• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.175-182
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• 2007

The support vector machine has been successful in many applications because of its flexibility and high accuracy. However, when a training data set is large or imbalanced, the support vector machine may suffer from significant computational problem or loss of accuracy in predicting minority classes. We propose a modified version of the support vector machine using the K-means clustering that exploits the information in class labels during the clustering process. For large data sets, our method can save the computation time by reducing the number of data points without significant loss of accuracy. Moreover, our method can deal with imbalanced data sets effectively by alleviating the influence of dominant class.

• Proceedings of the IEEK Conference
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• summer
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• pp.371-375
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• 2004

Fault diagnosis is one of the most studied problems in process engineering. Recently, great research interest has been devoted to approaches that use classification methods to detect faults. This paper presents an application of a newly developed classification method - support vector machines - for fault diagnosis in an industrial case. A real set of operation data of a motor pump was used to train and test the support vector machines. The experiment results show that the support vector machines give higher correct detection rate of faults in comparison to rule-based diagnostics. In addition, the studied method can work with fewer training instances, what is important for online diagnostics.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.26-29
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• 2012

In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3B
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• pp.100-111
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• 2008

In this paper, to support a QoS level appropriate for the user in Wireless Home Network based Wireless LAN, we propose a QoS support architecture which includes Wired Network and Wireless Network. Actually, an important problem to support QoS in Wireless Home Network is approached not only on a MAC level in Wireless LAN but on a integrated method to combine Network layer with Datalink layer. Applying the integrated QoS support method. It is possible to provide QoS support architecture using a Wireless LAN terminal with a minimum changing, the proposed scheme has advantage of QoS support method, which is more superior than a existing scheme to support QoS in MAC level of Wireless LAN. Simulation results that overall performance of the proposed scheme can be improved.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.14-19
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• 2019

Stress affects the type of adaptation required for each case and the type of social support is also different. In order for social support to have a buffer effect on stress, we want to understand how to measure social support and support according to specific stress situations. Therefore, this study examines coping behaviors of community service workers exposed to these job stresses and examines the effect of support system (family support, peer support, superior support) on coping behavior. The purpose of this study is to investigate the effects of stress, coping resources and coping behaviors of community service workers. In this study, self - report method was used to investigate the questionnaire using structured questionnaires. In this study, the statistical program was used for data analysis and hierarchical regression analysis.

• Journal of Power System Engineering
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• v.11 no.1
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• pp.33-38
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• 2007

Recent, The propeller had high performance according as high performance of small ship. So, We has the development for azimuth thrusters. This Paper has structure improvement of steering support flange in azimuth thrusters. Steering support flange is very important part. because, Steering support flange supports all weight of azimuth thrusters. We has static & dynamic analysis of Steering support flange, and we discover the very safety. So, We has optimum design for the cost reduction. The first method of optimum design, We has the thickness reduce to 30mm from 5mm. Next method of optimum design, We had added stiffener. And we has the structure & dynamic behavior analysis. We had to dynamic behavior analysis. The first, We had to modal analysis. The result of 1st-modal analysis is that original model had to 76.48hz and new model had to 200.9hz. The second, We had to harmonic analysis. The result, We gave the thrust power to steering support flange. and We had to frequency analysis to $0{\sim}500hz$. The result, Deflection ration reduce to 16.64.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.221-235
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• 2023

To calculate the vibrations of a tout cable subjected to axial support excitations, a nonlinear relationship of cable force and the support displacement under static situations are employed to depict the quasi-static vibration of the cable. The dynamic components of quasi-static vibration are inputted as "direct loads" to cause the parametric vibrations on the cable. Both the governing equations of motion and deformation compatibility for parametric vibrations are then derived, which indicates the high coupling of cable parametric force and deformation. Numerical solutions, based on the finite difference method, are put forward for the parametric vibrations, which is validated by the finite element method under periodic axial support excitations. For the quasi-static response, the shorter cables are more sensitive to support excitations than longer ones at small cable force. The quasi-static cable force makes the greatest contribution to the total cable force, but the parametric cable force is responsible for the occurrence of cable loosening at large excitation amplitudes. Moreover, this study also revealed that the traditional approach, assuming a linear relationship between quasi-static cable force and axial support displacement, would result in some great error of the cable parametric responses.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.1-12
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• 2020

This is a study on the direction of the teaching support program contents analysis and teaching support platform of the teaching and learning center. To this end, in April 2020, a literature study was conducted, an analysis of the current status of teaching support at other universities and K universities, an analysis of professor interviews, and expert verification were conducted. The main research results are as follows. First, as a result of examining the current status of teaching support programs at 24 universities, it was confirmed that special lectures on teaching methods, class consulting, teaching method research meetings, and educational resource rooms were operated as representative programs. Second, the basic structure of the platform is composed of a lecture case sharing bulletin board to enable active exchange of opinions on teaching methods among teachers, a teaching support program application bulletin board to enable application for a teaching method program, and Edu-tech to activate the platform, and a professor support menu. Third, the contents of the teaching support platform were implemented based on the basic structure of the teaching support platform. This study analyzed the contents of the teaching support program and conducted a study to suggest the direction of the teaching support platform to discuss the direction of establishing an effective teaching support platform.

• Journal of Family Resource Management and Policy Review
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• v.19 no.1
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• pp.23-47
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• 2015

The purpose of this study was to investigate social workers' personal experiences providing social support to multi-cultural family in a multi-cultural family center. The data were collected through in-depth interviews with 14 social workers at the multi-cultural family center, and were analyzed using a phenomenological research method. The major findings were as follows : The social workers' personal experiences with and understanding of social support were classified as 4 categories : 'source of emotional support to the multi-cultural family', 'diverse and systematic educational support', 'excessive demands on material support', and 'daily life support and connection with community network'. The social workers recognized emotional and educational support as essential factors in providing social support to multi-cultural family. However, the social workers' perceptions of material support derived from negative personal experiences stemming from excessive demands and misunderstanding for material support. These results showed that social workers at the multi-cultural family center provided multi-cultural families with social support and that they interacted with community support system and multi-cultural families to increase their satisfaction.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.