• Ocean Systems Engineering
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• 제9권3호
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• pp.287-328
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• 2019

Comprehensive understanding of the flood risk assessments via frequency analysis often demands multivariate designs under the different notations of return periods. Flood is a tri-variate random consequence, which often pointing the unreliability of univariate return period and demands for the joint dependency construction by accounting its multiple intercorrelated flood vectors i.e., flood peak, volume & durations. Selecting the most parsimonious probability functions for demonstrating univariate flood marginals distributions is often a mandatory pre-processing desire before the establishment of joint dependency. Especially under copulas methodology, which often allows the practitioner to model univariate marginals separately from their joint constructions. Parametric density approximations often hypothesized that the random samples must follow some specific or predefine probability density functions, which usually defines different estimates especially in the tail of distributions. Concentrations of the upper tail often seem interesting during flood modelling also, no evidence exhibited in favours of any fixed distributions, which often characterized through the trial and error procedure based on goodness-of-fit measures. On another side, model performance evaluations and selections of best-fitted distributions often demand precise investigations via comparing the relative sample reproducing capabilities otherwise, inconsistencies might reveal uncertainty. Also, the strength & weakness of different fitness statistics usually vary and having different extent during demonstrating gaps and dispensary among fitted distributions. In this literature, selections efforts of marginal distributions of flood variables are incorporated by employing an interactive set of parametric functions for event-based (or Block annual maxima) samples over the 50-years continuously-distributed streamflow characteristics for the Kelantan River basin at Gulliemard Bridge, Malaysia. Model fitness criteria are examined based on the degree of agreements between cumulative empirical and theoretical probabilities. Both the analytical as well as graphically visual inspections are undertaken to strengthen much decisive evidence in favour of best-fitted probability density.

• Computers and Concrete
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• 제31권3호
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• pp.253-265
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• 2023

In this research, the gene expression programming (GEP) technique was employed to provide a new model for predicting the maximum loading capacity of concrete-encased steel (CES) columns. This model was developed based on 96 CES column specimens available in the literature. The six main parameters used in the model were the compressive strength of concrete (f_c), yield stress of structural steel (f_ys), yield stress of steel rebar (f_yr), and cross-sectional areas of concrete, structural steel, and steel rebar (A_c, A_s and A_r respectively). The performance of the prediction model for the ultimate load-carrying capacity was investigated using different statistical indicators such as root mean square error (RMSE), correlation coefficient (R), mean absolute error (MAE), and relative square error (RSE), the corresponding values of which for the proposed model were 620.28, 0.99, 411.8, and 0.01, respectively. Here, the predictions of the model and those of available codes including ACI ITG, AS 3600, CSA-A23, EN 1994, JGJ 138, and NZS 3101 were compared for further model assessment. The obtained results showed that the proposed model had the highest correlation with the experimental data and the lowest error. In addition, to see if the developed model matched engineering realities and corresponded to the previously developed models, a parametric study and sensitivity analysis were carried out. The sensitivity analysis results indicated that the concrete cross-sectional area (A_c) has the greatest effect on the model, while parameter (f_yr) has a negligible effect.

• ETRI Journal
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• 제15권2호
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Structural Engineering and Mechanics
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• 제14권6호
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• pp.679-698
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• 2002

In this paper some techniques for the dynamic analysis of non-classically damped linear systems are reviewed and compared. All these methods are based on a transformation of the governing equations using a basis of complex or real vectors. Complex and real vector bases are presented and compared. The complex vector basis is represented by the eigenvectors of the complex eigenproblem obtained considering the non-classical damping matrix of the system. The real vector basis is a set of Ritz vectors derived either as the undamped normal modes of vibration of the system, or by the load dependent vector algorithm (Lanczos vectors). In this latter case the vector basis includes the static correction concept. The rate of convergence of these bases, with reference to a parametric structural system subjected to a fixed spatial distribution of forces, is evaluated. To this aim two error norms are considered, the first based on the spatial distribution of the load and the second on the shear force at the base due to impulsive loading. It is shown that both error norms point out that the rate of convergence is strongly influenced by the spatial distribution of the applied forces.

• 전자공학회논문지SC
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• 제41권1호
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• pp.9-16
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• 2004

본 논문에서는 특징점 기반 시각 구동 제어 시스템을 이용하여 파라미터 불확실성을 가지는 로봇 매니플레이터에 대한 강인 제어기를 제안한다. 시스템 내부 서부 루틴인 동력학 제어부에 적분 작용을 포함시켜 파라미터 변동에 의한 로봇 매니플레이터의 정상 상태 오차를 개선하기 위하여 시스템 내부 서부 루틴인 동력학 제어부에 적분 작용을 포함되도록 하였다. 이적분 작용은 이미지 평면상의 특징점 추정 오차도 개선시킨다. 폐루프 시스템의 안정도는 Lyapunov 기법에 의하여 해석한다. 5링크 2 자유도의 로봇에 적용한 컴퓨터 시뮬레이션 및 실험을 통하여 제안된 제어기법의 실용성을 보인다. .

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.385-397
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• 2016

The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.

• 대한전자공학회논문지
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• 제27권10호
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• pp.34-43
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• 1990

본 논문에서는 로보트 매니퓰레이터의 기준모델 적응제어계 설계에 있어서 계통의 미지 파라미터에 대해 계통식이 선형화됨에 착안하고 Augmented 오차변수를 도입하여 파라미터 제이칙 및 제어입력을 제안하였고, 계통의 모델링 과정에서 불가피하게 도입되는 모델링 오차 및 미소한 시정수를 가진 기생요소(parasitics)들이 계통의 파라미터 동정 및 추종오차에 미치는 영향을 검토하였으며 개선책으로 저역 필터를 토입한 적응제어기를 구성하여 제안된 제어칙으로 별다른 가정없이 계통이 대국적으로 안정함을 밝혔다. 끝으로 컴퓨터 시뮬레이션을 통하여 제안된 제어기 구성법이 기생요소의 영향감소에 효과적이고 유용함을 밝혔다.

• 제어로봇시스템학회논문지
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• 제17권12호
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• pp.1256-1265
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• 2011

Automated parking assist systems are being commercialized and rapidly spread in the market. In order to improve odometry accuracy, we proposed a practical odometry calibration scheme of Car-Like Mobile Robot (CLMR). However, there were some open problems in our prior work. For example, it was not clear whether the kinematic parameters always converged or not using the proposed calibration scheme. In addition, test driving had to be carried out "twice" without detailed explanation. This research aims to provide answers for the addressed questions though the convergence property analysis of the calibration scheme. In this paper, we evaluate on the effect of the kinematic parameter error on the odometry error at the final pose by numerical computation. The evaluation will show that the wheel diameter and tread of the CLMR can be calibrated by iterative test drives. In addition, the region of convergence in the parametric space will be discussed. Presented experimental results clearly showed that the proposed calibration scheme would be useful in practical applications.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2013년도 춘계학술대회 논문집
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• pp.454-459
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• 2013

For the purpose of rapid development and superior design quality assurance, sophisticated finite element model for SOM(Spatial Optical Modulator) piezo actuator of MOEMS device has been developed and evaluated for the accuracy of dynamics and residual stress analysis. Parametric finite element model is constructed using ANSYS APDL language to increase the design and analysis performance. Geometric dimensions, mechanical material properties for each thin film layer are input parameters of FE model and residual stresses in all thin film layers are simulated by thermal expansion method with psedu process temperature. $6^{th}$ mask design samples are manufactured and $1^{st}$ natural frequency and 10V PZT driving displacement are measured with LDV. The results of experiment are compared with those of the simulation and validate the good agreement in $1^{st}$ natural frequency within 5% error. But large error over 30% occurred in 10V PZT driving displacement because of insufficient PZT constant $d_{31}$ measurement technology.

• 한국레이저가공학회지
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• 제14권2호
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• pp.24-29
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• 2011

The design of a telecentric f-${\theta}$ lens with a field of view (FOV) $30^{\circ}$ and an effective focal length of 1000mm is presented. The optical stop is placed at the front plane and the design is based on a geometric ray tracing technique, and the designed system consists of a series of convex and concave lenses. The designed f-${\theta}$ lens showed a considerable reduction in weight with a simplified structure and resulted in a good performance in the designated FOV. Detail analysis of rays is also presented. 653nm (red laser), 586nm (green laser), and 468nm (blue laser) were simulated as a light source and image illuminating source. The developed optical design requires 7 pieces of lenses made of SF1, N-FK56, N-LAK33, and BK7 glass materials. With optimal parametric design, the effective focal length was calculated to be 974.839mm which is very close to the initial design target. For the manufacturing purpose, the dimensions of lens curvature and thickness were truncated with error ranging 0.1% to 3.2%. As a result, the overall error was calculated to be 3.2% which can be still tolerable for display, laser material, and machining processing.