• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.1-12
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• 2010

According to the capacity design concept which forms the basis of the current steel seismic codes, the braces in concentrically braced frames (CBFs) should dissipate seismic energy through cyclic tension yielding and cyclic compression buckling while the beams and the columns should remain elastic. Brace buckling in inverted V-braced frames induces unbalanced vertical forces which, in turn, impose the additional beam moments and column axial forces. However, due to difficulty in predicting the location of buckling stories, the most conservative approach implied in the design code is to estimate the column axial forces by adding all the unbalanced vertical forces in the upper stories. One alternative approach, less conservative and recommended by the current code, is to estimate the column axial forces based on the amplified seismic load expected at the mechanism-level response. Both are either too conservative or lacking technical foundation. In this paper, three combination rules for a rational estimation of the column axial forces were proposed. The idea central to the three methods is to detect the stories of high buckling potential based on pushover analysis and dynamic behavior. The unbalanced vertical forces in the stories detected as high buckling potential are summed in a linear manner while those in other stories are combined by following the SRSS(square root of sum of squares) rule. The accuracy and design advantage of the three methods were validated by comparing extensive inelastic dynamic analysis results. The mode-shape based method(MSBM), which is both simple and accurate, is recommended as the method of choice for practicing engineers among the three.

• Journal of the Korean Vacuum Society
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• v.22 no.6
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• pp.313-320
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• 2013

The $AlAs_xSb_{1-x}$ step-graded buffer (SGB) layer was grown on the Silicon (Si) substrate to overcome lattice mismatch between Si substrate and $Al_{0.3}Ga_{0.7}As$/GaAs multiple quantum wells (MQWs). The value of root-mean-square (RMS) surface roughness for 5 nm-thick GaAs grown on $AlAs_xSb_{1-x}$ step-graded buffer layer was ~1.7 nm. $Al_{0.3}Ga_{0.7}As$/GaAs MQWs with AlAs/GaAs short period superlattice (SPS) were formed on the $AlAs_xSb_{1-x}$/Si substrate. Photoluminescence (PL) peak at 10 K for the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure showed relatively low intensity at ~813 nm. The RMS surface roughness of the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure was ~42.9 nm. The crystal defects were observed on the cross-sectional transmission electron microscope (TEM) images of the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure. The decrease of PL intensity and increase of RMS surface roughness would be due to the formation of the crystal defects.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.847-860
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• 2020

The 2-pass DInSAR (Differential Interferometric SAR) processing steps for DEM generation consist of the co-registration of SAR image pair, interferogram generation, phase unwrapping, calculation of DEM errors, and geocoding, etc. It requires complicated steps, and the accuracy of data processing at each step affects the performance of the finally generated DEM. In this study, we developed an improved method for enhancing the performance of the DEM generation method based on the 2-pass DInSAR technique of TanDEM-X bistatic SAR images was developed. The developed DEM generation method is a method that can significantly reduce both the DEM error in the unwrapped phase image and that may occur during geocoding step. The performance analysis of the developed algorithm was performed by comparing the vertical accuracy (Root Mean Square Error, RMSE) between the existing method and the newly proposed method using the ground control point (GCP) generated from GPS survey. The vertical accuracy of the DInSAR-based DEM generated without correction for the unwrapped phase error and geocoding error is 39.617 m. However, the vertical accuracy of the DEM generated through the proposed method is 2.346 m. It was confirmed that the DEM accuracy was improved through the proposed correction method. Through the proposed 2-pass DInSAR-based DEM generation method, the SRTM DEM error observed by DInSAR was compensated for the SRTM 30 m DEM (vertical accuracy 5.567 m) used as a reference. Through this, it was possible to finally create a DEM with improved spatial resolution of about 5 times and vertical accuracy of about 2.4 times. In addition, the spatial resolution of the DEM generated through the proposed method was matched with the SRTM 30 m DEM and the TanDEM-X 90m DEM, and the vertical accuracy was compared. As a result, it was confirmed that the vertical accuracy was improved by about 1.7 and 1.6 times, respectively, and more accurate DEM generation was possible with the proposed method. If the method derived in this study is used to continuously update the DEM for regions with frequent morphological changes, it will be possible to update the DEM effectively in a short time at low cost.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• The Journal of Korean Society for Radiation Therapy
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• v.19 no.1
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• pp.19-26
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• 2007

Purpose: To compare of the accuracy among various measurement procedures of HDR Brachytherapy, and to evaluate the clinical suitability and usefulness of alternative PMMA (polymethylmethacrylateplastics: $C_5H_8O_2$) plate phantom without any additional cost due to the purchase of measuring apparatus. Materials and Methods: We made a comparative study on three types of measuring systems: well type chamber, source calibration jig, and PMMA plate phantom. Farmer type chamber was used for source calibration jig method and PMMA plate phantom method. Measurement was done 5 times each in comparison with the measurement values from manufacturer. Measurement results from experiment were compared with that from the manufacturer which is offered with the source whenever a source is substituted by a new one and evaluate the accuracy of source activity. Results: As a consequence of Ir-192 source measurement using well type chamber, source calibration jig and PMMA plate phantom, RMS (Root Mean Square) values for the relative error are 0.6%, 1.57%, 2.1%, respectively, compared with the data from manufacturer. And the mean errors with standard deviation are given $-0.2{\pm}0.5%$, $0.97{\pm}1.23%$, $-0.89{\pm}1.87%$ respectively. Conclusion: From the results shown by the three types of measurement system (well type chamber, source calibration jig, and PMMA plate phantom), the measurement with well type chamber produced the best accuracy. It turns out that we can also use the alternative system of PMMA plate phantom clinically without purchasing any additional particular apparatus since the system does not exceed the recommendation of AAPM (American Association of Physicists in Medicine), which requires the error range of within ${\pm}5%$.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.375-387
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• 2013

Accuracy assessment of tide models in polar ocean has to be performed to accurately analyze tidal response of glaciers by using Double-Differential Interferometric SAR (DDInSAR) technique. In this study, we used 120 DDInSAR images generated from 16 one-day tandem COSMO-SkyMed DInSAR pairs obtained for 2 years and in situ tide height for 11 days measured by a pressure type wave recorder to assess the accuracy of tide models such as TPXO7.1, FES2004, CATS2008a and Ross_Inv in Terra Nova Bay, East Antarctica. Firstly, we compared the double-differential tide height (${\Delta}\dot{T}$) for Campbell Glacier Tongue extracted from the DDInSAR images with that predicted by the tide models. Tide height (T) from in situ measurement was compared to that of the tide models. We also compared 24-hours difference of tide height ($\dot{T}$) from in situ tide height with that from the tide models. The root mean square error (RMSE) of ${\Delta}\dot{T}$, T and $\dot{T}$ decreased after the inverse barometer effect (IBE)-correction of the tide models, from which we confirmed that the IBE of tide models should be corrected requisitely. The RMSE of $\dot{T}$ and ${\Delta}\dot{T}$ were smaller than that of T. This was because $\dot{T}$ is the difference of tide height during temporal baseline of the DInSAR pairs (24 hours), in which the errors from mean sea level of the tide models and in situ tide, and the tide constituents of $S_2$, $K_2$, $K_1$ and $P_1$ used in the tide models were canceled. This confirmed that $\dot{T}$ and ${\Delta}\dot{T}$ predicted by the IBE-corrected tide models can be used in DDInSAR technique. It was difficult to select an optimum tide model for DDInSAR in Terra Nova Bay by using in situ tide height measured in a short period. However, we could confirm that Ross_Inv is the optimum tide model as it showed the smallest RMSE of 4.1 cm by accuracy assessment using the DDInSAR images.

• Radiation Oncology Journal
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• v.26 no.3
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• pp.181-188
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• 2008

Purpose: In order to enhance the efficiency of respiratory gated 4-dimensional radiation therapy for more regular and stable respiratory period and amplitude, a respiration training system was designed, and its efficacy was evaluated. Materials and Methods: The experiment was designed to measure the difference in respiration regularity following the use of a training system. A total of 11 subjects (9 volunteers and 2 patients) were included in the experiments. Three different breathing signals, including free breathing (free-breathing), guided breathing that followed training software (guided-breathing), and free breathing after the guided-breathing (post guided-breathing), were consecutively recorded in each subject. The peak-to-peak (PTP) period of the breathing signal, standard deviation (SD), peak-amplitude and its SD, area of the one cycle of the breathing wave form, and its root mean square (RMS) were measured and computed. Results: The temporal regularity was significantly improved in guided-breathing since the SD of breathing period reduced (free-breathing 0.568 vs guided-breathing 0.344, p=0.0013). The SD of the breathing period representing the post guided-breathing was also reduced, but the difference was not statistically significant (free-breathing 0.568 vs. guided-breathing 0.512, p=ns). Also the SD of measured amplitude was reduced in guided-breathing (free-breathing 1.317 vs. guided-breathing 1.068, p=0.187), although not significant. This indicated that the tidal volume for each breath was kept more even in guided-breathing compared to free-breathing. There was no change in breathing pattern between free-breathing and guided-breathing. The average area of breathing wave form and its RMS in postguided-breathing, however, was reduced by 7% and 5.9%, respectively. Conclusion: The guided-breathing was more stable and regular than the other forms of breathing data. Therefore, the developed respiratory training system was effective in improving the temporal regularity and maintaining a more even tidal volume.

• Journal of dental hygiene science
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• v.14 no.2
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• pp.158-166
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• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.567-579
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• 2015

The accurate simulation of micro-scale weather phenomena such as fog using the mesoscale meteorological models is a very complex task. Especially, the uncertainty arisen from initial input data of the numerical models has a decisive effect on the accuracy of numerical models. The data assimilation is required to reduce the uncertainty of initial input data. In this study, the limitation of the mesoscale meteorological model was verified by WRF (Weather Research and Forecasting) model for a summer fog event around the Nakdong river in Korea. The sensitivity analyses of simulation accuracy from the numerical model were conducted using two different initial and boundary conditions: KLAPS (Korea Local Analysis and Prediction System) and LDAPS (Local Data Assimilation and Prediction System) data. In addition, the improvement of numerical model performance by FDDA (Four-Dimensional Data Assimilation) using the observational data from AWS (Automatic Weather System) was investigated. The result of sensitivity analysis showed that the accuracy of simulated air temperature, dew point temperature, and relative humidity with LDAPS data was higher than those of KLAPS, but the accuracy of the wind speed of LDAPS was lower than that of KLAPS. Significant difference was found in case of relative humidity where RMSE (Root Mean Square Error) for LDAPS and KLAPS was 15.7 and 35.6%, respectively. The RMSE for air temperature, wind speed, and relative humidity was improved by approximately $0.3^{\circ}C$, $0.2m\;s^{-1}$, and 2.2%, respectively after incorporating the FDDA.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.3
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• pp.119-130
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• 2015

Impacts of Argo temperature assimilation on the analysis fields in the East Sea is investigated by using DAESROM, the East Sea Regional Ocean Model with a 3-dimensional variational assimilation module (Kim et al., 2009). Namely, we produced analysis fields in 2009, in which temperature profiles, sea surface temperature (SST) and sea surface height (SSH) anomaly were assimilated (Exp. AllDa) and carried out additional experiment by withdrawing Argo temperature data (Exp. NoArgo). When comparing both experimental results using assimilated temperature profiles, Root Mean Square Error (RMSE) of the Exp. AllDa is generally lower than the Exp. NoArgo. In particular, the Argo impacts are large in the subsurface layer, showing the RMSE difference of about $0.5^{\circ}C$. Based on the observations of 14 surface drifters, Argo impacts on the current and temperature fields in the surface layer are investigated. In general, surface currents along the drifter positions are improved in the Exp. AllDa, and large RMSE differences (about 2.0~6.0 cm/s) between both experiments are found in drifters which observed longer period in the southern region where Argo density was high. On the other hand, Argo impacts on the SST fields are negligible, and it is considered that SST assimilation with 1-day interval has dominant effects. Similar to the difference of surface current fields between both experiments, SSH fields also reveal significant difference in the southern East Sea, for example the southwestern Yamato Basin where anticyclonic circulation develops. The comparison of SSH fields implies that SSH assimilation does not correct the SSH difference caused by withdrawing Argo data. Thus Argo assimilation has an important role to reproduce meso-scale circulation features in the East Sea.