• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Journal of radiological science and technology
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• v.30 no.4
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• pp.373-379
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• 2007

Purpose : There is difference between PET and PET/CT method on their transmission image for attenuation correction. The CT image is used for attenuation correction on PET/CT and the parameters of CT may be affected on PET image. We performed the phantom study to evaluate whether the change of CT parameters(kilovolts peak and milliampere) affect standardized uptake value(SUV) on PET image. Material and Method: The data spectrum lung phantom containing diluted [18F]fluorodeoxyglucose ([18F]FDG) solution(1.909 mCi for phantom 1, $913\;{\mu}Ci$ for phantom 2) was used. The CT images of phantom were acquired with varying parameters (80, 100, 120, 140 for kVp, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 for mA). The PET images were reconstructed with the each CT images and SUVs were compared. Result : The SUVs of phantom 1 reconstructed with each 80, 100, 120 and 140 kVp showed $12.26{\pm}0.009$, $12.27{\pm}0.005$, $12.27{\pm}0.006$ and $12.27{\pm}0.009$, respectively. The SUVs of phantom 2 revealed $4.52{\pm}0.043$, $4.53{\pm}0.004$, $4.52{\pm}0.007$ and $4.52{\pm}0.005$ with elevation of voltage. There was no statistically significant difference of SUVs between groups based on various kVp. Also SUVs of phantom 1 and 2 showed no significant change with elevation of milliampere in CT parameter. Conclusion : The parameters of CT did not significantly affect SUV on PET image in our study. Therefore we can apply various parameters of CT appropriated for clinical conditions without significant change of SUV on PET CT image.

• Korean Chemical Engineering Research
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• v.56 no.4
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• pp.479-495
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• 2018

This study was carried out to research the multimedia fate modeling, concentration distribution and impact assessment of polycyclic aromatic hydrocarbons (PAHs) emitted from automobiles, which are known as carcinogenic and mutation chemicals. The amount of emissions of PAHs was determined based on the census data of automobiles at a target S-city and emission factors of PAHs, where multimedia fugacity modeling was conducted by the restriction of PAHs transfer between air-soil at the impervious area. PAHs' Concentrations and their distributions at several environmental media were predicted by multimedia fugacity model (level III). The residual amounts and the distributions of PAHs through mass transfer of PAHs between environment media were used to assess the health risk of PAHs at unsteady state (level IV), where the sensitivity analyses of the model parameter of each variable were conducted based on Monte Carlo simulation. The experimental result at S-city showed that Fluoranthene among PAHs substances are the highest residual concentrations (60%, 53%, 32% and 34%) at all mediums (atmospheric, water, soil, sediment), respectively, where most of the PAHs were highly accumulated in the sediment media (more than 80%). A result of PAHs concentration changes in S-city over the past 34 years identified that PAHs emissions from all environmental media increased from 1983 to 2005 and decreased until 2016, where the emission of heavy-duty vehicle including truck revealed the largest contribution to the automotive emissions of PAHs at all environment media. The PAHs concentrations in soil and water for the last 34 years showed the less value than the legal standards of PAHs, but the PAHs in air exceeded the air quality standards from 1996 to 2016. The result of this study is expected to contribute the effective management and monitoring of toxic chemicals of PAHs at various environment media of Metropolitan city.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.27-57
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• 2008

Many consumers enjoy the challenge of purchasing a brand that matches well with their own values and personalities (for example, Ko et al., 2008; Ko et al., 2006). Therefore, the personalities of consumers can impact on the final selection of a brand and its brand personality in two ways: first, the consumers may incline to purchase a brand or a product that reflects their own personalities; second, consumers tend to choose a company that has similar brand personalities to those brands that are being promoted. Therefore, the objectives of this study are following: 1. Is there any empirical relationship between a consumer's personality and the personality of a brand that he or she chooses? 2. Can a corporate brand be differentiated by the brand personality? In short, consumers are more likely to hold favorable attitudes towards those brands that match their own personality and will most probably purchase those brands matching well with their personality. For example, Matzler et al. (2006) found that extraversion and openness were positively related to hedonic product value; and that the personality traits directly (openness) and indirectly (extraversion, via hedonic value) influenced brand effects, which in turn droved attitudinal and purchase loyalty. Based on the above discussion, the following hypotheses are proposed: Hypothesis 1: the personality of a consumer is related to the brand personality of a product/corporate that he/she purchases. Kuksov (2007) and Wernerfelt (1990) argued that brands as a symbolic language allowed consumers to communicate their types to each other and postulated that consumers had a certain value of communicating their types to each other. Therefore, how brand meanings are established, and how a firm communicate with consumers about the meanings of the brand are interesting topics for research (for example, Escalas and Bettman, 2005; McCracken, 1989; Moon, 2007). Hence, the following hypothesis is proposed: Hypothesis 2: A corporate brand identity is differentiated by the brand personality. And there are significant differences among companies. A questionnaire was developed for collecting empirical measures of the Big-Five personality traits and brand personality variables. A survey was conducted to the online access panel members through the Internet during December 2007 in Korea. In total, 500 respondents completed the questionnaire, and considered as useable. Personality constructs were measured using the Five-factor Inventory (NEO-FFI) scale and a total of 30 items were actually utilized. Brand personality was measured using the five-dimension scale developed by Aaker (1997). A total of 17 items were actually utilized. The seven-point Likert-type scale was the format of responses, for example, from 1 indicating strongly disagreed to 7 for strongly agreed. The Analysis of Moment Structures (AMOS) was used for an empirical testing of the model, and the Maximum Likelihood Estimation (MLE) was applied to estimate numerical values for the components in the model. To diagnose the presence of distribution problems in the data and to gauge their effects on the parameter estimates, bootstapping method was used. The results of the hypothesis-1 test empirically show that there exit certain causality relationship between a consumer's personality and the brand personality of the consumer's choice. Thus, the consumer's personality has an impact on consumer's final selection of a brand that has a brand personality matches well with their own personalities. In other words, the consumers are inclined to purchase a brand that reflects their own personalities and tend to choose a company that has similar brand personalities to those of the brand being promoted. The results of this study further suggest that certain dimensions of the brand personality cause consumers to have preference to certain (corporate) brands. For example, the conscientiousness, neuroticism, and extraversion of the consumer personality have positively related to a selection of "ruggedness" characteristics of the brand personality. Consumers who possess that personality dimension seek for matching with certain brand personality dimensions. Results of the hypothesis-2 test show that the average "ruggedness" attributes of the brand personality differ significantly among Korean automobile manufacturers. However, the result of ANOVA also indicates that there are no significant differences in the mean values among manufacturers for the "sophistication," "excitement," "competence" and "sincerity" attributes of the corporate brand personality. The tight link between what a firm is and its corporate brand means that there is far less room for marketing communications than there is with products and brands. Consequently, successful corporate brand strategies must position the organization within the boundaries of what is acceptable, while at the same time differentiating the organization from its competitors.

• Proceedings of the Korea Environmental Mutagen Society Conference
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• 2003.10a
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• pp.34-63
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• 2003

Occupational and environmental exposure to manganese continue to represent a realistic public health problem in both developed and developing countries. Increased utility of MMT as a replacement for lead in gasoline creates a new source of environmental exposure to manganese. It is, therefore, imperative that further attention be directed at molecular neurotoxicology of manganese. A Need for a more complete understanding of manganese functions both in health and disease, and for a better defined role of manganese in iron metabolism is well substantiated. The in-depth studies in this area should provide novel information on the potential public health risk associated with manganese exposure. It will also explore novel mechanism(s) of manganese-induced neurotoxicity from the angle of Mn-Fe interaction at both systemic and cellular levels. More importantly, the result of these studies will offer clues to the etiology of IPD and its associated abnormal iron and energy metabolism. To achieve these goals, however, a number of outstanding questions remain to be resolved. First, one must understand what species of manganese in the biological matrices plays critical role in the induction of neurotoxicity, Mn(II) or Mn(III)? In our own studies with aconitase, Cpx-I, and Cpx-II, manganese was added to the buffers as the divalent salt, i.e., $MnCl_2$. While it is quite reasonable to suggest that the effect on aconitase and/or Cpx-I activites was associated with the divalent species of manganese, the experimental design does not preclude the possibility that a manganese species of higher oxidation state, such as Mn(III), is required for the induction of these effects. The ionic radius of Mn(III) is 65 ppm, which is similar to the ionic size to Fe(III) (65 ppm at the high spin state) in aconitase (Nieboer and Fletcher, 1996; Sneed et al., 1953). Thus it is plausible that the higher oxidation state of manganese optimally fits into the geometric space of aconitase, serving as the active species in this enzymatic reaction. In the current literature, most of the studies on manganese toxicity have used Mn(II) as $MnCl_2$ rather than Mn(III). The obvious advantage of Mn(II) is its good water solubility, which allows effortless preparation in either in vivo or in vitro investigation, whereas almost all of the Mn(III) salt products on the comparison between two valent manganese species nearly infeasible. Thus a more intimate collaboration with physiochemists to develop a better way to study Mn(III) species in biological matrices is pressingly needed. Second, In spite of the special affinity of manganese for mitochondria and its similar chemical properties to iron, there is a sound reason to postulate that manganese may act as an iron surrogate in certain iron-requiring enzymes. It is, therefore, imperative to design the physiochemical studies to determine whether manganese can indeed exchange with iron in proteins, and to understand how manganese interacts with tertiary structure of proteins. The studies on binding properties (such as affinity constant, dissociation parameter, etc.) of manganese and iron to key enzymes associated with iron and energy regulation would add additional information to our knowledge of Mn-Fe neurotoxicity. Third, manganese exposure, either in vivo or in vitro, promotes cellular overload of iron. It is still unclear, however, how exactly manganese interacts with cellular iron regulatory processes and what is the mechanism underlying this cellular iron overload. As discussed above, the binding of IRP-I to TfR mRNA leads to the expression of TfR, thereby increasing cellular iron uptake. The sequence encoding TfR mRNA, in particular IRE fragments, has been well-documented in literature. It is therefore possible to use molecular technique to elaborate whether manganese cytotoxicity influences the mRNA expression of iron regulatory proteins and how manganese exposure alters the binding activity of IPRs to TfR mRNA. Finally, the current manganese investigation has largely focused on the issues ranging from disposition/toxicity study to the characterization of clinical symptoms. Much less has been done regarding the risk assessment of environmenta/occupational exposure. One of the unsolved, pressing puzzles is the lack of reliable biomarker(s) for manganese-induced neurologic lesions in long-term, low-level exposure situation. Lack of such a diagnostic means renders it impossible to assess the human health risk and long-term social impact associated with potentially elevated manganese in environment. The biochemical interaction between manganese and iron, particularly the ensuing subtle changes of certain relevant proteins, provides the opportunity to identify and develop such a specific biomarker for manganese-induced neuronal damage. By learning the molecular mechanism of cytotoxicity, one will be able to find a better way for prediction and treatment of manganese-initiated neurodegenerative diseases.

• Investigative Magnetic Resonance Imaging
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• v.5 no.1
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• pp.33-37
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• 2001

Purpose : The water exchange rate between bulk water and bound water is an important parameter in deciding the efficiency of paramagnetic contrast agents. In this study, we evaluated the water exchange rates of various Gd-chelates using oxygen-17 NMR technique. Material and Methods : The samples (Gd-DTPA, Gd-DTPA-BMA, Gd-DOTA, Gd-EOB-DTPA) were prepared by mixing 5% $^{17}O-enriched$ water (Isotech, USA). The pH of the samples was adjusted to physiological value [pH=7.0] by buffer solution. The variable temperature $^{17}O-NMR$ measurements were performed using Bruker-600 (14.1 T, 81.3 MHz) spectrometer. Bruker VT-1000 temperature control units were used to stabilize the temperature. The $^{17}O$ spin-spin relaxation times (T2) were measured using Carr-Purcell-Meiboom-Gill (CPMG)I pulse sequence with 24 echo trains. The variable temperature T2 relaxation data were then fitted into Solomon-Bloembergen equations using least square fit algorithm to estimate the water exchange times. Results : From the measured $^{17}O-NMR$ relaxation rates, the determined water exchange rates at 300K are $0.42{\;}{\mu}s$ for Gd-DTPA, $1.99{\;}{\mu}s$ for Gd-DTPA-BMA, $0.27{\;}{\mu}s$ for Gd-DOTA, and $0.11{\;}{\mu}s$ for Gd-EOB-DTPA. The Gd-DTPA-BMA showed slowest exchange whereas Gd-EOB-DTPA had fastest water exchange rate. In addition, it was found that the water exchange rates (${\tau}_m$) of all samples had exponential temperature dependence with different decay constant. Conclusion : $^{17}O-NMR$ relaxation rate measurements, when combined with variable temperature technique, provide a solid tool for studying water exchange rate, which is very important in investigating the detailed mechanism of relaxation enhancement effect of the paramagnetic contrast agents.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.55-62
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• 2015

Purpose Various methods for reducing radiation exposure have been continuously being developed. The aim of this study is to evaluate effectiveness of dose reduction, image quality and PET SUV changes by applying combination of automatic exposure dose(AEC), automated dose-optimized selection of X-ray tube voltage(CAREkV) and sinogram affirmed iterative reconstruction(SAFIRE) which can be controled by user. Materials and Methods Torso, AAPM CT performance and IEC body phantom images were acquired using biograph mCT64, (Siemens, Germany) PET/CT scanner. Standard CT condition was 120 kV, 40 mAs. Radiation exposure and noise were evaluated by applying AEC, CAREkV(120 kV, 40 mAs) and SAFIRE(120 kV, 25 mAs) with torso phantom compare to standard CT condition. And torso, AAPM and IEC phantom images were acquired with combination of 3 methods in condition of 120 kV, 25 mAs to evaluate radiation exposure, noise, spatial resolution and SUV changes. Results When applying AEC, CTDIvol and DLP were decreased by 50.52% and 50.62% compare to images which is not applying AEC. mAs was increased by 61.5% to compensate image quality according to decreasing 20 kV when applying CAREkV. However, CTDIvol and DLP were decreased by 6.2% and 5.5%. When reference mAs was the lower and strength was the higher, reduction of radiation exposure rate was the bigger. Mean SD and DLP were decreased by 2.2% and 38% when applying SAFIRE even though mAs was decreased by 37.5%(from 40 mAs to 25 mAs). Combination of 3 methods test, SD decreased by 5.17% and there was no significant differences in spatial resolution. And mean SD and DLP were decreased by 6.7% and 36.9% compare to 120 kV, 40 mAs with AEC. For SUV test, there was no statistical differences(P>0.05). Conclusion Combination of 3 methods shows dose reduction effect without degrading image quality and SUV changes. To reduce radiation exposure in PET/CT study, continuous effort is needed by optimizing various dose reduction methods.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.62-69
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• 2012

Purpose: The present study has an objective of effectively separating and making observations on a portion of radiopharmaceutical excreted via digestive organ to remain in the organ and invade a heart shadow. Materials and methods: When heart shadow is blocked by the organ in tests during a resting phase and a loaded phase, additional images were obtained using immobilization device. The immobilization devices were used to tilt the upper body forward from supine position. Results: In the reconstructed image for the separated case, as compared with the case where a part of organ is overlapped with heart, in terms of an overall mean value for each parameter, the end-diastolic volume increased by 2.75 mL, the end-systolic volume decreased by 3.16 mL, the left ventricle cardiac coefficient increased by 3.58%, and the area of defect region decreased by 3.58 and 3.92 cm for loading and resting phase, respectively. Conclusions: In the present study with myocardial perfusion SPECT, overlapped areas of heart and other organs could be effectively separated and visualization by the use of an immobilization device.

• Korean Journal of Poultry Science
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• v.30 no.3
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• pp.197-202
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• 2003

Feeding probiotics in broiler chicks still critical in several aspects. Thus, this study was conducted to investigate the impact of feeding multiple probiotics on performance, intestinal microflora, blood cholesterol and ND antibody vaccine titer in broiler chicks. Three hundred twenty one day old male broiler chicks(cobb ${\times}$ cobb) were divided into four levels of multiple probiotics(0, 0.1, 0.2, 0.3%) with five replicates for 35 days. Basal diets contained 21.5, 19.0% CP and 3,100 kcal/kg ME for starting and finishing period, respectively. Weight gain, feed intake and feed conversion were measured weekly. The number of Salmonella, E. coli, Lactobacillus, and yeast were examined from ileum and cecum at the end of experiment. ND vaccine titer, cholesterol were detected from sera. Weight gain of birds fed probiotics were 669.33, 679.75 at the level of 0.1 and 0.2% supplemental groups for starting period. It was also improved in those treatments for finishing period and higher than control for total period. Feed conversion tended to be improved compared to that of control by the supplementation of probiotics for the first three weeks and seemed to show the similar tendency for the rest of two weeks. It was 1.611, 1.621 for the entire feeding period and improved compared with control. Total salmonella, was not decreased in ileal digesta of birds fed the probiotics compared with control, whereas the number of yeast increased in 0.1% treatment. However, the number of Lactobacillus and yeast in cecum was higher than control. Even though the blood cholesterol seem to high in 0.1% probiotics treatment, the ratio of HDL to total cholesterol showed higher than control. ND vaccine titer of birds fed probiotics were significantly higher than control (P<0.05). These results 0.1% multiple probiotics would be possible to improve the performance of broiler chicks and ND vaccine titer.