• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.603-613
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• 2008

We often encounter the situation that discrete count data have a large portion of zeros. In this case, it is not appropriate to analyze the data based on standard regression models such as the poisson or negative binomial regression models. In this article, we consider Bayesian analysis for two commonly used models. They are zero-inflated poisson and negative binomial regression models. We use the Bayes factor as a model selection tool and computation is proceeded via Markov chain Monte Carlo methods. Crash count data are analyzed to support theoretical results.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4436-4452
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• 2015

The IEEE 802.15.6 standard is introduced to satisfy all the requirements for monitoring systems operating in, on, or around the human body. In this paper, analytical models are developed for evaluating the performance of the IEEE 802.15.6 CSMA/CA-based medium access control protocol for wireless body area networks (WBAN) under unsaturation condition. We employ a three-dimensional Markov chain to model the backoff procedure, and an M/G/1/K queuing system to describe the packet queues in the buffer. The throughput and delay performances of WBAN operating in the beacon mode are analyzed in heterogeneous network comprised of different user priorities. Simulation results are included to demonstrate the accuracy of the proposed analytical model.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.244-248
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• 2007

In this paper, we propose a novel self-networking and replaceable structure method for the ubiquitous multimedia. As the contents in the ubiquitous multimedia should be realistic and continuously updated in the real-time manner, an efficient scheme of a self-networking and replaceable structure is necessary. In the proposed method, the contents itself connects to the server or corresponding devices and updates itself autonomously. Also, we can reduce the total amount of data transmission comparing to the cases where the whole contents should be downloaded. A Markov chain model is introduced for the proposed structure in order to perform the throughput analysis. The whole mechanism is implemented in the wireless handset and also, various applications of the scheme are discussed.

• Convergence Security Journal
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• v.14 no.5
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• pp.37-47
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• 2014

A Trojan malicious code is one of largest malicious codes and has been known as a virus that causes damage to a system as itself. However, it has been changed as a type that picks user information out stealthily through a backdoor method, and worms or viruses, which represent a characteristic of the Trojan malicious code, have recently been increased. Although several modeling methods for analyzing the diffusion characteristics of worms have proposed, it allows a macroscopic analysis only and shows limitations in estimating specific viruses and malicious codes. Thus, in this study an ESP model that can estimate future occurrences of Trojan malicious codes using the previous Trojan data is proposed. It is verified that the estimated value obtained using the proposed model is similar to the existing actual frequency in causes of the comparison between the obtained value and the result obtained by the Markov chain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2305-2312
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• 1998

This paper analyzed the delay characteristics of speech packets in virtual cellular network(VCN). The probability distribution of packet delay is obtained using the markov chain model when periodic speech packets are transmitted by slotted-ALOHA protocol. The effects of probility of capture and retransmission policy on the performance were also analyzed. At first, the probability cumulative function of packet delay is calculated from the probability of capture as a function of location of mobile terminal. In order to investigate the effects of backoff delay, we defined a parameter NPr, where N is the period (frame size) of the speech packets and Pr is the retransmission probability for each speech packet. We also obtained the 1% outage delay for various frame size N.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1B
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• pp.15-20
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• 2012

In this paper, an algorithm that enhances the conventional directional CSMA/CA protocol in IEEE 802.15.3c is proposed under saturation environments. For the algorithm, a Markov chain model is presented and analyzed in no-ACK mode. The effects of directional antennas and the features of IEEE 802.15.3c MAC are considered in the model. The optimal sizes of contention window are derived from the numerical results. The numerical results show that the proposed directional CSMA/CA algorithm outperforms conventional one. The overall analysis is verified by simulation. The obtained results provide the criterion for selecting the optimal parameters and developing a MAC protocol that enhances the performance of mmWave WPANs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.37-46
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• 2005

In the Web environment with a huge amount of information, Web page access patterns for the users visiting certain web site can be diverse and change continually in accordance with the change of its environment. Therefore it is almost impossible to develop and design web sites which fit perfectly for every web user's desire. Adaptive web site was proposed as solution to this problem. In this paper, we will present an effective method that uses a probabilistic model of DTMC(Discrete-Time Markov Chain) for learning user's access patterns and applying these patterns to construct an adaptive web site.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.857-865
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• 2013

Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to 2010. It becomes clear that the probability of the extreme rainfall is increasing for last 20 years in Seoul area and the model proposed works relatively well for both point prediction and predictive interval approach.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.73-81
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• 2013

In this paper, we have proposed the interference analysis method which uses both an interference probability model at the PHY layer of RFID system and the DTMC model at the MAC layer of USN system. Using the proposed method, we have performed sharing analysis between passive RFID and USN systems at the Korean RFID/USN frequency bands. If 1% performance degradation of USN system is allowed, RFID and USN systems can share the frequency bands where channel number is greater or equal to 20 on condition that radius of protection area is greater than 300 m.