• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.257-267
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• 2010

A flood event can be characterized by three attributes such as peak discharge, total flood volume, and flood duration, which are correlated each other. However, the amount of peak discharge is only used to evaluate the flood events for the hydrological plan and design. The univariate analysis has a limitation in describing the complex probability behavior of flood events. Thus, the univariate analysis cannot derive satisfying results in flood frequency analysis. This study proposed bivariate flood frequency analysis methods for evaluating flood events considering correlations among attributes of flood events. Parametric distributions such as Gumbel mixed model and bivariate gamma distribution, and a non-parametric model using a bivariate kernel function were introduced in this study. A time series of annual flood events were extracted from observations of inflow to the Soyang River Dam and the Daechung Dam, respectively. The joint probability distributions and return periods were derived from the relationship between the amount of peak discharge and the total volume of flood runoff. Applicabilities of bivariate flood frequency analysis were examined by comparing the return period acquired from the proposed bivariate analyses and the conventional univariate analysis.

• Particle and aerosol research
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• v.7 no.2
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• pp.59-68
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• 2011

The objective of the study was to investigate the main factors that contribute the variation of $PM_{10}$ concentration of Seoul and to quantify their effects using generalized additive model (GAM). The analysis was performed with 3 year air pollution data (2004~2006) measured at 27 urban sites and 7 roadside sites in Seoul, a background site in Gangwha and a rural site in Pocheon. The diurnal variation of urban $PM_{10}$ concentrations of Seoul showed a typical bimodal pattern with the same peak times as that of roadside, and the maximum difference of $PM_{10}$ level between urban and roadside was about $14{\mu}g/m^{3}$ at 10 in the morning. The wind direction was found to be a major factor that affects $PM_{10}$ level in all investigated areas. The overall $PM_{10}$ level was reduced when air came from east, but background $PM_{10}$ level in Gangwha was rather higher than the urban $PM_{10}$ level in Seoul, indicating that the $PM_{10}$ level in Gangwha is considerably influenced by that in Seoul metropolitan area. When hourly variations of $PM_{10}$ were analyzed using GAM, wind direction and speed explained about 34% of the variance in the model where the variables were added as a 2-dimensional smoothing function. In addition, other variables, such as diurnal variation, difference of concentrations between roadside and urban area, precipitation, month, and the regression slope of a plot of carbon monooxide versus $PM_{10}$, were found to be major explanatory variables, explaining about 64% of total variance of hourly variations of $PM_{10}$ in Seoul.

• World Technopolis Review
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• v.1 no.3
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• pp.192-205
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• 2012

Globalization has fuelled the desire for simplicity and flexibility in rules and processes within nations. de Soto (2000) calls for the simplification of rules to enable people to join the formal economy. Friedman (2005) echoes the need for simpler rules, to attract business and capital. Market-based approaches to governing have been adopted in many nations due to globalization. Recent developments demonstrate that such approaches fail. Globalization may lead to impoverishment in the absence of proper forms of governance (Cooney 2000). That is why it has the tendency to become a "race to the bottom." Regulatory measures can be costly, and the costs of doing business are uneven across nations. This unevenness is being used as a comparative advantage. Others call this regulatory competition (Smith-Bozek 2007) or competitive governance (Schachtel and Sahmel 2000), which is similar to the model of Charles Tiebout. Collaborative governance is an approach that governments could use in lieu of the competitive method. Mechanisms that enable stakeholders to exchange information, harmonize activities, share resources, and enhance capacities (Himmelman 2002) are needed. Philippine public policy encourages a shift in modes of realizing labor market governance outcomes from command to collaboration (Sale and Bool 2010B; Sale 2011). Is labor market governance and regional development in the Philippines collaborative? Or is the opposite - competitive governance (Tiebout model) - more evident? What is the dominant approach? This preliminary research tackles these questions by looking at recent data on average and minimum wages, wage differentials, trade union density, collective bargaining coverage, small and bigger enterprises, employment, unemployment and underemployment, inflation, poverty incidence, labor productivity, family income, among others, across regions of the country. The issue is studied in the context of legal origins. Cultural explanations are broached.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.8-15
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• 2020

This research is a case study of underwater object tracking based on real-time recurrent regression networks (Re³). Re³ has the concept of generic object tracking. Because of these characteristics, it is very effective to apply this model to unclear underwater sonar images. The model also an pursues object tracking method, thus it solves the problem of calculating load that may be limited when object detection models are used, unlike the tracking models. The model is also highly intuitive, so it has excellent continuity of tracking even if the object being tracked temporarily becomes partially occluded or faded. There are 4 types of the dataset using multi-beam sonar images: including (a) dummy object floated at the testbed; (b) dummy object settled at the bottom of the sea; (c) tire object settled at the bottom of the testbed; (d) multi-objects settled at the bottom of the testbed. For this study, the experiments were conducted to obtain underwater sonar images from the sea and underwater testbed, and the validity of using noisy underwater sonar images was tested to be able to track objects robustly.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Advances in Computational Design
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• v.2 no.3
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• pp.225-240
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• 2017

This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days' curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes.

• Journal of computational fluids engineering
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• v.17 no.3
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• pp.75-86
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• 2012

We developed a preliminary CFD analysis methodology to predict a pressure build up due to hydrogen flame acceleration in the APR1400 IRWST on the basis of CFD analysis results for test data of hydrogen flame acceleration in a scaled-down test facility performed by Korea Atomic Energy Research Institute. We found out that ANSYS CFX-13 with a combustion model of the so-called turbulent flame closure and a model constant of A = 5.0, a grid model with a hexahedral cell length of 5.0 mm, and a time step size of $1.0{\times}10^{-5}$ s can be a useful tool to predict the pressure build up due to the hydrogen flame acceleration in the test results. Through the comparison of the simulated results with the test results, we found out that the proposed CFD analysis methodology enables us to predict the peak pressure within an error range of about ${\pm}29%$ for the hydrogen concentration of 19.5%. However, the error ranges of the peak pressure for the hydrogen concentration of 15.4% and 18.6% were about 66% and 51%, respectively. To reduce the error ranges in case of the hydrogen concentration of 15.4% and 18.6%, some uncertainties of the test conditions should be clarified. In addition, an investigation for a possibility of flame extinction in the test results should be performed.

• Journal of Technologic Dentistry
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• v.40 no.2
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• pp.63-69
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• 2018

Purpose: The purpose of this study is to investigate the non-precious metal core materials used in the dental laboratory to fabricate the implant superstructure by CAD / CAM method. And to observe and compare the morphology and distribution of the osteoblasts in relation to implant osseointegration. Methods: In this study, the mandibular right first molar tooth model was selected as an international standard to produce a single core. Using this model, the impression was made with the silicone rubber, the tooth model was scanned, and a single core was designed and 5-axis milling was performed. The materials used were Cobalt-Chromium and Nickel-Chromium, and the cores for dental implant top structures were fabricated according to the procedures of the dental labs. After the fabrication, the marginal area of the core was separated and cell culture experiment was performed. The osteoblast cells used MC3T3-E1, which is currently widely used. For morphological analysis of osteoblasts, cells were posttreated and observed using CLSM (Confocal Laser Scanning Microscope) and compared. Results: The cell adhesion behavior of the specimen surface measured by CLSM was uniformly distributed in specimen A (Cobalt-Chromium) than in specimen B (Nickel-Chromium). The distribution and changes of the cells were different in the two specimens. Conclusion : It is possible to confirm that specimen A (Cobalt-Chromium) is suitable for the living body through adhesion and proliferation of osteoblasts related to implant osseointegration in the non-precious metal superstructure used after implantation. It is considered that it is preferable to use Co-Cr when fabricating the superstructure.

• Korean Medical Education Review
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• v.16 no.3
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• pp.126-131
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• 2014

The purpose of this study is to analyze the medical education system of Korea and to propose a method of curriculum redesign. Although there have been many attempts by medical educators to improve the quality of medical education, the results have not been fruitful. First, there exists a limitation to the dualistic curriculum design based on Flexnerianism, and thus, this model does not provide an integrated experience to medical students. Therefore, we propose a unidimensional model for curriculum redesign. Second, it is impossible to promote excellence in medical education without solving the structural problems of teaching and learning, such as the teaching competency of the faculty, large-scale lectures, and team teaching systems. A curricular strategy that emphasizes mutual interaction and teaching accountability is necessary to promote meaningful learning. Third, the current clinical training system, the circulation model, provides incomplete training as well as a lack of sequence and articulation experiences. This system needs to be redesigned in a way that allows only those students who have mastered both the knowledge and the application of medical education to advance to the next step. Fourth, norm-referenced assessments of a medical college distort the learning process and create unconstructive system energy. A criterion-referenced assessment that values cooperation, independent study, and intrinsic motivation is more important for the reliability and validity of the assessment. Medical students should not focus on formative and informative learning. Medical colleges should investigate the multifaceted potential of the students and provide transformative learning to grow students into change agents. For this to take place, curriculum redesign-not new methods of medical education-is required.

• Journal of Environmental Policy
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• v.9 no.1
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• pp.31-55
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• 2010

This study aims to estimate potential climate change damage in Korea using the PAGE model. This study reviewed previous a reasearch to compare relative sensitivity to climate change in Korea and other regions to generate climate change damage function. It was found that sensitivity to climate change in Korea is similar to other Organization for Economic Cooperation and Development (OECD) countries. This study estimated climate change impact for three scenarios. If no action is taken, climate change damage cost in Korea could reach US$ 12,928 ~ 57,900 M. Cumulative Net Present Value (NPV)of climate change impact from 1990 to 2100 would be between US$ 143,226 ~ 921,701 Mdepending on emission scenarios. However, this result should be interpreted with caution as it draws its damage function based on only a few available references. Results also showed that an adaptation policy could decrease the degree of climate change impact significantly. If an adaptation policy is implemented, climate change impact will be decreased by US$ 11,355 million dollars in Korea in 2100.