• Journal of Korean Philosophical Society
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• v.123
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• pp.57-86
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• 2012

Many contemporary philosophers argue that modern philosophy is only the philosophy being imprisoned in subject and consciousness without communicating other subjects with language. They criticize that it is solipsistic. Today, those who are taking part in the communication theory, hermeneutics, and de-constructivism are trying to overcome this problem. The practical philosophers, especially those who advocate communintarianism criticize that modern libertarianism is not free from the isolated autonomy and breaks the solidarity of the traditional community with treating formally others. They criticize Kant's philosophy in the same way. But it is unreasonable. Because Kant was not the philosopher who pursued the same philosophy of subjectivity and liberalism as the earlier modern philosophers pursued. He tried to criticize its limits and overcome them. Especially he did not remain within the modern subjectivity, but rather tried to come up with the inter-subjectivity communicating between subjects. He showed this side through the 'sensus communis'. He thought of a judgement of taste as an effect resulting from the free play between imagination and understanding, and postulated the 'sensus communis' as a ground of the universal validity of this judgement. Therefore this 'sensus communis' is the subjective principle of a judgement of taste. Furthermore, he did not treat this 'sensus communis' merely as a self-relation of a subject, but rather developed it into an communicative relation among subjects. This position of Kant enables us to seek the harmony between the aesthetic sphere and social-moral sphere, and to overcome the conflicts between the autonomy of the liberalism and the solidarity of the communitarianism. Especially, his 'sensus communis' can be developed into the 'critical hermeneutics' and the 'relational autonomy'. Therefore his 'sensus communis' has the possibility to overcome the negative points of the traditional community and the modern community, and to overcome the conflicts among the isolated selves occurring in today's society. Hence Kant's 'sensus communis' has still the important values in the contemporary philosophy, especially in the practical philosophy being now discussed over the relation between autonomy and solidarity.

• Journal of Nutrition and Health
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• v.49 no.3
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• pp.179-188
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• 2016

Purpose: This cross-sectional study aimed to document the dietary behaviors, dietary changes, and health status of female marriage immigrants residing in Gwangju, Korea. Methods: The survey included 92 female immigrants attending Korean language class at a multi-cultural family support center. General characteristics, health status, anthropometric data, dietary behaviors, and dietary changes were collected. Results: Mean age of subjects was 31.3 years, and home countries of subjects were Vietnam (50.0%), China (26.0%), Philippines (12.0%), and others (12.0%). Frequently reported chronic diseases were digestive diseases (13.2%), anemia (12.1%), and neuropsychiatry disorder (8.9%). Seventeen percent of the subjects was obese ($BMI{\geq}25kg/m^2$). Dietary score by Mini Dietary Assessment was 3.45 out of 5 points. Dietary scores for dairy foods, meat/fish/egg/bean intake, meal regularity, and food variety were low, and those for fried foods and high fat meat intake were also low. Thirty-three percent of subjects answered that they have changed their diet and increased their consumption of fruits and vegetables after immigration. Length of residence in Korea was positively associated with BMI and waist circumference. Length of residence tends to be positively associated with dietary changes and obesity as well as inversely associated with disease prevalence. Conclusion: The study shows that length of residence is inversely related to disease prevalence. However, this association is thought to be due to the relatively short period of residence in Korea and thus the transitional phase to adapting to dietary practices. As the length of residence increases, disease patterns related to obesity are subject to change. Healthy dietary behaviors and adaptation to dietary practices in Korea in female marriage immigrants will not only benefit individuals but also their families and social structure. Therefore, varied, long-term, and target-specific studies on female marriage immigrants are highly needed.

• (The)Study of the Eastern Classic
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• no.57
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• pp.331-357
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• 2014

This paper is to examine Okdong Lee Seo's historical view through analyzing Yeokdaega("歷代歌"), Okdong's full-length historical epic. As long as Okdong Lee Seo was a Confucian scholar holding moral cultivation as the highest value, his Yeokdaega is hard to explain separately from the Confucian world view. Okdong's Yeokdaega is a long old-style sino-korean poem consisting of 526 7-syllable verses, yet it considerably differs in structure from other historical epics known so far. Okdong's Yeokdaega consists of two parts: the first narrates Chinese historical facts from the beginning to the fall of Ming dynasty, and the second describes the social irrationality of the time and reveals his strong social criticism. It is very different from an ordinary historical epic piece narrating the orders and disorders and the rise and fall of historical facts. It is thought that Okdong's Yeokdaega was written based on his Confucian historical view. It seems that for Okdong the rise and fall of Chinese historical dynasties did not merely mean historical facts but functioned as a tool explaining the reason for people to persue moral cultivation. Okdong summed up his knowledge of the rise and fall of Chinese historical dynasties, his sharp criticism on social irrationality, and his stimulation about the necessity of moral cultivation, and then created a long 526-verse historical epic Yeokdaega. For the reasons, it is not easy to say that Okdong's Yeokdaega is the result of pure literary activities only for artistry. However, Okdong's Yeokdaega is not inferior to other historical epic pieces written by the time in literary value. Especially, Okdong's Yeokdaega can be said to be more meaningful since it was, over its literary value, not only a tool to strengthen his own study and will but also a educational tool for others around himself.

• The Journal of Korean Philosophical History
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• no.52
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• pp.9-35
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• 2017

This article is to study the life and philosophy of Jonjae Gidaeseung, who was at strife with his days and did not negotiate with himself, with focus on two concepts of buron(不穩, unrest) and 'sympathy'. It is the fact that to study the traditional philosopher is likely to be enlightening. In order to prevent the risk, we need to define first the concept of unrest as including anxiety to critical resistance. Also, I would like to propose the concept of sympathy in order to grasp the function of his mind which judges whether his feelings and actions are valid from an emotional horizon of unrest. Methodologically this article is to adopt a transversal and correlative thinking by combining an east Asian Confucian traditional concept unrest with a modern one space. It is because this research is to show a significant meaning when we study highlighted and hidden layers of our life and politics in 'now-here' and the 'between space' even though this transversal and correlative study shows the horizon of his life. This article is to investigate how a case is structured by occurrences and divergences and reinterpret a meaning from an emotional horizon. This process is done centering on two terms Guchatuan(pursuing ease ignobly), and Suwolbingho(moon reflected in the water and ice in a bottle), which is the source of Bingwoldang. The two terms were used by Jonjae himself. The latter shows an opposite meaning from the first and is accordingly a way by which we can look into his life and days. My research of Jonjae's life and politics from the emotional-philosophical level is original in that it reveals emotional traces beyond his philosophical ideas which previous studies did not show. In this article, I showed that Gobong was ambitious and resolute, and definite in his judgment and therefore was not good at controlling his uprightness. Also he was too straightforward to purify a language. His unrest characters made him conflict with old ministers and high ranking officials and therefore they avoided him even thought he was excellent in writing and learning and talented. He was oriented toward living by goodness and right Ways, which is summed up as Gisesa(vague movement, situational advantage, and death).

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

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