• Industry Promotion Research
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• v.9 no.2
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• pp.45-58
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• 2024

This study modelled the social network structure characteristics between Innopolis Start-ups located in Daejeon and Innopolis Start-ups' customers scattered across the country as a tendency of regional clustering among homogeneous technologies, and the observed values were included within the 95% confidence interval of the ERGM(Exponential Random Graph Model) analysis model. If both the research institute and the customer company are located in Yuseong-gu, Daejeon, the probability of being connected is about 13 times higher than if they are located in other administrative districts, and there is a strong tendency of connection between firms with the same technology with a negative value of assortment and homogeneity (0.1904), especially among the six technology sectors, with a P value of 0.035. There was a negative value (-0.0035) among firms not located in Yuseong-gu, with less clustering tendency. This confirms that Yuseong-gu, Daejeon, where the Daedeok Innopolis is located, is forming the centre of an innovation cluster.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.71-80
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• 2013

This work studies the reliability analysis of a slope that considers multiple failure modes. The analysis consists of two parts. First, significant failure modes that contribute most to system reliability are determined. The so-called barrier method proposed by Der Kiureghian and Dakessian to identify significant failure modes successively is employed. Second, the failure probability for the slope is estimated on the basis of the identified significant failure modes and corresponding design points. For reliability problems entailing multiple design points, failure probability can be estimated by the multi-point first-order reliability method (FORM), Ditlevsen's bounds method, and Monte Carlo simulation. In this paper, a comparative study between these methods has been made through example problems. Analysis results showed that while a soil slope may have a large number of potential slip surfaces, its system failure probability is usually governed by a few significant slip surfaces. Therefore, the most important step in the system reliability analysis for a soil slope is to identify all the significant failure modes in an efficient way.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.365-365
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• 2012

이수 및 치수를 위한 수공구조물 설계 및 하천기본계획 수립의 요점은 설계홍수량의 산정에 있으며, 통계적으로 유의성을 가지는 설계홍수량을 산정하기 위해서는 일반적으로 30년 이상 관측된 홍수자료가 요구된다. 우리나라의 경우 대부분의 유역이 미계측 유역이거나 관측년수가 비교적 작은 경우가 많으므로, 상대적으로 자료 연한이 긴 강우자료를 빈도분석한 후 이를 강우-유출 모형에 입력하여 확률홍수량을 추정하는 간접적인 방법이 주로 이용되며 사용된 강우의 빈도가 홍수의 빈도와 동일하다는 가정을 기본으로 한다. 그러나 동일한 강우량이 발생하더라도 강우의 강도, 지속시간, 유역의 선행함수조건 등과 같은 유역 특성에 따라 유출의 특성은 현저히 다르게 나타나며 결국 이러한 특성은 입력자료, 강우-유출 모형, 기후변동성 등과 같은 불확실성 요소로 인식될 수 있다. 따라서 본 연구에서는 이러한 불확실성을 고려할 수 있는 강우-유출 모의기법을 개발하여 이를 통해 홍수빈도곡선을 유도할 수 있는 방법론을 제시하고자 한다. 불확실성 분석을 위해 기존 HEC-1 강우-유출 모형에서 Bayesian MCMC 기법을 적용하여 매개변수들의 사후분포를 추정하여 매개변수들의 최적화 및 불확실성 분석을 수행하였다. 마지막으로 기후변화 영향을 통합한 홍수빈도곡선을 유도하기 위해서 극치강수를 모의하는 것이 필요하며, 본 연구에서는 극치값 재현에 있어서 우수한 성능을 발휘하는 Kernel-Pareto Piecewise분포 기반의 강우모의발생 기법을 적용하여 HEC-1모형과 연동되도록 모형을 개발하였다. 본 연구에서 제안하는 방법론은 기존 홍수빈도곡선 유도 방법에서 불확실성을 분석하기 위해 모든 변수들을 독립사상으로 간주하고 Monte Carlo Simulation을 수행함으로서 매개변수들간의 상호연관성, 상관성, 조건부 확률들을 고려할 수 없었던 점을 Bayesian 모형을 통해 매개변수들간의 조건부 확률을 고려한 매개변수의 사후분포 도출을 가능하게 하여 보다 현실적인 강우-유출 관계 도출이 가능하고 불확실성 구간이 자연적으로 도출됨으로서 향후, 신뢰성 있는 수자원 계획수립에 유용한 자료로 활용이 가능할 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.325-333
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• 2020

Current methods of measuring the sediment concentration of natural streams can be affected by weather conditions and have lower reliability in bed-load sections due to mechanical limits. Theoretical methods have to be used to solve this problem, but they have low reliability compared to the measured values and diverse results for the bed-load sediment concentration. This study proposes a new way to reliably determine the bed-load sediment concentration from the relation with theoretical depth-integrated concentration based on the informational entropy concept. Sediment distribution shows a uniform probability distribution under maximized entropy conditions under some constraints, so a function can be calculated for the sediment distribution and depth-integrated concentration. The parameters of a stream were estimated by a nonlinear regression method using the concentration data from a past experiment. Equilibrium N (EN) was estimated using the relation between two different formulas proposed in this study, which can ease the estimation of both the total sediment distribution and depth-integrated sediment concentration with high reliable results with an average R2 of 0.924.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.49-67
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• 2016

SP 800-90B of NIST(USA) and AIS.31 of BSI(Germany) are representative statistical tests for TRNGs. In this paper, we concentrate on AIS.31 which is under the ongoing international standardization process. We examine the probabilistic meaning of each statistic of the test in AIS.31 and investigate its probability distribution. By changing significance level and the length of sample bits, we obtain formalized accept region of the test. Furthermore we propose the accept regions for some iterative tests, that are not mentioned in AIS.31, and provide some simulations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.79-88
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• 1987

This study is intended to propose a system reliability analysis model for R.C. bridge superstructures based on the systems reliability theory. Approximately assuming that the ultimate capacity of the superstructures is reached, when two adjacent girders fail subsequently, a practical system reliability model is proposed, which is based on a point estimate for Level II parallel-series system modelling. The sensitivity analysis of system reliabilities for the variation of the coefficients of correlations between the failure modes is performed by applying the proposed model for R.C. T beam bridges. It is observed that the point estimate method for the proposed model corresponds to the average value of the Ditlevsen's bound, and the system reliability index, ${\beta}_s$, varies quite sensitively according to the variation of the cofficients of correlations. Systems reliabilities of a few existing T beam bridges are analyzed by applying the proposed practical system reliability method of this study, and, in addition, the preferable direction of the development of the reliability-based code calibration using the system target reliability index concept are suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.280-280
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• 2016

특정 자료의 시간의 흐름에 따른 예측치를 추정하는 방법으로 AR Model 즉, 자기회귀모형이 많이 사용되고 있다. AR Model은 변수의 현재 값을 과거 값의 함수로 나타내게 되는데, 이런 시계열 분석 모델을 사용할 때 매개변수의 추정 과정이 필수적으로 요구된다. 일반적으로 매개변수를 추정하는 방법에는 확률적근사법(stochastic approximation), 최소제곱법(method of least square), 자기상관법(method of autocorrelation method), 최우도법(method of maximum likelihood) 등이 있다. AR Model에서 가장 많이 사용되는 최우도법은 표본크기가 충분히 클 때 가장 효율적인 방법으로 평가되지만 수치적으로 해를 구하는 과정이 복잡한 경우가 많으며, 해를 구하지 못하는 어려움이 따르기도 한다. 또한 표본 크기가 작을 때 일반적으로 잘 일치하지 않은 결과를 얻게 된다. 우리나라의 강우, 유량 등의 자료는 자료의 수가 적은 경우가 많기 때문에 최우도법을 통한 매개변수 추정 시 불확실성이 내재되어있지만 그것을 정량적으로 제시하는데 한계가 있다. 본 연구에서는 AR Model의 매개변수 추정 시 Bayesian 기법으로 매개변수의 사후분포(posterior distribution)를 제공하여 매개변수의 불확실성 구간을 정량적으로 표현하게 됨으로써, 시계열 분석을 통해 보다 신뢰성 있는 예측치를 얻을 수 있으리라 판단된다.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.495-502
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• 2006

The importance of the bandwidth selection has been more emphasized than the kernel function selection for nonparametric frequency analysis since the interpolation is more reliable than the extrapolation method. However, when the extrapolation method is being applied(i.e. recurrence interval more than the length of data or extreme probabilities such as $200{\sim}500$ years), the selection of the kernel function is as important as the selection of the bandwidth. So far, the existing kernel functions have difficulties for extreme value estimations because the values extrapolated by kernel functions are either too small or too big. This paper suggests a Modified Cauchy kernel function that is suitable for both interpolation and extrapolation as an improvement.

• Tunnel and Underground Space
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• v.15 no.6 s.59
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• pp.441-451
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• 2005

It is the unavoidable problem that the RMR rock classification method has the uncertainty resulted from uncertain definition of measured value in RMR grade table, hence in this paper, the estimation of probability density function$(p{\cdot}d{\cdot}f)$ graph with the evaluation of continuos RMR and the Monte Carlo Simulation and statistic reasoning were carried out to evaluate the uncertainty quantitatively. Also, the modified RMR rock classification table was presented in order to apply the uncertainty of RMR to the practice, and then the design process of standard support pattern and the tunnel support material was proposed.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.327-344
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• 2011

This study is the first step for us toward improving high school students' capability of statistical inferences, such as obtaining and interpreting the confidence interval on the population mean that is currently learned in high school. We suggest 5 underlying concepts of 'discretion of contingency and inevitability', 'discretion of induction and deduction', 'likelihood principle', 'variability of a statistic' and 'statistical model', those are necessary to appreciate statistical inferences as a reliable arguing tools in spite of its occasional erroneous conclusions. We assume those 5 concepts above are to be gradually developing in their school periods and Korean mathematics textbooks of grades 1-12 were analyzed. Followings were found. For the right choice of solving methodology of the given problem, no elementary textbook but a few high school textbooks describe its difference between the contingent circumstance and the inevitable one. Formal definitions of population and sample are not introduced until high school grades, so that the developments of critical thoughts on the reliability of inductive reasoning could not be observed. On the contrary of it, strong emphasis lies on the calculation stuff of the sample data without any inference on the population prospective based upon the sample. Instead of the representative properties of a random sample, more emphasis lies on how to get a random sample. As a result of it, the fact that 'the random variability of the value of a statistic which is calculated from the sample ought to be inherited from the randomness of the sample' could neither be noticed nor be explained as well. No comparative descriptions on the statistical inferences against the mathematical(deductive) reasoning were found. Few explanations on the likelihood principle and its probabilistic applications in accordance with students' cognitive developmental growth were found. It was hard to find the explanation of a random variability of statistics and on the existence of its sampling distribution. It is worthwhile to explain it because, nevertheless obtaining the sampling distribution of a particular statistic, like a sample mean, is a very difficult job, mere noticing its existence may cause a drastic change of understanding in a statistical inference.