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1

Center, Langley Research, ed. Simulated dynamic response of a multi-stage compressor with variable molecular weight flow medium. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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2

Schwenzfeger, K. J. Comparison of ERS-1 scatterometer Monte Carlo performance simulations using a weighted nonlinear least-squares and a maximum likelihood estimation method. Neubiberg: Hochschule der Bundeswehr München, 1985.

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3

Micheline, Frenette, Gard Barbara, Educational Technology Center (Cambridge, Mass.) y National Institute of Education (U.S.), eds. Weight, density and matter: A study of elementary children's reasoning about density with concrete materials and computer analogs. Cambridge, MA: Educational Technology Center, Harvard Graduate School of Education, 1985.

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4

Bitter, Rick. LabVIEW advanced programming techniques. Boca Raton, Fla: CRC Press, 2000.

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5

Taqi, Mohiuddin y Nawrocki Matt, eds. LabVIEW advanced programming techniques. Boca Raton, FL: CRC Press, 2001.

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6

Taqi, Mohiuddin y Nawrocki Matt, eds. LabView advanced programming techniques. 2a ed. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2007.

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7

Allen, Michael P. y Dominic J. Tildesley. Advanced Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0009.

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This chapter describes the ways in which the Monte Carlo importance sampling method may be adapted to improve the calculation of ensemble averages, particularly those associated with free energy differences. These approaches include umbrella sampling, non-Boltzmann sampling, the Wang–Landau method, and nested sampling. In addition, a range of special techniques have been developed to accelerate the simulation of flexible molecules, such as polymers. These approaches are illustrated with scientific examples and program code. The chapter also explains the analysis of such simulations using techniques such as weighted histograms, and acceptance ratio calculations. Practical advice on selection of methods, parameters, and the direction in which to make comparisons, are given. Monte Carlo methods for modelling phase equilibria and chemical reactions at equilibrium are described.
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8

Allen, Michael P. y Dominic J. Tildesley. Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0004.

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The estimation of integrals by Monte Carlo sampling is introduced through a simple example. The chapter then explains importance sampling, and the use of the Metropolis and Barker forms of the transition matrix defined in terms of the underlying matrix of the Markov chain. The creation of an appropriately weighted set of states in the canonical ensemble is described in detail and the method is extended to the isothermal–isobaric, grand canonical and semi-grand ensembles. The Monte Carlo simulation of molecular fluids and fluids containing flexible molecules using a reptation algorithm is discussed. The parallel tempering or replica exchange method for more efficient exploration of the phase space is introduced, and recent advances including solute tempering and convective replica exchange algorithms are described.
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9

Levin, Ines y Betsy Sinclair. Causal Inference with Complex Survey Designs. Editado por Lonna Rae Atkeson y R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.4.

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This article discusses methods that combine survey weighting and propensity score matching to estimate population average treatment effects. Beginning with an overview of causal inference techniques that incorporate data from complex surveys and the usefulness of survey weights, it then considers approaches for incorporating survey weights into three matching algorithms, along with their respective methodologies: nearest-neighbor matching, subclassification matching, and propensity score weighting. It also presents the results of a Monte Carlo simulation study that illustrates the benefits of incorporating survey weights into propensity score matching procedures, as well as the problems that arise when survey weights are ignored. Finally, it explores the differences between population-based inferences and sample-based inferences using real-world data from the 2012 panel of The American Panel Survey (TAPS). The article highlights the impact of social media usage on political participation, when such impact is not actually apparent in the target population.
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10

Simulated dynamic response of a multi-stage compressor with variable molecular weight flow medium. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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11

Value-Focused Thinking in the Presence of Weight Ambiguity: A Solution Technique Using Monte Carlo Simulation. Storming Media, 2004.

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12

(Editor), Zoltan Füzessy, Werner Jüptner (Editor) y Wolfgang Osten (Editor), eds. Simulation and Experiment in Laser Metrology: Proceedings of the International Symposium on Laser Applications in Precision Measurements held in Balatonfüred/Hungary, ... 3-6, 1996 (AKV Series in Optical Metrology). Wiley-VCH, 1996.

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13

Krasnopolskaia, Iuliia. Design and Parametric Modeling of Pretensioned and Stiffened Membranes Project Work. Technische Universität Dresden, 2021. http://dx.doi.org/10.25368/2022.407.

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This research aimed to develop conceptually the pretensioned and stiffened membrane structures, using an experimental approach and computer simulation. The physical method of form finding included the pretensioned fabric with the glued grid made of the wooden sticks. Relaxation of the stressed membrane contributed to forming the specific anticlastic hyparic surface by energy release. The influence of the rigid elements pattern, intensity and direction of pretensioning on the final shape was investigated. The tensegrity structures were also built applying the same form finding way. These experiments led to the modelling of resulting samples with parametric design tools, namely Rhino and Grasshopper. Optimization of the final shape was carried out by changing parameters such as stiffenings configuration and membrane strength. This digital approach demonstrated successful simulation and rationalization of considered structures. Moreover, the final models can be used for further structural analysis and BIM. Considered membrane structures have very efficient load-bearing behavior. They are characterized by small weight, high light transmission and the ability to create large usable spaces free from columns. The most dangerous loads for membrane structures are wind and ponding. In practice, PTFE coated glass-fibre fabric and PVC coated polyester fabric are most suitable for pretensioned and stiffened membrane structures. The role of stiff elements can be played by steel profiles or metal tubes. The average time for the construction of a membrane structure is 6-15 months. Resulted pretensioned and stiffened membrane structures can be used as pavilions, roofs and awnings. They are distinguished by spectacular architectural view and very effective structural system. In addition, membrane tensile structures are characterized by high eco-efficiency and sustainability compared to other types of construction.
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14

Spuybroek, Lars y Bob Lang. The Weight of the Image : Teaching Design and Computing in Architecture. NAi Publishers, 2001.

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15

Bitter, Rick, Taqi Mohiuddin y Matt Nawrocki. LabVIEW Advanced Programming Techniques. Taylor & Francis Group, 2000.

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16

Bitter, Rick, Taqi Mohiuddin y Matthew R. Nawrocki. LabVIEW. CRC, 2000.

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