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Yesterday and Today of Twelve Excellent Sceneries at Banbyeoncheon Expressed in Heojoo's Sansuyucheop (허주(虛舟) 산수유첩(山水遺帖)에 표현된 반변천(半邊川) 십이승경(十二勝景)의 어제와 오늘)

  • Kim, Jeong-Moon;Rho, Jae-Hyun
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.30 no.1
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    • pp.90-102
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    • 2012
  • Sansuyucheop by Heojoobugun(虛舟府君) as the subject of this study is a 십이-width picture album by the eldest grandson of 11 generations for Goseong Lee family, Lee Jong Ak(李宗岳: 1726-1773), a figure having five habits(五癖) for ancient documents(古書癖), playing the gayageum(彈琴癖), flowering plant(花卉癖), paintings and calligraphic works(書畵癖) and boating(舟遊癖) etc., who boated with 18 relatives, and those by marriage from old home, home of mother's side, wife's home, and his home for 5 days Apr. 4 through 8, 1763, starting from Imcheonggak, through Yangjeong(羊汀), Chiltan(七灘), Sabin Auditorium(泗濱書院), Seonchang(船倉), Nakyeon(落淵), Seonchal(仙刹), Seonyujeong(仙遊亭), Mongseongak(夢仙閣), Baekwoonjeong(白雲亭) and Naeap Village(川前里), Iho(伊湖), Seoeodae(鮮魚帶) to the returning point, Bangujeong(伴鷗亭), cruised magnificent views around Banbyeoncheon called 'Andong 8 Gyeong' or 'Imhagugok', and whenever the boat anchored, appreciated the scenery at each point, and enjoyed and loved arts playing the geomungo. This study reached following findings through grasping physical, ecological, visual and aesthetic changes about the places, sceneries, plant elements and past and current scenery of the width pictures expressed at this Sansuyucheop. The refinement on the boat seeing the clear river water, white sand beach, fantastically-shaped cliffs expressed at this Sansuyucheop, exchanging poems and calligraphies, and enjoying the geomungo is a good example displaying the play culture of high-class in Joseon Dynasty. Also construction of Imha Dam and Andong Dam has caused serious visual and ecological changes, making us not enable to feel the original mood of the background spots such as Yangjeonggwabeom(羊汀過帆), Chiltanhuseon(七灘候船), Sasubeomjoo(泗水泛舟), Seonchanggyeram(船倉繫纜), Nakyeonmosaek(落淵莫色), Mangcheonguido(輞川歸棹), Ihojeongdo(伊湖停棹), but only discern then landscape or sentiment through the landscape described at the canvas. The 1st picture(Donghohaeram, 東湖解纜), and the 11th picture(Seoeobanjo, 鮮魚返照) of Heojoobugun's Sansuyucheop expressed trees thought to be fallen, brad-leaf tall trees, and the 9th picture(Unjeongpungbeom, 雲亭風帆) formed a pine forest called 'Gaeho(開湖)' by Uncheongong planting 1,000 pine trees with the village people in 1617. In addition, Seunggyeongdo expressed ever-green needle leaf trees at the natural topography, and fallen-leaf tall trees around the pavilion and building. Comparative consideration of Heojoobugun's Sansuyucheop and Shinam's Dongyusipsogi(東遊十小記) showed that the location of Samgok is assumed to be Macheon and Chiltan, so Imhagugok is assumed to start from Baekunjeong of Ilgok, Igok from Imcheon and Imcheon auditorium, Samgok from Mangcheon and Chiltan, Sagok from Sabin Auditorium of Sasoo, Ogok from Songseok, Yukgok from Sooseok of Seonchang, Chilgok from Nakyeonhyeonryu, Palgok from Seonchalsa and Seonyoojeong, and Gugok from Pyong Yuheo. This study can be significant in that it could clarify that Heojoobugun's Sansuyucheop is judged to be valuable in exquisitively expressing the coast of Banbyeon River, the biggest branch stream in the Nakdong River at the latter half of Joseon Dynasty, and as a vital diagrammatical historical data to make a comparative analysis of currently rarely-seen ancestors' life traces and landscape factors with present ones.

Corporate Default Prediction Model Using Deep Learning Time Series Algorithm, RNN and LSTM (딥러닝 시계열 알고리즘 적용한 기업부도예측모형 유용성 검증)

  • Cha, Sungjae;Kang, Jungseok
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.1-32
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    • 2018
  • In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

School Experiences and the Next Gate Path : An analysis of Univ. Student activity log (대학생의 학창경험이 사회 진출에 미치는 영향: 대학생활 활동 로그분석을 중심으로)

  • YI, EUNJU;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.149-171
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    • 2020
  • The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.

An Exploratory Study on Marketing of Financial Services Companies in Korea (한국 금융회사 마케팅 현황에 대한 탐색 연구)

  • Chun, Sung Yong
    • Asia Marketing Journal
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    • v.12 no.2
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    • pp.111-133
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    • 2010
  • Marketing financial services used to be easier. Today, the competition in financial services is fierce. Not only has the competition become more intense, financial services have also changed structurally. In an environment with various customer needs and severe competitions, the marketing in financial services industry is getting more difficult and more important than before. However, there are still not enough studies on financial services marketing in Korea whereas lots of research papers have been published frequently in some international journals. The purpose of this paper is (1)to review the literature on financial services marketing, (2)to investigate current marketing activities based on in-depth interview with financial marketing managers in Korea, and (3)to suggest some implications for future research on the financial services marketing. Financial products are not consumer products. In fact, they are not products at all in the way product marketing is usually described. Nor are they altogether like services. The financial industry operates in a unique way, and its marketing tasks are correspondingly complex. However, the literature review shows that there has been a lack of basic studies which dealt with inherent characteristics of financial services marketing compared to the research on marketing in other industries. Many studies in domestic marketing journals have so far focused only on the general customer behaviors and the special issues in some financial industries. However, for more effective financial services marketing, we have to answer following questions. Is there any difference between financial service marketing and consumer packaged goods marketing? What are the differences between the financial services marketing and other services marketing such as education and health services? Are there different ways of marketing among banks, securities firms, insurance firms, and credit card companies? In other words, we need more detailed research as well as basic studies about the financial services marketing. For example, we need concrete definitions of financial services marketing, bank marketing, securities firm marketing, and etc. It is also required to compare the characteristics of each marketing within the financial services industry. The products sold in each market have different characteristics such as duration and degree of risk-taking. It means that there are sub-categories in financial services marketing. We have to consider them in the future research on the financial services marketing. It is also necessary to study customer decision making process in the financial markets. There have been little research on how customers search and process information, compare alternatives, make final decision, and repeat their choices. Because financial services have some unique characteristics, we need different understandings in the customer behaviors compared to the behaviors in other service markets. And also considering the rapid growth in financial markets and upcoming severe competition between domestic and global financial companies, it is time to start more systematic and detailed research on financial services marketing in Korea. In the second part of this paper, I analyzed the results of in-depth interview with 20 marketing managers of financial services companies in Korea. As a result, I found that the role of marketing departments in Korean financial companies are mainly focused on the short-term activities such as sales support, promotion, and CRM data analysis although the size and history of marketing departments to some extent show a sign of maturity. Most companies established official marketing departments before 2001. Average number of employees in a marketing department is about 58. However, marketing managers in eight companies(40% of the sample) still think that the purpose of marketing is only to support and manage general sales activities. It shows that some companies have sales-oriented concept rather than marketing-oriented concept. I also found three key words which marketing managers think importantly in financial services markets. They are (1)Trust in customer relationship, (2)Brand differentiation, and (3)Rapid response to customer needs. 50% of the sample support that "Trust" is the most important key word in the financial services marketing. It is interesting that 80% of banks and securities companies think that "Trust" is the most important thing, whereas managers in credit card companies consider "Rapid response to customer needs" as the most important key word in their market. In addition, there are different problems recognition of marketing managers depending on the types of financial industries they belong to. For example, in the case of banks and insurance companies, marketing managers consider "a lack of communication with other departments" as the most serious problem. On the other hand, in the case of securities firms, "a lack of utilization of customer data" is the most serious problem. These results imply that there are different important factors for the customer satisfaction depending on the types of financial industries, and managers have to consider them when marketing financial products in more effective ways. For example, It will be necessary for marketing managers to study different important factors which affect customer satisfaction, repeat purchase, degree of risk-taking, and possibility of cross-selling according to the types of financial industries. I also suggested six hypothetical propositions for the future research.

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