• Nuclear Engineering and Technology
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• v.29 no.6
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• pp.433-443
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• 1997

In this work, an analytic approach to the dependability of software in the operational phase is suggested with special attention to the hardware fault effects on the software behavior : The hardware faults considered are memory faults and the dependability measure in question is the reliability. The model is based on the simple reliability theory and the graph theory which represents the software with graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph and the software reliability is derived from this graph. Using this model, we predict the reliability of an application software in the digital system (ILS) in the nuclear power plant and show the sensitivity of the software reliability to the major physical parameters which affect the software failure in the normal operation phase. We also found that the effects of the hardware faults on the software failure should be considered for predicting the software dependability accurately in operation phase, especially for the software which is executed frequently. This modeling method is particularly attractive for the medium size programs such as the microprocessor-based nuclear safety logic program.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1321-1328
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• 2005

Based upon the Floquet theory, the complex modal solution for general rotor systems with periodically time-varying parameters is newly derived. The complete modal response can be obtained from the orthonormality condition between the time-variant eigenvectors and the corresponding adjoint vectors. The harmonic solutions such as the response and directional special a patterns are then derived in terms of harmonic modes whose coefficients are obtained from the modal analysis. The stability analysis by the Floquet's transition matrix and the eigen-analysis is also performed.

• Proceedings of the Membrane Society of Korea Conference
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• 1997.06a
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• pp.55-66
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• 1997

A brief introduction to NRC's research activities will be given with special emphasis on membrane processes. NIRC's membrane research group has been involved in many membrane research projects with industrial clients in various sectors of the industry. These projects generally were focused on using membranes for treating industrial wastewater streams for recycling process water, recovering of valuable components and meeting the environmental regulations. The group looked in to various aspects of process development dealing with membrane performance evaluation, optimization of operational parameters, determination of fouling propensities of membranes and simple cost analyses in some cases. Case studies dealing with process development for effluent treatment for the pulp & paper, mining & mineral processing and poultry processing industries will be discussed briefly.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.11-12
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• 2016

SVM (Support Vector machine) is powerful machine-learning method, and obtains better performance than traditional methods in the applications of muti-dimension nonlinear pattern classification. For the case of SVM model training and low efficiency in large samples, this paper proposes a combination of statistical parameters of the GMM-UBM (Universal Background Model) model. It is very effective to solve the problem of the large sample for the SVM training. The experiment is carried on four special dynamic hand gestures using the EPIC sensors. And the results show that the improved dynamic hand gesture recognition system has a high recognition rate up to 96.75%.

• Journal of the Korea Society for Simulation
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• v.10 no.4
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• pp.41-50
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• 2001

When optimizing a complex system by determining the optimum condition of the system parameters of interest, we often employ the process of estimating the unknown objective function, which is assumed to be a second order spline function. In doing so, we normally use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. In this paper, we will show some mathematical result for the analysis of variance when using common random numbers in terms of the regression error, the residual error and the pure error terms. In fact, if we can realize the special structure of the covariance matrix of the error terms, we can use the result of analysis of variance for the uncorrelated experiments only by applying minor changes.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1559-1565
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• 2004

Railway system is consisted of various resources such as rail-line, signal, and railcar. It is necessary to efficiently utilize these limited and expensive resources as much as possible up to given line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present an improved systematic line capacity model. The proposed model has three main components ; TPS(tain performance simulator), PES (parameter evaluation simulator), LCS(line capacity simulator). The concept of each sub-component is described, including the evaluation method of capacity parameters. And capacity parameter evaluation and estimation results using sample line section data are presented.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.289-298
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• 1999

We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.901-909
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• 2013

A skewed double power function distribution is defined by a double power function distribution. We shall evaluate the coefficient of the skewness of a skewed double power function distribution. We shall obtain an approximate maximum likelihood estimator (MLE) and a moment estimator (MME) of the skew parameter in the skewed double power function distribution, and compare simulated mean squared errors for those estimators. And we shall compare simulated MSEs of two proposed reliability estimators in two independent skewed double power function distributions with different skew parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.9
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• pp.671-683
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• 1989

A controller of interconnected power systems is investigated using an optimal multidimensional variable structure control. The switching hyperplane of the variable structure stabilizer is obtained by minimizing a quadratic performance index in continuous-time. A special feature of the optimal multidimensional variable structure stabilizer is that, when it is operated in the so-called sliding mode, the system response becomes insensitive to changes in the plant parameters. A digital simulation is performed by a digital computer using the Advanced Continuous Simulation Language (ACSL) package, which shows that the dynamic performance of the power system in response to mechanical torque changes is improved when optimal multidimensional variable sturcture stabilizers are employed.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.337-354
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• 2015

In this article, free vibration of functionally graded (FG) elliptic plates subjected to various classical boundary conditions has been investigated. Literature review reveals no study has been performed based on functionally graded elliptic plates till date. The mechanical kinematic relations are considered based on classical plate theory. Rayleigh-Ritz technique is used to obtain the generalized eigenvalue problem. The material properties of the FG plate are assumed to vary along thickness direction of the constituents according to power-law form. Trial functions denoting the displacement components are expressed in simple algebraic polynomial forms which can handle any edge support. The objective is to study the effect of geometric configurations and gradation of constituent volume fractions on the natural frequencies. New results for frequency parameters are incorporated after performing a test of convergence. A comparison study is carried out with existing literature for validation in special cases. Three-dimensional mode shapes for circular and elliptic FG plates are also presented with various boundary conditions at the edges.