• Annual Conference of KIPS
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• 2009.04a
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• pp.35-38
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• 2009

The paper presents an effective method to detect fire in video surveillance and monitoring system. The main contribution of this work is that we successfully use the Hidden Markov Models in the process of detecting the fire with a few preprocessing steps. First, the moving pixels detected from image difference, the color values obtained from the fire flames, and their pixels clustering are applied to obtain the image regions labeled as fire candidates; secondly, utilizing massive training data, including fire videos and non-fire videos, creates the Hidden Markov Models of fire and non-fire, which are used to make the final decision that whether the frame of the real-time video has fire or not in both temporal and spatial analysis. Experimental results demonstrate that it is not only robust but also has a very low false alarm rate, furthermore, on the ground that the HMM training which takes up the most time of our whole procedure is off-line calculated, the real-time detection and alarm can be well implemented when compared with the other existing methods.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.500-504
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• 2009

A reliability of software is a type of nonfunctional requirement. Traditionally, a validation of the reliability is processed at the integration phase in software development life cycle. However, it increases the cost and the risk for the development. In this paper, we propose reliability analysis method based on mathematical analytic model at the architecture design phase of the development process as follows. First, we propose the software modeling methodology for reliability analysis using Hierarchical combined Queueing Petri Nets(HQPN). Second, we derive the Markov Reward Model from the HQPN based model. We apply our approach to the video conference system to verify the usefulness of our approach. Our approach supports quantitative evaluation of the reliability.

• Journal of the Korean Statistical Society
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• v.4 no.1
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• pp.39-56
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• 1975

Ever since Gauss discussed the least-squares method in 1812 and Bertrand translated Gauss's work in French, the least-squares method has been used for various economic analysis. The justification of the least-squares method was given by Markov in 1912 in connection with the previous discussion by Gauss and Bertrand. The main argument concerned the problem of obtaining the best linear unbiased estimates. In some modern language, the argument can be explained as follow.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.285-295
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• 2001

We consider a queueing system under overload control to support bursty traffic. The queueing system under overload control is modelled by MMBP/D1/K queue with two thresholds on buffer. Arrival of customer is assumed to be a Markov-modulated Bernoulli process (MMBP) by considering burstiness of traffic. Analysis is done in discrete-time case. Using the generating function method, we obtain the stationary queue length distribution. Finally, the loss probability and the waiting time distribution of a customer are given.

• Journal of the military operations research society of Korea
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• v.15 no.2
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• pp.20-37
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• 1989

A markov chain is used to derive the models for determining the size of persons to be promoted and for conducting the sensitivity analysis of promotion probabilities. To compute the former case a future wastage rate is forecasted by using the double exponential smoothing method. The model for sensitivity analysis is used to simulate the impact of change in graded-size targets and hiring policy on the promotion probabilities.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.59-64
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• 2006

In this study, the risk of SRRs was assessed upon the scale of the damage of marine accidents. For the risk assessment, inner-outer dependence methods and special knowledge-based fuzzy logic were introduced. Also, in order to calculate the importance of assessment value in this study, a max min composition method was used for fuzzy logic based on the principle of fuzzy extension and the centroid of gravity method was used for non-fuzzy formation. In order to produce the importance of assessment items, the inner-outer dependence methods were used for assessment items, and markov analysis method was used for the importance of the final comprehensive assessment. As a result, the risk of SRR of Tongyoung and Yeosu was proven relatively higher, thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.3 s.26
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• pp.219-224
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• 2006

In this study, the risk of SRRs was assessed upon the scale of the damage of marine accidents. For the risk assessment, inner-outer dependence methods and special knowledge-based fuzzy logic were introduced. Also, in order to calculate the importance of assessment value in this study, a max-min composition method was used for fuzzy logic based on the principle of fuzzy extension and the centroid of gravity method was used for non-fuzzy formation. In order to produce the importance of assessment items, the inner-outer dependence methods were used for assessment items, and markov analysis method was used for the importance of the final comprehensive assessment. As a result, the risk of SRR of Tongyoung, Mokpo and Yeosu was proven relatively higher, thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.06a
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• pp.131-159
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• 2006

This paper consider multinomial group testing which is concerned with classification each of N given units into one of k disjoint categories. In this paper, we propose exact Bayesian, approximate Bayesian, bootstrap methods for estimating individual category proportions using the multinomial group testing model proposed by Bar-Lev et al (2005). By the comparison of Mcan Squre Error (MSE), it is shown that the exact Bayesian method has a bettor efficiency and consistency than maximum likelihood method. We suggest an approximate Bayesian approach using Markov Chain Monte Carlo (MCMC) for posterior computation. We derive exact credible intervals based on the exact Bayesian estimators and present confidence intervals using the bootstrap and MCMC. These intervals arc shown to often have better coverage properties and similar mean lengths to maximum likelihood method already available. Furthermore the proposed models are illustrated using data from a HIV blooding test study throughout California, 2000.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1133-1140
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• 2013

A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.1
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• pp.23-32
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• 2015

Modeling of fighter pilots, which is a fundamental technology for war games using defense M&S (Modeling & Simulation) becomes one of the prominent research issues as the importance of defense M&S increases. Especially, the recent accumulation of combat logs makes it possible to adopt statistical learning methods to pilot modeling, and an HMM (Hidden Markov Model) which is able to utilize the sequential characteristic of combat logs is suitable for the modeling. However, since an HMM works only by using one type of features, discrete or continuous, to apply an HMM to heterogeneous features, type integration is required. Therefore, we propose a dPCA-HMM method, where dPCA (Discrete Principal Component Analysis) is combined with an HMM for the type integration. From experiments conducted on combat logs acquired from a simulator furnished by agency for defense development, the performance of the proposed model is evaluated and was satisfactory.