• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.287-293
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• 2017

The naval unmanned surface vehicle (USV) conducts the surveillance operations, based on the mission plan set by the user. For setting the mission planning, the user needs to analyze the suitability of the operation for the mission planning. In this paper, we proposed a simulation program that estimates the probability of detecting targets of the mission planning in the analysis. In the simulation analysis, we design the USV's maneuvering characteristics, radar detection operational performance equipped on the USV, and targets infiltrating into surveillance area in the simulation experiment scenario. Based on the simulation results, we evaluated the mission planning suitability and find a mission planning solution recursively.

• Earthquakes and Structures
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• v.19 no.2
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• pp.79-90
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• 2020

4- and 8-storey reinforced-concrete frame buildings are analyzed under the suites of the near-fault pulse-like, and the corresponding spectrally equivalent far-fault ground-motion records. Seismic fragility curves for the slight, moderate, extensive, and complete damage states are developed, and the damage probability matrices, and the mean loss ratios corresponding to the Design Basis Earthquake and the Maximum Considered Earthquake hazard levels are compared, for the investigated buildings and sets of ground-motion records. It is observed that the spectrally equivalent far-fault ground-motion records result in comparable estimates of the fragility curve parameters, as that of the near-fault pulse-like ground-motion records. As a result, the derived damage probability matrices and mean loss ratios using two suites of ground-motion records differ only marginally (of the order of ~10%) for the investigated levels of seismic hazard, thus, implying the potential for application of the spectrally equivalent ground-motion records, for seismic fragility and risk assessment at the near-fault sites.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.125-140
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• 2011

This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.737-745
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• 2010

In this paper, various methods for finding confidence intervals for the p of binomial parameter are reviewed. We compare the performance of several confidence interval estimates in terms of actual coverage probability by small sample Monte Carlo simulation.

• Proceedings of the KIEE Conference
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• summer
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• pp.464-466
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• 2004

This paper proposes a method to consider an aging failure probability and survival probability of power system components unlike uses only aging failure probability in existing mean life calculation. The estimates of the mean and its standard deviation is calculated by using Weibull distribution and each estimated parameters is obtained from Data Analytic Method (Type II Censoring). The parameter estimation using Data Analytic Method is simpler and faster than a traditional calculation method. This paper shows how to calculate the mean life and its standard deviation by the proposed method and illustrates a exactness using real historical records of generator utilities in korea.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.380-386
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• 2017

Fennovoima's nuclear power plant, Hanhikivi 1, $Pyh{\ddot{a}}joki$, Finland, is currently in design phase, and its construction is scheduled to begin in 2018 and electricity production in 2024. The objective of this paper is to produce a preliminary list of safety-significant external event combinations including preliminary probability estimates, to be used in the probabilistic risk assessment of Hanhikivi 1 plant. Starting from the list of relevant single events, the relevant event combinations are identified based on seasonal variation, preconditions related to different events, and dependencies (fundamental and cascade type) between events. Using this method yields 30 relevant event combinations of two events for the Hanhikivi site. The preliminary probability of each combination is evaluated, and event combinations with extremely low probability are excluded from further analysis. Event combinations of three or more events are identified by adding possible events to the remaining combinations of two events. Finally, 10 relevant combinations of two events and three relevant combinations of three events remain. The results shall be considered preliminary and will be updated after evaluating more detailed effects of different events on plant safety.

• IE interfaces
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• v.12 no.2
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• pp.312-318
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• 1999

This paper considers the cell loss probability(CLP) in a multiplexer with the superposition of heterogeneous ON/OFF sources. The input traffic is composed of k classes. Traffic of class i is the superposition of M_(i) ON/OFF sources. Recently, the method based on the Markov modulated deterministic process(MMDP) is presented. Basically, it is the discretized model of stochastic fluid flow process(SFFP) and gives the CLP very fast, but under-estimates the CLP especially when the value of estimated CLP is very low. This paper develops the discretized model of Markov modulated Poisson process(MMPP). It is a special type of switched batch Bernoulli process(SBBP). Combining the transition probability matrix of MMDP and SBBP according to the state which is characterized by the arrival rate, this paper presents hybrid algorithm. The hybrid algorithm gives better estimate of CLP than that of MMDP and faster than SBBP.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.679-682
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• 2008

Probability precipitation is one of the most important factor for designing the hydrology structures. Probability precipitation is calculated based on the frequency analysis on each durations of annual maximum rainfall data. For frequency analysis we need a conversion factor between the rain data per random-time interval and fixed-time-interval. In this study, the minutely precipitation data on observatory of the Meteorological Administration are used for 37 stations. Therefore, we should conversion factors between the rain data per minute and fixed-time-interval.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1109-1115
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• 2010

In this paper, exact confidence interval of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the performance of exact confidence interval estimates of hypergeometric parameter in terms of actual coverage probability by small sample Monte Carlo simulation.

• Journal of Korea Trade
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• v.25 no.5
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• pp.110-128
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• 2021

Purpose - The essential purpose of this study is to analyze the possibility of substitution of an individual job resulting from technological development represented by the 4th Industrial Resolution, considering the different effects of digital transformation on the labor market. Design/methodology - In order to estimate the substitution probability, this study used two data sets which the job characteristics data for individual occupations provided by KEIS and the information on occupational status of substitution provided by Frey and Osborne(2013). In total, 665 occupations were considered in this study. Of these, 80 occupations had data with labels of substitution status. The primary goal of estimation was to predict the degree of substitution for 607 of 665 occupations (excluding 58 with markers). It utilized three methods a principal component analysis, an unsupervised learning methodology of machine learning, and Ridge and Lasso from supervised learning methodology. After extracting significant variables based on the three methods, this study carried out logistics regression to estimate the probability of substitution for each occupation. Findings - The probability of substitution for other occupational groups did not significantly vary across individual models, and the rank order of the probabilities across occupational groups were similar across models. The mean of three methods of substitution probability was analyzed to be 45.3%. The highest value was obtained using the PCA method, and the lowest value was derived from the LASSO method. The average substitution probability of the trading industry was 45.1%, very similar to the overall average. Originality/value - This study has a significance in that it estimates the job substitution probability using various machine learning methods. The results of substitution probability estimation were compared by industry sector. In addition, This study attempts to compare between trade business and industry sector.