• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.227-232
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• 2003

Recently, support vector learning attracts an enormous amount of interest in the areas of function approximation, pattern classification, and novelty detection. One of the main reasons for the success of the support vector machines(SVMs) seems to be the availability of global and sparse solutions. Among the approaches sharing the same reasons for success and exhibiting a similarly good performance, we have KFD(kernel Fisher discriminant) approach. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and the KFD approach for regression. After reviewing support vector regression, semi-parametric approach for including predetermined basis functions, and the KFD regression, this paper presents an extension of the conventional KFD approach for regression toward the direction that can utilize predetermined basis functions. The applicability of the presented method is illustrated via a regression example.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.153-160
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• 2002

This paper describes the design and implementation of library for real-time operating system Q+, that was developed for the internet appliance. The library in the real-time operating system should be defined according to the standard interface and support the functions that are adequate to the real-time application. To ensure the compatibility between application programs, the Q+ library follows industrial and international standards, such as POSIX.1, ISO 7942 GKS. And, to support the Q+ application, library provides C standard functions, graphic/window functions, network functions, security support functions, file system functions. The Q+ library was implemented using the Q+ kernel, Digital TV set-top box, and KBUG debugging tool.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.397-407
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• 2017

This study aims to suggest development direction of smart city service support institutions for the development of smart cities. For this purpose, First of all, the necessity of smart city service support organization, legal basis and major functions were theoretically examined. Second, reviewed the functions of smart city service support institutions and conducted relative importance and in depth interviews with experts. Third, suggested development direction of smart city service support institutions which summarized the above results is suggested. The result of this study is meaningful in that it suggests roles, functions and future directions of smart city service support institutions.

• Korean Journal of Child Studies
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• v.17 no.2
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• pp.61-78
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• 1996

The purpose of this study was to describe maternal social networks and to examine their relationships to maternal perceptions of parenting task difficulty. One hundred and thirty-three mothers of preschool children responded to a questionnaire indicating individuals in their networks, support functions, and perceptions of task difficulty. Mothers reported an average of 6.5 persons in their networks, including primarily with her own mother, the husband, mother-in-law, and sisters. While support was provided mainly by her husband and her own family members, the kinds of support varied depending on the person in networks. It was also found that support functions were different in terms of maternal job status, sex of the child, and the child's previous experience in day care or early childhood education settings. Emotional support from networks was significantly related to parenting task difficulty, especially in daily routine care. Mothers who perceived more emotional support from networks reported parenting to be less difficult.

• Journal of applied mathematics & informatics
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• v.2 no.2
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• pp.83-95
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• 1995

Given a closed subset of the family $S^{*}(\alpha)$ of functions starlike of order $\alpha$, a continuous Frechet differentiable functional J, is constructed with this collection as the solution set to the extremal problem ReJ(f) over $S^{*}(\alpha)$. The support points of $S^{*}(\alpha)$ is completely characterized and shown to coincide with the extreme points of its convex hulls. Given any finite collection of support points of $S^{*}(\alpha)$ a continuous linear functional J, is constructed with this collection as the solution set to the extremal problem ReJ(f) over $S^{*}(\alpha)$.

• Bulletin of the Korean Mathematical Society
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• v.36 no.3
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• pp.609-619
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• 1999

IN this note we study more about the omitted are for the extremal functions and its {{{{ {π } over {4 } }}}}-property based upon Schiffer's variational method and zBrickman-Wilken's result. we give an example other than the Koebe function which is both a support point of S and the extreme point of HS. Furthermore, we discuss the relations between the support points and the L wner chain.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.211-225
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• 2004

A mixed type dual to a programming problem containing support functions in a objective as well as constraint functions is formulated and various duality results are validated under generalized convexity and invexity conditions. Several known results are deducted as special cases.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1381-1395
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• 2009

Mixed type second order dual to the non-differentiable problem containing support functions is formulated and duality theorems are proved under generalized second order convexity conditions. It is pointed out that the mixed type duality results already reported in the literature are the special cases of our results.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.125-136
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• 2008

In many practical engineering design problems, the form of objective functions is not given explicitly in terms of design variables. Given the value of design variables, under this circumstance, the value of objective functions is obtained by real/computational experiments such as structural analysis, fluid mechanic analysis, thermodynamic analysis, and so on. These experiments are, in general, considerably expensive. In order to make the number of these experiments as few as possible, optimization is performed in parallel with predicting the form of objective functions. Response Surface Methods (RSM) are well known along this approach. This paper suggests to apply Support Vector Machines (SVM) for predicting the objective functions. One of most important tasks in this approach is to allocate sample data moderately in order to make the number of experiments as small as possible. It will be shown that the information of support vector can be used effectively to this aim. The effectiveness of our suggested method will be shown through numerical example which is well known in design of engineering.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.