• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.19-24
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• 2004

Introduction : The Vaginal, the urethra, the vulva and anal cancer avoid the many dose to femur head and the additional treatment is necessary in inguinal LN. The partial transmission block to use inguinal LN addition there is to a method which it treats and produce partial transmission block a method and the MLC which to it analyzes. Material & Methode : The Inguinal the LN treatment patient partial transmission it used block and the MLC in the object and with solid water phantom with the patient it reappeared the same depth. In order to analyze the error of the junction the EDR2 (Extended dose range, the Kodak and the U.S) it used the Film and it got film scanner it got the beam profile. The partial transmission block and the MLC bias characteristic, accuracy and stability of production for, it shared at hour and comparison it analyzed. Result : The partial the transmission block compares in the MLC and the block production is difficult and production hour also above 1 hours. The custom the block the place where it revises the error of the junction is a difficult problem. If use of the MLC the fabrication will be break and only the periodical calibration of the MLC it will do and it will be able to use easily. Conclusion : The Inguinal there is to LN treatment and partial transmission block and the MLC there is efficiency of each one but there is a place where the junction of block for partial transmission block the production hour is caught long and it fixes and a point where the control of the block is difficult. like this problem it transfers with the MLC and if it treats, it means the effective treatment will be possible.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Analytical Science and Technology
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• v.31 no.2
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• pp.96-105
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• 2018

This study aimed to improve the method for detecting eight secondary aliphatic amines (SAAs), so as to measure their concentrations in fresh water and tap water samples. NaOH (8 mL, 10 M) and benzenesulfonyl chloride (2 mL) were added to a water sample (200 mL), and the mixture was stirred at $80^{\circ}C$ for 30 min. An additional NaOH solution (10 mL) was added and the stirring was continued for another 30 min. The pH of the cooled mixture was adjusted to 5.5-6.0 by adding HCl (35 %), and the SAAs were extracted using dichloromethane (50 mL). This extraction was repeated once. The extract was then washed with $NaHCO_3$ (15 mL, 0.05 M) and dried over $Na_2SO_4$ (4 g). The extract was finally concentrated to 0.1 mL, of which $1{\mu}L$ was analyzed for SAAs by GC-MS. The linearity of the spike calibration curves was high ($r^2=0.9969-0.9996$). The detection limits of the method ranged from 0.01 to $0.20{\mu}g/L$, and its repeatability and reproducibility (expressed as relative standard deviation) were both less than 10 % (6.6-9.4 %). Its accuracy (measured in percentage error) ranged between 2.4 % and 6.1 %. The established method was applied to the analysis of five surface water and 82 tap water samples. Dimethylamine was the only SAA detected in all the water samples, and its average concentration was $0.79{\mu}g/L$ (range: $0.20-2.54{\mu}g/L$). Therefore, this study improved the analytical method for SAAs in surface water and tap water, and the regional and seasonal concentration distributions were obtained.

• The Journal of Korean Society for Radiation Therapy
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• v.17 no.2
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• pp.133-140
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• 2005

Purpose : This test is designed to identify the validity of treatment plan by implementing real-time dosimetry by means of dose that is absorbed into PTV and OAR when preparing doses of 3D and POP plans. Materials and Methods : In treatment. error can be calculated be comparing Exp. Dose with the actual dose, which has been converted from 'the reading value obtained by placing diode detector on the area to be measured'. Same test can be repeated using Alderson-Rando phantom. Results : Errors were found: A patient(POP plan): 197.6/199=-1.2%, B patient(3D-plan): 199.9/198.7=+0.6%, C patient: 196/200=-1.5%. In addition, considering the resulted value of measuring OAR besides target-dose for C patient showed 96/200, representing does of 47%, the purpose of protection was judged to be duly accomplished. Also it was acknowledged the resulted value of -3.7% met the targeted dose within the range of ${\pm}5%$. Conclusion : Aimed for identifying the usefulness of pre-treatment dose measurement using diode detector, this test was useful to evaluate the validity of curing because it resulted in the identification of category to be protected as well as t dose. Moreover, it is thought to have great advantage in ascertaining the dose of target, dose of which is not calculated yet. Similar to L-gram before treatment, this test is thought to be very effective so that it can bring great advantages in the aspects such as validity of curing method and post-treatment plan as well.

• Korean Journal of Food Science and Technology
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• v.36 no.5
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• pp.701-710
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• 2004

Uncertainty was quantified to evaluate calcium determination result in infant formula with AAS (Atomic Absorption Spectrometry) and ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry). Uncertainty sources in measurand, such as sample weight, final volume of sample, sample dilution and the instrumental result were identified and used as parameters for combined standard uncertainty based on the GUM (Guide to the expression of uncertainty in measurement) and Draft EURACHEM/CITAC Guide. Uncertainty components of each sources in measurand were identified as resolution, reproducibility and stability of chemical balance, standard material purity, standard material molecular weight, standard solution concentration, standard solution dilution factor, sample dilution factor, calibration curve, recovery, instrumental precision, reproducibility, and stability, Each uncertainty components were evaluated by uncertainty types and included to calculate combined uncertainty. The kinds of uncertainty sources and components in the analytical method by AAS and ICP-AES were same except sample dilution factor for AAS. The analytical results and combined standard uncertainties of calcium content were estimated within the certification range $(367{\pm}20\;mg/100g)$ of CRM (Certified Reference Material) and were not significantly different between method by AAS followed by ashing and method by ICP-AES followed by acid digestion as $359.52{\pm}23.61\;mg/100g\;and\;354.75{\pm}16.16\;mg/100g$, respectively. Identifying uncertainty sources related with precision, repeatability, stability, and maintaining proper instrumental conditions as well as personal proficiency was needed to reduce analytical error.