• Journal of the Society of Naval Architects of Korea
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• v.61 no.5
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• pp.297-311
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• 2024

In this study, a combined seakeeping performance evaluation method has been developed for the design purpose of the light aircraft carrier CVX of Korean Navy. A frequency domain analysis method was developed for evaluation of safe operating envelope up to sea state 6, while a time domain analysis method was developed for survival condition of sea state 7 and higher. The frequency-domain solver AdFLOW-Navy was developed by adding empirical formula of roll damping and fin-stabilizer to the existing AdFLOW by KRISO, which was based on the three-dimensional higher order boundary element method (HOBEM). For the estimation of the roll damping coefficient, a two-dimensional cross-section was automatically extracted from the three-dimensional panel, and the roll damping coefficient was analyzed for the two-dimensional cross-section. As for the time domain analysis method, KIMAPS-Navy was developed by improving and expanding the KIMAPS series developed by KRISO which is based on the impulse response function by utilizing the hydrodynamic coefficients obtained from the AdFLOW-Navy. In addition, a weakly nonlinear analysis approach was applied to analyze highly nonlinear motion under heavy sea states. Finally numeraical analysis results were compared with model tests, which showed practical usefulness of the present combined seakeeping analysis approach.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.95-110
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• 2020

Comparisons between two different surface temperatures from high-resolution ECMWF ReAnalysis 5 (ERA5) and Automated Synoptic Observing System (ASOS) observations were performed to investigate the reliability of the new reanalysis data over South Korea. As ERA5 has been recently produced and provided to the public, it will be highly used in various research fields. The analysis period in this study is limited to 1999-2018 because regularly recorded hourly data have been provided for 61 ASOS stations since 1999. Topographic characteristics of the 61 ASOS locations are classified as inland, coastal, and mountain based on Digital Elevation Model (DEM) data. The spatial distributions of whole period time-averaged temperatures for ASOS and ERA5 were similar without significant differences in their values. Scatter plots between ASOS and ERA5 for three different periods of yearlong, summer, and winter confirmed the characteristics of seasonal variability, also shown in the time-series of monthly error probability density functions (PDFs). Statistical indices NMB, RMSE, R, and IOA were adopted to quantify the temperature differences, which showed no significant differences in all indices, as R and IOA were all close to 0.99. In particular, the daily mean temperature differences based on 1-hour-averaged temperature had a smaller error than the classical daily mean temperature differences, showing a higher correlation between the two data. To check if the complex topography inside one ERA5 grid cell is related to the temperature differences, the kurtosis and skewness values of 90-m DEM PDFs in a ERA5 grid cell were compared to the one-year period amplitude among those of the power spectrum in the time-series of monthly temperature error PDFs at each station, showing positive correlations. The results account for the topographic effect as one of the largest possible drivers of the difference between ASOS and ERA5.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.25 no.4
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• pp.282-290
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• 1992

Based on surplus production models using fishery data for the last 20 years, a stock assessment was conducted for the small yellow croaker in Korean waters. The maximum sustainable yields (MSY) from the Schaefer and Fox models were estimated to be 37,000 metric tons (mt) and 33,450 mt. Zhang's model using time-series biomass with instantaneous coefficients of fishing mortality (F) and using time-series biomass and catch yielded MSY estimates of 45,328 mt and 40,160 mt, respectively. A yield-per-recruit analysis showed that the current yield per recruit of about 20g with F= 1.11 $yr^{-l}$, where the age at first capture $(t_c)$ is 0.604, was much lower than the maximum possible yield per recruit of 43g. Fixing $t_c$ at the current level and reducing fishing intensity (F) from 1.11 $yr^{-l}$ to 0.4 $yr^{-l}$ yielded only a small increase in predicted yield per recruit, from 20 to 25g. However, estimated yield per recruit increased to 43g by increasing $(t_c)$ from the current age (0.604) to age three with F fixed at the current level. This age at first capture corresponded to the optimal length which was obtained from the $F_{0.1}$ method. According to the analysis of stock recovery strategies employing the Zhang model, the optimum equilibrium biomass $(B^*_{MSY})$ which produces the maximum yield could be achieved after approximately five years at the lower fishing intensity (F=0.5).

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Korea Water Resources Association
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• v.42 no.7
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• pp.579-589
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• 2009

Hwang River in South Korea, has experienced channel adjustments due to dam construction. Hapcheon main dam and re-regulation dam. The reach below the re-regulation dam (45 km long) changed in flow regime, channel width, bed material distribution, vegetation expansion, and island formation after dam construction. The re-regulation dam dramatically reduced annual peak flow from 654.7 $m^3$/s to 126.3 $m^3$/s and trapped the annual 591 thousand $m^3$ of sediment load formerly delivered from the upper watershed since the completion of the dam in 1989. An analysis of a time series of aerial photographs taken in 1982, 1993, and 2004 showed that non-vegetated active channel width narrowed an average of 152 m (47% of 1982) and non-vegetated active channel area decreased an average of 6.6 km2 (44% of 1982) between 1982 and 2004, with most narrowing and decreasing occurring after dam construction. The effects of daily pulses of water from peak hydropower generation and sudden sluice gate operations are investigated downstream of Hapcheon Dam in South Korea. The study reach is 45 km long from the Hapcheon re-regulation Dam to the confluence with the Nakdong River. An analysis of a time series of aerial photographs taken in 1982, 1993, and 2004 showed that the non-vegetated active channel width narrowed an average of 152 m (47% reduction since 1982). The non-vegetated active channel area also decreased an average of 6.6 $km^2$ (44% reduction since 1982) between 1982 and 2004, with most changes occurring after dam construction. The average median bed material size increased from 1.07 mm in 1983 to 5.72 mm in 2003, and the bed slope of the reach decreased from 0.000943 in 1983 to 0.000847 in 2003. The riverbed vertical degradation is approximately 2.6 m for a distance of 20 km below the re-regulation dam. It is expected from the result of the unsteady sediment transport numerical model (GSTAR-1D) steady simulations that the thalweg elevation will reach a stable condition around 2020. The model also confirms the theoretical prediction that sediment transport rates from daily pulses and flood peaks are 21 % and 15 % higher than their respective averages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.188-198
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• 2016

This study examined the effects of a smoking cessation coaching program based on the motivation stage applying the Transtheoretical Model to stop the smoking of patients in terms of the amount of smoking, nicotine dependence, CO level, and urine cotinine. The study design was a multi-repeat multiple repeat intermittent time series study with one-group, a pre-post design. The participants were 47 smoking patients (44 males and 3 females), who were treated at a public hospital in N city. The participants were 4 (8.51%) subjects in the action stage and 43 subjects (91.49%) in the preparation stage of the motivation stage. The coaching program intervention was conducted at the first day, second week, and 6th week. The smoking cessation maintenance of the subjects was checked at the 12th week. A chi-square test and t-test were used to analyze the data. The subjects in the action stage were kept under the condition of no smoking and nicotine dependence. After the program of subjects in the preparation stage, the amount of smoking, nicotine dependence, and CO level were significantly lower compared to the pre-test (p<.001). The findings suggest that the coaching program based on the motivation stage was effective in improving the smoking cessation for patients who smoke. On the other hand, the patients in the smoking cessation program may require much more financial assistance than those of healthy people. A greater workforce and budget will be needed for patients to stop smoking.

• International Area Studies Review
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• v.21 no.4
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• pp.41-63
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• 2017

FDI can either be absorbed in the production cycle with domestic investment and create an inducement effect or it can remain as an exogenous factor and increase the volatility of GDP. The purpose of this paper is to research these different impacts that FDI could have. For that, the endogenous growth theory was employed. The statistic method used are the panel model for sectoral analysis, and GARCH model and VAR for time series analysis. Myanmar was selected as this paper's research subject because it is one of countries which had a colossal amount of FDI inflow recently. The panel analysis did not confirm the causality between sectoral FDI and sectoral GDP. The reason for this could be in the lack of data, since sectoral data exists yearly only during 2006-2016. Therefore this study conducted the times series analysis. According to the results, during 2006 until 2010, it showed signs of GARCH but the effect of FDI on GDP was nonexistent, which means FDI was not integrated into the domestic production cycle but stayed in residual terms. During 2011 to 2016, FDI seemed to affect the growth of Myanmar's GDP. The estimation confirmed the existence of GARCH and the Granzer causality test confirmed that FDI influenced the GARCH, which signified FDI increased the volatility of GDP. The VAR analysis showed responses of GDP to FDI was small(about 0.0007). This research assumes that FDI can be divided in two parts: one part which can be assimilated in the domestic production cycle and the other where it stays outside of the production cycle. The former creates production inducement effect and the latter only increases the volatility of GDP. According to this study, the latter outweighs the former impact in Myanmar.

• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.5-16
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• 2007

The simple linear elastic-perfectly plastic model with soil parameters $s_u,\;E_u$ and n of undrained condition is usually applied to predict the displacement of a constructed diaphragm wall(DW) on soft soils during excavation. However, the application of this soil model for finite element analysis could not interpret the continued increment of the lateral displacement of the DW for the large and deep excavation area both during the elapsed time without activity of excavation and after finishing excavation. To study the characteristic behaviors of soil behind the DW during the periods without excavation, a series of tests on soft Bangkok clay samples are simulated in the same manner as stress condition of soil elements happening behind diaphragm wall by triaxial tests. Three kinds of triaxial tests are carried out in this research: $K_0$ consolidated undrained compression($CK_0U_C$) and $K_0$ consolidated drained/undrained unloading compression with periodic decrement of horizontal pressure($CK_0DUC$ and $CK_0UUC$). The study shows that the shear strength of series $CK_0DUC$ tests is equal to the residual strength of $CK_0UC$ tests. The Young's modulus determined at each decrement step of the horizontal pressure of soil specimen on $CK_0DUC$ tests decreases with increase in the deviator stress. In addition, the slope of Critical State Line of both $CK_0UC$ and $CK_0DUC$ tests is equal. Moreover, the axial and radial strain rates of each decrement of horizontal pressure step of $CK_0DUC$ tests are established with the function of time, a slope of critical state line and a ratio of deviator and mean effective stress. This study shows that the results of the unloading compression triaxial tests can be used to predict the diaphragm wall deflection during excavation.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.65-88
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• 2008

Since the implementation of economic reforms in 1978, the Chinese economy grows rapidly at an average annul growth rate of 9% over the post two decades. Franchising has been widely recognized as an important source of entrepreneurial activity. Trust is important in that it facilitates relational exchanges by permits partners to transcend short-run inequities or risks to concentrate on long-term profits or gains. In the relationship between the franchisors and franchisees, trust has been described as an important source of competitive advantage. However, little research has been done on the factors affecting trust in Chinese franchisor-franchisee relationships. The purpose of this study is to investigate what factors affect the trust in the franchise system in China, and to provide guidelines and insights to franchisors which enter Chinese market. In this study, according to Morgan and Hunt (1994), trust is defined as the extending when one party has confidence in an exchange partner's reliability and integrity. We offered a conceptual model of the empirical study. The model shows that the factors affecting the trust include franchisor's supports, communication, satisfaction with previous outcome and conflict. We also suggested the franchisor's supports and communication like to enhance the franchisee's satisfaction with previous outcome, and the franchisor's supports, communication and he franchisee's satisfaction with previous outcome tend to decrease conflict. Before the formal study, a pretest involving exploratory interviews with owners from three franchisees was conducted to make sure the questionnaire was relevant and clear to the respondents. The data were collected using trained interviewers to carry out personal interviews with the aid of an unidentified, muti-page, structured questionnaire. The respondents comprised of owners, managers, and owner managers of franchisee-owned food service franchises located in Beijing, China. Even though a total of 256 potential franchises were initially contacted, the finally usable sample consisted of 125 respondents. As expected, the sampling method was successful in soliciting respondents with waried personal and firm characteristics. Self-administrated questionnaires were used for all measures. And established scales were used to measure the latent constructs in this study. The measures tapped the franchisees' perceptions of the relationship with the referent franchisor. Five-point Likert-type scales ranging from "strongly disagree" (=1) to "strongly agree" (=7) were used throughout the constructs (trust, eight items; support, five items; communication, four items; satisfaction, six items; conflict, three items). The reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.80. The proposed measurement model was estimated using SPSS 12.0 and AMOS 5.0 analysis package. We conducted A series of exploratory factor analyses and confirmatory factor analyses to assess the convergent validity, discriminant validity, and reliability. The results indicate reasonable overall fits between the model and the observed data. The overall fit of measurement model were $X^2$= 159.699, p=0.004, d.f. = 116, GFI =.879, NFI =.898, CFI =.969, IFI =.970, TLI =.959, RMR =.058. The results demonstrated that the data reasonably fitted the model. We also examined construct reliability and reliability and average variance extracted (AVE). The construct reliability of each construct was greater than.80 and the AVE of each construct was greater than.50. According to the analysis of Structure Equation Modeling (SEM), the results of path model indicated an adequate fit of the model: $X^2$= 142.126, p = 0.044, d.f. = 115, GFI =.892, NFI =.909, CFI =.981, IFI =.981, TLI =.974, RMR =.057. As hypothesized, the results showed that it is strategically important to establish trust in a franchise system, and the franchisor's supports, communication and satisfaction with previous outcome tend to reinforce franchisee's trust. The results also showed trust seems to decrease as the experience of conflict episodes increases. And we also noticed that franchisor's supports and communication tend to enhance the franchisee's satisfaction with previous outcome, and communication tend to decrease conflict. If the trust between the franchisor and franchisee can be established in a franchise system, franchising offers many benefits and reduces many costs. To manage a mutual trust of relationship with their franchisees, franchisor's should provide support effectively to their franchisees. Effective assistant services have direct effect on franchisees' satisfaction with previous outcome and trust in franchisor. Especially, franchise sales process, orientation, and training in the start-up period are key elements for success of the franchise system. Franchisor's support is an accumulated separate satisfaction evaluation with different kind of service provided by the franchisor. And providing support definitely can improve the trustworthy image of the franchisor. In the franchise system, conflicts of interests and exertions of different power sources are very common. The experience of conflict episodes seems to negatively relate to trust. Therefore, it is important to reduce the negative side of the relationship conflicts. Communication actually plays a broader role in reducing conflict and establish mutual trust in franchisor-franchisee relationship. And effective communication between franchisors and franchisees can improve franchisees' satisfaction toward the franchise system. As the diversification of Chinese markets, both franchisors and franchisees must keep the relevant, timely, and reliable communication. And it is very important to improve the quality of communication. Satisfaction with precious outcomes seems to positively relate to trust. Franchisors and franchisees that are highly satisfied with the previous outcomes that flow from their relationship will perceive their partner as advancing their goal achievement. Therefore, it is necessary for both franchisor and their franchisees to make the welfare of partner with effort. Little literature has focused on what factors affect the trust between franchisors and their franchisees in China. This study developed the hypotheses regarding the factors affecting trust in the transaction relationship. The results of data analysis supported the hypotheses strongly. There are certain limitations in this study. First, we may point out that some other factors missed in this study could be significantly important. Second, the context of this study, food service industry, limits its potential generalizability for all franchise systems. More studies in different categories of franchise system are needed to broaden its generalizability. Third, the model was tested empirically in a sample in Beijing, more empirical tests of the proposed model in other Chinese areas are needed. Finally, the analysis in this study was solely based on the perception of franchisees and the opinions of franchisors were not included.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.