• Steel and Composite Structures
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• v.15 no.1
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• pp.15-39
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• 2013

The sensitivities of a structural response due to variation of its design parameters are prerequisite in the majority of the algorithms used for fundamental problems in engineering as system uncertainties, identification and probabilistic assessments etc. The paper presents the concept of probabilistic sensitivity of suspension bridges with respect to near-fault ground motion. In near field earthquake ground motions, large amplitude spectral accelerations can occur at long periods where many suspension bridges have significant structural response modes. Two different types of suspension bridges, which are Bosporus and Humber bridges, are selected to investigate the near-fault ground motion effects on suspension bridges random response sensitivity analysis. The modulus of elasticity is selected as random design variable. Strong ground motion records of Kocaeli, Northridge and Erzincan earthquakes are selected for the analyses. The stochastic sensitivity displacements and internal forces are determined by using the stochastic sensitivity finite element method and Monte Carlo simulation method. The stochastic sensitivity displacements and responses obtained from the two different suspension bridges subjected to these near-fault strong-ground motions are compared with each other. It is seen from the results that near-fault ground motions have different impacts stochastic sensitivity responses of suspension bridges. The stochastic sensitivity information provides a deeper insight into the structural design and it can be used as a basis for decision-making.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.603-605
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• 1999

In this paper, the aspects on modeling and control of an existing wind turbine are discussed. When designing control for variable-speed wind turbine, one deals with highly resonant, nonlinear dynamic systems subject to random excitation, i.e. wind turbulence. This requires good knowledge of the dynamics to be controlled. This paper describes an mathematical modeling of wind turbines with emphasis on control design for an existing wind turbine.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.4
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• pp.432-446
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• 1996

A stochastic Hamilton variational principle(SHVP) is formulated for dynamic problems of linear continuum. The SHVP allows incorporation of probabilistic distributions into the finite element analysis. The formulation is simplified by transformation of correlated random variables to a set of uncorrelated random variables through a standard eigenproblem. A procedure based on the Fourier analysis and synthesis is presented for eliminating secularities from the perturbation approach. In addition to, a method to analyse stochastic design sensitivity for structural dynamics is present. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element codes. An alternative form of the constraint functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The algorithms developed can readily be adapted to existing deterministic finite element codes. The numerical results for stochastic analysis by proceeding approach of cantilever, 2D-frame and 3D-frame illustrates in this paper.

• Journal of the Korean Mathematical Society
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• v.45 no.6
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• pp.1753-1767
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• 2008

Consider the nonparametric regression model $Y_{ni}\;=\;g(x_{ni})+{\epsilon}_{ni}$ ($1\;{\leq}\;i\;{\leq}\;n$), where g($\cdot$) is an unknown regression function, $x_{ni}$ are known fixed design points, and the correlated errors {${\epsilon}_{ni}$, $1\;{\leq}\;i\;{\leq}\;n$} have the same distribution as {$V_i$, $1\;{\leq}\;i\;{\leq}\;n$}, here $V_t\;=\;{\sum}^{\infty}_{j=-{\infty}}\;{\psi}_je_{t-j}$ with ${\sum}^{\infty}_{j=-{\infty}}\;|{\psi}_j|$ < $\infty$ and {$e_t$} are negatively associated random variables. Under appropriate conditions, we derive a Berry-Esseen type bound for the estimator of g($\cdot$). As corollary, by choice of the weights, the Berry-Esseen type bound can attain O($n^{-1/4}({\log}\;n)^{3/4}$).

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.115-123
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• 1994

Under variable amplitude loading conditions, retardation or accelerated condition of fatigue crack growth occurs with every cycle, Because fatigue crack growth behavior varied depend on load time history. The modeling of stress amplitude with storm loading acted to ships and offshore structures applied this paper. The crack closure behavior examine by recording the variation in load-strain relationship. By taking process mentioned above, fatigue crack growth rate, crack length, stress intensity factor, and crack closure stress intensity factor were obtained from the stress cycles of each type of storm ; A(6m), B(7m), C(8m), D(9m), E(11m) and F(15m) which was wave height. It showed that the good agreement with between the experiment results and simulation of storm loads. So this estimated method of crack propagtion rate gives a good criterion for the safe design of vessels and marine structure.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.145-157
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• 2024

Purpose - In this study, we propose an empirical model for predicting seasoned equity offering (SEO here after) using machine learning methods. Design/methodology/approach - The models utilize the random forest method based on decision trees that considers non-linear relationships, as well as the gradient boosting tree model. SEOs incur significant direct and indirect costs. Therefore, CEOs' decisions of seasoned equity issuances are made only when the benefits outweigh the costs, which leads to a non-linear relationship between SEOs and a determinant of them. Particularly, a variable related to market timing effectively exhibit such non-linear relations. Findings - To account for these non-linear relationships, we hypothesize that decision tree-based random forest and gradient boosting tree models are more suitable than the linear methodologies due to the non-linear relations. The results of this study support this hypothesis. Research implications or Originality - We expect that our findings can provide meaningful information to investors and policy makers by classifying companies to undergo SEOs.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.21-31
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• 2010

In the architectural design technologies being changed recently, there is the study to develop the way that will enable the designers to get access logically to the processes of deciding the values of design factors which depend on the experience of the designers. This study, which is one part of those studies, has been carried out to develop the model that can decide the values logically for the design factors having the character that the design values are changed by the time variation out of design factors involved in the building energy saving design. As a result, the structure of the decision model which can decide the design values logically from the computer simulation that solve the problem by interpreting the real world as the probability distribution, has been established through this study. For the application and verification of these decision model, the case study has been carried out for the outdoor climate factors that stand for the design factors having the time variation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.187-190
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• 2009

네트워크 코딩 중 RLC (random linear coding)은 다양한 연구들에서 이미 그 효용성이 입증되었으며 실제 유/무선 네트워크 환경에서 RLC를 적용하는 연구들이 최근 활발하게 진행되고 있다. RLC는 간단한 방법론적인 특성과 그 효용성으로 인해 많은 관심을 받고 있지만, 실제 환경에서 RLC 디코딩 과정이 요구하는 높은 성능 복잡도로 인하여 실용성에 한계를 가진다. 이러한 상황에서 최근 병행 방법 (Parallelized method)을 이용해 RLC 디코딩 과정의 복잡도를 개선하고 이를 실제적인 비디오 전송에 적용하는 연구들이 진행되고 있다. 본 논문에서는 이러한 연구들과 더불어 무선 환경에서의 실시간 비디오 전송을 위한 비디오의 특성을 고려하는 RLC 기반의 실시간 비디오 전송 시스템을 제안한다. 또한 제안한 시스템 실험적으로 구현하고, 이를 실제 무선 네트워크 환경에서 검증하였다.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• Computational Structural Engineering
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• v.4 no.4
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• pp.125-133
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• 1991

For the purpose of efficiently calculating the design sensitivity and the reliability for the complicated structures in which the structural responses or limit state functions are given by implicit form, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis method needed in the reliability-based design is proposed. As numerical examples, two thin plates are analyzed for the cases of plane stress and plate bending. The initial yielding is defined as failure criterion, and applied loads, yield stress, plate thickness, Young's modulus and Poisson's ratio are treated as random variables. It is found that the response variances and the failure probabilities calculated by the proposed PFEM-based reliability method show good agreement with those by Monte Carlo simulation. The probabilistic design sensitivity evaluates explicitly the contribution of each random variable to probability of failure. Further, the design change can be evaluated without any difficulty, and their effect on reliability can be estimated quickly with high accuracy.