• The Journal of Art Theory & Practice
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• no.4
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• pp.123-144
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• 2006

Foreigners who arrived in Korea after the age of enlightenment were Japanese, Chinese and 'Westerners' who were Europeans and Americans. The westerners were diplomats who visited Korea for colonization or for increasing their economical profits by trading after the spread of imperialism, and tourists curious of back countries, artists, explores and missionaries to perform their roles for their religious beliefs. They contacted with Korean cultural and educational people as missionaries and instructors during Japanese colonial period. In 1945, the allied forces occupied Korea under the name of takeover of Japanese colony after Japan's surrender and the relation between foreigners and Korean cultured men enter upon a new phase. For 3 years, American soldiers enforced lots of systems in Korea and many pro-American people were educated. This relationship lasted even after the establishment of the government of Korean Republic and especially, diplomats called as pro-Korean group came again after Korean War. Among them, there were lots of foreigners interested in cultures and arts. In particular, government officials under American Forces who were influential on political circles or diplomats widened their insights toward Korean cultural assets and collected them a lot. Those who were in Korea from the period of independence to 1950s wrote their impressions about Korean cultural assets on newspapers or journals after visiting contemporary Korean exhibitions. Among them, A. J. McTaggart, Richard Hertz and the Hendersons were dominant. They thought the artists had great interests in compromising and uniting the Orient and the West based on their knowledge of Korean cultural assets and they advised. However, it was different from Korean artist's point of view that the foreigners thought Korean art adhered oriental features and contained western contents. From foreigners' point of view, it is hard to understand the attitude Korean artists chose to keep their self-respect through experiencing the Korean war. It is difficult to distinguish their thought about Korean art based on their exotic taste from the Korean artists' local and peninsular features under Japanese imperialism. We can see their thought about Korean art and their viewpoint toward the third world, after staying in Korea for a short period and being a member of the first world. The basic thing was that they could see the potentialities through the worldwide, beautiful Korean cultural assets and they thought it was important to start with traditions. It is an evidence showing Korean artists' pride in regard to the art culture through experiencing the infringement of their country. By writing about illuminating Korean art from the third party's view, foreigners represented their thoughts through it that their economical, military superiority goes with their cultural superiority. The Korean artist's thought of emphasizing Korean history and traditions, reexamining and using it as an original creation may have been inspired by westerners' writings. 'The establishment of national art' that Korean artists gave emphasis then, didn't only affect one of the reactions toward external impact, 'the adhesion of tradition'. In the process of introducing Korean contemporary art and national treasure in America, different view caused by role differences-foreigner as selector and Korean as assistant-showed the fact evidently that the standard of beauty differed between them. By emphasizing that the basis to classify Korean cultural assets is different from the neighborhood China and Japan, they tried to reflect their understanding that the feature of Korean art is on speciality other than universality. And this make us understand that even when Korean artists profess modernism, they stress that the roots are on Korean and oriental tradition. It was obviously a different thought from foreigners' view on Korean art that Korean artists' conception of modernism and traditional roots are inherent in Korean history. In 1950s, after the independence, Korea had different ideas from foreigners that abstract was to be learned from the west. Korea was enduring tough times with their artists' self-respect which made them think that they can learn the method, but the spirit of abstract is in the orient.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Korean Academy of Nursing
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• v.21 no.3
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• pp.396-417
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• 1991

In order that nursing care an essential quality of nursing practice be acceptable and satisfying, it is necessary that client's culture be respected and that nursing practice be appropriate to that culture. Since cultural elements are an important influence on health practices and life patterns related to medical treatment, recovery from and prevention of disease, nurses need to have an understanding and knowledge of social and cultural phenomena to aid in the planning of nursing interventions. To understand the health practices surrounding health and illness, the health beliefs and practices of both folk and professional healing systems should be ascertained. Cultural data are required to provide care of high quality to clients and to reduce possible conflict between the client and the nurse. It is nursing's goal to provide clients from various cultures with quality nursing care which is satisfying and valuable. The problem addressed by this study was to identify Korean health practices which would contribute to the planning of professional caring practice with the culture : ultimately this study was intended to make a contribution to the development of the science of nursing. The concrete objectives of this study were ; 1) to identify Korean health practices, 2) to interpret the identitial health practices through traditional cultural thought, and 3) to compare the Korean health practices with those of other cultures. The investigator used the ethnosceintific approach outlined by spradly in a qualitative study. To discover ancestral wisdom and knowledge related to traditional health practeces, the subjects of this study were selected from residents of a small rural mountain village in south west Korea, a place considered to be maintaining and transmitting the traditional culture in a relatively well -preserved state because of being isolated from the modern world. The number of subjects was 18, aged 71 to 89. Research data were collected from January 8 to March 31, 1990. Five categories of health practices were identified : “Manage one's own mind”, “Moderation in all thing”, “Live in accord with nature”, “Live in mutuality with others”, and “Live to the best of one's ability”. Values derived from these ways of thinking from Confucianism, Taoism and Buddhism help fashion a traditional way of life, examplified by the saying “Benifience to all”. Korean thought and philosophy is influenced primerily by Confucianism, Confucian principles of ethics, embedded deeply in the peoples' minds, form the idea that “heaven and human being are intimately united” based on concept that “heaven is, so to speak, reason”. Twoe Gae's theory of existential subjectivity develops the concept of self which is the basis of the spirit of reverence in modern Confucian philosophy. The human md is granted from heaven out of the idea of matter, and what control the mind is the spirit of reverence. Hence the idea of “The primacy of the mind" and provided that one should control one's own mind. The precepts of duty to parents, respect for elders and worship of ancestors, and moderation in all behavior put a restraint on life which directed that one live earnestly according to Nature's laws with their neighbors. Not only Confucianism, but also Buddism and Taoism have had an important effect upon these patterns of ideas. When compared with western culture, Korean health practices tend to be more inclusive, abstract and intuitive while westerner health practices found to be mere concrete, practical and personal. Values and beliefs based and pragmatism and existentialism infuence western civilization, Ethical values may be founded on utilitarianism, which considers what is good for the persons in their circumstances as the basis of conduct and takes a serious view of their practical lives including human aspirations rather than an absolute truth. These philosophical and ethical ideas are foundations for health practices related to active, practical and progressive attitudes. This study should be enable nursing not only to understand clients as reflections of the traditional culture when planning nursing practice, but to dovelop health education corresponding to cultural requiments for the purpose of protection against disease and improvement of health, and thus promote sound health practice. Eventually it is hoped that through these processes quality nursing care as the central idea of the science of nursing will be achieved.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.