• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.377-387
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• 1998

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced latent variables that indicates with component of the Superposition model. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Metropolis algorithms along with Gibbs steps are proposed to preform the Bayesian inference of such models. for model determination, we explored the Pre-quential conditional predictive Ordinate(PCPO) criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions, we consider in this paper Superposition of Musa-Okumoto and Erlang(2) models. A numerical example with simulated dataset is given.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.527-534
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• 2023

Triple modular redundancy (TMR) systems can continue their mission by virtue of their structural redundancy even if one processor is attacked by faults. In this paper, we propose a new fault tolerance strategy by introducing checkpoints into the TMR system in which data saving and fault detection processes are separated while they corporate together in the conventional checkpoints. Faults in one processor are tolerated by synchronizing the state of three processors upon detecting faults. Simultaneous faults occurring to more than one processor are tolerated by re-executing the task from the latest checkpoint. We propose the checkpoint placement and fault detection strategy to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for the TMR system having the proposed checkpoint strategy, and derive the optimal fault detection and checkpoint interval.

• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.59-70
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• 2003

Proposed CCRSVP (Candidate Casting RSVP) algorithm is a new fast handoff method which uses advanced multicasting method and RSVP for IEEE 802.11 Wireless LAN (WLAN) environments. The proposed algorithm shows good performance in the handoff latency and the B/W efficiency aspect and guarantees QoS because it uses L2 information (BSSID) of WLAN and starts to reserve resources and multicast packets before L2 handoff completes. We also propose a Markov chain performance analysis model in which we can analyze the handoff performance of various handoff algorithms. Using the model, we compare bandwidth efficiency of the proposed algorithm with existing handoff algorithms which use RSVP by analyzing blocking probability of session, resource usage, and the average number of ongoing session in a cell. The results show that the proposed algorithm shows better performance than the existing algorithms in the above three performance aspects.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.316-328
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• 2003

In this paper, we propose and analyze two adaptive channel allocation schemes for supporting multimedia traffics in hierarchical cellular systems. It is guaranteed to satisfy the required quality of service of multimedia traffics according to their characteristics such as a mobile velocity for voice calls and a delay tolerance for multimedia calls. In the scheme 1, only slow-speed voice calls are allowed to overflow from macrocell to microcell and only adaptive multimedia calls can overflow from microcell to macrocell after reducing its bandwidth to the minimum channel bandwidth. In the scheme II, in addition to the first scheme, non-adaptive multimedia calls can occupy the required channel bandwidth through reducing the channel bandwidth of adaptive multimedia calls. The proposed scheme I is analyzed using 2-dimensional Markov model. Through computer simulations, the analysis model and the proposed schemes are compared with the fixed system and two previous studies. In the simulation result, it is shown that the proposed schemes yield a significant improvement in terms of the forced termination probability of handoff calls and the efficiency of channel usage.