• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.45-54
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• 2012

In order to predict trailing edge noise from a flat plate more effectively and accurately, the prediction algorithm based on semi-analytic model for point pressure spectrum is proposed. The semi-analytic model consists of empirical models for point pressure spectra and theoretical model to determine the boundary layer characteristics needed for the empirical models. The proposed methods are applied to predict the trailing edge noise of the flat plate located in the mean flow of speed 38 m/s, for which the measured data are available. In present study, six empirical models for point pressure spectra are utilized for the predictions of trailing edge noise and their prediction results are compared to the measured data. Through the analysis of these comparisons, it is revealed that the present method based on non-frozen formula using Efimtsov model and Smol'yakov-Tkachenko model can provide more accurate and efficient predictions of trailing edge noise.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.120-121
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• 2006

In this paper, We have designed a face recognition system based on the embedded Linux. This paper has an aim in embedded system to recognize the face more exactly. At first, the contrast of the face image is adjusted with lightening compensation method, the skin and lip color is founded based on YCbCr values from the compensated image. To take advantage of the method based on feature and appearance, these methods are applied to the eyes which has the most highly recognition rate of all the part of the human face. For eyes detecting, which is the most important component of the face recognition, we calculate the horizontal gradient of the face image and the maximum value. This part of the face is resized for fitting the eye image. The image, which is resized for fit to the eye image stored to be compared, is extracted to be the feature vectors using the continuous wavelet transform and these vectors are decided to be whether the same person or not with PNN, to miminize the error rate, the accuracy is analyzed due to the rotation or movement of the face. Also last part of this paper we represent many cases to prove the algorithm contains the feature vector extraction and accuracy of the comparison method.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1876-1881
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• 2003

When a projectile travels at high speed underwater, supercavitating flow arises, in which a huge cavity is generated behind the projectile so that only the nose, i.e., the cavitator, of the projectile is wetted, while the rest of it should be surrounded by the cavity. In that case, the projectile can achieve very high speed due to the reduced drag. Furthermore if the nose of the body is shaped properly, the attendant pressure drag can be maintained at a very low value, so that the overall drag is also reduced dramatically. In this study, shape optimization technique is employed to determine the optimum cavitator shape for minimum drag, given certain operating conditions. Shape optimization technique is also used to solve the potential flow problem for any given cavitator, which is a free boundary value problem having the cavity shape as unknown a priori. Analytical sensitivities are derived for various shape parameters in order to implement a gradient-based optimization algorithm. Simultaneous optimization technique is proposed for efficient cavitator shape optimization, in which the cavity and cavitator shape are determined in a single optimization routine.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.10
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• pp.480-486
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• 2005

This paper proposes a method to consider an aging failure probability and survival probability of power system components, though only aging failure probability has been considered in existing mean life calculation. The estimates of the mean and its standard deviation is calculated by using Weibull distribution, and each estimated parameters is obtained from Data Analytic Method (Type H Censoring). The parameter estimation using Data Analytic Method is simpler and faster than the traditional calculation method using gradient descent algorithm. This paper shows calculation procedure of the mean life and its standard deviation by the proposed method and illustrates that the estimated results are close enough to real historical data of combustion turbine generating units in Korean systems. Also, this paper shows the calculation procedures of a probabilistic failure prediction through a stochastic data analysis. Consequently, the proposed methods would be likely to permit that the new deregulated environment forces utilities to reduce overall costs while maintaining an are-related reliability index.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.26-31
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• 2010

We proposed a new directional edge based interpolation, DEBI, by combining two weighted directional information to reduce blurred edges and annoying artifacts. Four isotropic gradient masks are employed in defining edge directions and they are proven to hold a first order derivative relation with respect to a rotating coordinate. Two minimum gradients among four absolute directional results are shown to be sufficient to describe slant edges efficiently. Compared with widely used bilinear and bicubic interpolation methods, the proposed algorithm results in a noticeable improvement along edge area.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.541-545
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• 1997

This paper presents a modified geometric active contour model or edge detection and segmentation of computed tomography(CT) scan images. The method is based on the level setup approach developed by Osher and Sethian and the modeling of propagation fronts with curvature dependent speeds by Malladi. Based on above algorithms, the geometric active contour is obtained through a particular level set of hypersurface lowing along its gradient force and curvature force. This technique retains the attractive feature which is topological and geometric flexibility of the contour in recovering objects with complex shapes and unknown topologies. But there are limitations in this algorithm which are being not able to separate the object with weak difference from neighbor object. So we use speed limitation filter to overcome those problems. We apply a 2D model to various synthetic cases and the three cases of real CT scan images in order to segment objects with complicated shapes and topologies. From the results, the presented model confirms that it attracts very naturally and efficiently to the desired feature of CT scan images.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.121-122
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• 1998

To induce perturbed magnetic field variations in the range of auto prescans permitted, we chose artificially shim values and applied manualy as DC offsets to X, Y, Z gradient amplifiers. The STEAM spectra were obtained from a localized region (8ml) of phantom's center and a Marquart Algorithm is employed to quantify MRS spectra. Results indicated that Creatine (Cr) which had a good correlation between a signal intensity and an area, changed little bit and showed extremly a stabilized state in perturbed magnetic field variations. Therefore, during the MRS experiments, to minimize the SNR reduction by means of unavoidable inhomogeneous magnetic fields, the present study suggested that the quantification method of relative ratios produced by replacing Cr concentration with standard quantify was most desirable.

• Tribology and Lubricants
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• v.36 no.5
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• pp.290-296
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• 2020

When two layers of carbon nanotube (CNT) arrays are loaded to mate, the free ends of individual CNTs come into contact at the interface of the two layers. This leads to a higher contact resistance due to a smaller contact region. However, when the free CNT ends of one array penetrate into the mating array, the contact region increases, effectively lowering the contact resistance. To explore the penetration of mating CNTs, we perform molecular dynamic simulations of a simple unit cell model, incorporating four CNTs in the lower array layer coupled with a single moving CNT on the upper layer. The interaction with neighboring CNTs is modelled by long-range carbon bond order potential (LCBOP I). The model structure is optimized by energy minimization through the conjugate gradient method. A NVT ensemble is used for maintain a room temperature during simulation. The time integration is performed through the velocity-Verlet algorithm. A significant vibrational motion of CNTs is captured when penetration is not available, resulting in a specific vibration mode with a high frequency. Due to this vibrational behavior, the random behaviors of CNT motion for predicting the penetration are confirmed under the specific gap distances between CNTs. Thus, the probability of penetration is examined according to the gap distance between CNTs in the lower array and the aspect ratio of CNTs. The penetration is significantly affected by the vibration mode due to the van der Waals forces between CNTs.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.231-234
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• 2005

The high temperature deformation behavior of AZ 31 Mg alloy was investigated by designing a back propagation neural network that uses a gradient descent-learning algorithm. A neural network modeling is an intelligent technique that can solve non-linear and complex problems by learning from the samples. Therefore, some experimental data have been firstly obtained from continuous compression tests performed on a thermo-mechanical simulator over a range of temperatures $(250-500^{\circ}C)$ with strain rates of $0.0001-100s^{-1}$ and true strains of 0.1 to 0.6. The inputs for neural network model are strain, strain rate, and temperature and the output is flow stress. It was found that the trained model could well predict the flow stress for some experimental data that have not been used in the training. Workability of a material can be evaluated by means of power dissipation map with respect to strain, strain rate and temperature. Power dissipation map was constructed using the flow stress predicted from the neural network model at finer Intervals of strain, strain rates and subsequently processing maps were developed for hot working processes for AZ 31 Mg alloy. The safe domains of hot working of AZ 31 Mg alloy were identified and validated through microstructural investigations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1235-1242
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.