• Journal of Environmental Impact Assessment
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• v.29 no.4
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• pp.272-285
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• 2020

We investigated statistical evaluation parameters for 3D meteorological and air quality models and selected several quantitative indicator references, and summarized the reference values of the statistical parameters for domestic air quality modeling researcher. The finally selected 9 statistical parameters are MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias), and the associated reference values are summarized. The results showed that MB and ME have been widely used in evaluating the meteorological model output, and NMB and NME are most frequently used for air quality model results. In addition, discussed are the presentation diagrams such as Soccer Plot, Taylor diagram, and Q-Q (Quantile-Quantile) diagram. The current results from our study is expected to be effectively used as the statistical evaluation parameters suitable for situation in Korea considering various characteristics such as including the mountainous surface areas.

• Earthquakes and Structures
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• v.21 no.6
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• pp.563-576
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• 2021

The rocking foundation is effective for reducing structural seismic demand and avoiding overdesign of the foundation. It is crucial to evaluate the performance of rocking foundations because they cause plastic hinging in the soil. In this study, to derive optimized ground motion intensity measures (IMs) for rocking foundations, the efficiency of IMs correlated with engineering demand parameters (EDPs) was estimated through the coefficient determination using a physical modeling database for rocking shallow foundations. Foundation deformations, the structural horizontal drift ratio, and contribution in drift from foundation rotation and sliding were selected as crucial EDPs for the evaluation of rocking foundation systems. Among 15 different IMs, the peak ground velocity exhibited the most efficient parameters correlated with the EDPs, and it was discovered to be an efficient ground motion IM for predicting the seismic performance of rocking foundations. For vector regression, which uses two IMs to present the EDPs, the IMs indicating time features improved the efficiency of the regression curves, but the correlation was poor when these are used independently. Moreover, the ratio of the column-hinging base shear coefficient to the rocking base shear coefficient showed obvious trends for the accurate assessment of the seismic performance of rocking foundation-structure systems.

• Journal of Microbiology and Biotechnology
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• v.21 no.4
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• pp.430-437
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• 2011

The effects of the agitation and aeration rates on the production of serratiopeptidase (SRP) in a 5-L fermentor (working volume 2-l) were systematically investigated using Serratia marcescens NRRL B-23112. The dissolved oxygen concentration, pH, biomass, SRP yield, and maltose utilization were all continuously measured during the course of the fermentation runs. The efficiencies of the aeration and agitation were evaluated based on the volumetric mass transfer coefficient ($K_La$). The maximum SRP production of 11,580 EU/ml with a specific SRP productivity of 78.8 EU/g/h was obtained with an agitation of 400 rpm and aeration of 0.075 vvm, which was 58% higher than the shake-flask level. The $K_La$ for the fermentation system supporting the maximum production (400 rpm, 0.075 vvm) was 11.3 $h^{-1}$. Under these fermentor optimized conditions, kinetic modeling was performed to understand the detailed course of the fermentation process. The resulting logistic and Luedeking-Piret models provided an effective description of the SRP fermentation, where the correlation coefficients for cell growth, SRP formation, and substrate consumption were 0.99, 0.94, and 0.84, respectively, revealing a good agreement between the model-predicted and experimental results. The kinetic analysis of the batch fermentation process for the production of SRP demonstrated the SRP production to be mixed growth associated.

• Structural Engineering and Mechanics
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• v.66 no.4
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• pp.423-438
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• 2018

This pioneer study focuses on finite element modeling and numerical modeling of three types of Reinforced Concrete Haunched Beams (RCHBs). Firstly, twenty RCHBs, consisting of three types, and four prismatic beams which had been tested experimentally were modeled via a nonlinear finite element method (NFEM) based software named as, ATENA. The modeling results were compared with experimental results including load capacity, deflection, crack pattern and mode of failure. The comparison showed a good agreement between the results and thus the model used can be effectively used for further studies of RCHB with high accuracy. Afterwards, new mechanism modes and design code equations were proposed to improve the shear design equation of ACI-318 and to predict the critical effective depth. These equations are the first comprehensive formulas in the literature involving all types of RCHBs. The statistical analysis showed the superiority of the proposed equation to their predecessors where the correlation coefficient, $R^2$ was found to be 0.89 for the proposed equation. Moreover, the new equation was validated using parametric and reliability analyses. The parametric analysis of both experimental and predicted results shows that the inclination angle and the compressive strength were the most influential parameters on the shear strength. The reliability analysis indicates that the accuracy of the new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.30-40
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• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.331-345
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• 2021

Virtual testing is considered a major requirement for the safety verification of autonomous driving functions. For virtual testing, both the autonomous vehicle and the driving environment should be modeled appropriately. In particular, a realistic modeling of the perception sensor system such as the one having a camera and radar is important. However, research on modeling to consistently generate realistic perception results is lacking. Therefore, this paper presents a sensor modeling method to provide realistic object detection results in a MILS (Model in the Loop Simulation) environment. First, the key parameters for modeling are defined, and the object detection characteristics of actual cameras and radar sensors are analyzed. Then, the detection characteristics of a sensor modeled in a simulation environment, based on the analysis results, are validated through a correlation coefficient analysis that considers an actual sensor.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.79-86
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• 2010

This research is a thing about reverse operation about the solar power for location decision and increasing efficiency of the solar power generation equipments. The purpose of this research is reverse operation about the amount of sunshine using the climate and spatial elements. Following the result of correlation analysis, the wind-speed and cloud-amount factor are excluded, because the correlation and significance coefficients are out of value. Each outcome of regression analysis using the other four climate elements, and regression analysis using spatial elements is what the amount of sunshine and the solar altitude are the most influence to the insolation-modeling. Doing the regression analysis based on the precedent result make the result that climate elements have bigger coefficient of regression than spatial elements. This outcome means the climate elements are more influence than spatial elements.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.162-165
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• 2004

The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

• New & Renewable Energy
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• v.20 no.1
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• pp.79-87
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• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.3
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• pp.173-182
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• 2022

The present study suggests a procedure of establishing a ship dynamics modeling by regression of free-running model test results. The hydrodynamic force and moment of the whole model ship is derived from the low-pass filtered acceleration in the turning circle and zigzag maneuver tests. Force and moment of the propeller and rudder are separated from that of the whole ship to acquire the hull force and moment terms, based on the principles of the component model. The low-pass filter frequency is verified in prior to dynamics modeling, to find the threshold frequency of 2.5 Hz. The dynamics modeling of the hull is compared with the component modeling by captive model tests. Because of strong correlation between sway velocity, yaw angular velocity, and heel angle, each maneuvering coefficient is not able to be validated, but the whole modeling shows good agreement with the captive model tests.