• 한국수자원학회논문집
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• 제31권3호
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• pp.243-252
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• 1998

본 연구에서는 새로운 무차원값을 제시하여 도시유출모형의 매개변수결정을 위한 상대적인 민감도분석을 실시하여 매개변수별 민감도특성을 구명하였다. 민감도분석을 위한 무차원값으로 총유출량비,첨두유출량비, 유출민감도비, 민감도비율을 다음과 같이 개발하였다. $$ 유역면적의 크기와 강우분포형과 강우지속기간별로 각 적용단계별 총유출량비, 첨두유출량비, 유출민감도를 산정하기 위해 ILLUDAS모형과 SWMM모형의 매개변수를 선저하고 적정 적용범위를 결정하였다.

• 한국보육지원학회지
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• 제14권6호
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• pp.69-88
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• 2018

Objective: The purpose of this study was to examine the relationships between child care teachers' mindfulness, burnout, and sensitivity. Also, the effects of child care teachers' mindfulness on teacher sensitivity, including the mediating effects of burnout, were investigated. Methods: A total of 263 child care teachers who work in Seoul, Gyeonggi and Incheon participated in this study. Data were analyzed by correlations and regressions using SPSS 21.0. Results: First, there were significant correlations between child care teachers' mindfulness, burnout and teacher sensitivity. Second, the relationship between mindfulness and teacher sensitivity was partially mediated by burnout. To be specific, mindfulness not only had a direct effect on teacher sensitivity, but also had an indirect effect on teacher sensitivity through burnout. Among the three dimensions of burnout, the decrease of personal accomplishments had the biggest significant mediation effect on the relationship between mindfulness and teacher sensitivity. Conclusion/Implications: In conclusion, this study highlights the importance of mindfulness in reducing burnout and enhancing teacher sensitivity toward children. Also, this research has implications for future research regarding the mindfulness of child care teachers and offers a foundation for the development of mindfulness training programs for child care teachers.

• 대한기계학회논문집A
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• 제29권12권
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• pp.1629-1637
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Transactions on Electrical and Electronic Materials
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• 제15권4호
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• pp.182-188
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• 2014

When the windowed DFT algorithm is applied in harmonic measurements, the problem of initial-phase sensitivity will be encountered, this has an effect on harmonic amplitude accuracy. In this paper, the origin of initial-phase sensitivity is analyzed and the main factors that influence the level of initial-phase sensitivity are demonstrated. A method of reducing initial-phase sensitivity is proposed to increase the stability of harmonic measurements. We found that initial-phase sensitivity is determined by the side lobe peak level of the window functions when synchronous deviation is fixed. In addition, increasing the length of the time recorded can be used to remove initial-phase sensitivity. The correctness and validity of our conclusions have been confirmed through numerical results and field tests.

• 제어로봇시스템학회논문지
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• 제10권4호
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• pp.295-303
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• 2004

Previously it has been shown that the all pole systems resulting good time responses can be characterized by so called K-polynomial. The polynomial is defined in terms of the principal characteristic ratio $\alpha_1$ and the generalized time constant $\tau$ . In this paper, Part II presents several sensitivity analyses of such systems with respect to $\alpha_1$ and $\tau$ changes. We first deal with the root sensitivity to the perturbation of $\alpha_1$ . By way of determining the unnormalized function sensitivity, both time response sensitivity and frequency response sensitivity are derived. Finally, the root sensitivity relative to $\tau$ change is also analyzed. These results provide some useful insight and background theory when we select of and l to compose a reference model of which denominator is a K-polynomial, which is illustrated by examples.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.508-512
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• 1997

Design sensitivity analysis of Eigen Problem give systematic design improvement information for noise and vibration of a system. Based on reliable results form commercial FE code(UAI/NASTRAN), three computational procedures for design sensitivity analysis of eigen problem are suggested. Those methods are finite difference,design sensitivity analysis using external module and design sensitivity analysis running with NASTRAN. To verify the suggested methods, a numerical example is given and these results are compared with the results from UAI/NASTRAN eigen sensitivity option. We can conclude that design sensitivity coefficient of eigen proplems can be computed outside of the FE code as easy as inside of the FE code.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1377-1382
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• 1990

In Multi-Layer Perceptron (MLP) which realizes continuous mappings, the output errors is directly affected by the weight errors which may be caused by the limited precision of digital or analog hardware in implementations. So, it is important to study the sensitivity due to the perturbation of connection weights between neurons. In this paper, we derive a sensitivity function to the statistical weight perturbations in MLP with differentiable activation functions. This sensitivity function can be regarded as an ensemble average of deterministic sensitivity measures due to the perturbations of weights. Hence, this sensitivity function can be used as the criteria for selecting weights with the minimum sensitivity among possible sets of connection weights in MLP. For the verification of the validity of the proposed sensitivity function, computer simulations have been performed and through the simulations we find good agreement between the theoretical and simulation results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1992년도 추계학술대회논문집; 반도아카데미, 20 Nov. 1992
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• pp.19-24
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• 1992

Design sensitivity analysis method for the vibration of vehicle structure is developed using adjoint variable method. A variational approach with complex response method is used to derive sensitivity expression. To evaluate sensitivity, FEM analysis of ship deck and vehicle structure are performed using MSC/NASTRAN on the super computer CRAY2S, and sensitivity computation is carried on PC. The accuracy of sensitivity is verified by the results of finite difference method. When compared to structural analysis time on CRAY2S, sensitivity computation is remarkably economical. The sensitivity of vehicle frame can be used to reduce the vibration responses such as displacement and acceleration of vehicle.

• International Journal of Aeronautical and Space Sciences
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• 제2권1호
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• pp.20-27
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• 2001

Aerodynamic sensitivity analysis is performed for the Navier-Stokes equations coupled with two-equation turbulence models using a discrete adjoint method and a direct differentiation method respectively. Like the mean flow equations, the turbulence model equations are also hand-differentiated to accurately calculate the sensitivity derivatives of flow quantities with respect to design variables in turbulent viscous flows. The sensitivity codes are then compared with the flow solver in terms of solution accuracy, computing time and computer memory requirements. The sensitivity derivatives obtained from the sensitivity codes with different turbulence models are compared with each other. The capability of the present sensitivity codes to treat complex geometry is successfully demonstrated by analyzing the flows over multi-element airfoils on Chimera overlaid grid systems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.464-469
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.