• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.3
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• pp.48-54
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• 2016

This paper proposes a prediction model of air traffic controller's take-off clearance under mixed mode runway operations. The proposed model has its purpose on the better prediction of the air traffic controller's clearance on take-offs of departure aircraft by considering various factors. For this purpose, support vector machine classification algorithm is used for the proposed model. The proposed model is applied to real air traffic operations to demonstrate its performances.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.461-471
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• 2017

In this paper we propose a feature selection method identifying important features in the semivarying coefficient model. One important issue in semivarying coefficient model is how to estimate the parametric and nonparametric components. Another issue is how to identify important features in the varying and the constant effects. We propose a feature selection method able to address this issue using generalized cross validation functions of the varying coefficient least squares support vector regression (LS-SVR) and the linear LS-SVR. Numerical studies indicate that the proposed method is quite effective in identifying important features in the varying and the constant effects in the semivarying coefficient model.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.199-207
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• 2010

The purpose of this study is looking for the support policies and factors to stimulate the quality innovation movement. Kano's model proposed a two-dimensional model on quality based on customer perception and experience. And Timko developed the customer satisfaction coefficient for overcome the weak points of Kano's model. In this paper, new approach framework is proposed by integrated Kano's model and Timko's customer satisfaction coefficient. And it applied to confirm the various factors which was offered by government and major company's policies for small and medium enterprises.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.117-124
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• 2017

The purpose of this study was to examine the factors influencing on Codependency of college students from Double ABCX model. This study examined the mediating relationship between boundary ambiguity, internal working model and psychological maladjustment, and then examined the moderating effects of Self-esteem, Social support and World view orientation. This study also examined the relationships of codependency with gender, enonomic level in college students. The results of the study are as follows. First, this study showed that codependency was related to economic level of college students. But it has not significant relationship with gender. Second, the moderating effects of Self-esteem, Social support and World view orientation was not significant. Third, mediating effects of Codependency on Boundary ambiguity, Internal working model and Psychological maladjustment were significant. This study suggested some theoretical and policy implications basing on this analytical results.

• The Journal of Information Systems
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• v.19 no.2
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• pp.73-95
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• 2010

This study shows the scientific and systematic Evaluation Model using factor analysis and AHP methods for the success of defense Information System R&D projects. The evaluation model was divided into 7 evaluation factors such as Developing support, Developing infrastructure, Developing management and test & evaluation, Support factors for strength, Understanding & developing strategy, Developing technology & organization, and Developing performance. And those were composed of totally 24 low level Evaluation index. The Developed Evaluation Model in the paper could be contributed more to objectively and transparently company selection of defense Information System R&D and other defense R&D Projects in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.408-411
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• 2006

Currently, the nano economy threatens the mass economy. This is based on the internet business models. In the nano business models based on internet, the diversely personalized services are needed. Many researches of the personalization on the web have been studied. The web usage mining using click stream data is a tool for personalization model. In this paper, we propose an internet business model using evolutionary support vector machine and web response survey as a web usage mining. After analyzing click stream data for web usage mining, a personalized service model is constructed in our work. Also, using an approach of web response survey, we improve the performance of the customers' satisfaction. From the experimental results, we verify the performance of proposed model using two data sets from KDD Cup 2000 and our web server.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.12-22
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• 2024

Software applications have a huge and inseparable impact on our lives. The complexity of the applications increases rapidly to support high performance and multifunction. Accordingly, the cost model for applications is increasingly important. Line of Code (LOC) and Man-Month (M/M) as the cost model measure the quantitative sides of the applications. Unlike them, Function Point (FP) measures the functionalities of the application. FP is efficient for estimating qualitative characteristics, but it is restricted to measuring the cost of an application using the wireless data broadcast which can support any number of clients. In this paper, we propose, a Function Point model for Information services using wireles data Broadcast (FPIB) to measure the development cost of an application that serves using the wireless data broadcast environment. FPIB adopts critical parameters of the wireless broadcast environment and the complexity of them to measure effectively the cost developing the application. Through the evaluation comparing the proposed FPIB with FP, we reveal the effectiveness of the proposed FPIB.

• The Journal of Korean Academic Society of Nursing Education
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• v.11 no.2
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• pp.161-168
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• 2005

Purpose: The purposes are to identify the factors that influence work-based stressor experienced by clinical nurses and to provide a perceived causal structural model among these factors. Method: Data was collected and analyzed in 2 steps to apply a perceived causal structure : network analysis which was developed by Kelley(1983). Results: 1. The extracted causes from qualitative data were identified 10 categories ; over loaded work, relative feelings of deprived, inefficient duty schedule, negative attitudes of patient, burden of extra affair, inadequate administrative support, negative attitudes of physician, conflict with other personnels in hospital, lack of professional knowledge and skill, nursing service marketing burden. 2. Construction of the perceived causal structural model ; 1) The most central cause is over loaded work and the distal causes were inadequate administrative support, lack of professional knowledge and skill in the systems of causation. 2) The causes that have a number of outgoing link were over loaded work, inadequate administrative support, negative attitudes of physician. 3) The cause that have a number of incoming link was relative feelings of deprived. Conclusion: The network suggests that the first centre cause was related on over loaded work.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.1-7
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• 2012

Hemorrhagic shock is a common cause of death in emergency rooms. Early diagnosis of hemorrhagic shock makes it possible for physicians to treat patients successfully. Therefore, the purpose of this study was to select an optimal survival prediction model using physiological parameters for the two analyzed periods: two and five minutes before and after the bleeding end. We obtained heart rates, mean arterial pressures, respiration rates and temperatures from 45 rats. These physiological parameters were used for the training and testing data sets of survival prediction models using an artificial neural network (ANN) and support vector machine (SVM). We applied a 5-fold cross validation method to avoid over-fitting and to select the optimal survival prediction model. In conclusion, SVM model showed slightly better accuracy than ANN model for survival prediction during the entire analysis period.

• Child Health Nursing Research
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• v.23 no.3
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• pp.268-278
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• 2017

Purpose: The purpose of this study was to set up a hypothetical model to explain causal relationships among influential variables in the mother-child relationship for Korean infants and toddlers and their mothers. The research was based on Barnard's (1978) mother-child relations model, and goodness-of-fit was examined. Methods: The participants were 207 mothers with infants or toddlers. Data were analyzed using SPSS and AMOS programs. Results: Regarding the influence of the variables on the mother-child relationship between infants and toddlers and their mothers, social support had a 75% explanation of mother-child relationships, and attachment had a 58% explanation of social support. Attachment had both direct and indirect effects on the mother-child relationships, and social support had direct and total effects on the mother-child relationships. Among child-related variables, child temperament had a moderating effect on the mother-child relationships. Conclusion: The findings indicate that the model has utility in developing effective nursing intervention methods to boost mother-child relationships between infants and toddlers and their mothers.