• Title/Summary/Keyword: Parameter calibration/validation

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Patient-Specific Quality Assurance in a Multileaf Collimator-Based CyberKnife System Using the Planar Ion Chamber Array

  • Yoon, Jeongmin;Lee, Eungman;Park, Kwangwoo;Kim, Jin Sung;Kim, Yong Bae;Lee, Ho
    • Progress in Medical Physics
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    • v.29 no.2
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    • pp.59-65
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    • 2018
  • This paper describes the clinical use of the dose verification of multileaf collimator (MLC)-based CyberKnife plans by combining the Octavius 1000SRS detector and water-equivalent RW3 slab phantom. The slab phantom consists of 14 plates, each with a thickness of 10 mm. One plate was modified to support tracking by inserting 14 custom-made fiducials on surface holes positioned at the outer region of $10{\times}10cm^2$. The fiducial-inserted plate was placed on the 1000SRS detector and three plates were additionally stacked up to build the reference depth. Below the detector, 10 plates were placed to avoid longer delivery times caused by proximity detection program alerts. The cross-calibration factor prior to phantom delivery was obtained by performing with 200 monitor units (MU) on the field size of $95{\times}92.5mm^2$. After irradiation, the measured dose distribution of the coronal plane was compared with the dose distribution calculated by the MultiPlan treatment planning system. The results were assessed by comparing the absolute dose at the center point of 1000SRS and the 3-D Gamma (${\gamma}$) index using 220 patient-specific quality assurance (QA). The discrepancy between measured and calculated doses at the center point of 1000SRS detector ranged from -3.9% to 8.2%. In the dosimetric comparison using 3-D ${\gamma}$-function (3%/3 mm criteria), the mean passing rates with ${\gamma}$-parameter ${\leq}1$ were $97.4%{\pm}2.4%$. The combination of the 1000SRS detector and RW3 slab phantom can be utilized for dosimetry validation of patient-specific QA in the CyberKnife MLC system, which made it possible to measure absolute dose distributions regardless of tracking mode.

Groundwater Recharge Estimation for the Gyeongan-cheon Watershed with MIKE SHE Modeling System (MIKE SHE 모형을 이용한 경안천 유역의 지하수 함양량 산정)

  • Kim, Chul-Gyum;Kim, Hyeon-Jun;Jang, Cheol-Hee;Im, Sang-Jun
    • Journal of Korea Water Resources Association
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    • v.40 no.6 s.179
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    • pp.459-468
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    • 2007
  • To estimate the groundwater recharge, the fully distributed parameter based model, MIKE SHE was applied to the Gyeongan-cheon watershed which is one of the tributaries of Han River Basin, and covers approximately $260km^2$ with about 49 km main stream length. To set up the model, spatial data such as topography, land use, soil, and meteorological data were compiled, and grid size of 200m was applied considering computer ability and reliability of the results. The model was calibrated and validated using a split sample procedure against 4-year daily stream flows at the outlet of the watershed. Statistical criteria for the calibration and validation results indicated a good agreement between the simulated and observed stream flows. The annual recharges calculated from the model were compared with the values from the conventional groundwater recession curve method, and the simulated groundwater levels were compared with the observed values. As a result, it was concluded that the model could reasonably simulate the groundwater level and recharge, and could be a useful tool for estimating spatially/temporally the groundwater recharges, and enhancing the analysis of the watershed water cycle.

Drought Forecasting Using the Multi Layer Perceptron (MLP) Artificial Neural Network Model (다층 퍼셉트론 인공신경망 모형을 이용한 가뭄예측)

  • Lee, Joo-Heon;Kim, Jong-Suk;Jang, Ho-Won;Lee, Jang-Choon
    • Journal of Korea Water Resources Association
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    • v.46 no.12
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    • pp.1249-1263
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    • 2013
  • In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

Development of water circulation status estimation model by using multiple linear regression analysis of urban characteristic factors (도시특성 요인의 다중선형회귀 분석을 이용한 물순환상태추정모델 개발)

  • Kim, Youngran;Hwang, Seonghwan;Lee, Yunsun
    • Journal of Korean Society of Water and Wastewater
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    • v.34 no.6
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    • pp.503-512
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    • 2020
  • Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

Characteristics of KOMPSAT-3A Key Image Quality Parameters During Normal Operation Phase (정상운영기간동안의 KOMPSAT-3A호 주요 영상 품질 인자별 특성)

  • Seo, DooChun;Kim, Hyun-Ho;Jung, JaeHun;Lee, DongHan
    • Korean Journal of Remote Sensing
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    • v.36 no.6_2
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    • pp.1493-1507
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    • 2020
  • The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

Airborne Hyperspectral Imagery availability to estimate inland water quality parameter (수질 매개변수 추정에 있어서 항공 초분광영상의 가용성 고찰)

  • Kim, Tae-Woo;Shin, Han-Sup;Suh, Yong-Cheol
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.61-73
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    • 2014
  • This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

Simultaneous Determination of Aminoglycoside Antibiotics in Meat using Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS를 이용한 육류 중 아미노글리코사이드계 항생제 9종의 동시분석 및 적용성 검증)

  • Cho, Yoon-Jae;Choi, Sun-Ju;Kim, Myeong-Ae;Kim, MeeKyung;Yoon, Su-Jin;Chang, Moon-Ik;Lee, Sang-Mok;Kim, Hee-Jeong;Jeong, Jiyoon;Rhee, Gyu-Seek;Lee, Sang-Jae
    • Journal of Food Hygiene and Safety
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    • v.29 no.2
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    • pp.123-130
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    • 2014
  • A simultaneous determination was developed for 9 aminoglycoside antibiotics (amikacin, apramycin, dihydrostreptomycin, gentamicin, hygromycin B, kanamycin, neomycin, spectinomycin, and streptomycin) in meat by liquid chromatography tandem mass spectrometry (LC-MS/MS). Each parameter was established by multiple reaction monitoring in positive ion mode. The developed method was validated for specificity, linearity, accuracy, and precision based on CODEX validation guideline. Linearity was over 0.98 with calibration curves of the mixed standards. Recovery of 9 aminoglycosides ranged on 60.5~114% for beef, 60.1~112% for pork and 63.8~131% for chicken. The limit of detection (LOD) and limit of quantification (LOQ) were 0.001~0.009 mg/kg and 0.006~0.03 mg/kg, respectively in livestock products including beef, pork and chicken. This study also performed survey of residual aminoglycoside antibiotics for 193 samples of beef, pork and chicken collected from 9 cities in Korea. Aminoglycosides were not found in any of the samples.