• The Korean Journal of Financial Management
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• v.25 no.3
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• pp.111-130
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• 2008

This paper compares long term equilibrium relation of KOSPI 200 which is underling stock and its futures by using general method fractional cointegration instead of existing integer cointegration. Existence of integer cointegration between two price time series gives much wider information about long term equilibrium relation. These details grasp long term equilibrium relation of two price time series as well as reverting velocity to equilibrium by observing difference coefficient of error term when it renounces from equilibrium relation. The result of this study reveals existence of long term equilibrium relation between KOSPI200 and futures which follow fractional cointegration. Difference coefficient, d, of 'two price time series error term' satisfies 0 < d < 1/2 beside bandwidth parameter, m(173). It means two price time series follow stationary long memory process. This also means impulse effects to balance price of two price time series decrease gently within hyperbolic rate decay. It indicates reverting speed of error term is very low when it bolts from equilibrium. It implies to market maker, who is willing to make excess return with arbitrage trading and hedging risk using underling stock, how invest strategy should be changed. It also insinuates that information transition between KOSPI 200 Index market and futures market does not working efficiently.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.133-146
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• 2015

This study is to investigate the causal relationship between exchange hedge and the net income of the shipbuilder through the unit root test and co-integration and vector autoregressive model(Vector Autoregressive Model: VAR). First, quarter net income of shipbuilders to order a unit root tests from 2000 to 2013 was used as a value after the Johnson transformation. In the same period, the return on bond futures(KTBF), three years bond yield(KTB3Y), America-Korea exchange differences are weekly data for each quarterly difference in value was converted by utilization, shipbuilding shares after log transformation which it was used. Also, structural change point investigation analysis to verify that looked to take advantage of the structural changes occur in the exchange hedge strategies affecting net income in the shipbuilding industry. Between the exchange hedge and net income of shipbuilders in structural change points detection and analysis showed that structural changes occur starting in 2004. In other words, strategy of shipbuilders about exchange hedge has occurred from "passive exchange hedge" to "active exchange hedge". The exchange hedge of the Korea shipbuilders through the estimation of the VAR was able to grasp that affect the profitability of mutual shipbuilders. Macroeconomic variables and stock prices could also check to see that affected the net income of the shipbuilding industry.

• Tuberculosis and Respiratory Diseases
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• v.60 no.1
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• pp.65-71
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• 2006

Background : Hemoptysis, when massive and untreated, has a mortality rate of over 50 percents, is considered as one of most dreaded of all respiratory emergencies and can have a variety of underlying causes. Bronchial artery embolization (BAE) has become an established procedure in the management of massive and recurrent hemoptysis, and its efficacy is widely documented thereafter by number of articles. However, the long-term success rate of BAE is known to be unfavorable. Risk factors influencing that control failure are inevitably needed. Materials and methods : Seventy-five patients underwent bronchial artery embolization due to massive hemoptysis in Severance Hospital from Jan. 2000 to Jan. 2005. Nine patients' data were not available and could not be contacted with. Finally 66 patients' (48 males, 18 females) medical records were analyzed retrospectively during a mean follow up period of 20.4 months (ranging from 1 month to 54 months). Results : Among 66 patients whose data were available, 23(34.9%) patients had recurrent major hemoptysis. Patients' age, sex, underlying disease, previous intervention history, and number of feeding vessels had no statistical validity as risk factors of recurred major hemoptysis. But bilaterality of lesion, amount of hemoptysis, and pleural thickening were revealed as meaningful factors for predicting relapse (p = 0.008, 0.018, and 0.001, respectively). Conclusion : According to our series, patients presenting with larger amount of hemoptysis, pleural thickening of chest radiography and bilateral lesion are associated with increased risk of major hemoptysis in patients treated with BAE.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1465-1475
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• 2016

In order to secure safe meals, the hazards of microorganisms associated with food poisoning accident should be monitored and controlled in real situations. It is necessary to determined the correlation between existing common bacteria number (aerobic plate count; APC) and RLU (relative light unit) in cookware. In this paper, we investigate the correlation between ATP (RUL) and APC (CFU) by using three types of transform (inverse, square root, log transforms) of raw data in two steps. Among these transforms, the log transform at the first step has been found to be optimal for the data of cutting board, knife, soup bowl (stainless), and tray (carbon). The square root-inverse and the square root-square root transform at the second step have been shown to be optimal respectively for the cup and for the soup bowl (carbon) data.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.155-164
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• 2012

This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function R. To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function R for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function R. Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted $R^2$ and the correlation of all variables against the values of the rating function R.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.7-17
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• 2006

The purpose or this paper is to investigate the relationship between highway improvement and Induced Travel Demand(ITD) focusing on the Seoul metropolitan area data. In addition, authors tried to estimate basic unit of demand elasticity focusing on zone and trip purpose which can be applied for the ITD forecasting. The results are based on the 2002 Metropolitan Household Transportation Survey Data, where the demand elasticity (DE) is -0.582 in Seoul, -0.597 in Incheon and -0.559 in Gyounggi province, respectively. This study revealed part of the relationship between highway improvement and ITD for metropolitan region and provided the framework for yielding real estimated values by applying the concept of demand elasticity in terms of the relationship by using regional and long-term data. We expect that the basic unit of demand elasticity focusing on zone and trip purpose can be applied for the ITD forecasting to analyze the whole demand exactly The estimated DE's for age group and day of week can also be used for Proper transportation management and transport Policy making. Some limitations have also been discussed.

• Journal of the Korean Geotechnical Society
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• v.35 no.6
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• pp.17-26
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• 2019

In this study, the statistical characteristics of the resistance bias factors were analyzed using a high-quality field load test database, and the total resistance bias factors were estimated considering the soil uncertainty and construction errors for the application of the limit state design of aggregate pier foundation. The MLR model by Bong and Kim (2017), which has a higher prediction performance than the previous models was used for estimating the resistance bias factors, and its suitability was evaluated. The chi-square goodness of fit test was performed to estimate the probability distribution of the resistance bias factors, and the normal distribution was found to be most suitable. The total variability in the nominal resistance was estimated including the uncertainty of undrained shear strength and construction errors that can occur during the aggregate pier construction. Finally, the probability distribution of the total resistance bias factors is shown to follow a log-normal distribution. The parameters of the probability distribution according to the coefficient of variation of total resistance bias factors were estimated by Monte Carlo simulation, and their regression equations were proposed for simple application.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.14-30
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• 2007

The purpose of this study was to evaluate trophic conditions of various Korean reservoirs using Trophic State Index (TSI) and predict the reservoir conditions by empirical models. The water quality dataset (2000, 2001) used here were obtained from the Ministry of Environment, Korea. The water quality, based on multi-parameters of dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), suspended solid (SS), Secchi depth (SD), chlorophyll-${\alpha}$ (CHL), and conductivity largely varied depending on the sampling watersheds and seasons. In general, trophic conditions declined along the longitudinal axis of headwater-to-the dam and the largest seasonal variations occurred during the summer monsoon of July-August. Major inputs of TP occurred during the monsoon (r=0.656, p=0.002) and this pattern was similar to solid dynamics of SS (r=0.678, p<0.001). Trophic parameters including CHL, TP, SD, and TN were employed to evaluate how the water systems varies with season. Trophic State Index (TSI, Carlson, 1977), based on TSI (CHL), TSI (TP), and TSI (SD), ranged from mesotrophic to eutrophic. However, the trophic state, based on TSI (TN), indicated eutrophic-hypereutrophic conditions in the entire reservoirs, regardless of the seasons, indicating a N-rich system. Overall, nutrient data showed that phosphorus was a primary factor regulating the trophic state. The relationships between CHL (eutrophication index) vs. trophic parameters (TN, TP, and SD) were analysed to develop empirical models which can predict the trophic status. Regression analyses of log-transformed seasonal CHL against TP showed that the value of $R^2$ was 0.31 (p=0.017) in the premonsoon but was 0.69 (p<0.001) during the postmonsoon, indicating a greater algal response to the phosphorus during the postmonsoon. In contrast, SD had reverse relation with TP, CHL during all season. TN had weak relations with CHL during all seasons. Overall, data suggest that TP seems to be a good predictor for algal biomass, estimated by CHL, as shown in the empirical models.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.630-642
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• 1997

The purpose of this study was to examine the mortality risk associated with cognitive impairment among the rural elderly. The subjective of study was 558 of 'A Study on the Depression and Cognitive Impairment in the Rural Elderly' of Jung Ae Rhee and Hyang Gyun Jung's study(1993). Cognitive impairment and other social and health factors were assessed in 558 elderly rural community residents. For this study, a Korean version of the Mini-Mental State Examination(MMSEK) was used as a global indicator of cognitive functioning. And mortality risk factors for each cognitive impairment subgroup were identified by univariate and multivariate Cox regression analysis. At baseline 22.6% of the sample were mildly impaired and 14.2% were severely impaired. As the age increased, the cognitive function was more impaired. Sexual difference was existed in the cognitive function level. Also the variables such as smoking habits, physical disorders had the significant relationship with cognitive function impairment. Across a 3-year observation period the mortality rate was 8.5% for the cognitively unimpaired, 11.1% for the mildly impaired, and 16.5% for the severly impaired respendents. And the survival probability was .92 for the cognitively unimpaired, .90 for the mildly impaired, and .86 for the severly impaired respondents. Compared to survival curve for the cognitively unimpaired group, each survival curve for the mildly and the severely impaired group was not significantly different. When adjustments models were not made for the effects of other health and social covariates, each hazard ratio of death of mildly and severely impaired persons was not significantly different as compared with the cognitively unimpaired. But, as MMSEK score increased, significantly hazard ratio of death decreased. Employing Cox univariate proportional hazards model, statistically other significant variables were age, monthly income, smoking habits, physical disorders. Also when adjustments were made for the effects of other health and social covariates, there was no difference in hazard ratio of death between those with severe or mild impairment and unimpaired persons. And as MMSEK score increased, significantly hazard ratio of death did not decrease. Employing Cox multivariate proportional hazards model, statistically other significant variables were age, monthly income, physical disorders. Employing Cox multivariate proportional hazards model by sex, at men and women statistically significant variable was only age. For both men and women, also cognitive impairment was not a significant risk factor. Other investigators have found that cognitive impairment is a significant predictor of mortality. But we didn't find that it is a significant predictor of mortality. Even though the conclusions of our study were not related to cognitive impairment and mortality, early detection of impaired cognition and attention to associated health problems could improve the quality of life of these older adults and perhaps extend their survival.