• 한국자기학회:학술대회 개요집
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• 한국자기학회 2007년도 The 1st International Symposium on Advanced Magnetic Materials
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• pp.137.1-137.1
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• 2007

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2007년도 The 1st International Symposium on Advanced Magnetic Materials
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• pp.135.2-135.2
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• 2007

• 스마트미디어저널
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• 제12권4호
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• pp.59-59
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• 2023

• International Journal of Aerospace System Engineering
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• 제6권2호
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• pp.1-10
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• 2019

In this paper, the probabilistic free vibration analysis of a geometrically coupled cantilever wing with uncertain material properties is carried out using stochastic finite element (SFEM) based on first order perturbation technique. Here, both stiffness and damping of the system are considered as random parameters. The bending and torsional rigidities are assumed as spatially varying second order Gaussian random fields and represented by Karhunen Loeve (K-L) expansion. Here, the expected value, standard deviation, and probability distribution of random natural frequencies and damping ratios are computed. The results obtained from the present approach are also compared with Monte Carlo simulations (MCS). The results show that the uncertain bending rigidity has more influence on the damping ratio and frequency of modes 1 and 3 while uncertain torsional rigidity has more influence on the damping ratio and frequency of modes 2 and 3.

• Structural Engineering and Mechanics
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• 제56권5호
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• pp.767-785
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• 2015

The stochastic finite element method is employed to obtain a stochastic dynamic model of angled beams subjected to impact loads when uncertain material properties are described by random fields. Using the perturbation technique in conjunction with a precise time integration method, a random analysis approach is developed for efficient analysis of random elastic waves. Formulas for the mean, variance and covariance of displacement, strain and stress are introduced. Statistics of displacement and stress waves is analyzed and effects of bend angle and material stochasticity on wave propagation are studied. It is found that the elastic wave correlation in the angled section is the most significant. The mean, variance and covariance of the stress wave amplitude decrease with an increase in bend angle. The standard deviation of the beam material density plays an important role in longitudinal displacement wave covariance.

• 한국해양공학회지
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• 제26권2호
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• pp.68-78
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• 2012

This study proposes an improved 3-D model that includes a new non-reflected wave generation system for oblique incident and multi-directional random waves, which enables us to estimate the effect of the various wave-types on 3-D wave fields in a coastal area with permeable submerged breakwaters. Then, using the numerical results,the three-dimensional wave field characteristics around permeable submerged breakwaters are examined in cases of oblique incident and multi-directional random waves. Especially, the wave height, mean surface elevation and mean flow around the submerged breakwaters are discussed in relation to the variation of incident wave condition.

• 대한수학회지
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• 제33권4호
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• pp.801-811
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• 1996

Let $Z^d$ denote the set of all d-tuples of integers$(d \geq 1, a positive integer)$. The points in $Z^d$ will be denoted by $\underline{m},\underline{n}$, etc., or sometime, when necessary, more explicitly by $(m_1, m_2, \cdots, m_d)$, $(n_1, n_2, \cdots, n_d)$ etc. $Z^d$ is partially ordered by stipulating $\underline{m} \underline{<}\underline{n} iff m_i \leq n_i$ for each i, $1 \leq i \leq d$.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제24권4호
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• pp.211-226
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• 2017

In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권9호
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• pp.706-711
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• 2010

음성 인식기의 오류는 음성기반 응용 시스템들의 성능에 크게 영향을 주기 때문에 오류를 줄이기 위한 효과적인 처리 방법이 필요하다. 기존의 후처리 기법들은 수동 작업을 통한 코퍼스나 규칙으로 후처리를 수행하는 것이 일반적이다. 본 논문에서는 문제나 인식기의 특성에 무관하게 자동으로 학습할 수 있는 후처리 모델을 제안한다. 후처리의 문제를 오류의 인식과 수정으로 구분하고 오류 검출 문제는 순차적인 분류 문제로 간주하여 conditional random fields(CRFs)를 사용하고 오류 수정 규칙은 transformation-based learning(TBL)을 이용하여 자동 생성하여 적용하였다. 제안한 방법을 여행 예약 영역의 음성 인식기에 적용한 결과 삽입, 삭제, 치환 오류를 각각 25.85%, 3.57%, 7.42%을 수정하였으며, 이로 인해 인식기의 어휘 오류율을 2% 감소시킬 수 있었다.