• Journal of the Chungcheong Mathematical Society
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• v.11 no.1
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• pp.35-44
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• 1998

Let {X(t), $t{\in}\mathbb{R}^n$} be a $S{\alpha}S$ H-sssis Chentsov random field with control measure m. We consider a geometric construction for L$\acute{e}$vy-Chentsov random fields and Takenaka random fields. Finally, we proved some property of conjugate classes and a.s. H$\ddot{o}$lder unboundedness of $S{\alpha}S$ H-sssis Chentsov random fields for all order ${\gamma}$ > H.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.1034-1037
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• 2009

Sign language spotting is the task of detecting the start and end points of signs from continuous data and recognizing the detected signs in the predefined vocabulary. The difficulty with sign language spotting is that instances of signs vary in both motion and shape. Moreover, signs have variable motion in terms of both trajectory and length. Especially, variable sign lengths result in problems with spotting signs in a video sequence, because short signs involve less information and fewer changes than long signs. In this paper, we propose a method for spotting variable lengths signs based on semi-CRF (semi-Markov Conditional Random Field). We performed experiments with ASL (American Sign Language) and KSL (Korean Sign Language) dataset of continuous sign sentences to demonstrate the efficiency of the proposed method. Experimental results show that the proposed method outperforms both HMM and CRF.

• ETRI Journal
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• v.40 no.2
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• pp.237-245
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• 2018

The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling. When the number of sparse subbands changes, the number of nodes can be adjusted flexibly to improve the reconstruction rate. Owing to the different attenuations of distributed nodes in different locations, it is worthwhile to find out how to select the optimal sensing node as the sampling channel. This paper proposes the spectrum sensing of DMWC based on a Markov random field (MRF) to select the ideal node, which is compared to the image edge segmentation. The attenuation of the candidate nodes is estimated based on the attenuation of the neighboring nodes that have participated in the DMWC system. Theoretical analysis and numerical simulations show that neighboring attenuation plays an important role in determining the node selection, and selecting the node using MRF can avoid serious transmission attenuation. Furthermore, DMWC can greatly improve recovery performance by using a Markov random field compared with random selection.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.31-40
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• 2022

In structural engineering, the material properties of the structures such as elastic modulus, shear modulus, density, and size may not be deterministic and may vary at different locations. The dynamic response analysis of such structures may need to consider these properties as stochastic. This paper introduces a stochastic finite element method (SFEM) approach to analyze moving loads problems. Firstly, Karhunen-Loéve expansion (KLE) is applied for expressing the stochastic field of material properties. Then the mathematical expression of the random field is substituted into the finite element model to formulate the corresponding random matrix. Finally, the statistical moment of the dynamic response is calculated by the point estimation method (PEM). The accuracy and efficiency of the dynamic response obtained from the KLE-PEM are demonstrated by the example of a moving load passing through a simply supported Euler-Bernoulli beam, in which the material properties (including elastic modulus and density) are considered as random fields. The results from the KLE-PEM are compared with those from the Monte Carlo simulation. The results demonstrate that the proposed method of KLE-PEM has high accuracy and efficiency. By using the proposed SFEM, the random vertical deflection of a high-speed railway (HSR) bridge is analyzed by considering the random fields of material properties under the moving load of a train.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.177-183
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• 2011

Hidden Markov random eld(HMRF) is one of the most common model for image segmentation which is an important preprocessing in many imaging devices. The HMRF has unknown hyper-parameters on Markov random field to be estimated in segmenting testing images. However, in practice, due to computational complexity, it is often assumed to be a fixed constant. In this paper, we numerically show that the segmentation results very depending on the fixed hyper-parameter, and, if the parameter is misspecified, they further depend on the choice of the class-labelling algorithm. In contrast, the HMRF with estimated hyper-parameter provides consistent segmentation results regardless of the choice of class labelling and the estimation method. Thus, we recommend practitioners estimate the hyper-parameter even though it is computationally complex.

• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.68-78
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• 2012

This study proposes an improved 3-D model that includes a new non-reflected wave generation system for oblique incident and multi-directional random waves, which enables us to estimate the effect of the various wave-types on 3-D wave fields in a coastal area with permeable submerged breakwaters. Then, using the numerical results,the three-dimensional wave field characteristics around permeable submerged breakwaters are examined in cases of oblique incident and multi-directional random waves. Especially, the wave height, mean surface elevation and mean flow around the submerged breakwaters are discussed in relation to the variation of incident wave condition.

• Communications of the Korean Mathematical Society
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• v.12 no.2
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• pp.411-418
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• 1997

In this note we prove a functional central limit theorem for nonstationary linearly positive quadrant dependent random fields. We extend it to the case of random measures.

• Communications of the Korean Mathematical Society
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• v.14 no.3
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• pp.597-609
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• 1999

In this article we prove a central limit theorem for strictly stationary weakly dependent random fields with some interlaced mix-ing conditions. Mixing coefficients are not assumed. The result it basically the same to Peligrad([4]), which is CLT weakly depen-dent arrays of random variables. The proof is quite similar to the of Peligrad.

• Honam Mathematical Journal
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• v.33 no.2
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• pp.163-171
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• 2011

In this paper we provide extensions of the Marcinkiewicz Zygmund laws of large numbers for i.i.d random variables with multidimensional indices to the case of negatively dependent random fields.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.793-802
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• 1998

We apply the generalization of Levy's infinitesimal equation $\delta$X(t) = $\psi$(X(s), s $\leq$ t, $Y_{t}$, t, dt), $t\in R^1$, for a random field X (C) indexed by a contour C or by a more general set. Assume that the X(C) is homogeneous in x, say of degree n, then we can appeal to the classical theory of variational calculus and to the modern theory of white noise analysis in order to discuss the innovation for the X (C.)