• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.27-40
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• 2022

In this paper, the focus on the removal noise in the binary image based on the variational Bayesian method with the Ising model. The observation and the latent variable are the degraded image and the original image, respectively. The posterior distribution is built using the Markov random field and the Ising model. Estimating the posterior distribution is the same as reconstructing a degraded image. MCMC and variational Bayesian inference are two methods for estimating the posterior distribution. However, for the sake of computing efficiency, we adapt the variational technique. When the image is restored, the iterative method is used to solve the recursive problem. Since there are three model parameters in this paper, restoration is implemented using the VECM algorithm to find appropriate parameters in the current state. Finally, the restoration results are shown which have maximum peak signal-to-noise ratio (PSNR) and evidence lower bound (ELBO).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.142-155
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• 2000

In this paper, we propose an efficient policing mechanism for Markov model-based traffic descriptors of VBR MPEG video traffic. A VBR video sequence is described by a set of traffic descriptors using a scene-basedMarkov model to the network for the effective resource allocation and accurate QoS prediction. The networkmonitors the input traffic from the source using a proposed new policing method. for policing the steady statetransition probability of scene states, we define two representative monitoring parameters (mean holding andrecurrence time) for each state. For frame level cell rate policing of each scene state, accumulated average cellrates for the frame types are compared with the model parameters. We propose an exponential bounding functionto accommodate dynanic behaviors during the transient period. Our simulation results show that the proposedpolicing mechanism for Markovian traffic descriptors monitors the sophisticated traffic such as MPEG videoeffectively and well protects network resources from the nalicious or misbehaved traffic.

• Journal of applied mathematics & informatics
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• v.31 no.5_6
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• pp.711-732
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• 2013

In this paper, we are interested in finding explicit numerical formulas to evaluate defaultable bonds prices of firms. For this purpose, we use a default intensity whose values depend on the credit rating of these firms. Each credit rating corresponds to a state of the default intensity. Then, this regime switches as soon as one of the credit rating of a firm also changes. Moreover, this regime switching default intensity model allows us to capture well some market features or economics behaviors. Thus, we obtain two explicit different formulas to evaluate the conditional Laplace transform of a regime switching Cox Ingersoll Ross model. One using the property of semi-affine of the model and the other one using analytic approximation. We conclude by giving some numerical illustrations of these formulas and real data estimation results.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.87-98
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• 2005

This research investigates economic-statistical characteristics of variable sampling size and interval (VSSI)$\bar{X}$charts under two assignable causes. A Markov chain approach is employed in order to calculate average run length (ARL) and average time to signal (ATS). Six transient states are derived by carefully defining the state. A steady state cost rate function is constructed based on Lorenzen and Vance(1986) model. The cost rate function is optimized with respect to six design parameters for designing the VSSI $\bar{X}$ charts. Computational experiments show that the VSSI $\bar{X}$ chart is superior to the Shewhart $\bar{X}$ chart in the economic-statistical sense, even under two assignable causes. A comparative study shows that the cost rate may increase up to almost 30% by overlooking the second cause. Critical input parameters are also derived from a sensitivity study and a few guideline graphs are provided for determining the design parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2644-2652
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• 1997

We ivestigate a two-stage queueing system which frequently arises in the study of overflow problems. A primary service facility consists of multiple primary queues where blocked calls are overflowed to a secondary queue. By approximating the input to the secondary queue with a two-state Markov Modulated Poisson Process (MMPP), we derive the blocking probability of the secondary queue. For the approximation, we employ the well-known Heffes' method and the SAM procedure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.355-362
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• 2009

In real-time communication services, delay constraints are among the most important QoS (Quality of Service) factors. In particular, it is difficult to guarantee the delay requirement over wireless channels, since they exhibit dynamic time-varying behavior and even severe burst-errors during periods of deep fading. Channel throughput may be increased, but at the cost of the additional delays when ARQ (Automatic Repeat Request) schemes are used. For real-time communication services, it is very essential to predict data deliverability. This paper derives the delay distribution and the successful delivery probability within a given delay budget using a priori channel model and a posteriori information from the perspective of queueing theory. The Gilbert-Elliot burst-noise channel is employed as an a Priori channel model, where a two-state Markov-modulated Bernoulli process $(MMBP_2)$ is used. for a posteriori information, the channel parameters, the queue-length and the initial channel state are assumed to be given. The numerical derivation is verified and analyzed via Monte Carlo simulations. This numerical derivation is then applied to a rate control scheme for real-time video transmission, where an optimal encoding rate is determined based on the future channel capacity and the distortion of the reconstructed pictures.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.1-7
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• 2013

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.261-276
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• 2015

Structural damage and moving load identification are the two aspects of structural system identification. However, they universally coexist in the damaged structures subject to unknown moving load. This paper proposed a dynamic response sensitivity-based model updating method to simultaneously identify the structural damage and moving force. The moving force which is equivalent as the nodal force of the structure can be expressed as a series of orthogonal polynomial. Based on the system Markov parameters by the state space method, the dynamic response and the dynamic response derivatives with respect to the force parameters and elemental variations are analytically derived. Afterwards, the damage and force parameters are obtained by minimizing the difference between measured and analytical response in the sensitivity-based updating procedure. A numerical example for a simply supported beam under the moving load is employed to verify the accuracy of the proposed method.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.311-326
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• 2004

We propose a Markov model of two bottleneck ECN/RED gateways experiencing a large number of TCP users. We show that, as the number of users becomes large, the queue sizes per user of the both gateways converge at steady-state to individual fixed points. Also, we derive a computational algorithm to exactly obtain the fixed points and present simulation example showing the limiting behavior of the gateway traffic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.699-706
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• 2003

This paper is to verify that 2-state MMPP Model conform to ATM VBR traffic characteristics by measuring and analyzing real-time VBR traffic in KT's ATM network. As a result, we validated the fact that real-time VBR traffic of ATM network cannot be apply to MMPP model and must be represented by previously general On-Off Model with characteristics as follows: arrival rate of On state (λ$_1$) is deterministic, arrival rate of Off state (λ$_2$) is zero, and two transition rate (T$_1$,T$_2$) is only random variable. As research results are to handle real traffic, these results can be used to all ATM network traffic model with traffic management function such as KT's ATM network.