• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.29 no.1
• /
• pp.14-27
• /
• 2024

Unlike the shelf sand ridges moribund in motion, nearshore sand ridges are highly mobile, sensitive to changes in ocean environments, thereby becoming of particular interest with respect to morphological changes. About 5 km off the Daesan port, the Jangan Sand Ridge has been undergoing severe subsea morphological change over the past two decades. Understanding the nature of sand ridges is critical to elucidate the causes of morphological changes. In this context, this study aims at understanding the characteristics and distribution patterns of surface sediments of the ridge and its vicinity. For this purpose, 227 sediment samples were acquired using a grab-sampler, the grain sizes being analysed by the sieve-pipette method. In addition, comparison of grain sizes in sediments between 1997 and 2021 was made in order to investigate the 25-years change in sediment composition. Surface sediments along the ridge axis are fine to medium sands with 2-3 phi in mean grain size, whereas, in the trough of ridge, the sediments are composed of gravels and muddy sandy gravels with mean sizes of -2 to -6 phi. Sediments in the crest of the ridge are well-sorted with normal distribution, on the other hand, the basal sediments are poorly-sorted and positively skewed. Along the ridge crest, the sediments are negatively skewed. From 1997 to 2021, the ridge sediments became largely coarser about 0.5 phi. Such coarsening trend in mean grain size can be explained either by elimination of fine sediments during high waves in winter or elimination of fines suspended during sand mining activities in the past. Spatial distribution pattern of surface sediments shows that ca. 30 m thick of the sand ridge itself overlies the thin relict gravels. The strong asymmetry of sand ridge, the exposure of ridge base, and reworked gravel lags suggest that Jangan sand ridge is probably sediment-deficit and hence erosive in nature at present.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Preventive Medicine and Public Health
• /
• v.30 no.4 s.59
• /
• pp.669-685
• /
• 1997

Previous studies, reporting the inverse relationship between osteoarthritis and osteoporosis suggest the existence of possible pathophysiologic mechanisms between them. To examinine the hypothesis that 'bone mineral densities of women with osteoarthritis are significantly higher than that of women without osteoarthritis in Korea', subjects from the health and nutritional examination survey in Kuri city were sampled. Samples were selected through multi-stage sampling frame using established clusters in Kuri city. From August 18 to September 10,1997, the survey was conducted. Among the. total number of selected sample population (1,656 people), response .ate was 52.4 percent (348 men and 519 women). 420 women who took BMD measurement, radiologic exam, and anthropometric exam were selected for the analysis. The analytic results are as follows. 1. General characteristics: Mean BMD was $0.493g/cm^2$, mean age was 43.0, mean BMI was $23.9kg/m^2$. The number of women who experienced menopause was 106, hysterectomy was 19. There were 0 case of osteoarthritis of hip, 64 cases of osteoarthritis of knee, and 2 cases of osteoarthritis of hand. 2. Univariate analysis results: Mean BMD of women with the osteoarthritis of knee was significantly lower than that of women without the osteoarthritis of knee(0.4269 vs. $0.5057g/cm^2$). But, there were too few cases of osteoarthritis of hip and hand, so comparative studies of BMD in osteoarthritis of hip and hand could not be conducted. There were significant differences of BMD among pre-menopause group(0.5204), post-menopause group(0.4206), and hysterectomy group(0.4881). Additionally, there were significant differences of BMD among diabetes group(0.4297), impaired glucose tolerance group(0.4874), and normal group(0.5057). Furthermore, age, parity, BMI, bioimpedance were significantly related with BMD. 3. Multivariate analysis results: To examinine the relationship between osteoarthritis and BMD while controlling the other variables' effects which were significant in the univariate analyses, multiple linear regression analysis was done. But, it was found that osteoarthritis of knee was not a significant variable to BMD anymore. While age and menopause had significant negative relationship with BMD. Diabetes, parity, BMI, and bioimpedance did not have significant relationships with BMD. After stratification of subjects according to menopause, multiple linear regression analyses were done to each strata. Consequently, age in post-menopause group, age and osteoarthritis of knee in hysterectomy group showed significant negative relationship with BMD. The results did not support the many results of other previous studies done with white men and women. further studies of biological plausibility to Korean women are recommended. Also it is suggested that longitudinal study to verify the relationship between osteoarthritis and BMD will be valuable.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.117-140
• /
• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.1-33
• /
• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Tuberculosis and Respiratory Diseases
• /
• v.44 no.4
• /
• pp.729-741
• /
• 1997

Background : We have recently reported that airway epithelial cells can produce RANTES and IL-8 in response to the stimulation of tubercle bacilli suggesting a certain role of airway epithelial cells in the pathogenesis of pulmonary tuberculosis. The pathogenesis of tuberculosis is determined by several factors including phagocytosis, immunological response of host, and virulence of tubercle bacilli. Interestingly, there have been reports suggesting that difference in immunological response of host according to the virulence of tubercle bacilli may be related with the pathogenesis of tuberculosis. We, therefore, studied the expressions and productions of RANTES and IL-8 in airway epithelial cells in response to tubercle bacilli(H37Rv, virulent strain and H37Ra, avirulent strain), in order to elucidate the possible pathophysiology of pulmonary tuberculosis. Methods : Peripheral blood monocytes were isolated from normal volunteers. Peripheral blood monocytes (PBM) were stimulated with LPS($10{\mu}g/ml$), H37Rv, or H37Ra($5{\times}10^5$ bacilli/well) along with normal control for 24 hours. A549 cells were stimulated with supernatants of cultured PBM for 24 hours. ELISA kit was used for the measurement of $TNF{\alpha}$ and IL-$1{\beta}$ production in supernatants of cultured PBM and for the measurement of RANTES and IL-8 in supernatants of cultured A549 cells. Northern blot analysis was used for the measurement of RANTES and IL-8 mRNA expression in cultured A549 cells. Results : $TNF{\alpha}$ and IL-$1{\beta}$ productions were increased in cultured PBM stimulated with LPS or tubercle bacilli(H37Rv or H37Ra) compared with the control. There was, however, no difference in $TNF{\alpha}$ and IL-$1{\beta}$ production between cultured PBM stimulated with H37Rv and H37Ra. RANTES and IL-8 expressions and productions were also increased in cultured A549 cells stimulated with LPS or tubercle bacilli compared with the control. RANTES and IL-8 mRNA expressions were significantly increased in cultured A549 cells stimulated with H37Ra-conditioned media(CM) compared with A549 cells stimulated with H37Rv-CM (p<0.05). However, there was no difference in RANTES and IL-8 productions between A549 cells stimulated with H37Rv-CM and H37Ra-CM. Conclusion : Airway epithelial cells can produce the potent chemokines such as RANTES and IL-8, in response to the stimulation of tubercle bacilli. These results suggest that airway epithelial cells may play a certain role in the pathogenesis of pulmonary tuberculosis. However, the role of airway epithelial cells in the pathogenesis of tuberculosis according to the virulence of tubercle bacilli was not clear in this study.