• Atmosphere
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• v.26 no.3
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• pp.373-386
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• 2016

The future variability of Wind Energy Density (WED) over the Korean Peninsula under RCP climate change scenario is projected using ensemble analysis. As for the projection of the future WED, changes between the historical period (1981~2005) and the future projection (2021~2050) are examined by analyzing annual and seasonal mean, and Coefficient of Variation (CV) of WED. The annual mean of WED in the future is expected to decrease compared to the past ones in RCP 4.5 and RCP 8.5 respectively. However, the CV is expected to increase in RCP 8.5. WEDs in spring and summer are expected to increase in both scenarios RCP 4.5 and RCP 8.5. In particular, it is predicted that the variation of CV for WED in winter is larger than other seasons. The time series of WED for three major wind farms in Korea exhibit a decrease trend over the future period (2021~2050) in Gochang for autumn, in Daegwanryeong for spring, and in Jeju for autumn. Through analyses of the relationship between changes in wind energy and pressure gradients, the fact that changes in pressure gradients would affect changes in WED is identified. Our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.3
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• pp.121-128
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• 2024

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f^0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune's source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

• Atmosphere
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• v.24 no.4
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• pp.533-540
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• 2014

Statistical forecast models for the prediction of the summertime Changma precipitation have been developed in this study. As effective predictors for the Changma precipitation, the springtime sea surface temperature (SST) anomalies over the North Atlantic (NA1), the North Pacific (NPC) and the tropical Pacific Ocean (CNINO) has been suggested in Lee and Seo (2013). To further improve the performance of the statistical prediction scheme, we select other potential predictors and construct 2 additional statistical models. The selected predictors are the Northern Indian Ocean (NIO) and the Bering Sea (BS) SST anomalies, and the spring Eurasian snow cover anomaly (EUSC). Then, using the total three statistical prediction models, a simple ensemble-mean prediction is performed. The resulting correlation skill score reaches as high as ~0.90 for the last 21 years, which is ~16% increase in the skill compared to the prediction model by Lee and Seo (2013). The EUSC and BS predictors are related to a strengthening of the Okhotsk high, leading to an enhancement of the Changma front. The NIO predictor induces the cyclonic anomalies to the southwest of the Korean peninsula and southeasterly flows toward the peninsula, giving rise to an increase in the Changma precipitation.

• Korean Journal of Human Ecology
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• v.10 no.1
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• pp.37-48
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• 2007

The purpose of this study was to investigate the proper combination of ensemble suit details for the body silhouette of elderly women. In this study, the principal component analysis was used to search for the proper combination of suit details for covering defects of body which has been changed unbalanced. The designs of evaluated suits were manipulated in 18 different kinds by the essential elements such as collars, neckline(round neckline, shirt collar, tailored collar), types of one-piece dress(pleats type, gather type, flare type), and opening(opened, closed). The data evaluated by a multiple ranking test was analyzed by mean, paired t-test, ANOVA and Duncan's multiple ranged test. The results were summarized as follows: In case of normal body type, it had complementary effects for upper body with closed round neckline jacket or shirt collar jacket, and for lower and the whole body with a combination of closed tailored collar jacket or shirt collar jacket with pleats or gored type one piece dress. The visual effect for elderly women's body shape was different in opened or closed jacket. And that enhanced by Jacket with collar.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.13-18
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• 2010

In this study the validities of runoff prediction methods are reviewed around ESP (Ensemble Streamflow Prediction) techniques. The improvements of runoff predictions on Yongdam river basin are evaluated by the comparison of different prediction methods including ESP incorporated with qualitative meteorological outlooks provided by meteorological agency as well as the runoff forecasting based on the analysis of the historical rainfall scenarios. As a result it is assessed that runoff predictions with ESP may give rise to more accurate results than the ordinary historical average runoffs. In deed the latter gave the mean of yearly absolute error as to be 60.86 MCM while the errors of the former ones amounted to 44.12 MCM (ESP) and 42.83 MCM (ESP incorporated with qualitative meteorological outlooks) respectively. In addition it is confirmed that ESP incorporated with qualitative meteorological outlooks could improve the accuracy of the results more and more. Especially the degree of improvement of ESP with meteorological outlooks shows rising by 10.8% in flood season and 8% in drought season. Therefore the methods of runoff predictions with ESP can be further used as the basic forecasting information tool for the purpose of the effective watershed management.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2423-2430
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• 1994

Several factors of the efficient combustion process are shape of combustion chamber, position of spark plug, turbulence flow and so on. the shape of combustion chamber and position of spark plug are constrained to geometrically, and then it could not make a change the shape easily. But the turlence flow in combustion chamber have a great influence on combustion phenomena, and which is much easier to control relatively. And since characteristics of turbulence flow would be very important to the stability of combustion and performances, This study is also essential to future engine-low emission and lean burn engine. This paper shows that the visualization of the turbulence flow of single cylinder engine by using 2way, $45^{\circ}$ inclined and 2 channel hot wire probe through the park plug hole. We also study the characteristics of turbulence flow by means of ensemble averaged mean velocity, turvulence intensity and integral length scale.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.382-389
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• 2000

The instantaneous and ensemble averaged flow characteristics of a round jet issuing normally into a crossflow was studied using a flow visualization technique and Particle Image Velocimetry measurements. Experiments were performed at a jet-to-crossflow velocity ratio, 3.3, and two Reynolds numbers, 1050 and 2100, based on crossflow velocity and jet diameter. Instantaneous laser tomographic images of the vertical center plane of the crossflow jet showed that there exist very different natures in the flow structures of the near field jet even though the velocity ratio is the same. It was found that the shear layer becomes much thicker when the Reynolds number is 2100 due to the strong entrainment of the inviscid fluid by turbulent interaction between the jet and crossflow. The mean and second order statistics were calculated by ensemble averaging over 1000 realizations of instantaneous velocity fields. The detail characteristics of mean flow field, stream wise and vertical r.m.s. velocity fluctuations, and Reynolds shear stress distributions were presented. The new PlV results were compared with those from previous experimental and LES studies.

• Smart Structures and Systems
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• v.11 no.1
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.524-527
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• 2022

본 연구에서는 머신러닝(Machine Learning, ML)과 딥러닝(Deep Learning, DL) 모델을 앙상블(Ensemble)하여 어떠한 주가 예측 방법이 우수한지에 대한 연구를 하고자 한다. 연구에 사용된 모델은 하이퍼파라미터(Hyperparameter) 조정을 통하여 최적의 결과를 출력한다. 앙상블 방법은 머신러닝과 딥러닝 모델의 앙상블, 머신러닝 모델의 앙상블, 딥러닝 모델의 앙상블이다. 세 가지 방법으로 얻은 결과를 평균 제곱근 오차(Root Mean Squared Error, RMSE)로 비교 분석하여 최적의 방법을 찾고자 한다. 제안한 방법은 주가 예측 연구의 시간과 비용을 절약하고, 최적 성능 모델 판별에 도움이 될 수 있다고 사료된다.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.