• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06a
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• pp.53-57
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• 1996

• Korean Journal of Mathematics
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• v.22 no.1
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• pp.1-28
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• 2014

We consider the hypergeometric translation operator associated to the Cherednik operators and the Heckman-Opdam theory attached to the root system of type $B_2$. We prove in this paper that these operators are positivity preserving and allow positive integral representations. In particular we deduce that the product formulas of the Opdam-Cherednik and the Heckman-Opdam kernels are positive integral transforms, and we obtain best estimates of these kernels. The method used to obtain the previous results shows that these results are also true in the case of the root system of type $C_2$.

• Korean Journal of Optics and Photonics
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• v.23 no.6
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• pp.246-250
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• 2012

We derive analytical expressions for the output spectral density and the noise power $P_{\beta}$ in noise loading analysis using Volterra kernels to characterize fiber nonlinearities. The bandwidth of the input noise source has little effect on $P_{\beta}$, but the power of the input noise source and the dispersion parameter value of the fiber have a significant effect on $P_{\beta}$. The Volterra method predicts ${\Delta}P_{\beta}[dB]$ = 30 dB/decade, which agrees very accurately over a wide range of fiber parameters compared with the numerical results by the split-step Fourier method. Therefore the Volterra method could be useful to predict the performance of a dense WDM system when we plan to upgrade fiber or increase signal power.

• ETRI Journal
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• v.31 no.5
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• pp.565-575
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• 2009

This paper concerns the use of support vector regression (SVR), which is based on the kernel method for learning from examples, in identification of walking robots. To handle complex dynamics in humanoid robot and realize stable walking, this paper develops and implements two types of reference natural motions for a humanoid, namely, walking trajectories on a flat floor and on an ascending slope. Next, SVR is applied to model stable walking motions by considering these actual motions. Three kinds of kernels, namely, linear, polynomial, and radial basis function (RBF), are considered, and the results from these kernels are compared and evaluated. The results show that the SVR approach works well, and SVR with the RBF kernel function provides the best performance. Plus, it can be effectively applied to model and control a practical biped walking robot.

• Honam Mathematical Journal
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• v.32 no.3
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• pp.389-397
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• 2010

Exton introduced 20 distinct triple hypergeometric functions whose names are Xi (i = 1,$\ldots$, 20) to investigate their twenty Laplace integral representations whose kernels include the confluent hypergeometric functions $_0F_1$, $_1F_1$, a Humbert function $\Psi_2$, a Humbert function $\Phi_2$. The object of this paper is to present 25 (presumably new) integral representations of Euler types for the Exton hypergeometric function $X_5$ among his twenty $X_i$ (i = 1,$\ldots$, 20), whose kernels include the Exton function X5 itself, the Exton function $X_6$, the Horn's functions $H_3$ and $H_4$, and the hypergeometric function F = $_2F_1$.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.385-400
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• 2009

The adverse effect of harmful plankton on the marine ecosystem is a topic of deep concern. To investigate the role of such phytoplankton, a mathematical model containing distinct dynamical equations for toxic and non-toxic phytoplankton is analyzed. Stability analysis of the resulting three equation model is carried out. A continuous time variation in toxin liberation process is incorporated into the model and a stability analysis of the resulting delay model is performed. The distributed delay model is then extended to include the spatial distribution of plankton and the delay-diffusion model is analyzed with spatial and spatiotemporal kernels. Conditions for diffusion-driven instability in both the cases are derived and compared to explore the significance of these kernels. Numerical studies are performed to justify analytical findings.

• Toxicological Research
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• v.23 no.1
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• pp.47-53
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• 2007

Amygdalin is a cyanogenic glycoside which is commonly found in almonds, bamboo shoots, and apri-cot kernels, and peach kernels. Amygdalin was first hydrolysed into prunasin, then degraded into cyanohydrin by sequential two-stage mechanism. The objective of this study was to examine the amygdalin decomposition and cyanide formation at various in vitro conditions, including acid, enzyme and anaerobic microbes (AM) in human feces (HF). In acid hydrolysis mimicking gastric environment, amygdalin was degraded to cyanide up to 0.2% in specific pH. In contrast, enzyme assay showed higher cyanide generation either by ${\beta}$-glucosidase, or by incubation with microbe. In conclusion, we are convinced of cyanide generation are occurred mainly by microbiological activities of the gut flora up to 41.53%. After ingestion with some staff, the degree and site of degradation in an organism is a key parst of regulatory decision making of that staff.

• Journal of Biosystems Engineering
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• v.35 no.3
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• pp.197-205
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• 2010

An automatic echelon feeder of brown rice was presented for quality inspection system using color image processing. A echelon feeder was developed with vibratory feeder and cylindrical indent singulator having oblique light. The vibratory feeder consisted of a hopper, electromagnetic vibrator and multichannel grooves and supply the grain sample to the singulator. The feeding performance such as feed rate, blocking frequency of the channel was dependent on the size of groove and vibration pattern. A cylindrical indent singulator consisted of a rotating cylinder, prisms and a tungsten-halogen light source. It delivered grain kernels under the camera in a echelon form and illuminate the kernels with oblique ray and ambient light. The size of the indents installed on the surface of the rotating cylinder was determined by the dimensions of the paddy and a small triangular prism was placed in each indent to apply $ 20^{\circ}$ oblique light to the grain kernel.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.329-368
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• 1999

This paper surveys recent remarkable progress in the study of potential theory for symmetric stable processes. It also contains new results on the two-sided estimates for Green functions Poisson kernels and Martin kernels of discontinuous symmetric $alpha$ -stable process in bounded $C^{1,1}$ open sets. The new results give ex-plicit information on how the comparing constants depend on pa-rametrer $alpha$ and consequently recover the green function and Poisson kernel estimates for Brownian motion by passing $alpha{\uparrow}2$. In addition to these new estimates this paper surveys recent progress in the study of notions of harmonicity integral representation of harmonic func-tions boundary harnack inequality conditional gauge and intrinsic ultracontractivity for symmetric stable processes. Here is a table of contents.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.515-521
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• 2020

Deep learning methods have been effectively used to provide great improvement in various research fields such as machine learning, image processing and computer vision. One of the most frequently used deep learning methods in image processing is the convolutional neural networks. Compared to the traditional artificial neural networks, convolutional neural networks do not use the predefined kernels, but instead they learn data specific kernels. This property makes them to be used as feature extractors as well. In this study, we compared the quality of CNN features for traditional texture feature extraction methods. Experimental results demonstrate the superiority of the CNN features. Additionally, the recognition process and result of a pioneering CNN on MNIST database are presented.