• Journal of the Korean GEO-environmental Society
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• v.21 no.4
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• pp.5-17
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• 2020

In recent years, the frequency of heavy rainfall associated with high rainfall intensity has been continuously increasing due to the effects of climate change; and thus also causes an increase in watershed soil erosion. The existing estimation techniques, used for the prediction of soil erosion in Korea have limitations in predicting the: average soil erosion in watersheds, and the soil erosion associated with abnormal short-term rainfall events. Therefore, it is necessary to consider the characteristics of torrential rainfall, and utilize physics-based model to accurately determine the soil erosion characteristics of a watershed. In this study, the rainfall kinetic energy equation, in the form of power function, is proposed by applying the probability density function, to analyze the rainfall particle distribution. The distributed rainfall-erosion model, which utilizes the proposed rainfall kinetic energy equation, was utilized in this study to determine the soil erosion associated with various typhoon events that occurred at Cheoncheon watershed. As a result, the model efficiency parameters of the model for NSE and RMSE are 0.036 and 4.995 ppm, respectively. Therefore, the suggested soil erosion model, coupled with the proposed rainfall-energy estimation, shows accurate results in predicting soil erosion in a watershed due to short-term rainfall events.

• Management & Information Systems Review
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• v.37 no.2
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• pp.87-108
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• 2018

This article explores the international trade flow of Bangladesh's ready-made garments (RMG). We first suggest the brief history and an international structure of trade among countries by using the trade volume. Then we implemented a gravity model regression with the sample of 38 major partner countries in order to investigate the potential export market for the RMG industry. The fixed effect and random effect model for the panel data during the period of 1990 to 2011 are estimated. Our result shows that Bangladesh's RMG exports are affected positively by the size of economy, inflation, exchange rate, foreign direct investment(FDI) and trade openness. On the other hand, the distance between trading partners are related negatively with the trade volume. We used the estimated coefficients from the panel regression in order to predict RMG export potential of Bangladesh. This might show which country is the promising export market for Bangladesh RMG industry. We found that Bangladesh has the highest potential of RMG export with Japan and USA, which seem to have considerable room for export growth if trade barriers and constraints are removed. We added some policy implications for encouraging the RMG export of Bangladesh by using the results from the analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.89-98
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• 2005

Fingerprint segmentation and ridge orientation estimation algorithms with images from a mobile camera are proposed. The fingerprint images from a mobile camera are quite different from those from conventional sensor, called touch based sensor such as optical, capacitive, and thermal. For example, the images from a mobile camera are colored and the backgrounds or non-finger regions are very erratic depending on how the image capture time and place. Also the contrast between ridge and valley of a mobile camera image are lower than that of touch based sensor image. To segment fingerprint region, we first detect the initial region using color information and texture information. The LUT (Look Up Table) is used to model the color distribution of fingerprint images using manually segmented images and frequency information is extracted to discriminate between in focused fingerprint regions and out of focused background regions. With the detected initial region, the region growing algerian is executed to segment final fingerprint region. In fingerprint orientation estimation, the problem of gradient based method is very sensitive to outlier that occurred by scar and camera noise. To solve this problem, we propose a robust regression method that removes the outlier iteratively and effectively. In the experiments, we evaluated the result of the proposed fingerprint segmentation algerian using 600 manually segmented images and compared the orientation algorithms in terms of recognition accuracy.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.745-758
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• 2017

The copula-based models have been successfully applied to hydrological modeling including drought frequency analysis and time series modeling. However, uncertainty estimation associated with the parameters of these model is not often properly addressed. In these context, the main purposes of this study are to develop the Bayesian inference scheme for bivariate copula functions. The main applications considered are two-fold: First, this study developed and tested an approach to copula model parameter estimation within a Bayesian framework for drought frequency analysis. The proposed modeling scheme was shown to correctly estimate model parameters and detect the underlying dependence structure of the assumed copula functions in the synthetic dataset. The model was then used to estimate the joint return period of the recent 2013~2015 drought events in the Han River watershed. The joint return period of the drought duration and drought severity was above 100 years for many of stations. The results obtained in the validation process showed that the proposed model could effectively reproduce the underlying distribution of observed extreme rainfalls as well as explicitly account for parameter uncertainty in the bivariate drought frequency analysis.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.109-121
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• 2024

This paper adopts a resource-based approach to analyze why some universities have a greater number of faculty startups, and how this impacts on performance, in terms of indictors such as the number of employees and revenue sales. More specifically, we propose 9 hypotheses which link institutional resources to faculty startups and their performance, and compare 5 different groups of university resources for cross-college variation, using data from 134 South Korean four-year universities from 2017 to 2020. We find that the institutional factors impacting on performance of faculty startups differ from other categories of startups. The results show that it is important for universities to provide a more favorable environment, incorporating more flexible personnel policies and accompanying startup support infrastructure, for faculty startups, whilest it is more effective to have more financial resources and intellectual property for other categories of startups. Our findings also indicate that university technology-holding company and technology transfer programs are crucial to increase the number of faculty startups and their performance. Our analysis results have implications for both university and government policy-makers, endeavoring to facilitate higher particaption of professors in startup formation and ultimate commercialization of associated teachnologies.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Life Science
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• v.23 no.5
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• pp.710-720
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• 2013

Radiotherapy is commonly used in treating many kinds of cancers which cannot be cured by other therapeutic strategies. However, radiotherapy also induces the damages on the normal tissues. Radiation-induced fibrosis is frequently observed in the patients undergoing radiotherapy, and becomes a major obstacle in the treatment of intrahepatic cancer. Hedgehog (Hh) that is an essential in the liver formation during embryogenesis is not detected in the healthy liver, but activated and modulates the repair process in damaged livers in adult. The expression of Hh increases with the degree of liver damage, regulating the proliferation of hepatic progenitors and hepatic stellate cells (HSC). In addition, Hh induces epithelial-to-mesencymal transition (EMT) and activation of myofibroblasts. In the irradiated livers, up-regulated expression of Hh signaling was associated with proliferation of progenitors, EMT induction, and increased fibrosis. Female-specific expression of Hh leaded to the expansion of progenitors and the accumulation of collagen in the irradiated livers of female mice, indicating that gender disparity in Hh expression may be related with radiation-susceptibility in female. Hence, Hh signaling becomes a novel object of studies for fibrogenesis induced by radiation. However, the absence of the established experimental animal models showing the similar physiopathology with human liver diseases and fibrosis-favorable microenvironment hamper the studies for the radiation-induced fibrosis, providing a few descriptive results. Therefore, further research on the association of Hh with radiation-induced fibrosis can identify the cell and tissue-specific effects of Hh and provides the basic knowledge for underlying mechanisms, contributing to developing therapies for preventing the radiation-induced fibrosis.