaces. Generally within a metropolitan region, there exists a growing mutual interdependence economically, as well as socially between a central city and its surrounding area. Seoul metropolitan region manifests itself not only as a coherent system of urbanized regions, but also as an integral part of the daily urban system. The surrounding Gyunggi province and Seoul city become closely linked both economically and functionally, constituting true functlonai urban system. This study is primarily undertaken with the purpose of delineation of the sphere of influence of Seoul city in 1990. At the time of 1985, Seoul metropolitan region was delineated according to the result of the study which was performed by Korea Research Institute for Human Settlements. Afterward, the rapid speed of metropolitanization process with dramatic increase in mobility through the provision of wider transportation system across the Capital region have evolved, resulting in the great expansion of the spatial influence of Seoul city. So this study examines the expanded area of Seoul metropolitan regin during the period of 1985-90. In order to delineate Seoul metropolitan region, the indices of urbanization and functional linkage are selected. Variables included in the measurement of the urbanization level are agricultural structure, population characteristics, manufacturing and service industries, and cultural aspects such as newspaper circulation, the ratio of car ownership and piped water supply. Variables included in the measurement of functional linkage are commuting, shopping pattern, centralized service such as medical facilities and trade of agricultural products. The standardization method and factor analysis are employed in making the delineation of Seoul metropolitan region. According to the result of this study, 2 cities, 8 Eups and 46 Myuns are included Seoul metropolitan region in 1990. If we compare this delineated area in 1990 to that of 1985, we can find the distinctive pattern of expanded axes according to the main transportation routes such as Seoul-Suweon, Seoul-Gwangju, Seoul-Incheon. In 199O, all the Gyunggi province, except a few Myuns located at the north and northwest part of Gyunggi province, are included in Seoul metropolitan region. Furthermore, this study attempts to the analysis of regional structure of Seoul metropolitan region according to the functional characteristics of each city and Gun. Variables included in this analysis are the new residential function, manufacturing function, service function, education and infermation function, public facility function and agricultural function. Factor analysis and cluster analysis are employed in making regionalization. Seoul metropolitan reaion is subdivided into four subregions which reflect different functional specialization. The first group is the specialized region of newly formed residential function. The second group is the specialized reaion of manufacturing function. The third group is the specialized region of service function. And the fourth group has little specialized in terms of manufacturing, service, and residential function. But this region has some potentiality of development when Seoul metropolitan region grow continuously. Seoul metropolitan region accounted for 43% of national population, despite 11.8% of national land size in 1990. Although Seoul metropolitan region enjoys important agglomeration economies, it also has huge social cost in the form of transportation congestion, housing shortage, rapid increase of land value, environment pollution, and etc. Efficient metropolitan plan making is a vital element in promoting Seoul's economic development and providing high quality living environment at low cost. In the light of the result of this study, the outer ring of Seoul metropolitan region, especially northeastern part, are underdeveloped compared to overdeveloped southwestern area. It is needed to develop the guidelines for the implement of the growth control and management plan, inducing more balanced development for whole Seoul metropolitan reaion.

• The Journal of Korean Society for School & Community Health Education
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• v.9 no.1
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• pp.63-83
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• 2008

Objectives: This study was to examine HIV/AIDS knowledge of transmission, attitudes toward homosexuals on stigma of HIV/AIDS and discriminatory attitudes towards person with HIV/AIDS (PWHAs) by middle and high school students in Seoul, Korea. Methods: The population of this study is middle and high school students in Seoul, Korea. Eight junior high schools and eight senior high schools were selected randomly. Three thousand and one hundred thirty-one students (1704 males and 1397 males) from 16 schools participated in the survey, and 2.977 cases were analyzed. A self-administered questionnaire measuring socio-demographic variables, HIV/AIDS knowledge of transmission, sigma of HIV/AIDS (3 items, 5-point Likert-type scale) and discriminatory attitudes PWHAs (5 items, 5-point Likert-type scale) was utilized. The Structural Equation Modeling was employed to investigate the research Model. Results: The empirical study shows that a number of statistical hypotheses are significant. The stigma and discriminatory attitudes PWHAs were significantly different by middle and high school students. The attitudes toward homosexuals and HIV/AIDS knowledge of transmission were important factors on stigma and discriminatory attitudes PWHAs. Socio-demographical variables such as sex was related to the stigma and discriminatory attitudes PWHAs. Conclusion: Therefore, it is important to design HIV prevention strategies that increase in positive attitudes towards PWHAs.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.1
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• pp.32-44
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• 2002

Gu-Chang is a disorder characterized by recurring ulcers confined to the oral mucosa. Despite much clinical and research attention, the causes remain poorly understood. In this paper, we will compare Gu-Chang with Recurrent Aphthous Stomatitis(RAS) in order to know what is the similiarity between Gu-Chang and RAS. So we will arrange various oriental and western medical literatures which are important. As a result of arrangement of the causes, symptoms and therapys of Gu-Chang, we can conclude through the studies as follows. 1. The etiologies of Gu-chang are following. In the Sthenia syndrome, there are evil heat of external factor, heat of heart and spleen, insomnia, heat of upper warmer, stress and diet, heat of lung and heart, excessive heat of upper warmer, inappropriate food intake, heat conveyance of organ, heat of stomach merdian, moistured heat of spleen and stomach and stasis of liver energy. In the Asthenia syndrome, there are deficiency of stomach energy, deficiency of upper warmer leading to heat, deficiency of middle warmer leading to cold, deficiency of lower warmer leading to heat, deficiency of middle energy, deficiency of blood, decreased fire and deficiency of soil, yin fire of lower warmer, deficiency of heart yin, deficiency of spleen yin and deficiency of qi and blood. 2. In western medicine the causes of RAS is presumed as local, microbial, systemic, nutritional, genetic, immunologic factors. 3. Once Gu-chang is compared with RAS, in the deficiency of yin leading to hyperactivity of fire, deficiency of yin leading to floating of fire and stasis of liver energy, recurring of Gu-chang is similar to RAS. Although recurring of Gu-chang due to tripple warmer of excessive fire has no recurrance, since there are the degree of Pain, site of lesion, dysphagia etc, it is similar to major RAS. It is may be believed that Sthenia Gu-chang is similar to major RAS, shape of recurring, site of lesion, degrree of Pain and white color of Asthenia Gu-chang are similar to minor RAS, but there is no similarity concerning herpes RAS in the literatures that describe the symptoms. 4. Generally, the treatment of Gu-chang is divided into Asthenia and Sthenia Syndrome. The method of cure to Sthenia syndrome is heat cleaning and purge fire, Asthenia syndrome is nourish yin to lower and adverse rising energy and strength the middle warmer and benefit vital energy. 5. Following is the medication for Sthenia syndrome. Heat of heart and spleen is Do Jok San, Yang Gyek San, Juk Yup Suk Go Tang, evil heat of external factor is Yang Gyek San Ga Gam, Stasis of liver energy is Chong Wi Fae Dok Yum, moistured heat of spleen and stomach is Chong Gi Sam Syep Tang. The medication for Asthenia Syndrome is following. Deficiency of upper warmer leading to heat is Bo Jung Ik Gi Tang, deficiency of middle warmer leading to cold is Bu Ja Lee Jung Tang, deficiency of lower warmer leading to heat is Yuk Mi Ji Hwang Tang, deficiency of yin leading to hyperactivity of fire is Ji Baek Ji Hwang Hwan, deficiency of yin leading to floating of fire is Lee Jung Tang Ga Bu Ja Medicine for external use were Yang Suk San, Boo Wyen San, Rok Po San, Yoo Hwa San ate. 6. In western medicine, there is no specific treatment for RAS, and management strategies depend on dinical presentation and symptoms and includes antibiotics, oral rinses, glucocorticoids, immunomodulatory drugs, vitamines, analgesics, laser and antiviral agents.