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Design Pattern to Improve the Applicability In a Reengineering Environment Represented with UML (재공학 환경에서 적용성 향상을 위한 디자인 패턴의 UML 표현)

  • 최성만;김송주;유철중;장옥배;이정열
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.04c
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    • pp.148-150
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    • 2003
  • 본 논문은 재공학 환경에서 기존의 디자인 패턴을 적용성 향상을 위해 UML로 표현하였으며, 대상으로는 디자인 패턴 중에서 Strategy Pattern과 Visitor Pattern을 이용해 보았다. Strategy Pattern에서는{variation}과 {incomplete}를 이용하였다.{variation}은 메소드 구현시 패턴을 캡슐화하여 다양하게 변경될 수 있도록 하였다. 또한,{incomplete}는 주어진 관계를 만족하는 새로운 클래스가 패턴 인스턴스화 동안에 추가될 수 있도록 하였다. Visitor pattern에서의{extensible}은 클래스 인터페이스가 패턴을 캡슐화하고 있는 개념으로 다양하게 변경될 수 있도록 하였다. 즉, 클래스 인터페이스는 패턴 인스턴스화에 의존적이며 새로운 메소드와 속성을 클래스가 기능적으로 확장할 수 있는 기능을 갖는다.

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미분구적법을 이용한 곡선보의 내평면 진동분석

  • Gang Gi-Jun;Han Ji-Won
    • Proceedings of the Korean Institute of Industrial Safety Conference
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    • 2000.11a
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    • pp.17-26
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    • 2000
  • The early investigators into the in-plane vibration of rings were Hoppe $Hoppe ^{1)}$ and $Love ^{2)}$. $Love ^{2)}$ Improved on Hoppe's theory by allowing for stretching of the ring. $Lamb ^{3)}$ investigated the statics of incomplete ring with various boundary conditions and the dynamics of an incomplete free-free ring of small curvature. Den $Hartog ^{4)}$ used the Rayleigh-Ritz method for finding the lowest natural frequency of circular arcs with simply supported or clamped ends and his work was extended by Volterra and $Morell ^{5)}$ for the vibrations of arches having center lines in the form of cycloids, catenaries or parabolas.(omitted)

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Option Pricing with Bounded Expected Loss under Variance-Gamma Processes

  • Song, Seong-Joo;Song, Jong-Woo
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.575-589
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    • 2010
  • Exponential L$\acute{e}$evy models have become popular in modeling price processes recently in mathematical finance. Although it is a relatively simple extension of the geometric Brownian motion, it makes the market incomplete so that the option price is not uniquely determined. As a trial to find an appropriate price for an option, we suppose a situation where a hedger wants to initially invest as little as possible, but wants to have the expected squared loss at the end not exceeding a certain constant. For this, we assume that the underlying price process follows a variance-gamma model and it converges to a geometric Brownian motion as its quadratic variation converges to a constant. In the limit, we use the mean-variance approach to find the asymptotic minimum investment with the expected squared loss bounded. Some numerical results are also provided.

An Application of Game theory to Power Transactions under Incomplete Information (불완전정보 전력거래 해석을 위한 게임이론의 적용)

  • Kang, Dong-Joo;Park, Man-Guen;Kim, Bal-Ho;Park, Jong-Bae
    • Proceedings of the KIEE Conference
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    • 2000.07a
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    • pp.19-21
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    • 2000
  • This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace such as PoolCo. The conventional least-cost approaches for the generation resource schedule can not exactly handle recent real-world situations. A systematic tool using game theory for the market participants is presented such that it determines the net profits through the optimal bidding strategies including the strategies for the bidding prices and bidding generations. We treat this power transaction game as incomplete information one, which means each market participants does not know other's cost function. And the demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

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An Improved Identification Method for Joint Parameters in Structures with Imcomplete Modal Parameters (불완전 모우드 변수를 이용한 구조물 결합부 변수 규명 방법의 개선)

  • 홍성욱
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1998.04a
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    • pp.244-249
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    • 1998
  • The present paper improves the direct identification scheme based upon the equation error formulation with incomplete modal data. First, an indirect estimation technique is considered for estimating unmeasured elements of latent vectors by the combined use of a model and measured incomplete eigen vectors. It is used for estimating the other elements of eigen vectors, which are essential for identification but not available. Next an index is introduced here to indicate the quality of estimation with respect to the mode and the measured positions. A sensitivity formula for eigenvalues with respect to the unknown joint coefficient is also derived to select the modes appropriate for identification. An identification strategy is suggested to meet with practical problems with the help of the index and sensitivity formula. The index and the sensitivity are proved to be useful for selecting measurement positions and modes appropriate for identification A comprehensive simulation study is performed to test the proposed method.

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Reconstruction of structured models using incomplete measured data

  • Yu, Yan;Dong, Bo;Yu, Bo
    • Structural Engineering and Mechanics
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    • v.62 no.3
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    • pp.303-310
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    • 2017
  • The model updating problems, which are to find the optimal approximation to the discrete quadratic model obtained by the finite element method, are critically important to the vibration analysis. In this paper, the structured model updating problem is considered, where the coefficient matrices are required to be symmetric and positive semidefinite, represent the interconnectivity of elements in the physical configuration and minimize the dynamics equations, and furthermore, due to the physical feasibility, the physical parameters should be positive. To the best of our knowledge, the model updating problem involving all these constraints has not been proposed in the existed literature. In this paper, based on the semidefinite programming technique, we design a general-purpose numerical algorithm for solving the structured model updating problems with incomplete measured data and present some numerical results to demonstrate the effectiveness of our method.

Recovering Incomplete Data using Tucker Model for Tensor with Low-n-rank

  • Thieu, Thao Nguyen;Yang, Hyung-Jeong;Vu, Tien Duong;Kim, Sun-Hee
    • International Journal of Contents
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    • v.12 no.3
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    • pp.22-28
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    • 2016
  • Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output.

A classification for the incomplete block designs according to the structure of multi-nested block circulant pattern matrix (다중순환형식행렬의 구조에 의한 불완비블럭 계획의 분류)

  • 배종성
    • The Korean Journal of Applied Statistics
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    • v.2 no.1
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    • pp.54-64
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    • 1989
  • The paper by Kurkjian and Zelen(1963) introducted the Property A which related to a structural property of concordance matrix of the column incidence matrix. On the other hand, Paik(1985) showed the property of the concordance matrix, which has multinested block circulant pattern matrix, and this structural property was termed Property C by Paik(1985). This paper classifies the incomplete block designs according to the pattern of the concordence matrix which has multi-nested block circulant pattern. The purpose of this classification simplified the solution of reduced normal equation and plan of the design.

Thermal Behavior of Silver Paste to Improve Reliability and Image Quality of LCoS Panel

  • Chen, Yu-Hsien;Huang, I-Chen;Huang, Li-Chen;Wang, Jiun-Ming;Chen, Kun-Hong;Liu, Kuang-Hua;Li, Huai-An;Lo, Yu-Cheng;Liu, Pei-Yu
    • 한국정보디스플레이학회:학술대회논문집
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    • 2006.08a
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    • pp.1398-1401
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    • 2006
  • Silver paste curing process is very important in LCoS panel manufacture because incomplete curing process will cause poor bonding strength and increase resistance. The imperfection situation results in poor reliability and the variation of the common voltage, respectively. The change of the common voltage causes image flicker. According to Kinetics, we acquire activation energy by using dynamic DSC and compare two kinds of silver paste. From the result of isothermal DSC, we get optimum curing parameters to solve the flicker problem caused of incomplete curing of the silver paste.

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Clustering of Incomplete Data Using Autoencoder and fuzzy c-Means Algorithm (AutoEncoder와 FCM을 이용한 불완전한 데이터의 군집화)

  • 박동철;장병근
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.700-705
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    • 2004
  • Clustering of incomplete data using the Autoencoder and the Fuzzy c-Means(PCM) is proposed in this paper. The Proposed algorithm, called Optimal Completion Autoencoder Fuzzy c-Means(OCAEFCM), utilizes the Autoencoder Neural Network (AENN) and the Gradiant-based FCM (GBFCM) for optimal completion of missing data and clustering of the reconstructed data. The proposed OCAEFCM is applied to the IRIS data and a data set from a financial institution to evaluate the performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the OCAEFCM shows 18%-20% improvement of performance over OCSFCM.