• ETRI Journal
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• v.41 no.5
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• pp.658-669
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• 2019

For dual-channel time-frequency (TF) overlapped signals with low sparsity in underdetermined blind source separation (UBSS), this paper proposes an effective method based on interval probability to estimate and expand the types of mixing matrices. First, the detection of TF single-source points (TF-SSP) is used to improve the TF sparsity of each source. For more distinguishability, as the ratios of the coefficients from different columns of the mixing matrix are close, a local peak-detection mechanism based on interval probability (LPIP) is proposed. LPIP utilizes uniform subintervals to optimize and classify the TF coefficient ratios of the detected TF-SSP effectively in the case of a high level of TF overlap among sources and reduces the TF interference points and redundant signal features greatly to enhance the estimation accuracy. The simulation results show that under both noiseless and noisy cases, the proposed method performs better than the selected mainstream traditional methods, has good robustness, and has low algorithm complexity.

• Journal of Educational Research in Mathematics
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• v.15 no.1
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• pp.21-38
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• 2005

The purpose of this research is to develop a probability program based on the actual condition of understanding of probability by the elementary school students from 3rd to 6th grade and search for ways to apply it to the 3rd grade of elementary school students. Based on the results from the research, the author reached a conclusion as following. After applying the learning program to five students of 3rd grade, all of the five students made progress understanding the concept of experimental and theoretical probability. However, for understanding the concept of example space, only two leading students were improved, which shows that students are having much difficulty in understanding the concept. As for under-standing the concept of experimental probability, many students gained the conceptual difference between the experimental and theoretical probability after using the program and enhanced their understanding of experimental probability.

• ETRI Journal
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• v.25 no.6
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• pp.523-526
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• 2003

This letter presents an approximation of the outage probability of the pilot channel that can be used for CDMA cell planning. The approximation can determine system parameters for soft handover in IS-95-based cellular CDMA downlink design. Computer simulations show that our analytical results agree with empirical results.

• Proceedings of the Korea Concrete Institute Conference
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• 1990.10a
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• pp.29-34
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• 1990

Based on the recent developments of the reliability-based structural analysis and design as well as the extending knowledge on the probabilistic characteristics of loadings and resistances, the probability based design criteria have been successfully developed for many standards. Since the probabilistic characteristics depend highly on the local environments(loadings) and workmanship resistances), it is recognized to develop the design creterion compatible with domestic requirements. In this study, therefore, the proper probability based design criterion(load and resistance factor design formats) has been developed based on the safaty levels observed from calibration with existing standards, which applies to the ultimate limit states of reinforced concrete members.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.293-301
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• 2014

In this paper, we propose a new measure based on the confidence of Bayesian posterior probability so as to reduce unimportant information in the clustering process. Because the performance of clustering is up to selecting the important degree of attributes within the databases, the concept of information entropy is added to posterior probability for attributes discernibility. Hence, The same value of attributes in the confidence of the proposed measure is considerably much less due to the natural logarithm. Therefore posterior probability-based clustering algorithm selects the minimum of attribute reducts and improves the efficiency of clustering. Analysis of the validation of the proposed algorithms compared with others shows their discernibility as well as ability of clustering to handle uncertainty with ACME categorical data.

• ETRI Journal
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• v.38 no.5
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• pp.952-961
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• 2016

In this paper, we study a spectrum sharing network (SSN) where a spectrum sharing device (SSD) coexists with multiple wireless communication systems (WCSs) in the same channel. The SSD can operate with either a duty cycle (DC) channel access mechanism or a listen-before-talk (LBT) channel access mechanism, whereas WCSs operate with an LBT mechanism. An opportunistic channel selection scheme for the SSD in the SSN is first proposed to minimize the outage probability. The optimal data transmission time for the DC-based SSD is derived to further improve the outage probability. We also derive the exact and closed-form outage probability of the proposed channel selection in the SSN by assuming that the number of WCSs operating in each channel is uniformly distributed. The simulation results show that the proposed channel selection scheme outperforms other channel selection schemes. It was also observed that a DC-based SSD with an optimal data transmission time provides a better outage performance than an LBT-based SSD. As the number of available channels increases, the channel selection scheme plays an important role in minimizing the outage probability of the SSNs.

• ETRI Journal
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• v.42 no.5
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• pp.712-720
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• 2020

Recently, to make the best use of limited and precious spectrum resources, spectrum sharing between satellite and cellular networks has received much interest. In this study, we mathematically analyze the success probability of a fixed (satellite) earth station (FES) based on a stochastic geometry framework. Both the FES and base stations (BSs) are assumed to be equipped with a directional antenna, and the location and the number of BSs are modeled based on the Poisson point process. Furthermore, an exclusion zone is considered, in which the BSs are prohibited from locating in a circular zone with a certain radius around the FES to protect it from severe interference from the cellular BSs. We validate the analytical results on the success probability of the cognitive satellite-terrestrial network with directional antennas by comparing it using extensive computer simulations and show the effect of the exclusion zone on the success probability at the FES. It is shown that the exclusion zone-based interference mitigation technique significantly improves the success probability as the exclusion zone increases.

• 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.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.