• The Journal of Korean Philosophical History
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• no.23
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• pp.155-180
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• 2008

Suam(遂庵) Kwon Sang-Ha(權尙夏) was a very important character in the late Chosoen Dynasty. He was a representative of the academic circles(school of Uam) and political circles(Nolon; 老論) after Uam(尤庵) Song Si-Yeol(宋時烈, 1607-1689). He represented learning and thought and undertaking of his academic circles and political circles, and handed down to his pupils. He thought his mission was "lighting the laws of heaven and aligning the human mind," "stopping the heretical study and repulsing uncivilization", to reform good virtues of humanity and justice. Kwon Sang-Ha was a successor of Song Si-Yeol, He succeeded learning and thought of his teacher and practiced "Upright"(直) and the Thought of ChunChu(春秋). He emphasized "Upright" as a fundamental principle, like his teacher. He thought ChuHsi(朱熹, 1130-1200) was the master who had inherited the spirit of Confucianism and Chosoen was the only country to successfully inherit this spirit of Confucianism. He declared any study counter to the study of ChuHsi as a rebellious pursuit. Therefore he rejected all other studies. He tried to "stop the heretical 'ism' and repulse uncivilization" and present this ideology as 'the Right way of Human Society(世道)'. He made efforts to reorganize books of ChuHsi to make perfect Book of righteousness with Song Si-Yeol. And he established Hwayang shrine, MandongMyo(萬東廟), Deabodan(大報壇) etc, in memory of fidelity and large rightness. Kwon Sang-Ha did these undertaking to establish 'Public morals and the Right way of Human Society(世道)' with self-confidence. In Dispute on the nature of man and animal(人物性同異論), he gives his approval to Han Won-Jin's opinion. Han Won-Jin's opinion was "the nature of man and animal is Different"(人物性異論). Whenever serious political accidents occurred, he took the lead to protect his teacher, Song Si-Yeol. The reason he did this was not because of his personal feelings for his teacher, but because of promoting 'Public morals(世道)' and 'Confucianism.' Kwon Sang-Ha regarded Mind control Law of "Upright" and the thought of ChunChu as his moralities, and was concerned about real politics and opposed social irregularities. Kwon Sang-Ha succeeded Song Si-Yeol's thought of "Upright" and volition of making an inroad on the Chung(淸), and gave to his political circles(Nolon; 老論) as a law of mind and mission.

• (The)Study of the Eastern Classic
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• no.49
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• pp.161-185
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• 2012

This thesis reorganized the life of Mrs. Yun who was a noble woman in the middle of the Joseon period with main material of Seopo, Kim, Man Joong(1637-1692)'s "Seonbijungkyungbuinhaengjang(先?貞敬夫人行狀)" and considered yeosa(女師)'s image of noble woman embodied by her son. Although women who were remarkable in premodern period nurtured their son well and they became excellent, it's easy that the life of their mother can be hidden by sons' shadow. Luckily, materials of Mrs. Yun were kept by her descendants, so people could analogize how she could endure difficulties and how she educate her children. In a word, the life of Mrs. Yun can be yeosa(女師)'s life. She was born as a only daughter of the best ancestry in the period and grown to be a considerable woman with strong will and discipline under the strict training of her grandmother, Junghye Ongju. And then, she married Gwangsan Kimmun, the best literature house of Joseon period, but her husband, Kim, Ik Kyum was died by unexampled difficulty, Byungjahoran. During the tribulation, Mrs. Yun was in charge of not only parents supporting but also two sons' education excellently. She educated not only her children but also grandchildren and nephews around her, so she had extraordinary passion and sincerity for the education. As the result, she enjoyed a glory that two sons and grandchildren became on daejehak. Mrs. Yun was living with thrift and saving continuously regardless of her circumstances. When her granddaughter became inkyungwanghoo who is a wife of sookjong, she didn't kick her common habit and trained strictly the mind of family members who could be easily in disorder. In spite of the richness, he obeyed manners and showed thrift and saving continuously and thoroughly. When there was a crisis in her family, the first son, Kim, Man Ki was died and the second son, Kim, Man Joong and grandson went into exile during the continuous political upheaval. But, she supported her house, obeyed the rules and promised the future. At that time, she continuously encouraged grandchildren and the eldest grandsons of the head family to study without any stop for themselves in spite of the difficulties. Mrs. Yun pursued truly valuable life. She considered that the life which didn't get praised by other people wasn't valid although he or she lived a pleasant life in luck and richness. Mrs. Yun was a true teacher yeosa (女師) who placed a true value on the life enduring hardship and poorness without fear and becoming an example of other people.

• The Journal of Korean Philosophical History
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• no.31
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• pp.53-86
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• 2011

Taoism exercised its influence and has made much progress apparently under the aegis of the Tang dynasty. But since the external alchemy, a traditional way of eternal life that they have pursued, met the limitation, they were placed in a situation where they needed to seek a new discipline. From this period to the early North Song dynasty, three religions have established the unique theoretical systems of their own theory of ascetic practices. They showed their own unique formats as follows. Neo-Confucianism established the theory of moral training, Buddhism did the theory of ascetic practices and Taoism had theory of discipline. By this time, a person who claimed the Intermixture of Three Religions composed the new system of theory of ascetic practice by taking advantage of other religions and putting them into his own view. Chen tuan established the theory of internal alchemy of Taoism and was the most influential figure in the world of thought since North Song dynasty. He clearly declared that he accepted the merits of other religions in his theory. He added I Ching of Confucianism in I Ching of secret of Taoism to stop the logical gaps during the process of disciplines in Taoism and took ascetic practices on mind of Buddhism into his system while he sought a way to integrate the dual structure of body and mind. The theory of Chen tuan's internal alchemy was training schema with stages of 'YeonJeongHwaGi', 'YeonGiHwaSin', and 'YeonSinHwanHeo' based on the concepts of vital, energy and spirit. The internal alchemy practice that Chen tuan was saying started from the practice of Zen to keep the mind calm with the basis of fundamental principles of interpretation of book of change according to Taoism. When a person reached the state to be in concert with all changes at the end of the silence and be full of wisdoms, he finally returned to the state of BokGwiMuGeuk by taking the flow of subtle mind and transforming it into energy. He expressed this process by drawing 'MuGeukDo'. Oriental philosophy categorized human into 'phenomenal existence' and 'original existence'. The logic of theory of ascetic practice has been established from these 'category of existence'. It would be determined whether it will return to 'original existence' or be stepped up from 'phenomenal existence' according to how the concept of 'self' or 'I' was made. Chen tuan who established the theory of internal alchemy in Taoism has established the unique theory of internal alchemy discipline and system of intermixture of three religions in this aspect. Today is called 'era of self-loss' or 'era of incurable diseases' caused by environmental pollution. It's still meaningful to review the theory of discipline of Chen tuan's connecting the body and the soul to heal the self, and keep life healthy and pursue the new way of discipline based on it.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.603-611
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• 2020

This study collected and analyzed transportation card data in order to better understand the operation and usage of city buses in Ulsan Metropolitan City in Korea. The analysis used quantitative and qualitative indicators according to the characteristics of the data, and also the categories were classified as general status, operational status, and satisfaction. The existing city bus survey method has limitations in terms of survey scale and in the survey process itself, which incurs various types of errors as well as requiring a lot of time and money to conduct. In particular, the bus means indicators calculated using transportation card data were analyzed to compensate for the shortcomings of the existing operational status survey methods that rely entirely on site surveys. The city bus index calculated by using the transportation card data involves quantitative operation status data related to the user, and this results in the advantage of being able to conduct a complete survey without any data loss in the data collection process. We took the transportation card data from the entire city bus network of Ulsan Metropolitan City on Wednesday April 3, 2019. The data included information about passenger numbers/types, bus types, bus stops, branches, bus operators, transfer information, and so on. From the data analysis, it was found that a total of 234,477 people used the city bus on the one day, of whom 88.6% were adults and 11.4% were students. In addition, the stop with the most passengers boarding and alighting was Industrial Tower (10,861 people), A total of 20,909 passengers got on and off during the peak evening period of 5 PM to 7 PM, and 13,903 passengers got on and off the No. 401 bus route. In addition, the top 26 routes in terms of the highest number of passengers occupied 50% of the total passengers, and the top five bus companies carried more than 70% of passengers, while 62.46% of the total routes carried less than 500 passengers per day. Overall, it can be said that this study has great significance in that it confirmed the possibility of replacing the existing survey method by analyzing city bus use by using transportation card data for Ulsan Metropolitan City. However, due to limitations in the collection of available data, analysis was performed only on one matched data, attempts to analyze time series data were not made, and the scope of analysis was limited because of not considering a methodology for efficiently analyzing large amounts of real-time data.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.3
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• pp.367-376
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• 2022

This study is a preliminary step to understand the reaction between various liquids and zeolite in the subduction zone environment. Stilbite, NaCa₄(Al₉Si₂₇)O₇₂·28(H₂O), was selected and high pressure study was conducted on compressional behavior by the pressure-transmitting medium (PTM). Water and NaHCO₃ solution that can exist in the subduction zone was used as PTM, and samples were pressurized from ambient to a maximum of 2.5 GPa. Below 1.0 GPa, both experiments show a low linear compressibility in the range of 0.001 to 0.004 GPa^-1 and a high bulk modulus of 220(1) GPa. This is presumably because the structure of the stilbite becomes very dense due to insertion of water molecules or cations into the channel. On the other hand, at 1.0 GPa or higher, the trends of the two experiments are different. In the water run, the linear compressibility of the c-axis is increased to 0.006(1) GPa^-1. In the NaHCO₃ run, the linear compressibility of the b- and c-axis is increased to 0.006(1) GPa^-1. The bulk modulus after 1.0 GPa shows values of 40(1) and 52(7) GPa in water and NaHCO₃ run, respectively, confirming that stilbite becomes more compressible than that before 1.0 GPa. It is caused by the migration of cations and water molecules inside the channel, as the water molecules in the PTM start to freeze and stop to insert toward the channel at 1.0 GPa or more. In the NaHCO₃ run, it is assumed that the distribution of extra-framework species inside the structure is changed by substitution of the Na⁺ cation. It can be expected from tendency of the relative intensity ratio of the (001) and (020) peaks which show a different from that of the water run.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.