• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.135-143
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• 2011

Currently network management systems(NMS) just give useful information about the criticality of the alarms and the process of the fault analysis is mainly dependent on the experts who have many years experiences in the field. Due to these reasons it takes very much time and manpower cost to localize the real root of the fault from the alarm information. Therefore, to solve these problems in this research we analyze the probability of the fault for each alarm and provide how to give the problem solving procedure with confidence level and give idea to build a system to realize the problem solving procedure. In addition, we give a case study to show how to use the proposed ideas.

• Magazine of the Korean Society of Agricultural Engineers
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• v.17 no.2
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• pp.3772-3777
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• 1975

This paper reports on the analysis of the distributions of probable days being good for mechanical rice harvesting and the method of determining the capacity of rice harvesting machinery for the given harvesting duration. In the analysis of the probability distribution of days being good for rice harvesting, the daily rainfalls above which mechanical field work may be impracticable were specified and their frequency of occurances was analyzed by using the weather records during past twenty-one years measured at five different locations. The conclusions being drawn from the analysis are as follows: 1. The distributions of probable workable days in different region and harvesting duration are very distinct and are different to set a uniform trend (refer to Fig. 1-4). 2. The occurance of probable days being good for mechanical field work under 66% confidence level are quite variable by region and by ten-day period. The analysis indicates that the probable workable days may range from 7.5 to 8.5 days of 10-day span within optimum harvesting duration (refer to Table 1). 3. Based on the probability distributions analyzed, the optimun capacities of harvesting machinery required for different harvesting areas and harvesting start-date were estimated as a function of operating duration (refer to Fig. 5 and Table 2)

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

• Smart Structures and Systems
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• v.33 no.1
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• pp.17-26
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• 2024

The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.889-900
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• 2008

Child labour is a disturbing issue for any society. It is attempted here in this article to develop an estimator to assess the numerical strength of this menace in Lahore division. A Horvitz and Thompson (1952) type of estimator is developed where weights are calculated on the basis of poverty and illiteracy to increase the sampling efficiency. Different characteristic features of this estimator, like its unbiasedness, variance, probability distribution, confidence intervals are also developed for its study from different angles.

• Journal of the Korean Statistical Society
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• v.25 no.2
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• pp.205-216
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• 1996

The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.672-676
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• 2002

In this paper, a reliability-based design optimization method, which enables the determination of optimum design that incorporate confidence range for structures, is studied. Response surface method and Monte Carlo simulation are utilized to determine limit state function. The proposed method is applied to the I-type steel structure for reliability based optimal design.

• Journal of the Korea Society for Simulation
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• v.1 no.1
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• pp.31-36
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• 1992

To estimate the probability of long delay in a queuing system using discrete-event simulation is studied. We contrast the coverage, half-width, and stability of confidence intervals constructed using two methods: batch means and new resampling technique; binary bootstrap. The binary bootstrap is an extension of the conventional bootstrap that resamples runs rather than data values. Empirical comparisons using known results for the M/M/1 and D/M/10 queues show the binary bootstrap superior to batch means for this problem.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.13-13
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• 1992

To estimate the probability of long delay in a queuing system using discrete-event simulation studied. We contrast the coverage, half-width, and stability of confidence intervals constructed using two methods: batch means and new resampling technique; binary bootstrap. The binary bootstrap is an extension of the conventional bootstrap that resamples runs rather than data values. Empirical comparisons using known results for the M/M/1 and D/M/10 queues show the binary bootstrap superior to batch means for this problem.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.95-106
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• 1983

The probability of failure is used to analyze the reliability of three dimensional slope failure, instead of conventional factor of safety. The strength parameters are assumed to be normal variated and beta variated. These are interval estimated under the specified confidence level and maximum likelihood estimation. The pseudonormal and beta random variables are generated using the uniform probability transformation method according to central limit theorem and rejection method. By means of a Monte-Carlo Simulation, the probability of failure is defined as; $$P_f$$=M/N N: Total number of trials M: Total number of failures some of the conclusions derived from the case study include; 1. If the strength parameters are assumed to be normal variated, the relationship between safety factor and the probability of failure is fairly consistent, regardless of the procedures of analysis and dimensions of assumed rupture surfaces. 2. However if the strength parameters are beta variated, general relationship between $F_s$ and $P_f$ is hardly found.