• Title/Summary/Keyword: Root mean square value

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Influence of Regularization Parameter on Algebraic Reconstruction Technique (대수적 재구성 기법에서 정규화 인자의 영향)

  • Son, Jung Min;Chon, Kwon Su
    • Journal of the Korean Society of Radiology
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    • v.11 no.7
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    • pp.679-685
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    • 2017
  • Computed tomography has widely been used to diagnose patient disease, and patient dose also increase rapidly. To reduce the patient dose by CT, various techniques have been applied. The iterative reconstruction is used in view of image reconstruction. Image quality of the reconstructed section image through algebraic reconstruction technique, one of iterative reconstruction methods, was examined by the normalized root mean square error. The computer program was written with the Visual C++ under the parallel beam geometry, Shepp-Logan head phantom of $512{\times}512$ size, projections of 360, and detector-pixels of 1,024. The forward and backward projection was realized by Joseph method. The minimum NRMS of 0.108 was obtained after 10 iterations in the regularization parameter of 0.09-0.12, and the optimum image was obtained after 8 and 6 iterations for 0.1% and 0.2% noise. Variation of optimum value of the regularization parameter was observed according to the phantom used. If the ART was used in the reconstruction, the optimal value of the regularization parameter should be found in the case-by-case. By finding the optimal regularization parameter in the algebraic reconstruction technique, the reconstruction time can be reduced.

Autonomic Nervous Properties of Atropine and Glycopyrrolate on Heart Rate Variability during Anesthesia with Ketamine-Xylazine in Dogs (개에서 케타민-자일라진 마취동안 심박변이도에 대한 아트로핀과 글리코피롤레이트의 자율신경적 특성)

  • Park, Woo-Young;Bae, Chun-Sik;Lee, Soo-Han;Park, Woo-Dae
    • Journal of Veterinary Clinics
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    • v.26 no.3
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    • pp.212-219
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    • 2009
  • Anticholinergics, which are commonly given as a pre-anesthetic medication to prevent adverse effects in canine anesthesia, can cause cardiac adverse effects. To determine the effects of atropine and glycopyrrolate on the balance of sympathetic nervous tone and parasympathetic nervous tone of the heart during ketamine anesthesia in beagle dogs, heart rate variability(HRV), duration of anesthesia and behavioral changes were evaluated. There were no significant temporal domain differences between atropine and glycopyrrolate. Concerning the frequency domain component, atropine and glycopyrrolate effects were significantly lower(P<0.05) than the control saline-treated group. However, the root mean square of the interval differences between consecutive R peaks(RMSSD) and the standard deviation of Poincare plot perpendicular to the line-of-identity(SD1) in atropine were significantly decreased(P<0.05) from the baseline value, and the low frequency/high frequency ratio(LF:HF ratio) in glycopyrrolate was significantly increased from baseline value(P<0.05). The change of SD1 agreed with that of the high frequency(HF) in the frequency domain component and also with those of respiratory rate and $SpO_2-R$. Our results prove that glycopyrrolate is more suitable as a pre-anesthetic anticholinergic in ketamine anesthesia of dogs with respect to safety and duration of action.

A Numerical Solution Method of the Boundary Integral Equation -Axisymmetric Flow- (경계적분방정식의 수치해법 -축대칭 유동-)

  • Chang-Gu,Kang
    • Bulletin of the Society of Naval Architects of Korea
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    • v.27 no.3
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    • pp.38-46
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    • 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.

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Accuracy Analysis for Slope Movement Characterization by comparing the Data from Real-time Measurement Device and 3D Model Value with Drone based Photogrammetry (도로비탈면 상시계측 실측치와 드론 사진측량에 의한 3D 모델값의 정확도 비교분석)

  • CHO, Han-Kwang;CHANG, Ki-Tae;HONG, Seong-Jin;HONG, Goo-Pyo;KIM, Sang-Hwan;KWON, Se-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.234-252
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    • 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.

A Study on Estimating Rice Yield in DPRK Using MODIS NDVI and Rainfall Data (MODIS NDVI와 강수량 자료를 이용한 북한의 벼 수량 추정 연구)

  • Hong, Suk Young;Na, Sang-Il;Lee, Kyung-Do;Kim, Yong-Seok;Baek, Shin-Chul
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.441-448
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    • 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.

Evaluation of beam delivery accuracy for Small sized lung SBRT in low density lung tissue (Small sized lung SBRT 치료시 폐 실질 조직에서의 계획선량 전달 정확성 평가)

  • Oh, Hye Gyung;Son, Sang Jun;Park, Jang Pil;Lee, Je Hee
    • The Journal of Korean Society for Radiation Therapy
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    • v.31 no.1
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    • pp.7-15
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    • 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.

Parameter Estimation of Coastal Water Quality Model Using the Inverse Theory (역산이론을 이용한 연안 수질모형의 매개변수 추정)

  • Cho, Hong-Yeon;Cho, Bum-Jun;Jeong, Shin-Taek
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.17 no.3
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    • pp.149-157
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    • 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.

Rice Yield Estimation of South Korea from Year 2003-2016 Using Stacked Sparse AutoEncoder (SSAE 알고리즘을 통한 2003-2016년 남한 전역 쌀 생산량 추정)

  • Ma, Jong Won;Lee, Kyungdo;Choi, Ki-Young;Heo, Joon
    • Korean Journal of Remote Sensing
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    • v.33 no.5_2
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    • pp.631-640
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    • 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.

Nondestructive Estimation of Lean Meat Yield of South Korean Pig Carcasses Using Machine Vision Technique

  • Lohumi, Santosh;Wakholi, Collins;Baek, Jong Ho;Kim, Byeoung Do;Kang, Se Joo;Kim, Hak Sung;Yun, Yeong Kwon;Lee, Wang Yeol;Yoon, Sung Ho;Cho, Byoung-Kwan
    • Food Science of Animal Resources
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    • v.38 no.5
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    • pp.1109-1119
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    • 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.

Comparative Analysis of SWAT Generated Streamflow and Stream Water Quality Using Different Spatial Resolution Data (SWAT모형에서 다양한 해상도에 따른 수문-수질 모의결과의 비교분석)

  • Park, Jong-Yoon;Lee, Mi-Seon;Park, Geun-Ae;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.102-106
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    • 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.

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