• The Journal of Korean Society for Radiation Therapy
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• v.18 no.1
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• pp.1-5
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• 2006

Purpose: IMRT quality assurance(Q.A) is consist of the absolute dosimetry using ionization chamber and relative dosimetry using the film. We have in general used 0.015 cc ionization chamber, because small size and measure the point dose. But this ionization chamber is too small to give an accurate measurement value. In this study, we have examined the degree of calculated to measured dose difference in intensity modulated radiotherapy(IMRT) based on the observed/expected ratio using various kinds of ion chambers, which were used for absolute dosimetry. Materials and Methods: we peformed the 6 cases of IMRT sliding-window method for head and neck cases. Radiation was delivered by using a Clinac 21EX unit(Varian, USA) generating a 6 MV x-ray beam, which is equipped with an integrated multileaf collimator. The dose rate for IMRT treatment is set to 300 MU/min. The ion chamber was located 5cm below the surface of phantom giving 100cm as a source-axis distance(SAD). The various types of ion chambers were used including 0.015cc(pin point type 31014, PTW. Germany), 0.125 cc(micro type 31002, PTW, Germany) and 0.6 cc(famer type 30002, PTW, Germany). The measurement point was carefully chosen to be located at low-gradient area. Results: The experimental results show that the average differences between plan value and measured value are ${\pm}0.91%$ for 0.015 cc pin point chamber, ${\pm}0.52%$ for 0.125 cc micro type chamber and ${\pm}0.76%$ for farmer type 0.6cc chamber. The 0.125 cc micro type chamber is appropriate size for dose measure in IMRT. Conclusion: IMRT Q.A is the important procedure. Based on the various types of ion chamber measurements, we have demonstrated that the dose discrepancy between calculated dose distribution and measured dose distribution for IMRT plans is dependent on the size of ion chambers. The reason is small size ionization chamber have the high signal-to-noise ratio and big size ionization chamber is not located accurate measurement point. Therefore our results suggest the 0.125 cc farmer type chamber is appropriate size for dose measure in IMRT.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.238-249
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• 2019

The evapotranspiration is estimated based on weather factors such as temperature, wind speed and humidity, and the Hargreaves equation is a simple equation for calculating evapotranspiration using temperature data. However, the Hargreaves equation tends to be underestimated in areas with wind speeds above 3 m s^-1 and overestimated in areas with high relative humidity. The study was conducted to determine Hargreaves equation coefficient in 82 regions in Korea by comparing evapotranspiration determined by modified Hargreaves equation and the Penman-Monteith equation for the time period of 2008~2018. The modified Hargreaves coefficients for 50 inland areas were estimated to be 0.00173~0.00232(average 0.00196), which is similar to or lower than the default value 0.0023. On the other hand, there are 32 coastal areas, and the modified coefficients ranged from 0.00185 to 0.00303(average 0.00234). The east coastal area was estimated to be similar to or higher than the default value, while the west and south coastal areas showed large deviations by area. As results of estimating the evapotranspiration by the modified Hargreaves coefficient, root mean square error(RMSE) is reduced from 0.634~1.394(average 0.857) to 0.466~1.328(average 0.701), and Nash-Sutcliffe Coefficient(NSC) increased from -0.159~0.837(average 0.647) to -0.053~0.910(average 0.755) compared with original Hargreaves equation. Therefore, we confirmed that the Hargreaves equation can be overestimated or underestimated compared to the Penman-Monteith equation, and expected that it will be able to calculate the high accuracy evapotranspiration using the modified Hargreaves equation. This study will contribute to water resources planning, irrigation schedule, and environmental management.

• Tuberculosis and Respiratory Diseases
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• v.46 no.6
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• pp.846-855
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• 1999

Background : Secondary pulmonary hypertension is an important final endpoint in patients with chronic hypoxic lung disease, accompanied by deterioration of pulmonary hemodynamics. The clinical diagnosis of pulmonary hypertension and/or cor pulmonale could be difficult, and simple noninvasive evaluation of pulmonary artery pressures has been an relevant clinical challenge for many years. Doppler echocardiography might to be a more reliable method for evaluating pulmonary hemodynamics in such patients in terms of the accuracy, reproducibility and easiness for obtaining an appropriate echocardiographic window than M-mode echocardiography. The aim of this study was to assess echocardiographic parameters associated with pulmonary arterial hypertension, defined by increasing right ventricular systolic pressure(RVSP), calculated from trans-tricuspid gradient in patients with chronic hypoxic lungs. Method : We examined 19 patients with chronic hypoxic lung disease, suspected pulmonary hypertension under the clinical guidelines by two dimensional echocardiography via the left parasternal and subcostal approach in a supine position. Doppler echocardiography measured RVSP from tricuspid regurgitant velocity in continuous wave with 2.5MHz transducer and acceleration time(AT) on right ventricular outflow tract in pulsed wave for the estimation of pulmonary arterial pressure. Results : On echocardiography, moderate to severe degree of pulmonary arterial hypertension was defined as RVSP more than 40mmHg, presenting tricuspid regurgitation. Increased right ventricular endsystolic diameter and shortened AT were noted in the increased RVSP group. Increased RVSP was correlated negatively with the shortening of AT. Other clinical data, including pulmonary functional parameters, arterial blood gas analysis and M mode echocardiographic parameters were not changed significantly with the increased RVSP. Conclusion : These findings suggest that shortened AT on pulsed doppler can be useful when quantifying pulmonary arterial pressure with increased RVSP in patients with chronic lung disease with hypoxemia. Doppler echocardiography in pulmonary hypertension of chronic hypoxic lungs is an useful option, based on noninvasiveness under routine clinical practice.

• Korean Journal of Poultry Science
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• v.43 no.2
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• pp.111-118
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• 2016

Mycotoxins are secondary metabolites produced by molds, such as Aspergillus, Fusarium and Penicillium, that have adverse effects on animals and humans. Aflatoxin, ochratoxin, zearalenone, fumonisin and deoxynivalenol are the mycotoxins of greatest agro-economic importance and cause acute disease called mycotoxicoses. Mycotoxicosis in poultry birds results in decreased meat/egg production, immunosuppressant, and hepatotoxicosis. Some of toxins or their metabolites may be retained in animal or human tissues and induce health problems. This study was designed to develop a sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous detection and quantification of mycotoxins, such as aflatoxin $B_1$, aflatoxin $M_1$, ochratoxin A, zearalenone, fumonisin B and deoxynivalenol, in chicken liver and kidney tissues. The mycotoxins were extracted and purified using modified QUECHERS methods, separated by LC and detected by an electrospray ionisation interface (ESI) and tandem MS. Good precision and linearity were observed for most of six mycotoxins. The recovery test for each mycotoxin in liver and kidney tissues mostly indicated good average recovery rates between 80.94% and 98.10% and the coefficient of variation mostly under 13.78%, except for aflatoxin $M_1$ and fumonisin $B_1$. The limit of detection (LOD) for six mycotoxins was $7.6{\sim}145.79{\mu}g/kg$ in liver tissues and $6.07{\sim}197.20{\mu}g/kg$ in kidney tissues. The quantification limits (LOQ) for 6 mycotoxins were in the range $23.04{\sim}441.78{\mu}g/kg$ in liver tissues and $18.40{\sim}597.59{\mu}g/kg$ in kidney tissues, respectively. The developed multi-mycotoxin method in this study permits simultaneous, simple, and rapid determination of several co-existing mycotoxins in chicken liver and kidney tissues.

• Journal of Food Hygiene and Safety
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• v.33 no.2
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• pp.124-130
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• 2018

The Ministry of Food and Drug Safety (MFDS) is amending its test methods for the use of health functional foods (dietary food supplement), in order to establish regulatory standards and specifications in Korea. In this regard, we continue to pursue and perform our research on the analytical method development for the items being researched and reviewed. In this study, we have developed a sensitive and selective test method that could simultaneously separate and determinate six major bioactive flavonolignans in silymarin, which are based on the use of a liquid chromatographic-tandem mass spectrometry (LC-MS/MS). The standard calibration curves presented a linearity effect with the correlation coefficient ($r^2$) > 0.999. The limits of detection (LODs) and limits of quantitation (LOQs) were in the range of $0.3{\sim}9.0{\mu}g/L$ and $0.8{\sim}27.3{\mu}g/L$, respectively. The recovery results ranged between 96.2~98.6% at 3 different concentration levels, and its relative standard deviations (RSDs) were less than 5% as noted in this study. The proposed analytical method was characterized with a noted high resolution of the individual silymarin constituents, and the assay was fully validated as well. Our research can provide a significant scientific evidence that can be useful to amend the silymarin test method for the Health Functional Food Code.

• Journal of Korean Society of Forest Science
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• v.34 no.1
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• pp.21-30
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• 1977

Japanese larch (Larix leptolepis) is one of main timber species in Korea that could find much plantation and growing stands on all over the country. It is thought to be in meaningful that a guiding diagram for density control of Japanese larch stands is made to estimate easily the density conditions in the quantitaive, ecological and economic viewpoint. Sample plots for this study are selected from the stands that have not been thinned in recent years, and mean height, mean diameter, dominant height, tree numbers per hectare and stem volume of mean tree are calculated from the each sample plots among total 165 plots In this study, especially, the theory of slenderness of mean tree are applied, that have been identified through the results of the spacing trial. Relative growth characteristics of this species are calculated from the general logistic curve and its formula is $Y=ax^b$. Relatwion between the measured items are found out as follows: 1. Relation between the mean height and tree numbers per hectare by slender class is showing the high correlation as table 1 and fig. 2, and between mean diameter and tree numbers per hectare is also high correlation as table 1 and fig 3. 2. The stem volume can be correctly estimated from height in case that slender class may be known, as showing in table 3 and fig. 4. 3. The stem volume can be more correctly estimated from the relation with $D^2H$ as formula, $Log_e\;V=0.9569\;Log_eD^2H-9.8431$, and relation between stem volume of single tree or volume per hectare and tree numbers per hectare are as following formulas: $Log_e$ stem volume=9.5026-1.6800 $Log_e$ tree numbers per hectare $Log_e$ stem volume per hectare=9.4911-0.6784 $Log_e$ tree numbers per hectare. Stem volume of mean tree, tree numbers per hectare and stem volume per hectare correspond to the mean tree height are calculated to slender class as table 5, 6, 7. Through the above steps, the diagram for density control of Japanese larch are produced as fig. 9. It is thought that this diagram could be applied to control the density of Japanese larch stands.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.19-25
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• 2019

The CleanSYS(Clean SYStem) is operated to monitor air pollutants emitted from specific industrial complexes in Korea. So the industrial complexes without the system are directly monitored by the control officers. For efficient monitoring, studies using various sensors have been conducted to monitor air pollutants emitted from industrial complex. In this study, hyperspectral sensors were used to model and verify the equations for estimating the concentration of $NO_2$(nitrogen dioxide) in air pollutants emitted. For development of the equations, spectral radiance were observed for $NO_2$ at various concentrations with different SZA(Solar Zenith Angle), VZA(Viewing Zenith Angle), and RAA(Relative Azimuth Angle). From the observed spectral radiance, the calculated value of the difference between the values of the specific wavelengths was taken as an absorption depth, and the equations were developed using the relationship between the depth and the $NO_2$ concentration. The spectral radiance mixed gas of $NO_2$ and $SO_2$(sulfur dioxide) was used to verify the equations. As a result, the $R^2$(coefficient of determination) and RMSE(Root Mean Square Error) were different from 0.71~0.88 and 72~23 ppm according to the form of the equation, and $R^2$ of the exponential form was the highest among the equations. Depending on the type of the equations, the accuracy of the estimated concentration with varying concentrations is not constant. However, if the equations are advanced in the future, hyperspectral sensors can be used to monitor the $NO_2$ emitted from the industrial complex.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.155-166
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• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.