• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 춘계학술대회 논문집
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• pp.209-212
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• 2001

It is known that the mim forming processes show somewhat different phenomena compared with the conventional metal forming processes, namely, the size effect, enhanced friction effect and etc. Such typical phenomena, however, are not predicted by the conventional finite element analysis, which has been an efficient numerical tool to predict the metal forming processes. It is due to the fact that the constitutive relations used does not describe the microstructural characteristics of the materials. In the present investigation, the finite element formulation using the rate-dependent rigid plastic crystal plasticity model of the face-centered cubic materials is conducted to predict the micro mechanical behaviors during the mim forming processes. The finite element analysis, however, provides mesh-dependent solutions for the intragranular deformations. Therefore, the couple stress energy is additionally introduced into the variational principle and formulated within the framework of the rigid plastic finite element method to obtain mesh-independent solutions. Micro deformations of single crystal and bicrystal with various orientations are calculated to show the potential of the developed formulation.

• Structural Engineering and Mechanics
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• 제24권5호
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• pp.621-639
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• 2006

Stability of a cylindrical shell subject to a uniform axial compression, which is a power function of time, is examined within the framework of small strain elasto-plasticity. The material of the shell is incompressible and the effect of the elastic unloading is considered. Initially, employing the infinitesimal elastic-plastic deformation theory, the fundamental relations and Donnell type stability equations for a cylindrical shell have been obtained. Then, employing Galerkin's method, those equations have been reduced to a time dependent differential equation with variable coefficient. Finally, for two initial conditions applying a Ritz type variational method, the critical static and dynamic axial loads, the corresponding wave numbers and dynamic factor have been found. Using those results, the effects of the variations of loading parameters and the variations of power of time in the axial load expression as well as the variations of the radius to thickness ratio on the critical parameters of the shells for two initial conditions are also elucidated. Comparing results with those in the literature validates the present analysis.

• Steel and Composite Structures
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• 제19권4호
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• pp.1011-1033
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• 2015

In this article, large amplitude bending behaviour of laminated composite flat panel under combined effect of moisture, temperature and mechanical loading is investigated. The laminated composite panel model has been developed mathematically by introducing the geometrical nonlinearity in Green-Lagrange sense in the framework of higher-order shear deformation theory. The present study includes the degraded composite material properties at elevated temperature and moisture concentration. In order to achieve any general case, all the nonlinear higher order terms have been included in the present formulation and the material property variations are introduced through the micromechanical model. The nonlinear governing equation is obtained using the variational principle and discretised using finite element steps. The convergence behaviour of the present numerical model has been checked. The present proposed model has been validated by comparing the responses with those available published results. Some new numerical examples have been solved to show the effect of various parameters on the bending behaviour of laminated composite flat panel under hygro-thermo-mechanical loading.

• 스마트미디어저널
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• 제9권3호
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• pp.80-89
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• 2020

Out - of - distribution (OOD) samples are frequently encountered when deploying a classification model in plenty of real-world machine learning-based applications. Those samples are normally sampling far away from the training distribution, but many classifiers still assign them high reliability to belong to one of the training categories. In this study, we address the problem of removing OOD examples by estimating marginal density estimation using variational autoencoder (VAE). We also investigate other proper methods, such as temperature scaling, Gaussian discrimination analysis, and label smoothing. We use Chonnam National University (CNU) weeds dataset as the in - distribution dataset and CIFAR-10, CalTeach as the OOD datasets. Quantitative results show that the proposed framework can reject the OOD test samples with a suitable threshold.

• Journal of the Optical Society of Korea
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• 제20권6호
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• pp.752-761
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• 2016

Hyperspectral images are often contaminated with stripe noise, which severely degrades the imaging quality and the precision of the subsequent processing. In this paper, a variational model is proposed by employing spectral-spatial adaptive unidirectional variation and a sparse representation. Unlike traditional methods, we exploit the spectral correction and remove stripes in different bands and different regions adaptively, instead of selecting parameters band by band. The regularization strength adapts to the spectrally varying stripe intensities and the spatially varying texture information. Spectral correlation is exploited via dictionary learning in the sparse representation framework to prevent spectral distortion. Moreover, the minimization problem, which contains two unsmooth and inseparable $l_1$-norm terms, is optimized by the split Bregman approach. Experimental results, on datasets from several imaging systems, demonstrate that the proposed method can remove stripe noise effectively and adaptively, as well as preserve original detail information.

• Geomechanics and Engineering
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• 제13권3호
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• pp.505-515
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• 2017

Based on the collapse characteristics of a shallow rectangular cavity, a three-dimensional failure mechanism which can be used to study the collapsing region of the rock mass above a shallow cavity roof is constructed. Considering the effects of surcharge pressure and surface bolt on the collapsing block, the external rate of works produced by surcharge pressure and surface bolt are included in the energy dissipation calculation. Using variational approach, an analytic expression of surface equation for the collapsing block, which can be used to study the collapsing region of the rock mass above a shallow cavity roof, is derived in the framework of upper bound theorem. Based on the analytic expression of surface equation, the shape of the collapsing block for shallow cavity is drawn. Moreover, the changing law of the collapsing region for different parameters indicates that the collapsing region of rock mass decreases with the increase of the density of surface bolt. This conclusion can provide reference for practicing geotechnical engineers to achieve an optimal design of supporting structure for a shallow cavity.

• Steel and Composite Structures
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• 제32권5호
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• pp.657-670
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• 2019

This paper proposes a one-dimensional fiber beam element model taking account of materially non-linear behavior, benefiting the highly efficient elastic-plastic analysis of girders with shear-lag effects. Based on the displacement-based fiber beam-column element, two additional degrees of freedom (DOFs) are added into the proposed model to consider the shear-lag warping deformations of the slabs. The new finite element (FE) formulations of the tangent stiffness matrix and resisting force vector are deduced with the variational principle of the minimum potential energy. Then the proposed element is implemented in the OpenSees computational framework as a newly developed element, and the full Newton iteration method is adopted for an iterative solution. The typical materially non-linear behaviors, including the cracking and crushing of concrete, as well as the plasticity of the reinforcement and steel girder, are all considered in the model. The proposed model is applied to several test cases under elastic or plastic loading states and compared with the solutions of theoretical models, tests, and shell/solid refined FE models. The results of these comparisons indicate the accuracy and applicability of the proposed model for the analysis of both concrete box girders and steel-concrete composite girders, under either elastic or plastic states.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5978-5999
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• 2018

Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.

• Structural Engineering and Mechanics
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• 제84권5호
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• pp.651-664
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• 2022

A precise prediction of the ultimate bond strength between rebar and surrounding concrete plays a major role in structural design, as it effects the load-carrying capacity and serviceability of a member significantly. In the present study, Gaussian models are employed for modelling bond strength of ribbed steel bars embedded in concrete. Gaussian models offer a non-parametric method based on Bayesian framework which is powerful, versatile, robust and accurate. Five different Gaussian models are explored in this paper-Gaussian Process (GP), Variational Heteroscedastic Gaussian Process (VHGP), Warped Gaussian Process (WGP), Sparse Spectrum Gaussian Process (SSGP), and Twin Gaussian Process (TGP). The effectiveness of the models is also evaluated in comparison to the numerous design formulae provided by the codes. The predictions from the Gaussian models are found to be closer to the experiments than those predicted using the design equations provided in various codes. The sensitivity of the models to various parameters, input feature space and sampling is also presented. It is found that GP, VHGP and SSGP are effective in prediction of the bond strength. For large data set, GP, VHGP, WGP and TGP can be computationally expensive. In such cases, SSGP can be utilized.

• 한국정보전자통신기술학회논문지
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• 제13권3호
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• pp.197-205
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• 2020

한국어는 자음과 모음과 같은 음소 단위의 발음은 고정되어 있고 표기에 대응하는 발음은 변하지 않기 때문에 외국인 학습자가 쉽게 접근할 수 있다. 그러나 단어와 어구, 문장을 말할 때는 음절과 음절의 경계에서 소리의 변동이 다양하고 복잡하며 표기와 발음이 일치하지 않기 때문에 외국어로서의 한국어 표준 발음 학습은 어려운 면이 있다. 그러나 영어 같은 다른 언어와 달리 한국어의 표기와 발음의 관계는 논리적인 원리에 따라 예외 없이 규칙화 할 수 있는 장점이 있으므로 발음오류에 대해 체계적인 분석이 가능한 것으로 여겨진다. 본 연구에서는 오류 발음과 표준 발음의 차이를 컴퓨터 화면상의 상대적 거리로 표현하여 시각화하는 모델을 제시한다. 기존 연구에서는 발음의 특징을 단지 컬러 또는 3차원 그래픽으로 표현하거나 입과 구강의 변화하는 형태를 애니메이션으로 보여 주는 방식에 머물러 있으며 추출하는 음성의 특징도 구간의 평균과 같은 점 데이터를 이용하는데 그치고 있다. 본 연구에서는 시계열로 표현되는 음성데이터의 특성 및 구조를 요약하거나 변형하지 않고 직접 이용하는 방법을 제시한다. 이를 위해서 딥러닝 기법을 토대로 자기조직화 알고리즘과 variational autoencoder(VAE) 모델 및 마코브 확률모델을 결합한 확률적 SOM-VAE 기법을 사용하여 클러스터링 성능을 향상시켰다.