• 한국지능시스템학회논문지
• /
• 제13권2호
• /
• pp.237-242
• /
• 2003

본 논문에서는 클러스터링을 기반으로 하는 새로운 침입탐지 알고리즘인 Kernel-ART를 제안한다. Kernel-ART는 개념벡터(concept vector)와 SVM(support vector machine)의 머서 커널(mercer-kernel)을 온라인 클러스터링 알고리즘인 ART(adaptive resonance theory)에 접목시킨 새로운 알고리즘으로서 교사학습 기반 침입탐지 시스템의 단점을 극복할 뿐만 아니라, 클러스터링 기반 침입탐지 시스템에서 요구되는 모든 평가 기준들을 만족한다. 본 논문에서 제안하는 알고리즘은 클러스터를 점증적으로 생성함으로써 여러 가지 다양한 침입 유형들을 실시간으로 탐지할 수 있다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
• /
• pp.109-113
• /
• 2002

In this paper, we propose a new intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based 105 but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.

• 충청수학회지
• /
• 제23권1호
• /
• pp.59-63
• /
• 2010

In this paper, we introduce the concept of weakly-ultra-${\alpha}{\psi}$-separation of two sets in a topological space using ${\alpha}{\psi}$-open sets. The ${\alpha}{\psi}$-closure and the ${\alpha}{\psi}$-kernel are defined in terms of this weakly ultra-${\alpha}{\psi}$-separation. We also investigate some of the properties of the ${\alpha}{\psi}$-kernel and the ${\alpha}{\psi}$-closure.

• 호남수학학술지
• /
• 제43권4호
• /
• pp.587-596
• /
• 2021

In this article, using the concept proposed reciently by the author, of a Generalized k-Proportional Fractional Integral Operators with General Kernel, new integral inequalities are obtained for convex functions. It is shown that several known results are particular cases of the proposed inequalities and in the end new directions of work are provided.

• 정보학연구
• /
• 제4권2호
• /
• pp.25-36
• /
• 2001

실시간 커널은 시간적인 요소를 가장 핵심으로 고려하여 설계된다. 따라서 실시간 커널은 작은 용량을 가지며 빠르게 예측할 수 있어야 한다. 또한 실시간 스케줄링에 요구되는 많은 변화들을 통해서 실시간 커널에 융통성을 부여해야 한다. 본 논문에서 제안한 분산 이중 실시간 커널 시스템은 실시간 제약들을 고려한 실시간 커널과 일반적인 커널의 특성을 가지도록 설계한다. 실시간 제약 조건인 인터럽트 지연 시간, 스케줄링의 정확성, 메시지 전달시간을 만족하기 위하여 실시간 커널에는 실시간 태스크 처리와 인터럽트 처리, 타이밍을 처리하도록 하였고 비실시간 커널은 일반적인 태스크를 처리하도록 한다. 또한, 기존의 실시간 커널인 RT-Linux, QNX와 제안한 실시간 커널이 인터럽트 지연, 스케줄링 정확성, 메시지 전달시간 등을 비교 분석함으로써 실시간 제약조건을 만족함을 보인다

• 한국통신학회논문지
• /
• 제36권7C호
• /
• pp.428-434
• /
• 2011

Recently, subspace analysis has raised its performance to a higher level through the adoption of kernel-based nonlinearity. Especially, the radial basis function, based on its nonparametric nature, has shown promising results in face recognition. However, due to the endemic small sample size problem of face data, the conventional kernel-based feature extraction methods have difficulty in data representation. In this paper, we introduce a novel variant of the RBF kernel to alleviate this problem. By adopting the concept of the nearest feature line classifier, we show both effectiveness and generalizability of the proposed method, particularly regarding the small sample size issue.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 ITC-CSCC -1
• /
• pp.489-492
• /
• 2000

Because of the great variety of demands on real-time scheduling, real-time kernel should be small, fast and predictable. In this paper, we present that Real-time applications should be split into small and simple parts with hard real-time constraints. Following this concept, we have designed and implemented to have the properties of both hard real-time kernel and general kernel. And, to prove be useful the proposal kernel, we compare and analyze the performance with RT-Linux 0.5a

• 한국수학교육학회지시리즈E:수학교육논문집
• /
• 제16권
• /
• pp.139-147
• /
• 2003

While the statistical concept 'order statistics' has a great number of applications in our society ranging from industry to military analysis, it is not necessarily an easy concept to understand for many people. Adding some interesting simulation activities of this concept to the probability or statistics curriculum, however, can enhance the learning curve greatly. A hands-on and a graphic calculator based activities of a missile simulation were introduced by Kim(2003) in the context of order statistics. This article revisits the two activities in his paper and point out a dilemma that occurs from the violation of an assumption on two deviation parameters associated with the missile simulation. A third activity is introduced to resolve the dilemma in the terms of a kernel density estimation which is a nonparametric approach.

• 한국기계가공학회지
• /
• 제8권3호
• /
• pp.21-26
• /
• 2009

The finite element analysis of metal forming processes often fails because of severe mesh distortion at large deformation. As the concept of meshless methods, only nodal point data are used for modeling and solving. As the main feature of these methods, the domain of the problem is represented by a set of nodes, and a finite element mesh is unnecessary. This computational methods reduces time-consuming model generation and refinement effort. It provides a higher rate of convergence than the conventional finite element methods. The displacement shape functions are constructed by the reproducing kernel approximation that satisfies consistency conditions. In this research, A meshless method approach based on the reproducing kernel particle method (RKPM) is applied with metal forming analysis. Numerical examples are analyzed to verify the performance of meshless method for metal forming analysis.

• Journal of the Korean Data and Information Science Society
• /
• 제16권3호
• /
• pp.705-712
• /
• 2005

Entropy is the basic concept of information theory. It is well defined for random varibles with known probability density function(pdf). For given data with unknown pdf, entropy should be estimated. Usually, estimation of entropy is based on the approximations. In this paper, we consider a kernel based approximation and compare it to the cumulant approximation method for several distributions. Monte carlo simulation for various sample size is conducted.