• Korean Journal of Soil Science and Fertilizer
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• v.18 no.2
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• pp.177-188
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• 1985

To clarify the characteristics and genesis of clayey terrace soils in Yeongnam area, macro-morphological features and soil profile development indexes were investigated with the sequential soils in Yeongcheon (inland region) and in Yeongil (coastal region). The results are summarized as follows; 1. According to the physiogaphy and landuse, the terrace soils were discernible to well drained yellowish red (5 YR) profile of higher terrace (Bancheon series), moderately well drained reddish yellow (7.5 YR) profile of middle terraces (Upyeong and Hwadong series), and lower terraces (Deogpyeong and Geugrag series) which were moderately well to imperfectly drained by paddy-fication. 2. The roundness and sphericity of the gravels contained in the terrace deposits were ranged around 0.543-0.546 and 0.723-0.722, respectively. The rounded to well rounded gravels were resemble to typical alluvial origins. 3. The amount of clay minerals formed in the soil horizons per 100g of parent materials were 50.8-30.7g while the rates of the clay leached were 30.1-7.4%, and the higher terrace had the more leaching rates. 4. The index of profile development of the terrace soils ranged from 37.95 to 22.01 and the index were positively correlated with relative elevations of the soils. The rates of clay leaching were positively correlated with the ratios of clay in the illuvial horizons to elluvial horizons. 5. A similarity was observed among cumulative grain size curves of the terrace soils, but the patterns of recalculated silt free cumulative grain size curve of terrace deposits in Upyeong soils in Yeongil area were abruptly different from down layer that suggest the soil to have bisequum profile.

• 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 Korean Society of Water and Wastewater
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• v.27 no.6
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• pp.689-701
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• 2013

Bacterial growth and corresponding consumption of carbon and phosphorus were examined in which tap water samples containing a very low concentration of free chlorine were supplemented with organic carbon and/or phosphorus. The experiments were performed in a fed-batch mode under a controlled temperature of $20^{\circ}C$. In the phosphorus alone-added water, there was no significant increase in bacterial numbers measured as heterotrophic plate count (HPC) in the bulk water. However, bacterial growth was stimulated by the addition of carbon (e.g., bulk HPC levels increased to $10^3CFU/mL$) and further stimulated by the combined addition of carbon and phosphorus (e.g., bulk HPC to $10^5CFU/mL$). The same effects were observed in biofilm HPC and biomass formed on polyethylene (PE) slide surfaces. In the water where organic carbon and phosphorus were added together, the highest biofilm HPC and biomass (measured as extracellular polymeric substance components) densities were observed which were $7.6{\times}10^5CFU/cm^2$ and $5.3{\mu}g/cm^2$, respectively. In addition to the bacterial growth, additions of organic carbon and/or phosphorus resulted in different bacterial carbon-to-phosphorus (C/P) consumption ratios. Compared to a typical bacterial C/P consumption ratio of 100:1, a higher C/P ratio (590:1) occurred in the carbon alone-added water, while a lower ratio (40:1) in phosphorus alone-added water. Comparative value (80:1) of C/P ratio was also observed in the water where organic carbon and phosphorus were added together. At the given experimental conditions, bacterial growth was deemed to be more sensitive to microbially available organic carbon than phosphorus. The effect of phosphorus addition, which resulted in a lower C/P consumption ratio, seemed to be tightly associated with the presence of microbially available organic carbon. These results suggested that the control of extrinsic carbon influx seemed to be more important to minimize bacterial regrowth in drinking water system, since even low content of phosphorus naturally occurring in drinking water was enough to allow a bacterial growth.

• Korean Journal of Food Science and Technology
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• v.23 no.5
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• pp.554-560
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• 1991

The physicochemical properties of Korean yam starches (D. aimadoimo, D. batatas and D. japonica) were investigated. The mean granular size of starches were 23.5 μm for D. aimadoimo, 23.9 μm for D. batatas and 18.2 μm for D. japonica. Amylose content, blue value and water binding capacity was $29{\sim}33%,\;0.42{\sim}0.51%\;and\;109.9{\sim}118.3%$, respectively. The optical transmittance of 0.3% (dry basis) yam starch suspensions were increased at $70{\sim}75^{\circ}C$ and D. japonica showed typical two-step transmittance curve. The swelling power and solubility patterns increased over $60^{\circ}C$, and D. aimadoimo was the highest values. Amylogram patterns of 5% (dry basis) yam starch suspensions, determined by Brabender amylograph, were similar to that of yam flours and the viscosity of D. aimadoimo had 630 BU, which was about 5 times higher than 130 BU for D. batatas and D. japonica. Observation under scanning electron microscope lefted marks of resistance to glucoamylase because these surfaces were similar to the natural granules. In rates of solubiliazation by dimethyl sulfoxide, D. aimadoimo showed the highest value. (3-Amylolysis limits of yam starches and their amylose were $71.8%{\sim}75.5%\;and\;90.2{\sim}92.1%$, respectively. Gel filtration patterns of debranched amylopectin by pullulanase were divided into 3 peaks. The weight ratios of peak III to peak II in yam starches were $2.15%{\sim}2.42%$.

• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.196-204
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• 1990

Pinus densiflora is not only widely distributed but also one of the most economically important timber species in Korea. In Korea, this species is classified into four local forms according to tree forms, as it has widely geographical variations. Trees of Ankang form are dwarfish nearly like shrubs, and those of Keumkang form are very tall and straight. Those of flatland and highland forms are exhibited in-between Ankang and Keumkang forms. This study was carried out to examine biomass, net production and production efficiency among four local forms of Pirzus densiflora forests growing in Korea. For the study, dimension analysis was used for trees and harvest method for shrubs and herbs in four 30-40 year-old stands showing the typical tree forms. Stand biomass of Ankang, flatland, highland and Keumkang forms were 29.87, 110.89, 133.53 and 205.42 t/ha, respectively. As going in order of Ankang, flatland, highland and Keumkang forms, the proportions of stem woods to total tree biomass increased while the proportions of stem barks, live branches, needles and roots showed a tendency to decrease. Stand net productions of Ankang, flatland, highland and Keumkang forms were 3.716, 10.796, 13.097 and 16.500 t/ha yr., respectively. As going in order of Ankang, flatland, highland and Keumkang forms, the proportions of stem woods and lire branches to total tree net production increased while the proportion of needles decreased. In case of live branches, the opposite trend of biomss and net production proportion may be resulted from the differences in the ratio of self-pruning. Net assimilation ratios of Ankang, flatland, highland and Keumkang forms were 1.406, 1.920, 1.487 and 1.677, respectively. Efficiency of needles to produce stems in those forms were 0.239, 0.714, 0.572 and 0.771, respectively. Considering the difference in measuring time, net assimilation ratio and efficiency of needles to produce stems may increase as going in order of Ankang, flatland, highland and Keumkang forms.