• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.679-686
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• 2012

KTX step 1 April 2004, after the opening, the second phase of the project was opened in November 2010. High-speed rail after the opening and continue to increase the demand of high-speed rail, Have the speed of competitive advantage compared too the means of transportation. The opening of these high-speed rail has led to changes of the move, the company's position, and the spatial structure of the population of reorganization, such as the social, economic, transportation. In this study, survey data using the High Speed Rail Station EMME/2 of the program to take advantage of the 2-Dimentional Blancing trip distribution to investigate the passage through the trip distribution by the estimation of the parameters of the model to estimate the distribution of the means of access and high-speed rail station to reproduce and Analysis of the results by means of access parameters (${\theta}$) autos 0.0395, buses 0.0390, subway 0.0650, taxi 0.0415, the frequency distribution (Trip Length Frequency Distribution: TLFD) were analyzed survey data value model with the results of comparing $R^2$ cars analysis and model values similar survey data 0.909 bus 0.923, subway 0.745 to 0.922, taxi, F test P value analysis is smaller than 0.05 at the 95% confidence level as a note that was judged to have been. Trip frequency distribution analysis, but in the future, set the unit to 5km-trip frequency distribution middle zone Units from small zone units (administrative district) segmentation research is needed, and can reflect the trip distance 0~5 km interval combined function to take advantage of the gravity model and the 3-Dimentional Blancing applied research is needed to be considered.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.158-170
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• 2013

With the recent 'Creative economy' and 'Cultural prosperity' coming to the fore as a new code to build up a city or a region, it is necessary to focus on strengthening the regional creative capacity as well as developing spontaneous regional culture. In such trend this research aims to explore the Kyunglidan-gil, Seoul, Korea in which creative-class are appearing autogenously in clusters and forming new cultural landscape, to identify the factors of their accumulation and changing aspect of cultural landscape. This study has the following purposes: First, Investigating the historical context of the Kyunglidan-gil's landscape. Second, considering the process of the creative-class being flowed into the Kyunglidan-gil as the subject leading to the modification of the region. Third, their activity was analyzed to consider the unique aspect of forming the cultural landscape at the Kyunglidan-gil. Regarding why the creative-class should flow in, results of the study drew five factors including region in issue compared to inexpensive rents, coexistence with nature, quiet atmosphere seeming isolated from the urban confusion, location possible to test and share individual materials one likes, and a site with synergy effect of activity through the network with acquaintances. Also, five characteristics of cultural landscape forming by the people's activity were drawn - space of communication for increasing creativity, temporary and flexible spatial use, expression of one's identity and taste, distinguishing, and positive use of the existing facilities. Like this, by exposing the 'creative-class', a subject of the leader in changing process of the Kyunglidan-gil, this research identified the aspect of forming cultural landscape.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Culinary science and hospitality research
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• v.10 no.3
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• pp.135-154
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• 2004

This study surveyed ancestral service preparation and sacrificial consciousness of housewives living in Pusan and Yeosu area. Statistical analysis of chi-square test was carried out by using SAS program. The results are summarized as follows. l. In major general characteristics of subjects, the forties(35.56%), Buddhism (57.79%), high school education(52.54%), a couple with children(63.45%) were the most abundant. 2. The time of sacrificial rites in both areas was usually hold from 23:00 to 01:00 (47.16%). The housewives having a job hold earlier the service than the full-time housewives(p<0.05). 3. The range of ancestor-memorial rites was usually up to 3rd generation(34.47%). The leader of sacrificial ceremony was mainly the eldest grandson by the eldest son (78.28%) in the old subjects and a person of wealth in the young subjects(p<0.05). 4. There were more positive answers for the necessity of a sacrificial ceremony (57.32%). Older than 50 years of subjects thought the sacrificial rites should be held(70.77%), while as the age of subjects was younger, they realized less necessity for that(p<0.05). Sacrificial consciousness was higher in Buddhists than the other religionists(p<0.0001). The sacrificial rites was thought to be needed for their harmonious family(50.43%). Younger subjects thought that it is necessary to succeed that as the tradition, while older housewives thought that it would contribute toward peace in their family(p<0.05). Buddhists and Christians answered that it was good for harmonious family, and Catholics and the others for tradition(p<0.01). Their consideration of sacrificial rites in the future was higher in keeping the traditional practice (37.04%) and Buddhists took higher these consideration(43.17%). Considering the sacrificial consciousness, there were statistical differences among the religionists (p<0.0001). The eldest daughter-in-raw had a different opinion about the following up the method of sacrificial ceremony from second eldest daughter-in-raw and the next one(p<0.05). The housewives in Pusan were showing more the affirmative attitudes to keep the traditional practice than those in Yeosu.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Journal of Korean Home Economics Education Association
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• v.32 no.4
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• pp.81-101
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• 2020

The purpose of this study is to develop and implement a process-based evaluation program with the theme of school space design in the housing area of the middle school home economics. In order to achieve For thispurpose, a process-based evaluation program based on the theme of school space design was developed following the ADDIE instructional design model, and the program was executed to a total of 93 students. A questionnaire survey and in-depth interview were conducted for the evaluation of the program. The results of this study are as follows. First, based on the results of a 2015-Revised Curriculum analysis, a school space design program evaluation plan was established, and two evaluation tasks were developed. Accordingly, scoring criteria were prepared and 8 evaluation materials for students and 2 evaluation materials for teachers were developed. A total of 9 sessions were developed for teaching and learning activities and evaluation-linked operation procedures to perform evaluation tasks. As a result of an expert validity test for the program, all items were verified to be appropriate in content validity and content composition with an average of 3.6 to 4 points (4 points). Second, after conducting the school space design program, a survey on students were conducted, and as a result, all three areas of school space design class, process-based evaluation, interest scored high in average scores of 4.12 to 4.27 out of 5. According to the survey and interview results, the program provided new learning opportunities for school space design, the students were able to reach the suggested achievement goals, and the self-assessment, peer evaluation and teacher feedback positively affected the students during the learning process so that they could reflect on their learning and actively participate in the subsequent learning activity. This study has a limitation in generalizability in that the program was conducted on a limited number of students, and future studies are expected to expand the scope in terms of research participants, evaluation criteria, and school space design classes. This study laid the foundation for theory and practice by developing and implementing a process-based evaluation program for home economics education, and it has contribution in that it suggested the possibility that teachers and students can take the initiatives in school space design, focusing on the housing content elements of home economics.

• Korean Journal of Culture and Social Issue
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• v.28 no.2
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• pp.187-217
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• 2022

The aim of this study is to examine the psychometric properties of the Korean version of the Post-traumatic Stress Disorder Checklist for DSM-5(PCL-5). For this purpose, online surveys were conducted for two times with a one year interval using the data from 1,077 Korean adults at time 1, and 563 Korean adults at time 2. First, from the result of the confirmatory factor analysis, comparing the model fit of the 1, 4, 6, and 7-factor model, the 4, 6, and 7-factor model showed a acceptable fit, and the best fit was seen in the order of the 7, 6, 4-factor model. Second, the internal consistency, omega coefficient, construct validity, average variance extracted, and test-retest reliability results were all satisfactory.. Third, a correlation analysis with the K-PC-PTSD-5 and the sub-factors of BSI-18 was conducted to check the validity of the Korean Version of PCL-5. As a result, a positive correlation was seen with both K-PC-PTSD-5 and BSI-18. Fourth, a hierarchical multiple regression was performed to examine whether the Korean Version of PCL-5 predicts future PTSD, depression, anxiety, and somatization. As a result, the Korean Version of PCL-5 measured at time 1 significantly predicted PTSD, depression, anxiety, and somatization symptoms at time 2. Fifth, by analyzing the ROC curve, the discriminant power of PCL-5 for screening PTSD symptom groups was confirmed, and the best cut-off score was suggested. As a result of the longitudinal validation of Korean version of PCL-5, it was found that this scale is a reliable and valid measure for Korean adults. By looking into the predictive validity of the scale, it was found that the Korean version of PCL-5 can predict not only PTSD symptoms but also PTSD-related symptoms such as depression, anxiety, and somatization. Also, this study differs from previous validation studies measuring PTSD symptoms in that it suggested a cut-off score to help differentiate PTSD symptom groups.

• Journal of Venture Innovation
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• v.3 no.1
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• pp.117-142
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• 2020

The purpose of this study is to explore the factors affecting the 6th industry experience by Schmitt experience model. The newly introduced variables are the cognitive experience, emotional experience, and social experience that are reconstructed based on Schmitt's experience theory and gender, family as a moderrating variable and trust as a mediation variable. In addition to experience intention. The hypothesis was set as follows. the experience factors that are the cognitive factor, the emotional factor, and the social factor will have a positive(+) influence on the intention to experience. Mooring factors will have a negative(-) effect on intention to experience. For statistical analysis, SPSS 24 and AMOS 23 statistical packages were used to test the research hypothesis. The research was based on 320 questionnaire data and tested by 314 valid responses were analyzed. As a result of the research, First, cognitive, emotional, and social factors had positive(+) effects on experience intention. Among the factors that directly affect the experience intention, the magnitude of influence appeared in the order of cognitive factors > social factors > emotional factors > mooring factors. Second, mooring factors have negative(-) effects on experience intention. Third, Trust has been partially influenced by factors of attraction, cognitive, emotional, and social. Fourth, there are significant statistical differences between men and women in cognitive and mooring factors in the path differences. Fifth, Social factors and mooring factors differed significantly in the composition of the household. Social factors with significant differences in path analysis have also been statistically demonstrated. The results of this study are academically verified that the cognitive, emotional, and social factors have an important influence on the experience intention in the 6th industry experience and the Schmitt's experience model proposed in this study is useful framework of analysis. In practical terms, it could provide implications for what factors should be strategically and marketingly focused to activate the 6th industry experience.