In this study, we suggest an empirical forecast of CIR (Corotating Interaction Regions) and geomagnetic storm based on the information of coronal holes (CH). For this we used CH data obtained from He I $10830{\AA}$ maps at National Solar Observatory-Kitt Peak from January 1996 to November 2003 and the CIR and storm data that Choi et al. (2009) identified. Considering the relationship among coronal holes, CIRs, and geomagnetic storms (Choi et al. 2009), we propose the criteria for geoeffective coronal holes; the center of CH is located between $N40^{\circ}$ and $S40^{\circ}$ and between $E40^{\circ}$ and $W20^{\circ}$, and its area in percentage of solar hemispheric area is larger than the following areas: (1) case 1: 0.36%, (2) case 2: 0.66%, (3) case 3: 0.36% for 1996-2000, and 0.66% for 2001-2003. Then we present contingency tables between prediction and observation for three cases and their dependence on solar cycle phase. From the contingency tables, we determined several statistical parameters for forecast evaluation such as PODy (the probability of detection yes), FAR (the false alarm ratio), Bias (the ratio of "yes" predictions to "yes" observations) and CSI (critical success index). Considering the importance of PODy and CSI, we found that the best criterion is case 3; CH-CIR: PODy=0.77, FAR=0.66, Bias=2.28, CSI=0.30. CH-storm: PODy=0.81, FAR=0.84, Bias=5.00, CSI=0.16. It is also found that the parameters after the solar maximum are much better than those before the solar maximum. Our results show that the forecasting of CIR based on coronal hole information is meaningful but the forecast of goemagnetic storm is challenging.
The Journal of Korean Institute of Electromagnetic Engineering and Science
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v.11
no.5
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pp.813-821
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2000
The engineering of satellite communication systems at frequencies above 10GHz requires a method for estimating rain-caused outage probabilities on the earth-satellite path. A procedure for predicting a rain attenuation distribution from a point rainfall rate distribution is, therefore, needed. In order to predict rain attenuation on the satellite link, several prediction models such as ITU-R, Global, SAM, DAH model, have been developed and used at a particular propagation condition, they may not be appropriate to a propagation condition in Korean territory. In this paper, a new rain attenuation prediction method appropriate to a propagation condition in Korea is introduced. Based on the results from ETRI measurements, a new method has been derived for an empirical approach with an identification on the horizontal correction factor as in current ITU-R method, and the vertical correction factor has been suggested with decreasing power law as a function of rainfall rate. This proposed model uses the entire rainfall rate distribution as input to the model, while the ITU-R and DAH model approaches only use a single 0.01% annual rainfall rate and assume that the attenuation at other probability levels can be determined from that single point distribution. This new model was compared with several world-wide prediction models. Based on the analysis, we can easily know the importance of the model choice to predict rain attenuation for a particular location in the radio communication system design.
Journal of the Korea Institute of Information Security & Cryptology
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v.26
no.6
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pp.1619-1637
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2016
With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.
Journal of the Korean Institute of Landscape Architecture
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v.45
no.2
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pp.76-88
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2017
The urban park plays important roles in protecting the urban landscape and improving citizens' health, recreation, and the emotional life. Above and beyond these roles, the urban park is expected to rearrange urban spatial structures as a kind of urban system. The purpose of this paper is to identify empirically to change urban spatial structures by construction of the urban park. This study regards gentrification around the urban park as a process to change urban spatial structures. The gentrification means the regeneration and upgrading of deteriorated urban property by the middle class or commercial developers. The site of case analysis is the Seoul Forestry Park in Sungdong-gu, Seoul. The Seoul Forestry Park is regarded as a representative urban park of Seoul, and caused gentrification around park after the 2005 opening. This study operationally defines the gentrification index and the accessibility index from an urban park and offers an empirical analysis of relation among the urban park, the gentrification and urban spatial structure in a statistic district which is the minimum unit of Korean statistic data in 2000, 2005, and 2010, using Difference-in-Difference method and linear probability model. The results of this empirical study show that the Seoul Forestry Park changes urban spatial structures by gentrification. It reverses a trend of migration of gentrifiers before and after construction of the Seoul Forestry Park. It suggests urban park construction as an alternative method for urban regeneration by inducing the middle class into the inner city of Seoul.
Technology innovation activity plays a pivotal role in constructing the entrance barrier for other firms and making process improvement and new product. and these activities give a profit increase and growth to firms. Thus, technology innovation activity can reduce the default risk of firms. However, technology innovation activity can also increase the firm's default risk because technology innovation activity requires too much investment of the firm's resources and has the uncertainty on success. The purpose of this study is to examine the effect of technology innovation activity on the default risk of firms. This study's sample consists of manufacturing firms listed on the Korea Securities Market and The Kosdaq Market from January 1,2000 to December 31, 2008. This study makes use of R&D intensity as an proxy variable of technology innovation activity. The default probability which proxies the default risk of firms is measured by the Merton's(l974) debt pricing model. The main empirical results are as follows. First, from the empirical results, it is found that technology innovation activity has a negative and significant effect on the default risk of firms independent of the Korea Securities Market and Kosdaq Market. In other words, technology innovation activity reduces the default risk of firms. Second, technology innovation activity reduces the default risk of firms independent of firm size, firm age, and credit score. Third, the results of robust analysis also show that technology innovation activity is the important factor which decreases the default risk of firms. These results imply that a manager must show continuous interest and investment in technology innovation activity of one's firm. And a policymaker also need design an economic policy to promote the technology innovation activity of firms.
KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.
This study examines the hazard rate of reemployment by conducting the Cox regression analysis. In addition, two gender groups are subjected to comparative analysis to identify the effect of the factors related to the human capital and human capability perspective on reemployment. For this purpose, 1,871 cases are selected from the 5th year data from Korea Labor and Income Panel Study. The results of study are as follows. First, the factors of human capital, such as education, appropriateness of skill level, and job tenure hold negative impact on the probability of reemployment, while factors of human capability, such as basic learning ability, health insurance, social insurance, residential area(living in the Seoul metropolitan area) hold positive on the probability of reemployment. It is interesting note that there are different sets of factors that affect the probability of reemployment in the two gender groups. This trend is even more apparent in the case of factors that pertain to human capability. The results of this study imply that the factors of human capability, which stress the socio-institutional characteristics, should be considered as comparably significant compared to the factors that pertain to human capital when it comes to the estimation of reemployment. Also, results of this comparative study teach us that various perspectives, such as dual labor market theory and gender-segmented labor market theory, should be factored in for reemployment discussion as well. In conclusion, this research delivers several significant messages since it introduces the concept of human capability perspective, subjected to few empirical analyses in the past, and also heralds the way for comparative analysis on the impact of the factors pertaining to human capability on reemployment.
The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.
KSCE Journal of Civil and Environmental Engineering Research
/
v.32
no.4D
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pp.345-356
/
2012
Road pavement requires repetitive maintenance works to maintain satisfactory service level to the public. However, the repetitive maintenance works upon deteriorated pavement structure make negative effects to deterioration speed. It often leads to inefficient use of limited budget. For that reason, the pavements require reconstruction work to recover their original performance. Recently, construction demands in the Korean national highway have already been reached to maximum level, and the aged pavements start to demand much more reconstruction works. However, in the real world, road agencies have often been confused when they determine maintenance design for such aged road sections due to budget constraint. It is because there is no reliable long-term maintenance strategy that supports their decision making. To support their decision making, this paper aimed to suggest the best maintenance strategy considering changing process of pavement performance by repetitive maintenance works. As an analysis method, probability distribution and hazard function to estimate the life expectancy were adopted, and then the results were used for long-term life cycle cost analysis with deterministic or Monte-Carlo method under various scenarios. As an empirical study, the Korean national highway data that has long-maintenance history data since 1986 has been applied. Last, this paper considered quality assurance of maintenance work to improve maintenance quality. These could be important information as a part of long-term maintenance strategy of pavement.
In this paper, we study empirically the dividend initiation decisions of IPO firms listed on Korea Securities Market and KOSDAQ Market. Specifically, we study three aspects of dividend initiation decision, (a) dividend initiation decision, (b) dividend level decision, (c) time-to-initiation decision. The main results of this study can be summarized as follows. First, determinants suggested by the major theories of dividends, namely, residual dividend, dividend signaling, agency, catering, and transactions cost theory explain significantly the dividend initiation decision. Second, determinants suggested by the major theories of dividends explain significantly the dividend level decision. So to speak, most of the findings for dividend initiation decision also hold for the dividend level decision. Third, most of the factors that increase(decrease) the probability of dividend initiation reduce(increase) the time-to-initiation. Almost of the dividend initiation firms start paying dividends within two years of the IPO. Thus, if IPO firm does not initiate dividend early in the life of the firm, then it is highly likely that it will never initiate dividend.
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