• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.667-680
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• 2007

The bio-data processing is used for a suitable purpose with bio-signals, which are obtained from human individuals. Recently, there is increasing demand that the bio-data has been widely applied to various applications. However, it is often that the number of data within each class is limited and the number of classes is large due to the property of problem domain. Therefore, the conventional pattern recognition systems and classification methods are suffering form low generalization performance because the system using the lack of data is influenced by noises of that. To solve this problem, we propose a modified additive factor model for bio-data generation, with two factors; the class factor which affects properties of each individuals and the environment factor such as noises which affects all classes. We then develop a classification system through defining a new similarity function using the proposed model. The proposed method maximizes to use an information of the class classification. So, we can expect to obtain good generalization performances with robust noises from small number of datas for bio-data. Experimental results show that proposed method outperforms significantly conventional method with real bio-data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.12
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• pp.1107-1114
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• 2011

In this paper, the fatigue life of a laser peened structure was predicted. In order to calculate residual stress induced by laser peening finite element simulation was carried out. Modified Goodman equation was used to consider the effect of compressive residual stress induced by laser peening in fatigue analysis. In addition, additive adjustment factor approach was applied to consider S-N curve model uncertainty. Consequently, the reliable bounds of the predicted fatigue life of the laser peened structure was determined.

• Journal of the Korea Institute of Building Construction
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• v.7 no.3
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• pp.123-130
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• 2007

This study investigated the fundamental properties and shrinkage properties of high performance concrete with water/binder ratio of 0, 30 and with combination of expansive additive and shrinkage reducing agent. According to the results, the fluidity of high performance concrete showed lower the using method in combination with expansive additive and shrinkage reducing agent than the separately using method of that, so the amount of superplasticizer increased when the adding ratio of expansive additive and shrinkage reducing agent increased. However the air content of concrete increased when used in combination with expansive additive and shrinkage reducing agent, so the amount of AE agent decreased. The compressive strength showed the highest at 5% of expansive additive, and decreased with an increase of the amount of shrinkage reducing agent. Furthermore, in order to reduce the shrinkage of high performance concrete, it was found that the using method in combination with expansive additive and shrinkage reducing agent was more effective than separately using method of that. Autogenous shrinkage was predicted using JCI model. Because JCI model is unable to consider the effect of EA and SRA, correction factor should be added to enhance the accuracy.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.3
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• pp.302-307
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• 2010

The present study aimed to investigate the effects of maternal factors on body weight at hatching (day-old) and at six weeks of age in a commercial broiler line. A total of 6,765 records on body weight at day-old (BWTDO) and 115,421 records on body weight at six weeks of age (BWT6W), originated from a commercial broiler line during 14 generations, were used to estimate genetic parameters related to the effects of maternal traits on body weight of chicks immediately after hatch or six weeks thereafter. The data were analyzed using restricted maximum likelihood procedure (REML) and an animal model with DFREML software. Direct heritability ($h^{2}{_a}$), maternal heritability ($h^{2}{_m}$), and maternal environmental variance as the proportions of phenotypic variance ($c^{2}$) for body weight at day-old were estimated to be 0.050, 0.351, and 0.173, respectively. The respective estimated values for body weight at six weeks of age were 0.340, 0.022, and 0.030. The correlation coefficient between direct and maternal genetic effects for six-week-old body weight was found to be -0.335. Covariance components and genetic correlations were estimated using a bivariate analysis based on the best model determined by a univariate analysis. Between weights at hatching and at six week-old, the values of -0.07, 0.53 and 0.47 were found for the direct additive genetic variance, maternal additive genetic variance and permanent maternal environmental variance, respectively. The estimated correlation between direct additive genetic effect influencing weight at hatch and direct additive maternal effect affecting weight at six weeks of age was -0.21, whereas the correlation value of 0.15 was estimated between direct additive maternal effect influencing weight at hatch and direct additive genetic effect affecting weight at six-week-old. From the present findings, it can be concluded that the maternal additive genetic effect observed for weight at six weeks of age might be a factor transferred from genes influencing weight at hatch to weight at six-week-old.

• Structural Engineering and Mechanics
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• v.62 no.1
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• pp.1-9
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• 2017

This paper describes laboratory tests carried out to evaluate the influence of class F fly ash (FA) on fracture toughness of plain concretes, specified at the third model fracture. Composites with the additives of: 0%, 20% and 30% siliceous FA were analysed. Fracture toughness tests were performed on axial torsional machine MTS 809 Axial/Torsional Test System, using the cylindrical specimens with dimensions of 150/300 mm, having an initial circumferential notch made in the half-height of cylinders. The studies examined effect of FA additive on the critical stress intensity factor $K_{IIIc}$. In order to determine the fracture toughness $K_{IIIc}$ a special device was manufactured.The analysis of the results revealed that a 20% FA additive causes increase in $K_{IIIc}$, while a 30% FA additive causes decrease in fracture toughness. Furthermore, it was observed that the results obtained during fracture toughness tests are convergent with the values of the compression strength tests.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.67-79
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• 2012

The car insurance market in Korea has already entered (or is in the process of entry) a mature market that is characterized by increased competition by market participants. Participants are expected to compete more intensively in order to survive. Together with a slowdown in market growth the goal of non-life insurers' marketing strategies is to enhance existing customer loyalty because it is easier to raise their loyalty via customer satisfaction than to attract new customers in a stagnant market. In this article, we investigate what factors affect customer loyalty, and suggest some specific ways to establish and implement marketing strategies. We use a generalized additive partial linear model in order to find some significant factors.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.11
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• pp.445-452
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• 2017

Electric pole is a supporting beam used for power transmission/distribution which accelerometer are used for measuring a external force. The meteorological condition has various effects on the external forces of electric pole. One of them is the elasticity change of the aerial wire. It is very important to perform modelling. The acceleration sensor is converted into a pitch and a roll angle. The meteorological condition has a high correlation between variables, and selecting significant explanatory variables for modeling may result in the problem of over-fitting. We constructed high deviance explained model considering multicollinearity using the Generalized Additive Model which is one of the machine learning methods. As a result of the Variation Inflation Factor Test, we selected and fitted the significant variable as temperature, precipitation, wind speed, wind direction, air pressure, dewpoint, hours of daylight and cloud cover. It was noted that the Hours of daylight, cloud cover and air pressure has high explained value in explonatory variable. The average coefficient of determination (R-Squared) of the Generalized Additive Model was 0.69. The constructed model can help to predict the influence on the external forces of electric pole, and contribute to the purpose of securing safety on utility pole.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.150-164
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• 2017

The development of an appropriate public service quality model has become increasingly recognised as an important subject of interest in the public sector as well as academia. In particular, the public systems enacted by governments are widely used and have a significant impact on national competitiveness. But few researches have been conducted to explore the quality dimensions of a public system service and empirically examine the relationship among related variables. Therefore, in this study, we strive to develop a quality measurement model of public system service that can be effectively used in practice. Using 601 samples gathered through a structured survey from project engineers, a conceptual quality model of public system is presented and discussed. Given the exploratory nature of this study, an exploratory factor analysis is used to investigate quality dimensions and partial least square (PLS) is employed in determining the structural relationships. From empirical results, we found that the quality dimensions of the public system had four distinct quality dimensions (design quality, environment quality, primary outcome quality, additive outcome quality). All four quality dimensions showed good representative factors in explaining user satisfaction. Perceived trust was proved to significantly mediate the relationship between quality dimensions and user satisfaction. Our research is expected to contribute to the literature by providing a good conceptual framework for assessing public system quality by linking four quality dimensions with user satisfaction. In particular, the developed model can elaborately measure process quality and multi-functional outcome quality of the system by the supplementation of design quality and additive outcome quality respectively. Practical implications are also suggested on the basis of our analysis.

• Journal of Korean Neurosurgical Society
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• v.60 no.4
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• pp.404-416
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• 2017

Objective : Functional and neural tissue recovery has been reported in many animal studies conducted with stem cells. However, the combined effect of cytokines and stem cells has not yet been adequately researched. Here, we analyzed the additive effects of granulocyte colony-stimulating factor (GCSF) on adipose-derived stem cells (ADSCs) infusion in the treatment of acute spinal cord injury (SCI) in rats. Methods : Four days after intrathecal infusion tubes implantation in Sprague-Dawley rats, SCI was induced with an infinite horizon impactor. In the Sham group (n=5), phosphate-buffered saline was injected 3, 7, and 14 days after SCI. GCSF, ADSCs, and ADSCs with GCSF were injected at the same time in the GCSF (n=8), ADSC (n=8), and ADSC+GCSF groups (n=7), respectively. Results : The ADSC and ADSC+GCSF groups, but not the GCSF group, showed significantly higher Basso-Beattie-Bresnahan scores than the Sham group during 8 weeks (p<0.01), but no significant difference between the ADSC and ADSC+GCSF groups. In the ladder rung test, all four groups were significantly different from each other, with the ADSC+GCSF group showing the best improvement (p<0.01). On immunofluorescent staining (GAP43, MAP2), western blotting (GAP43), and reverse transcription polymerase chain reaction (GAP43, nerve growth factor), the ADSC and ADSC+GCSF groups showed higher levels than the Sham and GCSF groups. Conclusion : Our analyses suggest that the combination of GCSF and ADSCs infusions in acute SCI in the rat does not have a significant additive effect. Hence, when combination agents for SCI stem cell therapy are considered, molecules other than GCSF, or modifications to the methodology, should be investigated.