• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.405-407
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• 2009

SVM(Support Vector Machine) is a classification method which is recently watched in mechanical learning system. Vapnik, Osuna, Platt etc. had suggested methodology in order to solve needed QP(Quadratic Programming) to realize SVM so that have extended application field. SVM find hyperplane which classify into 2 class by converting from input space converter vector to characteristic space vector using Kernel Function. This is very systematic and theoretical more than neural network which is experiential study method. Although SVM has superior generalization characteristic, it depends on Kernel Function. There are three category in the Kernel Function as Polynomial Kernel, RBF(Radial Basis Function) Kernel, Sigmoid Kernel. This paper has analyzed performance of SVM against kernel using virtual data.

• Advances in aircraft and spacecraft science
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• v.7 no.6
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• pp.517-536
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• 2020

The present study investigates axial vibration of a FG nanobeam using nonlocal elasticity theory under clamped-clamped and clamped-free boundary conditions. Power law, exponential law and sigmoid law are applied as grading laws to examine the effect of the material distribution on axial vibration of the FG nanobeam. A parametric study was done to examine the effect of length scale on the dynamic behavior of the structure and the results are presented. It was observed that consideration of the nonlocal length scale is essential when analyzing the free vibration of a FG nanobeam. The results of the present study can be used as benchmarks in future studies of FG nanostructures.

• Journal of Chest Surgery
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• v.46 no.4
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• pp.295-298
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• 2013

Solitary fibrous tumor is a rare spindle cell mesenchymal tumor entity, with either benign or malignant behavior that cannot be accurately predicted by histological findings. An intrapulmonary site of origin is even rarer. We report a case of a 51-year-old woman in whom an abnormal nodule in the lower right lung was detected during staging for sigmoid adenocarcinoma. The nodule was excised and pathological examination revealed an intrapulmonary solitary fibrous tumor.

• Steel and Composite Structures
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• v.11 no.6
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• pp.489-504
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• 2011

This paper presents a theoretical investigation in free vibration of sigmoid functionally graded beams with variable cross-section by using Bernoulli-Euler beam theory. The mechanical properties are assumed to vary continuously through the thickness of the beam, and obey a two power law of the volume fraction of the constituents. Governing equation is reduced to an ordinary differential equation in spatial coordinate for a family of cross-section geometries with exponentially varying width. Analytical solutions of the vibration of the S-FGM beam are obtained for three different types of boundary conditions associated with simply supported, clamped and free ends. Results show that, all other parameters remaining the same, the natural frequencies of S-FGM beams are always proportional to those of homogeneous isotropic beams. Therefore, one can predict the behaviour of S-FGM beams knowing that of similar homogeneous beams.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.594-601
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• 1997

A new algorithm is proposed for training the multilayer perceptrion(MLP) in pattern classification problems to accelerate the learning speed. It is shown that the sigmoid activation function of the output node can have deterimental effect on the performance of learning. To overcome this detrimental effect and to use the information fully in supervised learning, an objective function for binary modes is proposed. This objective function is composed with two new output activation functions which are selectively used depending on desired values of training patterns. The effect of the objective function is analyzed and a training algorithm is proposed based on this. Its performance is tested in several examples. Simulation results show that the performance of the proposed method is better than that of the conventional error back propagation (EBP) method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.145-154
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• 2000

In this paper we proposed the orthogonal neural network(ONN) to control and identify the unknown controlled system. The proposed ONN used the buffer layer in front of the hidden layer and the hidden layer used the sigmoid function and its derivative a derived RBF that is a derivative of the sigmoid function. In order to verify the property of the proposed, it is examined by simulation results of the Narendra model. Controlled system is composed of ONN and confirmed its usefulness through simulation and experimental results.

• Textile Coloration and Finishing
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• v.24 no.4
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• pp.239-246
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• 2012

The binding isotherms of ionic dyes with Poly(vinylpyrrolidone) in aqueous solution were determined by the dynamic dialysis technique. The shape of the isotherms of cationic dye, C. I. Basic Red 18 with poly(vinlypyrrolidone) showed a partition type. It suggests that the binding involves a non-cooperative mode. Isotherms of an anion dye, a synthesized dye by coupling of diazotized m-trifluoromethylaniline with 2-naphthol-6-sulfonic acid, were sigmoid type and showed multimode interaction. The results were interpreted by the McGhee von Hippel theory. The thermodynamic parameters for the complex formation of the dyes-polymer were calculated from their temperature dependences of the intrinsic binding constant.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.285-292
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• 2021

Autonomous vehicles are divided into an upper controller that calculates control value through cognitive judgment and a lower controller that appropriately transmits its control value to an actuator. Here, the longitudinal control in a lower controller has a problem as the road slopes due to the property of the Acceleration sensor to output the acceleration as the slope of the device. Therefore, in this paper, a sigmoid function is proposed to determine the slope to compensate for this problem. Through the experiment, Checked performance by comparing the existing table model with the proposed model.

• Journal of Applied and Pure Mathematics
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• v.5 no.1_2
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• pp.69-93
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• 2023

Here we give multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or ℝ^N, N ∈ ℕ, by the multivariate normalized, quasi-interpolation, Kantorovich type and quadrature type neural network operators. We treat also the case of approximation by iterated operators of the last four types. These approximations are derived by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by a parametrized Gudermannian sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.201-206
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• 2021

The most common malignant tumors in the colon are adenocarcinomas, while leiomyosarcoma (LMS) are rare. Here, we report a case of LMS of the sigmoid colon in a 73-year-old man who presented with sigmoido-rectal intussusception, which was discovered by abdominal computed tomography. As LMS of the colon is uncommon and is rarely associated with intussusception, we have described the imaging features in this case report.