• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.199-205
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• 2020

As many government policies have been announced today regarding real estate, especially housing, interest in prices in the housing market has increased significantly. In this study, I would like to present the direction of government policies by analyzing the relationship among income instability, the psychological condition of real estate price changes and willingness to adjust real estate holding ratio. First, major variables were extracted through the prior study review, and using a survey, data were collected and path analysis was conducted. According to the analysis, the current income instability had a negative impact on the psychological condition of real estate price changes, and a positive influence on the willingness to adjust real estate holding ratio, but the psychological condition of real estate price changes did not have a statistically significant impact on the willingness to adjust real estate holding ratio. Thus, the difference analysis was conducted between groups by dividing the ages and the number of dependents respectively. According to the analysis, the impact of income instability and psychological condition of real estate price changes on willingness to adjust real estate holding ratio differed between groups divided by ages and number of dependents. The results of this analysis will help the government to establish real estate policies and help each household to use the analysis as basic data when they make a decision about real estate. On the other hand, this study has limitations that have only been conducted cross-sectional analysis and analyzing time series changes and differences in perception between regions are going to be conducted in a future study.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.469-479
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• 2021

As a material for preventing spalling of concrete, the effectiveness of PP fiber has already been confirmed. However, it is necessary to consider the maximum temperature that occurs during a fire, and to solve the mixing problem and the strength reduction problem that occur depending on the mixing amount. In this study, the fire resistance performance of tunnel segment linings according to the PP fiber content and air volume under the RABT fire scenario was investigated. As a result, no spalling or cross-sectional loss occurred in all test specimens, and when the PP fiber content was small, the maximum temperature was relatively high and the maximum temperature arrival time was also fast. On the other hand, no trend was found for the maximum temperature and arrival time according to the difference in air volume. In the internal temperature distribution results for the PP fiber mixing amount of 0.75, 1.0, 1.5, and 2.0 kg/m³, the results of 0.75 and 1.0 kg/m³ showed similar temperature distribution, and the results of 1.5 and 2.0 kg/m³ were similar. It was confirmed that the internal temperature distribution tends to decrease at the same depth when the amount of PP fiber mixed is large, and it was confirmed that a remarkable difference occurred from the results of 1.0 kg/m³ and 1.5 kg/m³ of PP fiber mixed amounts.

• Korean journal of aerospace and environmental medicine
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• v.31 no.1
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• pp.24-30
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• 2021

Purpose: The purpose of this study is to consider ways to strengthen it through comparison and curriculum while recognizing the importance of global competencies in liberal arts education in universities. Methods: In order to explore ways to reinforce the sub-competence of global competencies, this study was conducted at a four-year university in Chungcheong-do for one year in 2019, such as 'Global Culture Talk', 'Global Travel', 'Global Nanta', and 'Making Global Friends'. Cases of comparison and application of educational programs were analyzed. The program was attended by the Department of Business Administration, Department of Aviation Service, Department of Design, Department of Manga Animation, Department of Broadcasting and Film, and foreign exchange students. The competency-centered curriculum not only has clear educational goals, but is also very advantageous in establishing a feedback system by measuring its performance. This study will assess the effectiveness of the education plan by diagnosing the change in competencies before and after the comparison and curriculum is operated. Results: The overall global competency has increased by 0.2 points compared to 2017. By subsector, it was found that the flexibility increased by 1.4 points. In the field of cross-cultural understanding, it rose 0.6 points, and in the field of global understanding, it rose 2.2 points, showing the largest increase in the sub-fields. Nevertheless, the field of global interest remains at a low level. This is considerably low compared to flexibility and ability to understand other cultures, and it is expected that measures for improvement should be continuously sought. Since the understanding of other cultures has already exceeded 60 points, it is expected that the global competency of the university will be strengthened if the level is consistently maintained and the emphasis is placed on enhancing flexibility and improving global understanding. Conclusion: The importance of strengthening global capabilities is steadily rising. Universities are also reorganizing the curriculum by analyzing the needs and satisfaction of education consumers to respond to this. The programs operated and analyzed in this study were also made as part of this effort. However, since there are various factors that affect global competency, it cannot be but admitted that it is not easy to gauge the change in competency with only a few programs and short-term efforts. However, if the efforts pursued by this study are accumulated and supplemented through feedback from a long-term perspective, it can be expected that there are not a lot of contributions to strengthening global competencies in liberal arts education.

• Korea Trade Review
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• v.43 no.2
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• pp.159-180
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• 2018

The purpose of this study is to contribute to the efficient selection of SMEs' trade settlement system through the empirical analysis of determinants of the payment method of SMEs in Korea. In the previous study, external factors, internal factors, settlement characteristics, transaction goods, transaction amount factors and risk management factors were used. Questionnaires were excluded from analysis, and the number of validated samples collected was 155. To conduct the study, all empirical analyses were verified at the significance level p <.005. Statistical analysis was performed using the SPSSWIN 18.0 program. Analysis results found the payment method used in the company was based on the year of establishment, export items, transaction area, type of transaction, and size of company. Empirical analysis showed that factors influencing the choice of the letter of credit are external factors, internal factors, the risk management factors, and the transaction amounts, etc. Results of this study are as follows: First, the effects of external factors, internal factors, settlement characteristics, and transaction amounts were significant. Hypothesis testing of collections trading methods has not been adopted in all areas presented. In order to utilize the research results, we conducted the study and comparison of the payment method of the income.

• Journal of Korea Trade
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• v.27 no.1
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• pp.139-158
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• 2023

Purpose - The study of co-movements between stock markets is a crucial area of finance and has recently received much interest in a variety of studies, especially in international finance. Stock market co-movements are a major phenomenon in financial markets, but they are not necessarily independent of the real market. Several studies support the idea that bilateral trade linkages significantly impact stock market correlations. Motivated by this perspective, this study investigates whether real market integration due to trade agreements brings about financial market integration in terms of stock market co-movement. Design/methodology - Over the 10 free trade agreements (FTAs) signed by the United States, using a dynamic conditional correlations (DCC) multivariate GARCH (MGRACH) model, we empirically measure the degree of integration by finding DCCs between the US market and the partner country's market. We then track how these correlations evolve over time and compare the results before and after trade agreements. Findings - According to the empirical results, there are positive return spillover effects from the US market to eight counterpart equity markets, except Jordan, Morocco, and Singapore. Especially Mexico, Canada, and Chile have large return spillover effects at the 1% significance level. All partner countries of FTAs generally have positive correlations with the US over the entire period, but the size and variance are somewhat different by country. Meanwhile, not all countries that signed trade agreements with the United States showed the same pattern of stock market co-movement after the agreement. Korea, Mexico, Chile, Colombia, Peru, and Singapore show increasing DCC patterns after trade agreements with the US. However, Canada, Australia, Bahrain, Jordan, and Morocco do not show different patterns before and after trade agreements in DCCs. These countries generally have the characteristic of relatively lower or higher co-movements in stock markets with the US before the signing of the FTAs. Originality/value - To our knowledge, few studies have directly examined the linkages between trade agreements and stock markets. Our approach is novel as it considers the problem of conditional heteroscedasticity and visualizes the change of correlations with time variations. Moreover, analyzing several trade agreements based on the United States enables the results of cross-country pairs to be compared. Hence, this study provides information on the degree of stock market integration with countries with which the United States has trade agreements, while simultaneously allowing us to track whether there have been changes in stock market integration patterns before and after trade agreements.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.121-131
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• 2023

The Chinese three northeastern three provinces - Heilongjiang, Liaoning, and Jilin - hold significant geographical, geopolitical, and commercial importance due to their location allowing for cross-border trade and transportation with North Korea. These provinces are crucial for establishing a complex Eurasian logistics network in line with South Korea's new northern policy. The Chinese three northeastern three provinces, as this region is known, boasts excellent maritime transportation links between South Korea, China, and North Korea, making it an logistics hub for transporting goods to Eurasia and Europe through multimodal transport. This study highlights the importance of securing a logistics hub area by fostering cooperation and friendly relations with China's three northeastern three provinces, which are crucial to the success of the New Northern Policy. In particular, the study aims to analyze current status of trade with these region and freight volume transported by ships and recommend political advice for securing logistics hub and revitalizing maritime transport. As the policy suggestion, this study is to establish a logistics hub by implementing joint port operations, constructing port infrastructure jointly, and operating shipping companies together. Additionally, we propose ways to revitalize the maritime passenger transport business between Korea and China, which involves expanding cultural exchanges and developing content.

• 한국노년학
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• v.29 no.1
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• pp.195-213
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• 2009

The purpose of this study is to analyse how consumption value affects the loyalty of green product through satisfaction and trust among elderly consumers. Data were collected from a cross-sectional survey of 314 older adults (age≥60) in the U. S., who bought and possessed a hybrid car, a representative green product. The statistical methodology is employed a structural equation model. The results demonstrated several important findings. First, perceived social value among elderly population had significant effects on green product satisfaction, while hedonic value did not. Second, both perceived functional value and environment friendly value had a significant positive effect on trust in green products. Third, satisfaction with green products also led to trust in green products. Finally, trust in green products showed their significant effects on loyalty in green product. These results provide practical implications to improve the trust and loyalty in green products among the elderly consumers. Furthermore, by deriving major components of consumption values in green products among the elderly, and analyzing the mechanism of satisfaction, trust, and loyalty, the study emphasizes relationship marketing in implementing "green" marketing strategies.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.39.1-39.14
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• 2023

Background: Diseases affecting the lungs and airways contribute significantly to the global burden of disease. The problem in low- and middle-income countries appears to be exacerbated by a shift in global manufacturing base to these countries and inadequate enforcement of environmental and safety standards. In Ghana, the potential adverse effects on respiratory function associated with occupational wood dust exposure have not been thoroughly investigated. Methods: Sixty-four male sawmill workers and 64 non-woodworkers participated in this study. The concentration of wood dust exposure, prevalence and likelihood of association of respiratory symptoms with wood dust exposure and changes in pulmonary function test (PFT) parameters in association with wood dust exposure were determined from dust concentration measurements, symptoms questionnaire and lung function test parameters. Results: Sawmill workers were exposed to inhalable dust concentration of 3.09 ± 0.04 mg/m³ but did not use respirators and engaged in personal grooming habits that are known to increase dust inhalation. The sawmill operators also showed higher prevalence and likelihoods of association with respiratory symptoms, a significant cross-shift decline in some PFT parameters and a shift towards a restrictive pattern of lung dysfunction by end of daily shift. The before-shift PFT parameters of woodworkers were comparable to those of non-woodworkers, indicating a lack of chronic effects of wood dust exposure. Conclusions: Wood dust exposure at the study site was associated with acute respiratory symptoms and acute changes in some PFT parameters. This calls for institution and enforcement of workplace and environmental safety policies to minimise exposure at sawmill operating sites, and ultimately, decrease the burden of respiratory diseases.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.729-736
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• 2024

In connection with the OECD's core competency proposal, we would like to consider an attempt to realize this in liberal arts education at Korean universities and examine what kind of education plan it is desirable to present to learners. Universities are expanding competency-based education into human and social fields by reconsidering new talent awards and the direction of education. In this way, each university selects and organizes core competencies and incorporates the core competencies that the university pursues into educational goals. Under the supervision of the Ministry of Education, education centered on core competencies is exploring its potential in liberal arts courses at universities above all else. We want to explore a methodology that can achieve learner-centered teaching and learning effects in the process of incorporating and accepting this. Language acquisition along with cross-cultural understanding is above all else a part that can promote learners' competencies in terms of diversity and mutual understanding. Therefore, we reflect this in French liberal arts education and explore teaching and learning processes by incorporating respect for diversity and mutual cultural understanding competency education related to learners' motivation into lectures. We aim to supplement this through collaboration and mutual cultural understanding processes as presentation tasks in order to overcome the existing competency-based evaluation while deriving acceptance results from learners. Therefore, they recognize that the direction of core competency education naturally shifts to value-centered education.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.