• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.1-19
• /
• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Distribution Science
• /
• v.9 no.1
• /
• pp.17-27
• /
• 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
• /
• v.20 no.2
• /
• pp.73-92
• /
• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.127-147
• /
• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Asia Marketing Journal
• /
• v.14 no.1
• /
• pp.1-24
• /
• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.2
• /
• pp.76-84
• /
• 2013

An adequate downscaling of the official forecasts of Korea Meteorological Administration (KMA) is a prerequisite to improving the value and utility of agrometeorological information in rural areas, where complex terrain and small farms constitute major features of the landscape. In this study, we suggest a simple correction scheme for scaling down the KMA temperature forecasts from mesoscale (5 km by 5 km) to the local scale (30 m by 30 m) across a rural catchment, especially under temperature inversion conditions. The study area is a rural catchment of $50km^2$ area with complex terrain and located on a southern slope of Mountain Jiri National Park. Temperature forecasts for 0600 LST on 62 days with temperature inversion were selected from the fall 2011-spring 2012 KMA data archive. A geospatial correction scheme which can simulate both cold air drainage and the so-called 'thermal belt' was used to derive the site-specific temperature deviation across the study area at a 30 m by 30 m resolution from the original 5 km by 5 km forecast grids. The observed temperature data at 12 validation sites within the study area showed a substantial reduction in forecast error: from ${\pm}2^{\circ}C$ to ${\pm}1^{\circ}C$ in the mean error range and from $1.9^{\circ}C$ to $1.6^{\circ}C$ in the root mean square error. Improvement was most remarkable at low lying locations showing frequent cold pooling events. Temperature prediction error was less than $2^{\circ}C$ for more than 80% of the observed inversion cases and less than $1^{\circ}C$ for half of the cases. Temperature forecasts corrected by this scheme may accelerate implementation of the freeze and frost early warning service for major fruits growing regions in Korea.

• Journal of Wetlands Research
• /
• v.18 no.4
• /
• pp.386-393
• /
• 2016

Agricultural ecosystem is recognized as a space for providing a variety of services, in addition to the food production that it originally encompassed, such as water purification, biological habitat, air purification, soil conservation, and landscape development. The construction of greenhouses in agricultural landscapes can cause deterioration of ecosystem services because of the increase of impermeable area and loss of biological habitats. This study aimed to compare insect diversity between different types of constructed greenhouses and paddy ecosystems. The target study area was selected by considering the distribution status of horticultural complexes and was classified as Single Vinyl Greenhouse, Multi Vinyl Greenhouse or Glass Greenhouse and they were compared with four paddies. The study locations were in Gu-Mi, Bu-Yeo, Ginje and Jin-Ju. A total of 2,333 individual insects belonging to 9 orders, 38 families, 76 genus, and 80 species were collected. The composition of orders was Hemiptera (22.37%), Coleoptera (18.42%), Hymenoptera (14.47%), Orthoptera (11.84%), and Diptera (10.53%). The average number of collected species were in the order Paddy (39.38 species) > Single Vinyl Greenhouse (35.50 species) > Multi Vinyl Greenhouse (22.50 species) > Glass Greenhouse (24.00 species). The Diversity Index (H') was Paddy (4.76) > Single Vinyl Greenhouse (4.57) > Multi Vinyl Greenhouse (4.12), and Glass Greenhouse (4.12). The Richness Index (RI) was Paddy (7.72) and Single Vinyl Greenhouse (7.03) > Multi Vinyl Greenhouse (4.99) and Glass Greenhouse (5.32). From our results, it can be seen that the biological diversity features of insects decreased when greenhouses are constructed.However, Single Vinyl Greenhouse is noted to promote insect diversity more than that by Multi Vinyl Greenhouse and Glass Greenhouse. Hence, when constructing greenhouses, it is necessary to consider insect habitat to conserve insect diversity.

• The Korean Journal of Air & Space Law and Policy
• /
• v.30 no.1
• /
• pp.117-149
• /
• 2015

On May 16, 2014 the Supreme Court of Korea rendered its decision with respect to litigation filed by All Nippon Airways Co., Ltd. ("ANA") for revocation of an order of correction and payment of a penalty imposed by the Korea Fair Trade Commission ("KFTC"). On or around September 2002, ANA and various airlines operating air cargo service from Japan to Korea were allegedly to have agree to introduce of fuel surcharge into their rates on cargo fares in an attempt to recoup falling profits from rising of oil price. As this hard core cartel was per se prohibited under Korean competition law (The Monopoly Regulation And Fair Trade Act), KFTC began an investigation and consequently with fruitful results imposed an amount of penalty and issued an order of prohibition. ANA protested against this imposition by filing suit against KFTC under the reasons that (1) their agreement was simply pursuant to the relevant laws and regulations including Air Transport Agreement between Korea and Japan, (2) there was an administrative guidance from Japanese government to allow this agreement, (3) extraterritorial application of Korean competition law to the agreement in this matter was improper as it was made within Japan and targeted only for the shipment from Japan to Korea: accordingly there is not a direct and serious effect between the agreement and any result of anti-competitive. This article aims to review ANA's allegation and the judgement delivered by Korean court under some issues respectively; (1) whether there is an effectively actual anti-competitive cartel between airlines including plaintiff, (2) whether filed rate doctrine is reasonable and applicable in this case for precluding wrongfulness, (3) what is the reasonable limitation of boundaries in extraterritorial application of Korean competition law. Additionally, this article also suggests to concern particular features of air transport business as an regulated industry in judging the unfair restrain on competition.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.33 no.2
• /
• pp.89-102
• /
• 2015

This study contemplates the tendency of the examination questions for History of Korean Landscape Architecture. The study targets the questions of 'Landscape Architecture History' which has been set in the written test for National Qualification Test of a landscape engineer for recent 10 years from 2005 to 2014 and derives analyzable items based on the guidelines of question-setting presented by Human Resources Development Service of Korea. The results of the study are drawn as follows. First, among 5 areas composing Landscape History, the proportion of Korean Landscape questions is getting increased while that of Western ones is decreasing. Second, about 30 traditional trees and 11 types of traditional landscape elements including traditional facilities were shown in Korean Landscape questions. Besides, history, geographic, practical science, horticulture, anthology books and the 25 tradition landscape-related historic documents categorized as the garden painting data were found. And the kings from ancient era to Choseon Dynasty who were associated with the time of palace garden building, the builders or owners of the villas, the authors of the document and Chinese scholars also appeared. Third, there were no the questions of prehistoric times and Balhae Kingdom, whereas those of Choseon Dynasty were dominantly focused. Among the traditional sites of Choseon Dynasty, Byeolseo(villas) were set most, followed by Dosung or Gung-gweol(castle towns or palaces), houses, Nu Jeong Dea(pavilions) and Seowon(local schools) in order. Nak-an eupseong and Yong-ju sa were the only cases for a castle town and a temple each. Fourth, being associated with tradition spaces, the questions asked for understanding the detailed contents of time of sites' construction, builders, location features, building structures, ground plan types and the components s of garden. In addition, as a result of checking whether traditional landscape sites were shown in the set questions in 9 Korean Landscape textbooks, Dongchundang, Pungamjeonsa, Simgogseowon did not appeared. As a result of reviewing the tendency of the examination questions for History of Korean Landscape Architecture, the questions which ask minor facts without generality and which include difficult information and site uncomprehended in the textbook should be reconsidered.

• The Mathematical Education
• /
• v.24 no.2
• /
• pp.48-73
• /
• 1986

Though the tradition of Korean mathematics since the ancient time up to the 'Enlightenment Period' in the late 19th century had been under the influence of the Chinese mathematics, it strove to develop its own independent of Chinese. However, the fact that it couldn't succeed to form the independent Korean mathematics in spite of many chances under the reign of Kings Sejong, Youngjo, and Joungjo was mainly due to the use of Chinese characters by Koreans. Han-gul (Korean characters) invented by King Sejong had not been used widely as it was called and despised Un-mun and Koreans still used Chinese characters as the only 'true letters' (Jin-suh). The correlation between characters and culture was such that, if Koreans used Han-gul as their official letters, we may have different picture of Korean mathematics. It is quite interesting to note that the mathematics in the 'Enlightenment Period' changed rather smoothly into the Western mathematics at the time when Han-gul was used officially with Chinese characters. In Koryo, the mathematics existed only as a part of the Confucian refinement, not as the object of sincere study. The mathematics in Koryo inherited that of the Unified Shilla without any remarkable development of its own, and the mathematicians were the Inner Officials isolated from the outside world who maintained their positions as specialists amid the turbulence of political changes. They formed a kind of Guild, their posts becoming patrimony. The mathematics in Koryo significant in that they paved the way for that of Chosun through a few books of mathematics such as 'Sanhak-Kyemong', 'Yanghwi-Sanpup' and 'Sangmyung-Sanpup'. King Sejong was quite phenomenal in his policy of promotion of mathematics. King himself was deeply interested in the study, createing an atmosphere in which all the high ranking officials and scholars highly valued mathematics. The sudden development of mathematic culture was mainly due to the personality and capacity of king who took anyone with the mathematic talent into government service regardless of his birth and against the strong opposition of the conservative officials. However, King's view of mathematics never resulted in the true development of mathematics perse and he used it only as an official technique in the tradition way. Korean mathematics in King Sejong's reign was based upon both the natural philosophy in China and the unique geo-political reality of Korean peninsula. The reason why the mathematic culture failed to develop continually against those social background was that the mathematicians were not allowed to play the vital role in that culture, they being only the instrument for the personality or politics of the king. While the learned scholar class sometimes played the important role for the development of the mathematic culture, they often as not became an adamant barrier to it. As the society in Chosun needed the function of mathematics acutely, the mathematicians formed the settled class called Jung-in (Middle-Man). Jung-in was a unique class in Chosun and we can't find its equivalent in China or Japan. These Jung-in mathematician officials lacked tendency to publish their study, since their society was strictly exclusive and their knowledge was very limited. Though they were relatively low class, these mathematicians played very important role in Chosun society. In 'Sil-Hak (the Practical Learning) period' which began in the late 16th century, especially in the reigns of Kings Youngjo and Jungjo, which was called the Renaissance of Chosun, the ambitious policy for the development of science and technology called for. the rapid increase of he number of such technocrats as mathematics, astronomy and medicine. Amid these social changes, the Jung-in mathematicians inevitably became quite ambitious and proud. They tried to explore deeply into mathematics perse beyond the narrow limit of knowledge required for their office. Thus, in this period the mathematics developed rapidly, undergoing very important changes. The characteristic features of the mathematics in this period were: Jung-in mathematicians' active study an publication, the mathematic studies by the renowned scholars of Sil-Hak, joint works by these two classes, their approach to the Western mathematics and their effort to develop Korean mathematics. Toward the 'Enlightenment Period' in the late 19th century, the Western mathematics experienced great difficulty to take its roots in the Peninsula which had been under the strong influence of Confucian ideology and traditional Korean mathematic system. However, with King Kojong's ordinance in 1895, the traditional Korean mathematics influenced by Chinese disappeared from the history of Korean mathematics, as the school system was hanged into the Western style and the Western mathematics was adopted as the only mathematics to be taught at the Schools of various levels. Thus the 'Enlightenment Period' is the period in which Korean mathematics shifted from Chinese into European.