• Tunnel and Underground Space
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• v.29 no.3
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• pp.172-183
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• 2019

The generalized Hoek-Brown (GHB) failure criterion developed by Hoek et al. (2002) is a nonlinear function which defines a stress condition at failure of rock mass. The relevant strength parameter values are systematically determined using the GSI value. Since GSI index is a value quantifying the condition of in-situ rock mass, the GHB criterion is a practical failure condition which can take into the consideration of in-situ rock mass quality. Considering that most rock mechanics engineers are familiar with the linear Mohr-Coulomb criterion and that many rock engineering softwares incorporate Mohr-Coulomb criterion, the equations for the equivalent friction angle and cohesion were also proposed along with the release of the GHB criterion. The proposed equations, however, fix the lower limit of the minor principal stress range, where the linear best-fitting is performed, with the tensile strength of the rock mass. Therefore, if the tensile stress is not expected in the domain of analysis, the calculated equivalent friction angle and cohesion based on the equations in Hoek et al. (2002) could be less accurate. In order to overcome this disadvantage of the existing equations for equivalent friction angle and cohesion, this study proposes the analytical formula which can calculate optimal equivalent friction angle and cohesion in any minor principal stress interval, and verified the accuracy of the derived formula.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.44-55
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• 1997

In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.274-274
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• 2004

조향성능은 완성된 자동차를 평가하는 아주 중요한 요소이며, 운전자에게 직접적인 영향을 가지는 까닭으로 우선적으로 해결되어야 할 문제이다. 자동차의 조향성능과 관련된 자동차 요소로는 프런트 샤시 모듈이 있으며, 프런트 샤시 모듈의 자세는 구성 요소인 서브프레임의 조립자세에 의하여 결정된다. 서브프레임은 4개의 원통형 지지부로 이루어져 있으며, 차체와의 조립시 지지부에 물리적 접촉이 발생한다. 즉 공간상에서 서브프레임의 자세는 지지부의 조립위치에 의하여 결정이 되며, 서브프레임의 자세를 결정하기 위해서는 지지부에 대한 적절한 해석이 필요하다.(중략)

• Electrical & Electronic Materials
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• v.1 no.3
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• pp.243-250
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• 1988

530A의 질화막과 23A의 엷은 산화막두께로 제작된 MNOS 소자의 기억트랩분포와 기억특성을 TSC방법과 C-V방법으로 조사하였다. 소자는 전기적으로 기억갱신이 가능하며 무전압유지가 반영구적임을 확인하였다. 기억트랩에 해당하는 TSC곡선을 분석하는데는 공간적, 에너지적인 트랩의 분포모형을 가정하고 best fitting법을 사용하였다. 그 결과 기억트랩은 질화막-산화막 계면에서 질화막안으로 10A 깊이로 분포되었으며 에너지준위는 질화막전도대 하단에서 2.35-2.38eV로 분포되어 있음을 밝혔다. 또한 방전기구는 산화막층을 통한 직접터널링과 열적여기를 함께 고려하여 설명할 수 있었다.

• The Journal of the Korean dental association
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• v.54 no.11
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• pp.850-864
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• 2016

The Generalized Estimating Equations (GEE) approach is a widely used statistical method for analyzing longitudinal data and clustered data in clinical studies. In dentistry, due to multiple outcomes obtained from one patient, the outcomes produced from an individual patient are correlated with one another. This study focused on the basic ideas of GEE and introduced the types of covariance matrix and working correlation matrix. The quasi-likelihood information criterion (QIC) and quasi-likelihood information criterion approximation ($QIC_u$) were used to select the best working correlation matrix and the best fitting model for the correlated outcomes. The purpose of this study is to show a detailed process for the GEE analysis using SPSS software along with an orthodontic miniscrew example, and to help understand how to use GEE analysis in dental research.

• International Journal of Railway
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• v.6 no.2
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• pp.45-52
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• 2013

Railway construction needs vast soil investigation for its infrastructure foundation designs along the planned railway path to identify the design parameters for stability and serviceability checks. The soil investigation data are usually classified and grouped to decide design input parameters per each construction section and budget estimates. Deterministic design method which most civil engineer and practitioner are familiar with has a clear limitation in construction/maintenance budget control, and occasionally produced overdesigned or unsafe design problems. Instead of using a batch type analysis with predetermined input parameters, data population collected from site soil investigation and design load condition can be statistically estimated for the mean and variance to present the feature of data distribution and optimized with a best fitting probability function. Probabilistic approach using entire feature of design input data enables to predict the worst, best and most probable cases based on identified ranges of soil and load data, which will help railway designer select construction method to save the time and cost. This paper introduces two Monte Carlo simulations actually applied on estimation of retaining wall external stability and long term settlement of organic soil in soil investigation area for a recent high speed railway project.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.1945-1947
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• 2005

This study considers find out best accelerated life testing and lifetime prediction of electrolytic capacitors. We proved about relation between failure and deterioration mechanism from last thesis. Beside we performed test that temperature and voltage press higher than allowance specification. Failure distribution acquired from those test. And wiebull function and Minitab program applied to accelerated constant and lifetime by means of calculation. At the result, goodness of fit affect to weibull function and acceleration factor therefore fitting is important factor in reliability testing.

• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.710-716
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• 2002

A General Pipe Break Prediction Model that incorporates linear and exponential models in its form is developed. The model is capable of fitting pipe break trends that have linear, exponential or in between of linear and exponential trend by using a weighting factor. The weighting factor is adjusted to obtain a best model that minimizes the sum of squared errors of the model. The model essentially plots a best curve (or a line) passing through "cumulative number of pipe breaks" versus "break times since installation of a pipe" data points. Therefore, it prevents over-predicting future number of pipe breaks compared to the conventional exponential model. The optimal replacement time equation is derived by using the Threshold Break Rate equation by Loganathan et al. (2002).

• Language and Information
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• v.9 no.1
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• pp.69-92
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• 2005

Pattern recognition in cognitive agents is based on (i) the uninterpreted input data (e.g. parameter values) provided by the agent's hardware devices and (ii) and interpreted patterns (e.g. templates) provided by the agent's memory. Computationally, the task consists in finding the memory data corresponding best to the input data, for any given input. Once the best fitting memory data have been found, the input is recognized by applying to it the interpretation which happens to be stored with the memorized pattern. This paper presents a fast converging procedure which starts from a few initially recognized items and then analyzes the remainder of the input by systematically checking for items shown by memory to have been related to the initial items in previous encounters. In this way, known patterns are tried first, and only when they have been exhausted, an elementary exploration of the input is commenced. Efficiency is improved further by choosing the candidate to be tested next according to frequency.