• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.215-226
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• 2010

Since product design strongly depends on the experience and ability of the designers, and a long lead time is required for the product design stage, introducing a support system related to this experience and ability is an effective technique to reduce the lead time. In this paper, an information system is developed to support the development of engineering mechanisms with the evaluation of the assembly process on the basis of the abstract functions required for new products. The developed system is based on a database system involving the following data structure: (1) a hierarchical structure related to information about the product functions, (2) the relationship between the parts and engineering functions and/or mechanisms of products, and (3) the relationship between the parts and manufacturing characteristics. The system stores the relationships between the product functions, structure of parts, and assembly characteristics. This information can then be interactively retrieved using the data structure described in (1), (2), and (3). A procedure for designing new products is proposed that involves using the information about existing products. This paper presents the characteristics of the proposed procedure and the developed information system. In addition, a case study of the redesign of a simple structured robot by using the proposed procedure is discussed.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1319-1325
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• 2010

Quantile regression provides a more complete statistical analysis of the stochastic relationships among random variables. Sometimes quantile functions estimated at different orders can cross each other. We propose a new non-crossing quantile regression method applying support vector median regression to restricted regression quantile, restricted support vector quantile regression. The proposed method provides a satisfying solution to estimating non-crossing quantile functions when multiple quantiles for high dimensional data are needed. We also present the model selection method that employs cross validation techniques for choosing the parameters which aect the performance of the proposed method. One real example and a simulated example are provided to show the usefulness of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.393-401
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• 2012

This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

• East Asian mathematical journal
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• v.37 no.3
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• pp.333-354
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• 2021

A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.315-315
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• 2000

In this paper, we perform the time series prediction using the SVM(Support Vector Machine). We make use of two different loss functions and two different kernel functions; i) Quadratic and $\varepsilon$-insensitive loss function are used; ii) GRBF(Gaussian Radial Basis Function) and ERBF(Exponential Radial Basis Function) are used. Mackey-Glass time series are used for prediction. For both cases, we compare the results by the SVM to those by ANN(Artificial Neural Network) and show the better performance by SVM than that by ANN.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.343-351
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• 2008

By supervised learning with p predictors, we frequently obtain a prediction function of the form $y\;=\;f(x_1,...,x_p)$. When $p\;{\geq}\;3$, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.

• Korean Journal of Social Welfare Studies
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• v.48 no.4
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• pp.91-120
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• 2017

This study aimed (a) to examine the association between chronic illness and multidimensional disability(i.e., psychological/emotional functions, activity capacity, and participation frequency) among older adults with disabilities, (b) to investigate the effect of formal and informal supports on multidimensional disability, and (c) to analyze the moderating effects of formal and informal supports on the association between chronic illness and multidimensional disability. This study used 2014 Korea Welfare Panel Study(the 9th wave) data and 450 older adults with disabilities aged 50 and over were selected as the study target. The research model was analyzed by structural equation modeling using IBM AMOS 22.0. Based on the ICF framework developed by WHO, health condition was measured by the level of chronic illness; psychological/emotional functions were measured by health satisfaction, self-esteem, and depression; activity capacity was measured by ADLs and IADLs; participation frequency was measured by the total number of social activities joined; formal support was measured by the total number of formal welfare services for people with disabilities utilized; informal support was measured by perceived social support. The findings showed that the level of chronic illness was negatively associated with psychological/emotional functions among the older adults with disabilities. The informal support positively affected psychological/emotional functions and activity capacity, whereas the formal support showed the opposite result. That is, the formal support negatively influenced activity capacity and showed a moderating effect on the association between the level of chronic illness and the psychological/emotional functions in a reverse way. Based on the results, practice and policy implications for alleviating disability level among the older adults with disabilities were discussed.

• Structural Engineering and Mechanics
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• v.52 no.3
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• pp.595-601
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• 2014

For analysis of the plates and membranes by numerical or analytical methods, the question of choice of the system of functions satisfying the different boundary conditions remains a major challenge to address. It is to this issue that is dedicated this work based on an approach of choice of combinations of trigonometric functions, which are shape functions of a bended beam with the boundary conditions corresponding to the plate support mode. To do this, the shape functions of beam vibrations for strength analysis of the rectangular plates by Kantorovich-Vlasov's method is considered. Using the properties of quasi-orthogonality of those functions allowed assessing to differential equation for every member of the series. Therefore it's proposed some new forms of integration of the beam functions, in order to simplify the problem.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.662-665
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• 2008

This research attempts to develop 4D CAD function to support optimal road design by expanding the existing 4D CAD utilization system, which focused on construction phase, to the design phase. The functions such as earthwork simulation for selecting of road alignment, alternative route simulation and structure type simulation were suggested as functions to support road design. Through those virtual reality (VR) functions, visual confirmation of the condition of route and earthwork Is possible by the developed system, and an optimal alternative route can be selected by carrying out layout simulation of the alternative route. The functions presented in this research provide the decision making tools based virtual model for efficient support to road design.

• The Journal of Sustainable Design and Educational Environment Research
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• v.4 no.4
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• pp.25-38
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• 2004

Schools have focused so far on a student-oriented education. As the roles of schools, however, have been increasingly emphasized in the information society, community-centered functions are now additionally required. Beyond simply allowing communities to utilize selected facilities, schools can conduct re-education programs for community residents and actively use their facilities for such purposes. As explained above, schools must continuously evolve to meet current needs and demands, such as by offering special classes and utilizing learning facilities in the elementary levels to promote learning in ever-changing societies. This study analyzed the functions of school facilities to communities, as well as the educational functions involved in teaching-learning processes, in light of the advent of a knowledge and information society. Through analysis, the types of information facilities in elementary schools were derived. On the basis of such derived types, systematic and reasonable methods to estimate the scope were suggested.