• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.546-554
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• 2018

The Bulk market, unlike the line market, is characterized by stiff competition where certain ship or freight owners have no influence on freight rates. However, freights are subject to macroeconomic variables and economic external shock which should be considered in determining management or chartering decisions. According to the results analyzed by use of ARIMA Inventiom model, the impact of the financial crisis was found to have a very strong bearing on the BDI index. First, according to the results of the VEC model, the libor rate affects the BDI index negatively (-) while exchange rate affects the BDI index by positively (+). Secondly, according to the results of the VEC model's J ohanson test, the order ship volume affects the BDI index by negatively (-) while China's economic growth rate affects the BDI index by positively (+). This shows that the shipping company has moved away from the simple carrier and responded appropriately to changes in macroeconomic variables (economic fluctuations, interest rates and exchange rates). It is believed that the shipping companies should be more aggressive in its "trading" management strategy in order to prevent any unfortunate situation such as the Hanjin Shipping incident.

• KDI Journal of Economic Policy
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• v.32 no.4
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• pp.1-34
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• 2010

We conduct a comprehensive risk analysis of household debt in Korea for the first time using the whole sample credit bureau (CB) data of 2.2 million individual debtors. After analysing debt service capacity profiles of debtor groups classified by the borrower characteristics such as income, age, occupation, credit scoring, and the type of creditor business companies, we investigate the impact of interest rate and income changes on debt service-to-income ratios (DTIs) and default rates of respective debtor groups. Empirical results indicate that debt service burdens are relatively high for low income wage earners, high income self-employed, low income capital and card loan holders, and high income mutual savings loan holders. We also find that debtors from multiple financial companies are particularly weak in their debt service capacity. The scenario analysis indicates that financial companies, with the current level of capital buffers, may be able to absorb negative consequences arising from the increase in DTIs and loan default rates if the interest rate and income changes remain modest. However, the negative consequences may fall disproportionately on non-bank financial companies such as capital, credit card, and mutual savings banks, whose debtors' DTIs are already high. We also find that the refinancing risk of household debt is relatively high in Korea as more than half of household mortgage debts are bullet loans. As the DTIs of mortgage loan holders are already high, under the current DTI regulation, mortgage loans may not be readily refinanced especially when the interest rate rises. Disruptions in mortgage loan refinancing may put downward pressure on housing prices, which may in turn magnify refinancing risk under the current loan-to-value (LTV) regulation. Overall our analysis suggests that, for more effective monitoring of household debt risk, it is necessary to combine existing surveillance schemes based on macro aggregate indicators with more comprehensive and detailed risk analyses based on micro individual data.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.51-56
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• 2015

Purpose As medical radiation exposures on patients are being social issues an interest in a relief of radiation exposures on patients is increasing. Further, there are many cases where some patients among who are getting PET/CT tests choose to get implanted with metal artifacts in their bodies. This study is to find out effects of presence or absence of metal artifacts when dose change or CT attenuation correction for the relief of radiation exposures are applied using phantoms through changes in standard uptake value (SUV). Materials and Methods GE company's Discovery 710 machine was used for PET/CT test equipments. We used NEMA IEC body phantoms. We also used screw and mesh cage made of titanium which are used in real clinical processes for the metal artifacts. Two experiments were conducted: One is to test and measure repeatedly about SUV about differences in CT attenuation corrections according to dose changes and another is to do the same procedure for SUV about the presence and absence of the metal artifacts. We injected $^{18}F-FDG$ into NEMA IEC body phantoms with a TBR ratio of 4:1 and then put the metal material into the transformation phantoms. Once a scanning for the metal artifacts was done we eliminated the metal artifacts and went on non-metal artifacts. For the each two experiments, we scanned repeatedly with CT kVp (140, 120, 100, 80) and mA (120, 80, 40, 20, 10) for an experimental condition. For PET, we reconstructed each with standard AC (STD) technique and quantitation achieved cnsistently QAC) technique among CT attenuation correction methods. We conducted a comparative analysis on measured average values and variations which were measured through repeated measure of SUV of region 1, 2, 3 spheres for each conditions of non-metal /metal scan. Results For each kVp, 120, 80, 40 (mA) of non/metal (screw, mesh cage) showed low frequency of fluctuation rates of above 2%. In 20, 10 mA above 2% of fluctuation rates appeared in high frequency. Also, when we compared the fluctuation rates of STD and QAC techniques in non/metal (screw, mesh cage) tests QAC technique showed about 1-10% of differences for each conditions compared to STD technique. In addition, metal types did not have significant effects on fluctuation rates. Conclusion We confirmed that SUV fluctuation rates for both STD and QAC techniques increase as dosage is lower. We also found that the SUV of PET data was maintained steadily in a low dosage for QAC technique when compared with STD technique. Hence, when the low dosage is used for the relief of radiation exposures on patients QAC technique may be exploited helpfully and this could be applied in the same way for patients with metal artifacts implanted in their bodies.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.38-50
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• 2020

The purpose of this study is to identify the risks to financial institutions in terms of expanding potential risks due to the deferral of exposure, by identifying the structures in which real estate finance and financial institutions affect real estate prices at low interest rates. To this end, real estate financing is categorized according to the method of financing and the type of value measurement from a risk management perspective and analyzed for each case. As a result of analysis, in the case of profitable real estate, the rate of real estate is increased by directly decreasing the cap rate and directly affecting the fair value calculation method. In the case of non-profitable real estate, the real estate price is increased by expanding the leverage width of investors or financial institutions. Through the analysis of this case, the continuous increase in real estate prices over the past 10 years has the potential to prevent financial institutions from losing under the circumstances such as the growth of real estate finance due to the advancement of the financial market and the continued low interest rate trend that has continued for 10 years. It is judged that the deferred delay is part of the cause, which leads to an increase in the risk to financial institutions.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.489-498
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• 2018

The purpose of this study is to examine whether there is a difference in the awareness of death based on happiness (since attitude or way of life differs among the general public, depending on the perception of death), and to investigate whether there is a difference in the interest in hospices between a group with a high happiness index and a group with a low happiness index. A survey was conducted on 200 men and women aged over 20 who participated in a walking event held in a metropolitan city on April 22, 2017. The survey consisted of eight demographic items: gender, age, education, occupation, marital status, family cohabitation, religion, and health status. It included 29 questions regarding happiness and nine questions regarding the perception of death. For the statistical tests, a chi-square test, an independent sample t-test, correlation analysis, and canonical correlation analysis were performed on the items of the survey based on a happiness index. The results of the study showed that, for a suitable place for death, medical institutions was the highest score (46.3%) for the group with a low happiness index, and own house was highest (59.4%) for the group with a high happiness index. This was a significant difference. It is thought that management systems should be supplemented by professional manpower, educating people so as to increase the utilization rates of home-based hospice as a way for patients to die in a comfortable and familiar place because, for Korea, death is much more common in hospitals. It is also necessary to increase the awareness of death and to make effective use of hospices through individual and various other approaches, considering the demographics of the subjects.

• Journal of The Korean Association For Science Education
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• v.40 no.4
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• pp.429-436
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• 2020

In this study, we examined students' science academic achievement through an analysis of the national assessment of educational achievement(NAEA) from 2015 to 2018 when the 2009 revised curriculum was applied. This study analyzed achievement average scores by gender and region and also analyzed the trend of the rate of achievement level in order to understand the characteristics of students' academic achievement. In addition, we analyzed the characteristics of the affective aspect using a survey of students' attitudes (confidence, interest, value, and willingness to learn) toward science. The main findings are as follows; First, the average science score shows a tendency to decrease year by year at the middle school level. Second, when analyzed by achievement level, the decline in the advanced group was large, and the rate of the below basic group increased. Third, comparisons of the average achievement scores by gender, female students' scores were generally high and the difference in achievement scores between male and female students tended to increase. Fourth, a characteristic gap was found between regional scales that increased in the advanced group. The results of a questionnaire on students' attitudes show that the four constructs of the students' attitudes had a significant correlation with the average achievement scores. In addition, the mean and positive response rates on the confidence, interest, and value of science in the above proficiency group increased but decreased in the below basic group. These results can be used as basic data for revising the curriculum, improving teaching and learning, and establishing educational policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.480-488
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• 2016

As the subprime mortgage crisis spread globally, it depressed not only the financial market, but also the construction business in Korea. In fact, according to CERIK, the BSI of the construction businesses plunged from 80 points in December 2006 to 14.6 points in November 2008, and the extent of the depression in the housing sector was particularly serious. In this respect, this paper analyzes the influence of the financial market fluctuation on the housing market before and after the Global Financial Crisis using VECM. The periods from January 2000 to December 2007 and January 2008 to October 2015, before and after the financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, when the economy is good, the Gangnam housing market is an attractive one for investment. However, when it is depressed, the Gangnam housing market changes in response to the macroeconomic fluctuations. Second, the Gangbuk and Gangnam housing markets showed different responses to fluctuations in the financial market. Third, when the economy is bad, the effect of low interest rates is limited, due to the housing market risk.