• Bulletin of the Korean Mathematical Society
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• v.40 no.4
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• pp.663-669
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• 2003

This paper investigates the tail asymptotic behavior of the severity of ruin (the deficit at ruin) in the renewal model. Under the assumption that the tail probability of the claimsize is dominatedly varying, a uniform asymptotic formula for the tail probability of the deficit at ruin is obtained.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.873-876
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.403-410
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.134-139
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• 2008

In this paper, we propose an analysis model for the performance of channel error probability in Stream Control Transmission Protocol (SCTP) using Markov model. In this model it is assumed that the compressor and decompressor work in Unidirectional Mode. And the average throughput of SCTP protocol is obtained by finding the throughputs of when the initial channel state is good or bad.

• Journal of the Korean Mathematical Society
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• v.59 no.6
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• pp.1185-1201
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• 2022

Feller introduced an unfair-fair-game in his famous book [3]. In this game, at each trial, player will win 2^k yuan with probability p_k = 1/2^kk(k + 1), k ∈ ℕ, and zero yuan with probability p₀ = 1 - Σ^∞_k=1 p_k. Because the expected gain is 1, player must pay one yuan as the entrance fee for each trial. Although this game seemed "fair", Feller [2] proved that when the total trial number n is large enough, player will loss n yuan with its probability approximate 1. So it's an "unfair" game. In this paper, we study in depth its convergence in probability, almost sure convergence and convergence in distribution. Furthermore, we try to take 2^k = m to reduce the values of random variables and their corresponding probabilities at the same time, thus a new probability model is introduced, which is called as the related model of Feller's unfair-fair-game. We find out that this new model follows a long-tailed distribution. We obtain its weak law of large numbers, strong law of large numbers and central limit theorem. These results show that their probability limit behaviours of these two models are quite different.

• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.160-168
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• 1999

This research focussed on developing a hit probability model for polygonal target to increase the survivability of weapon systems by its shape design. First, we defined the delivery errors and derived functions for these errors based on the assumption of bivariate normal distribution, and the derived functions for probability of shot hitting of various shapes of polygonal target. Also, we developed computer program for computation of the probability of hitting a general n-sided polygon and we have shown a sample run output. The model could be used to improve the survivability from design phase by designing optimal polygonal shape of weapon system.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.116-123
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• 2001

A failure probability model based on Von-Mises failure criterion and the standard normal probability function is proposed. The effects of varying boundary conditions such as nearby cavity, backfill, load cycle and corrosion on failure probability of the buried pipes are systematically investigated. The location of cavity is found to affect failure probability of buried pipeline within a certain limit. It is noted that the flexibility of backfill plays a great role to change the failure probability of buried pipeline. Furthermore, the corrosion gives less effects than other boundary conditions such as cavity, load as cavity, load cycle, and backfill to the failure probability of buried pipeline.

• Journal of Korean Society of Water and Wastewater
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• v.24 no.5
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• pp.509-517
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• 2010

Statistical distribution of annual maximum rainfall intensity of 18 cities in Korea was analyzed and applied to the reliability model which can calculate the probability of performance failure of storm sewer. After the analysis, it was found that distribution of annual maximum rainfall intensity of 18 cities in Korea is well matched with Gumbel distribution. Rational equation was used to estimate the load and Manning's equation was used to estimate the capacity in reliability function to calculate the probability of performance failure of storm sewer. Reliability analysis was performed by developed model applying to the real storm sewer. It was found that probability of performance failure is abruptly increased if the diameter is smaller than certain size. Therefore, cleaning the inside of storm sewer to maintain the original diameter can be one of the best ways to reduce the probability of performance failure. In the present study, probability of performance failure according to accumulation of debris in storm sewer was calculated. It was found that increasing the amount of debris seriously decrease the capacity of storm sewer and significantly increase the probability of performance failure.