Relevant bibliographies by topics / Sensitivity Analysis

Academic literature on the topic 'Sensitivity Analysis'

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Published: 4 June 2021
Last updated: 31 August 2024

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Journal articles on the topic "Sensitivity Analysis"

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Yunanto, Muhamad, and Henny Medyawati. "Fiscal Policy and Monetary Policy: Sensitivity Analysis." International Journal of Trade, Economics and Finance 6, no. 2 (April 2015): 79–84. http://dx.doi.org/10.7763/ijtef.2015.v6.447.

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Dragičević, N., B. Karleuša, and N. Ožanić. "Erosion Potential Method (Gavrilović method) sensitivity analysis." Soil and Water Research 12, No. 1 (January 18, 2017): 51–59. http://dx.doi.org/10.17221/27/2016-swr.

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In recent decades, various methods for erosion intensity and sediment production assessment have been developed. The necessity for better model performance has led to the more frequent application of the method sensitivity and uncertainty assessments in order to decrease errors that arise from the model concept and its main assumptions. The analysis presented in this paper refers to the application of the Gavrilović method (Erosion Potential Method), an empirical and semi-quantitative method that can estimate the amount of sediment production and sediment transport as well as the erosion intensity and indicate the areas potentially threatened by erosion. The emphasis in this paper is given upon the method sensitivity analysis that has not previously been conducted for the Gavrilović method. The sensitivity analysis was conducted for fourteen different parameters included in the method, all in relation to different model outputs. Each parameter was perceived and discussed individually in relation to its effect upon the method outputs, and ranked into categories depending on their influence on one or more model outputs. The objective of the analysis was to explore the constraints of the Gavrilović method and the method response to changes deriving from the each individual parameter in an attempt to provide a better understanding of the method, the weight and the contribution of each parameter in the overall method. The parameters that could potentially be used in future research, for method modification and calibration in areas with different catchment characteristics (e.g. climate, geological, etc.) were identified. The most sensitive model parameters resulting from conducted sensitivity analysis for the Gavrilović method are also those considered to be significant in the scientific literature on erosion. The Gavrilović method sensitivity analysis has been done on a case study for the Dubracina catchment area, Croatia.
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Plümper, Thomas, and Richard Traunmüller. "The sensitivity of sensitivity analysis." Political Science Research and Methods 8, no. 1 (August 29, 2018): 149–59. http://dx.doi.org/10.1017/psrm.2018.30.

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AbstractThis article evaluates the reliability of sensitivity tests. Using Monte Carlo methods we show that, first, the definition of robustness exerts a large influence on the robustness of variables. Second and more importantly, our results also demonstrate that inferences based on sensitivity tests are most likely to be valid if determinants and confounders are almost uncorrelated and if the variables included in the true model exert a strong influence on outcomes. Third, no definition of robustness reliably avoids both false positives and false negatives. We find that for a wide variety of data-generating processes, rarely used definitions of robustness perform better than the frequently used model averaging rule suggested by Sala-i-Martin. Fourth, our results also suggest that Leamer’s extreme bounds analysis and Bayesian model averaging are extremely unlikely to generate false positives. Thus, if based on these inferential criteria a variable is robust, it is almost certain to belong into the empirical model. Fifth and finally, we also show that researchers should avoid drawing inferences based on lack of robustness.
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Qichang An, Qichang An, Jingxu Zhang Jingxu Zhang, Fei Yang Fei Yang, and Hongchao Zhao Hongchao Zhao. "Normalized point source sensitivity analysis in GSSM prototype." Chinese Optics Letters 15, no. 11 (2017): 111202. http://dx.doi.org/10.3788/col201715.111202.

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Klimoski, Richard. "Introduction: Sensitivity Analysis." Academy of Management Learning & Education 5, no. 4 (December 2006): 461–62. http://dx.doi.org/10.5465/amle.2006.23473206.

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Wagner, Harvey M. "Global Sensitivity Analysis." Operations Research 43, no. 6 (December 1995): 948–69. http://dx.doi.org/10.1287/opre.43.6.948.

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Seth, A. K. "Network Sensitivity Analysis." IETE Technical Review 2, no. 12 (December 1985): 399–407. http://dx.doi.org/10.1080/02564602.1985.11437861.

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Allaire, Douglas L., and Karen E. Willcox. "Distributional sensitivity analysis." Procedia - Social and Behavioral Sciences 2, no. 6 (2010): 7595–96. http://dx.doi.org/10.1016/j.sbspro.2010.05.134.

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Irving, A. D. "Stochastic sensitivity analysis." Applied Mathematical Modelling 16, no. 1 (January 1992): 3–15. http://dx.doi.org/10.1016/0307-904x(92)90110-o.

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Somayajula, Gopichand, and James E. Bernard. "Grid sensitivity analysis." Finite Elements in Analysis and Design 7, no. 4 (February 1991): 307–15. http://dx.doi.org/10.1016/0168-874x(91)90046-2.

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Dissertations / Theses on the topic "Sensitivity Analysis"

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Wan, Din Wan Ibrahim. "Sensitivity analysis intolerance allocation." Thesis, Queen's University Belfast, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675480.

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In Computer Aided Design model the shape is usually defined as a boundary representation, a cell complex of faces, edges, and vertices. The boundary representation is generated from a system of geometric constraints, with parameters as degrees of freedom. The dimensions of the boundary representation are determined by the parameters in the CAD system used to model the part, and every single parametric perturbation may generate different changes in the part model shape and dimensions. Thus, one can compute dimensional sensitivity to parameter perturbations. A "Sensitivity Analysis" method is proposed to automatically quantify the dependencies of the Key Characteristic dimensions on each of the feature parameters in a CAD model. Once the sensitivities of the feature parameters to Key Characteristic dimensions have been determined the appropriate perturbations of each parameter to cause a desired change in critical dimension can be determined. This methodology is then applied to real applications of tolerancing in mechanical assembly models to show the efficiencies of this new developed strategy. The approach can identify where specific tolerances need to be applied to a Key Control Characteristic dimension, the range of part tolerances that could be used to achieve the desired Key Product Characteristic dimension tolerances, and also if existing part tolerances make it impossible to achieve the desired Key Product Characteristic dimension tolerances. This thesis provides an explanation of a novel automated tolerance allocation process for an assembly model based on the parametric CAD sensitivity method. The objective of this research is to expose the relationship between parameters sensitivity of CAD design in mechanical assembly product and tolerance design. This exposes potential new avenues of research in how to develop standard process and methodology for geometrical dimensioning and tolerancing (GD&T) in a digital design tools environment known as Digital MockUp (DMU).
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Poveda, David. "Sensitivity analysis of capital projects." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27990.

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This thesis presents a very generalized model useful in the economic evaluation of capital projects. Net Present Value and the Internal Rate of Return are used as the performance measures. A theoretical framework to perform sensitivity analysis including bivariate analysis and sensitivity to functional forms is presented. During the development of the model, emphasis is given to the financial mechanisms available to fund large capital projects. Also, mathematical functions that can be used to represent cash flow profiles generated in each project phase are introduced. These profiles are applicable to a number of project types including oil and gas, mining, real estate and chemical process projects. Finally, a computer program has been developed which treats most of the theoretical concepts explored in this thesis, and an example of its application is presented. This program constitutes a useful teaching tool.
Applied Science, Faculty of
Civil Engineering, Department of
Graduate
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Faria, Jairo Rocha de. "Second order topological sensitivity analysis." Laboratório Nacional de Computação Científica, 2008. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=141.

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The topological derivative provides the sensitivity of a given shape functional with respect to an infinitesimal non-smooth domain pertubation (insertion of hole or inclusion, for instance). Classically, this derivative comes from the second term of the topological asymptotic expansion, dealing only with inifinitesimal pertubations. However, for pratical applications, we need to insert pertubations of finite sizes.Therefore, we consider other terms in the expansion, leading to the concept of higher-order topological derivatives. In a particular, we observe that the topological-shape sensitivity method can be naturally extended to calculate these new terms, resulting in a systematic methodology to obtain higher-order topological derivatives. In order to present these ideas, initially we apply this technique in some problems with exact solution, where the topological asymptotic expansion is obtained until third order. Later, we calculate first as well as second order topological derivative for the total potential energy associated to the Laplace equation in two-dimensional domain pertubed with the insertion of a hole, considering homogeneous Neumann or Dirichlet boundary conditions, or an inclusion with thermal conductivity coefficient value different from the bulk material. With these results, we present some numerical experiments showing the influence of the second order topological derivative in the topological asymptotic expansion, which has two main features:it allows us to deal with pertubations of finite sizes and provides a better descent direction in optimization and reconstruction algorithms.
A derivada topológica fornece a sensibilidade de uma dada função custo quando uma pertubação não suave e infinitesimal (furo ou inclusão, por exemplo) é introduzida. Classicamente, esta derivada vem do segundo termo da expansão assintótica topológica considerando-se apenas pertubações infinitesimais. No entanto, em aplicações práticas, é necessário considerar pertubação de tamanho finito. Motivado por este fato, o presente trabalho tem como objetivo fundamental introduzir o conceito de derivadas topológicas de ordem superiores, o que permite considerar mais termos na expansão assintótica topológica. Em particular, observa-se que o topological-shape sensitivity method pode ser naturalmente estendido para o cálculo destes novos termos, resultando em uma metodologia sistemática de análise de sensibilidade topológica de ordem superior. Para se apresentar essas idéias, inicialmente essa técnica é verificada através de alguns problemas que admitem solução exata, onde se calcula explicitamente a expansão assintótica topológica até terceira ordem. Posteriormente, considera-se a equação de Laplace bidimensional, cujo domínio é topologicamente pertubado pela introdução de um furo com condição de contorno de Neumann ou de Dirichlet homogêneas, ou ainda de uma inclusão com propriedade física distinta do meio. Nesse caso, são calculadas explicitamente as derivadas topológicas de primeira e segunda ordens. Com os resultados obtidos em todos os casos, estuda-se a influência dos termos de ordem superiores na expansão assintótica topológica, através de experimentos numéricos. Em particular, observa-se que esses novos termos, além de permitir considerar pertubações de tamanho finito, desempenham ainda um importante papel tanto como fator de correção da expansão assintótica topológica, quanto como direção de descida em processos de otimização. Finalmente, cabe mencionar que a metodologia desenvolvida neste trabalho apresenta um grande potencial para aplicação na otimização e em algoritimos de reconstrução.
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Witzgall, Zachary F. "Parametric sensitivity analysis of microscrews." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4892.

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Thesis (M.S.)--West Virginia University, 2006.
Title from document title page. Document formatted into pages; contains xi, 73 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 52-53).
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鄧國良 and Kwok-leong Tang. "Sensitivity analysis of bootstrap methods." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31977479.

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Fang, Xinding S. M. Massachusetts Institute of Technology. "Sensitivity analysis of fracture scattering." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/59789.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 40-42).
We use a 2-D finite difference method to numerically calculate the seismic response of a single finite fracture in a homogeneous media. In our experiments, we use a point explosive source and ignore the free surface effect, so the fracture scattering wave field contains two parts: P-to-P scattering and P-to-S scattering. We vary the fracture compliance within a range considered appropriate for field observations, 10-12 m/Pa to 10-9 m/Pa, and investigate the variation of the scattering pattern of a single fracture as a function of normal and tangential fracture compliance. We show that P-to-P and P-to-S fracture scattering patterns are sensitive to the ratio of normal to tangential fracture compliance and different incident angle, while radiation pattern amplitudes scale as the square of the compliance. We find that, for a vertical fracture system, if the source is located at the surface, most of the energy scattered by a fracture propagates downwards, specifically, the P-to-P scattering energy propagates down and forward while the P-to-S scattering energy propagates down and backward. Therefore, most of the fracture scattered waves observed on the surface are, first scattered by fractures, and then reflected back to the surface by reflectors below the fracture zone, so the fracture scattered waves have complex ray paths and are contaminated by the reflectivity of matrix reflectors.
by Xinding Fang.
S.M.
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Masinde, Brian. "Birds' Flight Range. : Sensitivity Analysis." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166248.

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’Flight’ is a program that uses flight mechanics to estimate the flight range of birds. This program, used by ornithologists, is only available for Windows OS. It requires manual imputation of body measurements and constants (one observation at a time) and this is time-consuming. Therefore, the first task is to implement the methods in R, a programming language that runs on various platforms. The resulting package named flying, has three advantages; first, it can estimate flight range of multiple bird observations, second, it makes it easier to experiment with different settings (e.g. constants) in comparison to Flight and third, it is open-source making contribution relatively easy. Uncertainty and global sen- sitivity analyses are carried out on body measurements separately and with various con- stants. In doing so, the most influential body variables and constants are discovered. This task would have been near impossible to undertake using ’Flight’. A comparison is made amongst the results from a crude partitioning method, generalized additive model, gradi- ent boosting machines and quasi-Monte Carlo method. All of these are based on Sobol’s method for variance decomposition. The results show that fat mass drives the simulations with other inputs playing a secondary role (for example mechanical conversion efficiency and body drag coefficient).
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Tang, Kwok-leong. "Sensitivity analysis of bootstrap methods." [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13793792.

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Munster, Drayton William. "Sensitivity Enhanced Model Reduction." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23169.

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In this study, we numerically explore methods of coupling sensitivity analysis to the reduced model in order to increase the accuracy of a proper orthogonal decomposition (POD) basis across a wider range of parameters. Various techniques based on polynomial interpolation and basis alteration are compared. These techniques are performed on a 1-dimensional reaction-diffusion equation and 2-dimensional incompressible Navier-Stokes equations solved using the finite element method (FEM) as the full scale model. The expanded model formed by expanding the POD basis with the orthonormalized basis sensitivity vectors achieves the best mixture of accuracy and computational efficiency among the methods compared.
Master of Science
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Konarski, Roman. "Sensitivity analysis for structural equation models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22893.pdf.

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Books on the topic "Sensitivity Analysis"

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Borgonovo, Emanuele. Sensitivity Analysis. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3.

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D, Roberts Gary, Bowles Kenneth J, and United States. National Aeronautics and Space Administration., eds. ICAN sensitivity analysis. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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Stanley, Lisa G. Design sensitivity analysis: Computational issues of sensitivity equation methods. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2003.

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United States. National Aeronautics and Space Administration., ed. Fault-sensitivity and wear-out analysis of VLSI sensitivity. [Urbana, IL]: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1994.

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United States. National Aeronautics and Space Administration., ed. Fault-sensitivity and wear-out analysis of VLSI sensitivity. [Urbana, IL]: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1994.

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Choi, Kyung K. Structural sensitivity analysis and optimization. New York: Springer Science+Business Media, 2005.

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Chatterjee, Samprit. Sensitivity analysis in linear regression. New York: Wiley, 1988.

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Barrick, Nettie J. OASDI short-range sensitivity analysis. [Washington, D.C.?]: Social Security Administration, Office of the Chief Actuary, 1996.

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Deif, Assem. Sensitivity Analysis in Linear Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-82739-6.

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Ustinov, Eugene A. Sensitivity Analysis in Remote Sensing. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15841-9.

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Book chapters on the topic "Sensitivity Analysis"

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Borgonovo, Emanuele. "Decisions and Sensitivity Analysis." In Sensitivity Analysis, 1–7. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_1.

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Borgonovo, Emanuele. "What to Use and When." In Sensitivity Analysis, 89–91. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_10.

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Borgonovo, Emanuele. "Value of Information." In Sensitivity Analysis, 93–100. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_11.

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Borgonovo, Emanuele. "Local Sensitivity Analysis with Constraints." In Sensitivity Analysis, 101–13. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_12.

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Borgonovo, Emanuele. "Uncertainty Quantification." In Sensitivity Analysis, 117–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_13.

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Borgonovo, Emanuele. "Global Sensitivity Analysis." In Sensitivity Analysis, 129–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_14.

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Borgonovo, Emanuele. "Variance-Based Methods." In Sensitivity Analysis, 139–62. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_15.

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Borgonovo, Emanuele. "The $$\delta $$ —Importance Measure." In Sensitivity Analysis, 163–80. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_16.

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Borgonovo, Emanuele. "CDF-Based Sensitivity Measures." In Sensitivity Analysis, 181–89. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_17.

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Borgonovo, Emanuele. "Transformation Invariant Sensitivity Measures." In Sensitivity Analysis, 191–99. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_18.

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Conference papers on the topic "Sensitivity Analysis"

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Goldberg, Ken. "Sensitivity analysis." In the 14th annual ACM international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1180639.1180650.

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Wang, Lan-Wei, Fuqin Li, Imam Alam, David Jupp, Simon Oliver, and Medhavy Thankappan. "Analysis Ready Data Sensitivity Analyses." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8898667.

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Lisowski, J. "Game ship control sensitivity in collision situations." In RISK ANALYSIS 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/risk120311.

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Pagaldipti, Narayanan, and Aditi Chattopadhyay. "A discrete semi-analytical procedure for aerodynamic sensitivity analysis including grid sensitivity." In 5th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-4268.

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Adion J. Chinkuyu, Tom Meixner, Timothy J. Gish, and Craig S. Daughtry. "Sensitivity analysis of GLEAMS model using a multiobjective sensitivity analysis procedure." In 2003, Las Vegas, NV July 27-30, 2003. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2003. http://dx.doi.org/10.13031/2013.14004.

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WANG, BO. "Eigensolution sensitivity of discrete structures." In 4th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-4800.

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Fister, J. C., L. M. Davis, S. C. Jacobson, and J. M. Ramsey. "High Sensitivity Detection on Microchips." In Laser Applications to Chemical and Environmental Analysis. Washington, D.C.: Optica Publishing Group, 1996. http://dx.doi.org/10.1364/lacea.1996.lwd.6.

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High efficiency separations coupled with rapid response times have been demonstrated on capillary electrophoresis devices micromachined on glass substrates. [1-3] Although detection of single organic dyes has been achieved with fluorescence detection in capillaries, [4] such detection limits have not yet been demonstrated in micromachined channels. Efficient, single molecule detection is desirable for many potential applications such as rapid DNA sequencing. The structure of microfabricated separation channels, however, does not readily facilitate a 90° fluorescence excitation/collection geometry which has been used to achieve high sensitivities in capillaries. [4] This optical geometry allows efficient spatial rejection of scattering at the capillary solution interfaces. Confocal detection in which the excitation source is introduced through the collection optics provides a means of achieving both high axial resolution and high collection efficiency.
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Tune, Paul, and Matthew Roughan. "Network-design sensitivity analysis." In The 2014 ACM international conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2591971.2591979.

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Patel, Hiral, Vishveshvar Tendulkar, Himanshi Baid, Vikas Bhosale, and Gururaj Bhavikatti. "Gearshift Quality Sensitivity Analysis." In Symposium on International Automotive Technology 2019. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-26-0328.

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Vytyaz, Igor, David C. Lee, Pavan Kumar Hanumolu, Un-Ku Moon, and Kartikeya Mayaram. "Sensitivity analysis for oscillators." In 2007 IEEE/ACM International Conference on Computer-Aided Design. IEEE, 2007. http://dx.doi.org/10.1109/iccad.2007.4397307.

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Reports on the topic "Sensitivity Analysis"

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Lombardi, D. D2PC sensitivity analysis. Office of Scientific and Technical Information (OSTI), August 1992. http://dx.doi.org/10.2172/7271811.

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Van Buren, Rachel. Railcar Sensitivity Analysis. Fort Belvoir, VA: Defense Technical Information Center, November 2011. http://dx.doi.org/10.21236/ada565001.

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Lehoucq, Richard, Brian Franke, Stephen Bond, and Scott McKinley. Particle Sensitivity Analysis. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1669202.

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Lombardi, D. D2PC sensitivity analysis. Office of Scientific and Technical Information (OSTI), August 1992. http://dx.doi.org/10.2172/10174720.

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Harder, Matthew Steven. Sensitivity Analysis using Continuous Sensitivity Equation Method (CSE). Office of Scientific and Technical Information (OSTI), July 2018. http://dx.doi.org/10.2172/1463456.

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Cheng, J. J., C. Yu, and A. J. Zielen. RESRAD parameter sensitivity analysis. Office of Scientific and Technical Information (OSTI), August 1991. http://dx.doi.org/10.2172/6400651.

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Friedman-Hill, Ernest J., Edward L. Hoffman, Marcus J. Gibson, and Robert L. Clay. Integrated Sensitivity Analysis Workflow. Office of Scientific and Technical Information (OSTI), August 2014. http://dx.doi.org/10.2172/1171554.

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Horwedel, J. E., R. Q. Wright, and R. E. Maerker. Sensitivity analysis of EQ3. Office of Scientific and Technical Information (OSTI), January 1990. http://dx.doi.org/10.2172/7079359.

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Keiter, Eric R., Laura Painton Swiler, Thomas V. Russo, and Ian Zachary Wilcox. Sensitivity Analysis in Xyce. Office of Scientific and Technical Information (OSTI), September 2016. http://dx.doi.org/10.2172/1562422.

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Ralston-Hooper, Kimberly. Hanford Site Composite Analysis: Dose Sensitivity Analyses. Office of Scientific and Technical Information (OSTI), April 2022. http://dx.doi.org/10.2172/1861434.

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