• 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.

• Progress in Medical Physics
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• v.9 no.4
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• pp.227-245
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• 1998

A most appropriate model of 3-D conformal radiotherapy has been induced by clinical evaluation and animal study, and therapeutic gains were evaluated by numerical equation of tumor control probability(TCP) and normal tissue complication probability (NTCP). The radiation dose to the tumor and the adjacent normal organs was accurately evaluated and compared using the dose volume histogram(DVH). The TCP and NTCP was derived from the distribution of given dosage and irradiated volume, and these numbers were used as the biological index for the assessment of the treatment effects. Ten patients with liver disease have been evaluated and 3 dogs were sacrificed for this study. Based on the 3-D images of the tumor and adjacent organs, the optimum radiation dose and the projection direction which could maximize the radiation effect while minimizing the effects to the adjacent organs could be decided. 3). The most effective collimation for the normal adjacent organs was made through the beams eye view with the use of multileaf collimator. When the dose was increased from 50Gy to 70Gy, the TCP for the conventional 2-port radiation and the 5-port multidimensional therapy was 0.982 and 0.995 respectively, while the NTCP was 0.725 and 0.142 respectively, suggesting that the 3-D conformal radiotherapy might be the appropriate therapy to apply sufficient radiation dose to the tumor while minimizing the damages to the normal areas of the liver. Positive correlation was observed between the NTCP and the actual complication of the normal liver in the animal study. The present study suggest that the use of 3-D conformal radiotherapy and the application of the mathematical models of TCP and NTCP may provide the improvements in the treatment of hepatoma with enhanced results.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.6
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• pp.302-308
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• 2006

Purpose: Although several neuroanatomical models of panic disorder have been proposed, little is known regarding the neurological mechanisms underlying cognitive-behavioral therapy (CBT) in patients with panic disorder. This study was performed to identify the brain structures that show changes of regnioal cerebral blood flow (rCBF) after CBT in patients with panic disorder. Materials and Methods: Seven patients who were diagnosed as panic disorder by DSM-IV were treated with CBT for 8 weeks and twelve healthy volunteers joined in this study. Serial $^{99m}Tc-ECD$ brain perfusion SPECT images were acquisited and PDSS-SR (Self-Report version of Panic Disorder Severity Scale) and ACQ (Agoraphobic Cognitive Question) scores were measured just before and after CBT in all patients. Data were analyzed using SPM2. Results: Subjective symptoms were improved, and PDSS-SR and ACQ scores were significantly reduced ($14.9{\pm}3.9\;vs.\;7.0{\pm}1.8$, p<0.05; $30.3{\pm}8.5\;vs.\;21.6{\pm}3.4$, p<0.05, respectively) after CBT in panic patients. Before CBT, a significant increase of rCBF was found in the cingulate gylus, thalamus, midbrain, both medial frontal and temporal lobes of the panic patients compared to the normal volunteers. After CBT, we observed a significant rCBF decrease in the left parahippocamus, right insula and cingulate gyrus, both frontal and temporal lobes, and a significant rCBF increase in both the occipital lobes, left insula, both frontal and left parietal lobes. Conclusion: These data suggested that CBT is effective for panic disorder and diminish the activity of the brain areas associated with fear in panic disorder.

• Journal of Distribution Science
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• v.9 no.1
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• pp.5-15
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• 2011

Research regarding corporate associations in marketing has generally been approached using the association theory. However, limited research investigates the effect of corporate associations on consumer loyalty to individual brands by examining the role of self connectedness with a corporate image. The activation of behavior-related constructs can influence individuals' behaviors without their intention or conscious awareness. A recently developed body of research suggests that self connection can play an important role in affecting subsequent behaviors. Although these effects have received considerable attention, the set of mechanisms involved in self connectedness and loyalty to individual brands is not clear. An active self account in which associative constructs can affect behavior by temporarily altering the active self-concept may lead to behavior or evaluation. If the exposure to a corporate brand can induce consumers' cognitive associations and goal-primed effects through the role of active self accounting, the connectedness between the consumer's self and the corporate brand could be developed and this connectedness could be explained by associative and connection models and the goal priming theory. Therefore, this study investigates the influence of corporate associations on loyalty to individual brands through connections between the corporate and the consumer's self. There are three main purposes of the research. First, theories regarding corporate associations will be explored. Second, theories of self-concept will be investigated and self connectedness with corporate brands will be explored. Third, the effects of the connectedness between the self and the corporation on corporate identification and loyalty to individual brands will be investigated. For the purposes of this research, the types of corporate associations are classified into corporate ability (CA) associations and corporate social responsibility (CSR) associations. Furthermore, the connectedness between the consumer's self and the corporate image are divided into two concepts: the connectedness between the individual self-concept and the corporate identity and the connectedness between social self-concept and the corporate identity. This study suggests the hypotheses that the types of consumer self connections with the corporate image could vary according to the types of corporate associations created and further that the connectedness between the corporate association and the consumer's self-concept have positive effects on loyalty to corporate individual brands. The results of testing these hypotheses are as follows. First, corporate ability associations enhance the connectedness between the consumer's individual self and corporate brands. That is, corporate ability associations influence individual connectedness between the corporate and individual self-concept positively from the viewpoint of the consumer's personal ability and branding success. In addition, corporate social responsibility associations have a positive effect on social connectedness between the corporation and the consumer's social self-concept. Second, the connectedness between the corporate brand and the consumer's self-concept affects identification with the corporation. The consumer's personal self and social self connectedness induces corporate identification. Third, individual self connectedness has a positive effect on loyalty to corporate individual brands, while social self connectedness does not. This also means that individual self connectedness with the corporate image or brand plays a more important role in forming individual brand loyalty than social self connectedness with the corporate does. In addition, social connectedness cannot influence individual brand loyalty until it passes through identification with the corporate. Fourth, consumers who experience identification with a corporate identity also show positive responses to corporate individual brands. That is, consumers also develop loyalties toward individual brands through the corporate identification because self-pursued goals that are induced by corporate associations can be achieved by consuming the individual brands that are sold by the corporate that the consumers identify with.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.5
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• pp.59-67
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• 2016

In landscape design by public institutions, although the costs and species of landscape trees stipulated by the Korean Public Procurement Service(PPS) are generally adhered to, the PPS regulations about planting trees with well-developed rootlets are almost entirely neglected. This study aimed to evaluate the performance of buried container modules, which are a new technology and product in landscape production that is able to reduce the defect rate while complying with regulations. To this end, this study measured rootlet density, rootlet development length, rootlet survival rate on excavation, and impairments of tree growth for 3 months after root pruning, and compared these variables for the container modules with those for trees that underwent root pruning in bare ground, and those that were cultivated in a container above ground. The results were as follows: First, the rootlet density was 88% for the trees in container modules, which was very high. Trees that underwent standard root pruning in bare ground had a somewhat lower density of 64%. Meanwhile, the trees that were cultivated in pots above ground died, invalidating measurement. Second, in terms of rootlet development and rootlet survival rate, the trees in container modules showed a mean length of 10.4cm, and 100% survival rate, indicating that there was no rootlet damage caused by excavation. For the trees that only underwent root pruning in bare ground, the mean length was 25.6cm and the rootlet survival rate was only half that of the trees in container modules, at 56%, demonstrating considerable damage. Rootlet development did not occur at all in the trees grown in pots. Third, the trees in container modules and those that underwent root pruning in bare ground did not show any deaths during the root pruning process, or any impairments such as stunted leaf growth. Conversely, the trees grown in pots nearly all died, and severe impairments of tree growth were observed. As shown by the results above, when we evaluated the performance of buried container modules, they showed the most outstanding performance of the three models tested in this study. The container modules prevent defects by stimulating early rooting in environments that with poor conditions for growth, or in trees that are not suited to the summer environment Therefore, it is expected that they would be an optimal means by which to enable compliance with rules such as the regulation presented by the PPS.

• Korean Journal of Food Science and Technology
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• v.40 no.6
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• pp.603-610
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• 2008

The principal objective of current study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS) as a non-destructive method for the prediction of the amylose and protein contents of un-hulled and brown rice in broad-based calibration models. The average amylose and protein content of 75 rice accessions were 20.3% and 7.1%, respectively. Additionally, the range of amylose and protein content were 16.6-24.5% and 3.8-9.3%, respectively. In total, 79 rice germplasms representing a wide range of chemical characteristics, variable physical properties, and origins were scanned via NIRS for calibration and validation equations. The un-hulled and brown rice samples evidenced distinctly different patterns in a wavelength range from 1,440 nm to 2,400 nm in the original NIR spectra. The optimal performance calibration model could be obtained by MPLS (modified partial least squares) using the first derivative method (1:4:4:1) for un-hulled rice and the second derivative method (2:4:4:1) for brown rice. The correlation coefficients $(r^2)$ and standard error of calibration (SEC) of protein and amylose contents for the un-hulled rice were 0.86, 2.48, and 0.84, 1.13, respectively. The $r^2$ and SEC of protein and amylose content for brown rice were 0.95, 1.09 and 0.94, 0.42, respectively. The results of this study suggest that the NIRS technique could be utilized as a routine procedure for the quantification of protein and amylose contents in large accessions of un-hulled rice germplasms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.29-36
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• 2007

This study was carried out to develop a water quality simulation model for the evaluation of an ungauged watershed. For this purpose, the WASP5 model was selected and modified. The model consists of three sub-models, LOAD-M, DYN-M, and EUT-M. LOAD-M, an empirical model, estimates runoff loadings using point and non-point source data of villages. The Geum River Estuary watershed was selected to calibrate and verify the Modified-WASP5. The LOAD-M model was established using field data of water quality and quantity at the gauging stations of the watershed and was applied to the ungauged watersheds, taking the watershed properties into consideration. The result of water quality simulation using Modified-WASP5 shows that the observed average BOD data from Gongju and Ganggyeong were 2.6 mg/L and 2.8 mg/L, and the simulated data were 2.5 mg/L and 2.4 mg/L, respectively. Generally, simulation results were in good agreement with the observed data. This study focused on formulating an integrated model for evaluating ungauged watersheds. Even though simulation results varied slightly due to limited availability of data, the model developed in this study would be a useful tool for the assessment and management of ungauged watersheds.

• International Journal of Highway Engineering
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• v.8 no.4 s.30
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• pp.63-74
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• 2006

It's essential to meet the expectations of drivers through reasonable road design, which makes the drivers to recognize the conditions of road sufficiently. In this case, we could say that because the roads are consistently designed, drivers can make a safe and comfortable drive. There are so many studies about the alignment design consistency methods which are previously mentioned. In this study, Firstly we categorize the studies which are concerned with the estimation of the alignment design consistency methods and then apply the method which fits for the actual condition into the practice. And we'll make a realistic method by using the data which aye collected from the National Road. The developed model in this study is the predicting model including speed($V_t$) as the variable on the upper stream 100m of the curve. This model was developed which divided to two cases in the all directions of two lanes; One case is the $R{\leq}200m$ and another case is the R>200m. In the section of the $R{\leq}200m$, this case was influenced on the road alignment(R) and($V_t$) and another section was found that is affected to the speed($V_t$) on the upper stream loom rather than the effect of road alignment(R). In the case of all directions of four lanes, however, this study is predicted divided to two sections on the 400m of R, these section have more influenced to($V_t$) than the road alignment factors. This result of the four lanes was represented to different result with the two lanes. This study will further need development of the predicting model with the higher confidence through collecting data with more the exact data, the various road alignment data and speed of the several sections on the upper stream on the curve.

• Food Science of Animal Resources
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• v.28 no.2
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• pp.232-239
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• 2008

The objective of this study is to estimate the shelf-life of Tteokgalbi containing dietary fiber extracted from rice bran by using the predictive microbiology. This Tteokgalbi was made with 0%, 1%, 2%, and 3% dietary fiber. The number of total viable cells, anaerobic, psychrotrophic, and heat-stable bacteria and coliforms was calculated during 15 days of storage under $4{\pm}1^{\circ}C$ and the obtained data was applied to Baranyi function. The evaluation of fitness between predicted and observed data showed that these were matched in a satisfactory way. Heat-stable bacteria was detected lower than <1 log CFU/g and coliforms were not detected during the storage. The changes of total viable cells and psychrotrophic bacteria in Tteokgalbi were increased gradually, but dramatically increased after 3 days of storage. The models of total viable cells and anaerobic bacteria showed very similar growth trends and values of growth parameters each other. The estimated shelf-life of each Tteokgalbi was calculated from the predictive model of total viable cells and the estimated shelf-life was 1.7, 2.3, 2.3, and 2.4 days, respectively. The results suggested that the prediction of bacteria growth could be used to evaluate the microbiological safety and determine the shelf-life of Tteokgalbi as ready-to-eat food in the local market.

• Korean Journal of Ecology and Environment
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• v.39 no.2 s.116
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• pp.145-156
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• 2006

The objective of this study was to evaluate biological health conditions and physicochemical status using multi-metric models at five sites of the Keum-Ho River during August 2004 and June 2005. The research approach was based on a qualitative habitat evaluation index (QHEI), index of biological integrity (IBI) using fish assemblage, and long-term chemical data (1995 ${\sim}$ 2004), which was obtained from the Ministry of Environment, Korea. For the biological health assessments, regional model of the IBI in Korea (An,2003), was applied for this study. Mean IBI in the river was 30 and varied from 23 to 48 depending on the sampling sites. The river health was judged to be "fair condition", according to the stream health criteria of US EPA (1993) and Barbour et al. (1999). According to the analysis of the chemical water quality data of the river, BOD, COD, conductivity, TP, TN, and TSS largely varied epending on the sampling sites, seasons and years. Variabilities of some parameters including BOD, COD, TP, TN, and conductivity were greater in the downstream than in the upstream reach. This phenomenon was evident in the dilution by the rain during the monsoon. This indicates that precipitation is a very important factor of the chemical variations of water quality. Community analyses showed that species diversity index was highest (H=0.78) in the site 1, while community dominance index was highest in the site 3, where Opsariichthys uncirostris largely dominated. In contrast, the proportions of omnivore and tolerant species were greater in the downstream reach, than in the upstream reach. Overall, this study suggests that some sites in the downstream reach may need to restore the aquatic ecosystem for better biological health.