• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.647-651
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• 1992

This paper presents a model-based control scheme for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload. The scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighborhood of the trajectory. Then a discrete-time PID regulator is designed based on the linearized dynamic model and Linear Quadratic(LQ) method, which generates the variational control that regulates perturbations in the vicinity of the desired trajectory.

• Structural Engineering and Mechanics
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• v.27 no.4
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• pp.457-475
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• 2007

Analysis of transverse stresses at layer interfaces in a composite laminate has always been a challenging task. Composite structures possess highly irregular material properties at layer interfaces, which cause high shear stresses. Classical Plate Theory and First Order Shear Deformation Theory (FSDT) use post computing to calculate transverse stresses. This paper presents Reissner Mixed Variational Theorem (RMVT) based finite element model to carry out layer-wise analysis of composite laminates. Selective integration scheme has been used. The formulation has been validated by solving numerical examples and comparing the results with those published in the literature.

• Structural Engineering and Mechanics
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• v.42 no.1
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• pp.1-12
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• 2012

In this study, Pasternak foundation model, which is a two parameter foundation model, is used to analyze the behavior of laterally loaded beams embedded in semi-infinite media. Total potential energy variation of the system is written to formulate the problem that yielded the required field equations and the boundary conditions. Shear force discontinuities are exposed within the boundary conditions by variational method and are validated by photo elastic experiments. Exact solution of the deflection of the beam is obtained. Both foundation parameters are obtained by self calibration for this particular problem and loading type in this study. It is shown that, like the first parameter k, the second foundation parameter G also depends not only on the material type but also on the geometry and the loading type of the system. On the other hand, surface deflection of the semi infinite media under singular loading is obtained and another method is proposed to determine the foundation parameters using the solution of this problem.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.142-146
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• 2023

We present a method for generating 3D structures and rendering objects by combining VAE (Variational Autoencoder) and GAN (Generative Adversarial Network). This approach focuses on generating and rendering 3D models with improved quality using residual learning as the learning method for the encoder. We deep stack the encoder layers to accurately reflect the features of the image and apply residual blocks to solve the problems of deep layers to improve the encoder performance. This solves the problems of gradient vanishing and exploding, which are problems when constructing a deep neural network, and creates a 3D model of improved quality. To accurately extract image features, we construct deep layers of the encoder model and apply the residual function to learning to model with more detailed information. The generated model has more detailed voxels for more accurate representation, is rendered by adding materials and lighting, and is finally converted into a mesh model. 3D models have excellent visual quality and accuracy, making them useful in various fields such as virtual reality, game development, and metaverse.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.3 no.2
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• pp.105-112
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• 1999

Density and temeprature fronts are common features of the ocean. However, frontal dynamics are not quasi-geostrophic because the isopycnal deflections associated with fronts are large compared with the scale height of the hydrostatic geopotential. The frontal geostrophic model, developed by Cushman-Roisin et al.(1992) is generally used fro describing the dynamics of surface-density ocean fronts, whereas the two-layer frontal geostrophic model is used for fronts on a sloping continental shelf. This paper investigates the baroclinic nonlinear stability of surface-density ocean fronts and fronts on a sloping continental shelf using the two-layer frontal geostrophic model mentioned above. Nonlinear stability criteria for the two kinds of fronts are obtained using Arnol'd's (1965; 1969) variational principle and a prior estimate method. This is the first time a nonlinear stability criterion for surface ocean fronts has been established, furthermore, the results obtained for fronts on a sloping bottom are superior to any previous ones.

• Journal of the Korean Solar Energy Society
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• v.36 no.3
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• pp.9-16
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• 2016

This paper discusses a refined model for investigating the micro-mechanical behavior of beam-like structures, which are composed of various elastic moduli and complex geometries varying through the cross-section directions and are also periodically-repeated and heterogeneous along the axial direction. Following the previous work (Lee and Yu, 2011), the original three-dimensional static problem is first formulated in a unified and compact form using the concept of decomposition of the rotation tensor. Taking advantage of the smallness of the cross-sectional dimension-to-length parameter and the micro-to-macro heterogeneity, while also performing homogenization along the dimensional reduction simultaneously, the variational asymptotic method is rigorously used to construct a total energy function, which is asymptotically correct up to the second order. Furthermore, through the transformation procedure based on the pure kinematic relations and the linearized equilibrium equations, a generalized Timoshenko model is systematically established. For the purpose of dealing with realistic and complex geometries and constituent materials at the microscopic level, this present approach is incorporated into a commercial analysis package. A few examples available in literature are used to demonstrate the consistency and efficiency of this proposed model, especially for the structures, in which the effects of transverse shear deformations are significant.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.403-412
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• 2018

In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.

• Steel and Composite Structures
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• v.44 no.4
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• pp.473-488
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• 2022

A high-speed railway (HSR) bridge may undergo long-term deformation due to the degradation of material stiffness, or foundation settlement during its service cycle. In this study, an analytical model is set up to evaluate the influence of this long-term vertical bridge deformation on the track geometry. By analyzing the structural characteristics of the HSR track-bridge system, the energy variational principle is applied to build the energy functionals for major components of the track-bridge system. By further taking into account the interlayer's force balancing requirements, the mapping relationship between the deformation of the track and the one of the bridge is established. In order to consider the different behaviors of the interlayers in compression and tension, an iterative method is introduced to update the mapping relationship. As for the validation of the proposed mapping model, a finite element model is created to compare the numerical results with the analytical results, which show a good agreement. Thereafter, the effects of the interlayer's different properties of tension and compression on the mapping deformations are further evaluated and discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.152-155
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• 2008

The blood flow characteristics have been closely related to various cardiovascular diseases, it is very important to predict them accurate enough in an efficient way. Thus, this paper proposes a one-dimensional spectral element model for the blood flow through blood vessels. The spectral element model is formulated by using the variational method. The nonlinear terms in spectral element model are all treated as the pseudo-force and an iterative solution method is applied in the frequency domain.