• Journal of radiological science and technology
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• v.40 no.2
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• pp.187-195
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• 2017

Early diagnosis for upper facial trauma is difficult by using the standard Water's view (S-Water's) in general radiograph due to overlapping of anatomical structures, the uncertainty of patient positioning, and specific patients with obese, pediatric, old, or high-risk. The purpose of this study was to analyze appropriate exposure angles through a comparison of two different protocols (S-Water's vs. reverse Water's view (R-Water's)) by using a head phantom. A head phantom and general radiograph with 75 kVp, 400 mA, 45 ms 18 mAs, and SID 100 cm. Images of R-Water's were obtained by different angles in the range of $0^{\circ}$ to $50^{\circ}$, which adjusted an angle at 1 degree interval in supine position. Survey elements were developed and three observers were evaluated with four elements including the maxillary sinus, zygomatic arch, petrous ridge, and image distortion. Statistical significant analysis were used the Krippendorff's alpha and Fleiss' kappa. The intra-class correlation (ICC) coefficient for three observers were high with maxillary, 0.957 (0.903, 0.995); zygomatic arch, 0.939 (0.866, 0.987); petrous ridge, 0.972 (0.897, 1.000); and image distortion, 0.949 (0.830, 1.000). The high-quality image (HI) and perfect agreement (PA) for acquired exposure angles were high in range of the maxillary sinus ($36^{\circ}-44^{\circ}C$), zygomatic arch ($33^{\circ}-40^{\circ}$), petrous ridge ($32^{\circ}-50^{\circ}$), and image distortion ($44^{\circ}-50^{\circ}$). Consequently, an appropriate exposure angles for the R-Water's view in the supine position for patients with facial trauma are in the from $36^{\circ}$ to $40^{\circ}$ in this phantom study. The results of this study will be helpful for the rapid diagnosis of facial fractures by simple radiography.

• Horticultural Science & Technology
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• v.30 no.6
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• pp.700-708
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• 2012

In order to optimize a method to determine the firmness of Chinese cabbage, hardness of midrib tissues was examined based on their chronological order of emergence. Texture measurement using volodkevich bite jaws gave a consistent and highest regression ($r^2=0.85$) between firmness and the order of leaf emergence, while blade set, cylinder probe, and crisp fracture support rig showed a lower coefficient of determination. Thickness of midrib tissue within an individual head from 16 cultivars of Chinese cabbage was positively correlated with the order of emergence, becoming thinner toward inner leaves. Mean thickness of midrib tissue from the head ranged from 7.74 mm for 'CR-shingshing' and 9.28 mm for 'Norangyeorum'. The covariance of leaf thickness within a head was highly cultivar-dependent, ranging from 23.6% for 'Chihili' and 5.8% for 'Bulam'. Firmness of the midrib tissue, defined as maximum peak height per tissue thickness, became higher from outer to inner leaves, showing $2^{nd}$ order of regression. Mean firmness of the midrib tissue from individual head varied from 1.58 N for 'Rangno' to 3.46 N for 'CR-shingshing'. The $10^{th}$ or $11^{th}$ leaf brought the best correlation coefficient (r = 0.81) between firmness of an individual leaf and the mean firmness of the entire leaves in a head, suggesting a reliable and rapid method to estimate the firmness of a head in lieu of examining all leaves in the head. The relationship between firmness of midrib tissue and dry mass ($r=0.70^{**}$) as well as cell wall content ($r=0.58^*$) of the head were positively correlated. Results obtained from the present study suggested that a new method to determine midrib firmness would enable to clarify the relationship between textural quality of fresh Chinese cabbage and their processed product, 'Kimchi'. It will also be important to apply this method to screen textural quality of various genotypes under breeding programs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.209-221
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• 2006

The purpose of this study is to analyze the effects of climate change on the nonpoint source pollution in a small watershed using a mid-range model. The study area is a basin in a rural area that covers 384 ha with a composition of 50% forest and 19% paddy. The hydrologic and water quality data were monitored from 1996 to 2004, and the feasibility of the GWLF (Generalized Watershed Loading function) model was examined in the agricultural small watershed using the data obtained from the study area. As one of the studies on climate change, KEI (Korea Environment Institute) has presented the monthly variation ratio of rainfall in Korea based on the climate change scenario for rainfall and temperature. These values and observed daily rainfall data of forty-one years from 1964 to 2004 in Suwon were used to generate daily weather data using the stochastic weather generator model (WGEN). Stream runoff was calibrated by the data of $1996{\sim}1999$ and was verified in $2002{\sim}2004$. The results were determination coeff, ($R^2$) of $0.70{\sim}0.91$ and root mean square error (RMSE) of $2.11{\sim}5.71$. Water quality simulation for SS, TN and TP showed $R^2$ values of 0.58, 0.47 and 0.62, respectively, The results for the impact of climate change on nonpoint source pollution show that if the factors of watershed are maintained as in the present circumstances, pollutant TN loads and TP would be expected to increase remarkably for the rainy season in the next fifty years.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.1082-1090
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• 2005

Jocheong was prepared by adding Lentinus edodes extract to improve its quality and to give some functional properties. Contents of crude protein, ash and crude lipid were similar to those of control, while carbohydrate content was decreased. Total mineral content were $1,916.03\~2,674.24mg/kg$ that was no difference between test samples. From HPLC determination of free sugars, Jocheong was found to contain maltose as the highest sugar, followed by glucose and fructose. In amino acid analysis, seventeen amino acid were identified and quantified. Glutamic acid in Jocheong was major amino acid. The major fatty acids in Jocheong $(0\%,\;control)$ were linoleic acid, palmitic acid, oleic acid, myristic acid and caproic acid. There was no significant differences in fatty acid composition, pH and reducing sugar content among the Jocheong samples. The viscosity and solid contents tended to decrease with the addition of Lentinus edodes extract. Increasing the ratio of mushroom extract in Jocheong tended to decrease the lightness, yellowness and redness in Hunter's color value. Although sensory value decreased with increasing Lentinus edodes extracts, use of mushroom extracts (7: 3; saccharification liquids: Lentinus edodes extracts) is recommended for making Jocheong.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.434-451
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• 2017

For this study, groundwater samples for 3 years from 2011 through 2013 were collected at 106 groundwater monitoring site in Korea. These groundwater samples were analyzed for 13 pesticides such as cabofuran, pentachlorobenzene, hexachlorobenzene, simazine, atrazine, lindane (gamma-HCH), alachlor, heptachlor, chlordane (total), endosulfan (1, 2), dieldrin, endrin, 4,4-DDT. The objectives of this study were to determine the detection frequency and their concentrations of 13 pesticides and evaluate the health risk level considering ingestion, inhalation, and skin contact using concentrations of 13 pesticides in groundwater samples. An analysis was used for the simultaneous determination for 13 pesticides using GC-MS. GC-MS was performed on HP-5ms, using helium ($1ml\;min^{-1}$) as carrier gas. The average recoveries of the pesticides were from 92.8% to 120.8%. The limits of detection (LODs) were between $0.004{\mu}g\;L^{-1}$ and $0.118{\mu}g\;L^{-1}$ and the limits of quantification (LOQs) were between $0.012{\mu}g\;L^{-1}$ and $0.354{\mu}g\;L^{-1}$. 106 groundwater wells were selected. 54 wells were from well to monitor background groundwater quality and 52 wells were from well to monitor groundwater quality in industrial or contamination source area. Eight pesticides including pentachlorobenzene, lindane (Gamma-HCH), heptachlor, chlordane (total), Endosulfan (1, 2), dieldrin, endrin, and 4,4-DDT were not detected in groundwater samples. The detection frequency for hexachlorobenzene, alachlor, carbofuran and simazine was 23.4%, 11.4%, 7.3%, and 1.0%, respectively. Atrazine was detected once in 2011. The average concentrations were $0.00423{\mu}g\;L^{-1}$ for carbofuran, $0.000243{\mu}g\;L^{-1}$ for alachlor, $0.00015{\mu}g\;L^{-1}$ for simazine, and $0.00001{\mu}g\;L^{-1}$ for hexachlorobenzene. The detection frequency of hexachlorobenzene was high, but the average concentration was low. In the contaminated groundwater, the detection frequency for hexachlorobenzene, alachlor, carbofuran, simazine and atrazine was 26.1%, 21.3%, 7.1%, 1.9% and 0.3%, respectively. In the uncontaminated groundwater, detection frequency for hexachlorobenzene, carbofuran and alachlor were 20.2%, 7.5%, and 1.9% respectively. Simazine and atrazine were not detected at uncontaminated groundwater wells. According to the purpose of groundwater use, atrazine was detected for agricultural groundwater use. Hexachlorobenzene showed high detection frequency at agricultural groundwater use area where the animal feeding area and golf course area were located. Alachlor showed more than 50% detection frequency at cropping area, pollution concern river area, and golf course area. Atrazine was detected in agricultural water use area. By land use, the maximum detection frequency of alachlor was found near an orchard. For human risk assessment, the cancer risk for the 5 pesticides was between $10^{-7}$ and $10^{-10}$, while the non-cancer risk (HQ value) was between $10^{-4}$ and $10^{-6}$. For conclusion, these monitoring study needs to continue because of the possibility of groundwater contamination based on various purpose of groundwater use.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.2
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• pp.75-82
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• 2008

In order to establish environmentally friendly phosphorus(P) and potassium(K) fertilizer application rates for rice cultivation in Korea, a field experiment was conducted in two different characterized paddy soils, higher and lower P and K content in soil from 2005 to 2006 in Suwon, Korea. Chuchong which is typical rice variety in Korea, was selected for experiment. Rice yields in base P-K fertilizer level ($30-30kg\;ha^{-1}$) and no P-K fertilizer level were 97~98% and 93~97% of standard P-K fertilizer level ($45-57kg\;ha^{-1}$), respectively. At the lower content of P and K in immatured paddy soil, the yield of no P plot was decreased by 7% compared to that of standard P-K plot. Significant difference in rice yield and yield characteristics was found neither in standard P-K fertilization plot nor in base P-K fertilization plot. There was no significant difference in P and K uptake at the harvest stage between standard P-K fertilizer plot and base P-K fertilizer plot. Phosphorus and K uptake was slightly decreased in no fertilizer plots compared to standard fertilizer plot. Phosphorus and K use efficiency of rice plant in base fertilizer plot was higher than that in standard fertilizer plot. Available phosphorus and exchangeable potassium content in soil at the harvest stage were increased in both standard and base fertilizer plot. But no significant difference of P and K content in ? was found between standard fertilizer plot and base fertilizer plot. Rice quality characteristics such as proportion of brewers rice, damaged kernel, broken rice, and content of amylose and protein were lowered in the base fertilizer plot than the standard fertilized plot, while the proportion of perfect kernel increased in the base fertilizer plot From the results, we generally recommend the base P-K fertilization ($30-30kg\;ha^{-1}$) instead of standard P-K fertilization ($45-57kg\;ha^{-1}$) for rice cultivation in Korea.

• The Korean Journal of Nuclear Medicine
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• v.34 no.4
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• pp.336-343
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• 2000

Purpose: Thallous-201 chloride produced at Korea Cancer Center Hospital(KCCH) is used in detecting cardiovascular disease and cancer. Thallium impurity can cause emesis, catharsis and nausea, so the presence of thallium and other metal impurities should be determined. According to USP and KP, their amounts must be less than 2 ppm in thallium and 5 ppm in total. In this study, the detection method of trace amounts of metal impurities in $[^{201}Tl]$TICI injection with polarography was optimized without environmental contamination. Materials and Methods: For the detection of metal impurities, Osteryoung Square Wave Stripping Voltammetry method was used in Bio-Analytical System (BAS) 50W polarograph. The voltammetry was composed of Dropping Mercury Electrode (DME) as a working electrode, Ag/AgCl as a reference electrode and Pt wire as a counter electrode. Square wave stripping method, which makes use of formation and deformation of amalgam, was adopted to determine the metal impurities, and pH 7 phosphate buffer was used as supporting electrolyte. Results: Tl, Cu and Pb in thallous-201 chloride solution were detected by scanning from 300 mV to -800 mV Calibration curves were made by using $TINO_3,\;CuSO_4\;and\;Pb(NO_3){_2}$ as standard solutions. Tl was confirmed at -450 mV peak potential and Cu at -50 mV Less than 2 ppm of Tl and Cu was detected and Pb was not detected in KCCH-produced thallous-201 chloride injection. Conclusion: Detection limit of thallium and copper is approximately 50 ppb with this method. As a result of this experiment, thallium and other metal impurities in thallous-201 chloride injection, produced at Korea Cancer Center Hospital, are in the regulation of USP and KP Polarograph could be applied for the determination of metal impurities in the quality control of radiopharmaceuticals conveniently without environmental contamination.

• 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.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.687-696
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• 2015

Black mini tomato 'Hei-G' fruits were harvested at different stages of maturity (immature-mature green and mature-black red) and stored at different temperatures (8, 12, and $20^{\circ}C$) to investigate the quality and lycopene content during storage. Weight loss increased dramatically at higher temperature for both harvesting stages without significant differences. Firmness of immature fruits decreased below the initial level of mature fruit (8.1N) after 5, 8, and 19 days storage, when they were stored at 20, 12, and $8^{\circ}C$, respectively. Soluble solid contents of mature fruit increased at initial storage, and were higher as compared to immature fruits before deterioration at each storage temperature. Decrease in titratable acid of mature fruits depended on storage time and temperature. However, titratable acid of immature fruits showed little change during storage, and so it did not affect flavor. Hunter a value changed greatly in immature fruit stored at high temperature. Unlike ripe tomatoes, there was no significant difference in black tomato Hunter b values of immature and mature fruit at initial and 12 days storage. However, immature fruits stored at $8^{\circ}C$ did not reach full maturity and color development and ripening. High storage temperature increased lycopene production while low storage temperature blocked lycopene development. Shelf life of the immature fruits, which was evaluated by elapsed days to conventional mature stage, was 12 and 15 days when they were stored at 20 and $12^{\circ}C$, respectively. The optimum storage temperature to maintain the quality and lycopene content of mature fruits was $12^{\circ}C$. Moreover, the shelf life of mature fruits stored at $20^{\circ}C$ could reach up to 5 days.