• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.19-28
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• 2017

Moments of stationary intervals and those of the counting process can be used for moment fittings of the point processes. As for the Markovian arrival processes, the moments of stationary intervals are given as a polynomial function of parameters whereas the moments of the counting process involve exponential terms. Therefore, moment fittings are more complicated with the counting process than with stationary intervals. However, in queueing network analysis, cross-correlation between point processes can be modeled more conveniently with counting processes than with stationary intervals. A Laplace-Stieltjies transform of the stationary intervals of MAP (3)s is recently proposed in minimal number of parameters. We extend the results and present the Laplace transform of the counting process of MAP (3)s. We also show how moments of the counting process such as index of dispersions for counts, IDC, and limiting IDC can be used for moment fittings. Examples of exact MAP (3) moment fittings are also presented on the basis of moments of stationary intervals and those of the counting process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.321-324
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• 2003

This paper discusses a robust stochastic stabilization of uncertain Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretixzd T-S fuzzy system is represented by a uncertain discrete-time T-S fuzy system with jumping parameters. The robust stochastic stabilizibility of the uncertain jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs).

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.464-469
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• 2009

This paper discusses a robust observer-based output-feedback stabilization of an uncertain Takagi-Sugeno (T-S) fuzzy system in a network. In the networked control system, the input delay occurs inevitably and it is expressed by the Markovian stochastic process. To design robust sampled-data observer-based output-feedback controller, we discretize the T-S fuzzy system and represent as a jump system. Stochastic robust stabilization condition is formulated in terms of linear matrix inequalities.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.293-299
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• 2003

This paper discusses a design of intelligent controller with time delay for Internet-based remote control. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The Takagi-Sugeno (T-S) fuzzy system with uncertain input delay is utilized to represent nonlinear plant. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The robust stochastic stabilizibility of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). An experimental results is provided to visualize the feasibility of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.298-303
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• 2004

This paper deals with a stochastic stabilization of observer-based output-feedback control Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The stochastic stabilizability of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). The usefulness of the proposed algorithm is also certificated by simulation of 2 degree of freedom helicopter model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.101-108
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• 2011

The turnover rate of information security professionals in Korea is over 10% and turnover into non-information security fields accounts for over 50% of all the turnovers [1]. It is not only important to recruit a new quality workforce, but also to make the current workforce perform satisfactorily, to improve their performance, and eventually to attain information security objectives. This study proposes a Markov chain model for the turnover process of information security professionals and forecasts the job duty composition of information security professionals. The results of this study can be applied to secure the justification of government policies for the promotion of information security professionals.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.202-207
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• 2016

Checkpoint placement is an effective fault tolerance technique against transient faults in which the task is re-executed from the latest checkpoint when a fault is detected. In this paper, we propose a new checkpoint placement strategy separating data saving and fault detection processes that are performed together in conventional checkpoints. Several fault detection processes are performed in one checkpoint interval in order to decrease the latency between the occurrence and detection of faults. We address the placement method of fault detection processes to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for a real-time task having the proposed checkpoints, and derive the optimal fault detection and checkpoint interval.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.741-750
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• 2011

In this paper, we derive an software mixed debugging model based on a Markov process, assuming that the length of time to perform the debugging is random and its distribution may depend on the fault type causing the failure. We assume that the debugging process starts as soon as a software failure occurs, and either a perfect debugging or an imperfect debugging is performed upon each fault type. One type is caused by a fault that is easily corrected and in this case, the perfect debugging process is performed. An Imperfect debugging process is performed to fix the failure caused by a fault that is difficult to correct. Distribution of the first passage time and working probability of the software system are obtained; in addition, an availability function of a software system which is the probability that the software is in working at a given time, is derived. Numerical examples are provided for illustrative purposes.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.288-294
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• 2011

In this paper we define the probability models for determining the disparity map given stereo images and derive the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. The proposed method alternates between estimating the parameters with the intermediate disparity map and estimating the disparity map with the estimated parameters, after computing it with random initial parameters. Our algorithm is applied to the stereo matching algorithms based on the dynamic programming and belief propagation to verify its operation and measure its performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.809-819
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• 2000

This paper deals with an optimal capacity allocation problem and performance analysis in Advanced Information Communication Processing System(AICPS). AICPS is a gateway system interconnection PSTN(Public Switched Telephone Network), ISDN(Intergrated Services Digital Network), PSDN(Packet Switched Data Network), internet, Frame Relay and ATM together. This study considers not only ISDN and Internet but also user behavior of On-line service which is analyzed by Markov process. A call blocking probability of TNAS and INAS is computed by Erlang's formula. Then, PNAS and WNAS's call blocking probability are computed by Stochastic knapsack modeling. The result is compared with result of simulation. Finally, we allocate an optimal capacity minimizing total call blocking probability.