• Bulletin of the Society of Naval Architects of Korea
• /
• v.27 no.3
• /
• pp.38-46
• /
• 1990

A numerical solution method of the boundary integral equation for axisymmetric potential flows is presented. Those are represented by ring source and ring vorticity distribution. Strengths of ring source and ring vorticity are approximated by linear functions of a parameter $\zeta$ on a segment. The geometry of the body is represented by a cubic B-spline. Limiting integral expressions as the field point tends to the surface having ring source and ring vorticity distribution are derived upto the order of ${\zeta}ln{\zeta}$. In numerical calculations, the principal value integrals over the adjacent segments cancel each other exactly. Thus the singular part proportional to $\(\frac{1}{\zeta}\)$ can be subtracted off in the calculation of the induced velocity by singularities. And the terms proportional to $ln{\zeta}$ and ${\zeta}ln{\zeta}$ can be integrated analytically. Thus those are subtracted off in the numerical calculations and the numerical value obtained from the analytic integrations for $ln{\zeta}$ and ${\zeta}ln{\zeta}$ are added to the induced velocity. The four point Gaussian Quadrature formula was used to evaluate the higher order terms than ${\zeta}ln{\zeta}$ in the integration over the adjacent segments to the field points and the integral over the segments off the field points. The root mean square errors, $E_2$, are examined as a function of the number of nodes to determine convergence rates. The convergence rate of this method approaches 2.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.234-252
• /
• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Korean Journal of Remote Sensing
• /
• v.31 no.5
• /
• pp.441-448
• /
• 2015

Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.

• The Journal of Korean Society for Radiation Therapy
• /
• v.31 no.1
• /
• pp.7-15
• /
• 2019

Purpose: The purpose of this study is to evaluate beam delivery accuracy for small sized lung SBRT through experiment. In order to assess the accuracy, Eclipse TPS(Treatment planning system) equipped Acuros XB and radiochromic film were used for the dose distribution. Comparing calculated and measured dose distribution, evaluated the margin for PTV(Planning target volume) in lung tissue. Materials and Methods : Acquiring CT images for Rando phantom, planned virtual target volume by size(diameter 2, 3, 4, 5 cm) in right lung. All plans were normalized to the target Volume=prescribed 95 % with 6MV FFF VMAT 2 Arc. To compare with calculated and measured dose distribution, film was inserted in rando phantom and irradiated in axial direction. The indexes of evaluation are percentage difference(%Diff) for absolute dose, RMSE(Root-mean-square-error) value for relative dose, coverage ratio and average dose in PTV. Results: The maximum difference at center point was -4.65 % in diameter 2 cm size. And the RMSE value between the calculated and measured off-axis dose distribution indicated that the measured dose distribution in diameter 2 cm was different from calculated and inaccurate compare to diameter 5 cm. In addition, Distance prescribed 95 % dose($D_{95}$) in diameter 2 cm was not covered in PTV and average dose value was lowest in all sizes. Conclusion: This study demonstrated that small sized PTV was not enough covered with prescribed dose in low density lung tissue. All indexes of experimental results in diameter 2 cm were much different from other sizes. It is showed that minimized PTV is not accurate and affects the results of radiation therapy. It is considered that extended margin at small PTV in low density lung tissue for enhancing target center dose is necessary and don't need to constraint Maximum dose in optimization.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.17 no.3
• /
• pp.149-157
• /
• 2005

Typical water quality (WQ) parameters defined in the governing equation of the WQ model are the pollutant loads from atmosphere and watersheds, pollutant release rates from sediment, diffusion coefficient and reaction coefficient etc. The direct measurement of these parameters is very difficult as well as requires high cost. In this study, the pollutant budget equation including these parameters was used to construct the linear simultaneous equations. Based on these equations, the inverse problems were constructed and WQ parameter estimation method minimizing the sum of squared errors between the computed and observed amounts of the mass changes was suggested. WQ parameters, i.e., the atmospheric pollutant loads, sediment release rates, diffusion coefficients and reaction coefficient, were estimated using .this method by utilizing the vertical concentration profile data which has been observed in Cheonsu Bay and Ulsan Port. Values of the estimated parameters show a large temporal variation. However, this technique is persuasive in that the RHS (root mean square) error was less than $5.0\%$ of the observed value ranges and the agreement index was greater than 0.95.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.631-640
• /
• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• Food Science of Animal Resources
• /
• v.38 no.5
• /
• pp.1109-1119
• /
• 2018

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.102-106
• /
• 2008

This study is to evaluated the impact of varying spatial resolutions of DEM (2 m, 10 m, and 30 m), land use (QuickBird, 1/25,000 and Landsat), and soil data (1/25,000 and 1/50,000) on the uncertainty of Soil and Water Assessment Tool (SWAT) predicted streamflow, sediment, T-N, and T-P transport in a small agricultural watershed ($1.21\;km^2$). SWAT model was adopted and the model was calibrated for a $255.4\;km^2$ watershed using 30 m DEM, Landsat land use, and 1/25,000 soil data. The model was run with the combination of three DEM, land use, and soil map respectively. The SWAT model was calibrated for 2 years (1999-2000) using daily streamflow and monthly water quality (SS, T-N, T-P) records from 1999 to 2000, and verified for another 2 years (2001-2002). The average Nash and Sutcliffe model efficiency was 0.59 for streamflow and the root mean square error were 2.08, 4.30 and 0.70 tons/yr for sediment, T-N and T-P respectively. The hydrological results showed that output uncertainty was biggest by spatial resolution of land use. Streamflow increase the watershed average CN value of QucikBird land use was 0.4 and 1.8 higher than those of 1/25,000 and Landsat land use caused increase of streamflow.

• Clean Technology
• /
• v.23 no.1
• /
• pp.42-53
• /
• 2017

Numerical analysis was done to evaluate the fluid distribution inside of the mixing quencher to increase the reaction efficiency of the aqueous hydrogen peroxide solution in the scrubbing column which is used for simultaneous desulfurization and denitrification. Effective injection of the aqueous hydrogen peroxide ($H_2O_2$) solution in the mixing quencher has major effects for improving the reaction efficiency in the scrubbing column by enhancing the mixing of the aqueous $H_2O_2$ solution with the exhaust gas. The current study is to optimize the array of nozzles and the spray angles of the aqueous $H_2O_2$ solution in the mixing quencher by using the computational method. Main concerns of the analysis are how to enhance the uniformity of the $H_2O_2$ concentration distribution in the internal flow. Numerical analysis was done to check the distribution of the internal flow in the mixing quencher in terms of RMS values of the $H_2O_2$ concentration at the end of quencher. The concentration distribution of $H_2O_2$ at the end of is evaluated with respect to the different array of the nozzle pipes and the nozzle tip angles, and we also analyzed the turbulence formation and fluid mixing in the zone. The effect of the spray angle was evaluated with respect to the mixing efficiency in different flow directions. The optimized mixing quencher had the nozzle array at location of 0.3 m from the inlet duct surface and the spray angle is $15^{\circ}$ with the co-current flow. The RMS value of the $H_2O_2$ concentration at the end of the mixing quencher was 12.4%.

• Korean Chemical Engineering Research
• /
• v.46 no.3
• /
• pp.486-491
• /
• 2008

This paper describes a model identification method that has been applied to a commercial 12-inch RTP (rapid thermal processing) equipment with an ultimate aim to develop a high-performance advanced controller. Seven thermocouples are attached on the wafer surface and twelve tungsten-halogen lamp groups are used to heat up the wafer. To obtain a MIMO balanced state space model, multiple SIMO (single-input multiple-output) identification with highorder ARX models have been conducted and the resulting models have been combined, transformed and reduced to a MIMO balanced state space model through a balanced truncation technique. The identification experiments were designed to minimize the wafer warpage and an output linearization block has been proposed for compensation of the nonlinearity from the radiation-dominant heat transfer. As a result from the identification at around 600, 700, and $800^{\circ}C$, respectively, it was found that $y=T(K)^2$ and the state dimension of 80-100 are most desirable. With this choice the root-mean-square value of the one-step-ahead temperature prediction error was found to be in the range of 0.125-0.135 K.