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Author: Grafiati

Published: 11 September 2023

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1

1939-, Fix George J., and Langley Research Center, eds. Least squares finite element simulation of transonic flows. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1986.

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2

Dilsavor, Ronald Louis. Analysis of modified SMI method for adaptive array weight control. Washington, DC: National Aeronautics and Space Administration, 1989.

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3

Kesoretskikh, Ivan, and Sergey Zotov. Landscape vulnerability: concept and assessment. ru: INFRA-M Academic Publishing LLC., 2019. http://dx.doi.org/10.12737/1045820.

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The monograph presents a methodology for assessing the vulnerability of landscapes to external influences. A comparative analysis of the concepts of "stability", "sensitivity", "vulnerability" in relation to natural complexes. An overview of existing methods for assessing the vulnerability of natural complexes is presented. The author's method of assessing the vulnerability of landscapes to anthropogenic impacts is described. The methodology is based on: selection and justification of criteria for assessing the vulnerability of landscapes; preparation of a parametric matrix and gradation of assessment criteria in accordance with the developed vulnerability classes; calculation of weighting factors of vulnerability assessment parameters; selection of optimal territorial operational unit for landscape vulnerability assessment. The method is implemented in the GIS environment "Assessment of vulnerability of landscapes of the Kaliningrad region to anthropogenic impacts", created by the authors using modern geoinformation products. The specificity of spatial differentiation of different landscapes in terms of vulnerability to anthropogenic impacts at the regional and local levels is revealed. It is stated that the use of the methodology for assessing the vulnerability of landscapes to anthropogenic impacts and its integration into the system of nature management will ensure a balanced account of geoecological features and environmental priorities in territorial planning. It is of interest to specialists in the field of rational nature management, environmental protection, spatial planning.

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4

Lerch, F. J. Optimum data weighting and error calibration for estimation of gravitational parameters. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1989.

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5

Zardari, Noorul Hassan, Kamal Ahmed, Sharif Moniruzzaman Shirazi, and Zulkifli Bin Yusop. Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12586-2.

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6

Oktay, Baysal, and United States. National Aeronautics and Space Administration., eds. Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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7

Oktay, Baysal, and United States. National Aeronautics and Space Administration., eds. Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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8

Branson, Nicola. Re-weighting the OHS and LFS national household survey data to create a consistent series over time: A cross entropy estimation approach. Cape Town: Southern Africa Labour and Development Research Unit, University of Cape Town, 2009.

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9

Christine, Bachrach, National Survey of Family Growth (U.S.), and National Center for Health Statistics (U.S.), eds. National survey of family growth, cycle III: Sample design, weighting, and variance estimation : this report describes the procedures used to select the sample. Hyattsville, Md: U.S. Dept. of Health and Human Services, Public Health Service, National Center for Health Statistics, 1985.

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10

Wright, A. G. Measurement of low light flux. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199565092.003.0007.

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There are three experimental methods for quantifying the flux of light incident on a photocathode: counting the anode output pulses initiated by photoelectrons—known as photon counting; measuring the DC current flowing at the anode—referred to as analogue detection, or charge integration; and determining the rms noise in the anode current—known as shot noise power detection. The statistical performances of the three methods, based on weighting factors, are compared, revealing the theoretical superiority of the photon-counting method. Optimal time allocation between signal and background measurement is derived for photon counting. An amplifier discriminator is the simplest and preferred instrumentation for photon counting, but setting the optimal counting threshold is ultimately a matter of judgement. This is because the plateau has a different slope for signal, background, and afterpulses. Rudiments of signal recovery instrumentation covering boxcar integrators, lock-in detection, and synchronous signal averaging are given.

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11

Chance, Kelly, and Randall V. Martin. Data Fitting. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199662104.003.0011.

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This chapter explores several of the most common and useful approaches to atmospheric data fitting as well as the process of using air mass factors to produce vertical atmospheric column abundances from line-of-sight slant columns determined by data fitting. An atmospheric spectrum or other type of atmospheric sounding is usually fitted to a parameterized physical model by minimizing a cost function, usually chi-squared. Linear fitting, when the model of the measurements is linear in the model parameters is described, followed by the more common nonlinear fitting case. For nonlinear fitting, the standard Levenberg-Marquardt method is described, followed by the use of optimal estimation, one of several retrieval methods that make use of a priori information to providing regularization for the solution. In the context of optimal estimation, weighting functions, contribution functions, and averaging kernels are described. The Twomey-Tikhonov regularization procedure is presented. Correlated parameters, with the important example of Earth’s atmospheric ozone, are discussed.

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12

Valliant, Richard, Frauke Kreuter, and Jill A. Dever. Practical Tools for Designing and Weighting Survey Samples. Springer London, Limited, 2013.

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13

Valliant, Richard, Frauke Kreuter, and Jill A. Dever. Practical Tools for Designing and Weighting Survey Samples. Springer New York, 2015.

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14

Valliant, Richard, Frauke Kreuter, and Jill A. Dever. Practical Tools for Designing and Weighting Survey Samples. Springer, 2018.

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15

Valliant, Richard, Frauke Kreuter, and Jill A. Dever. Practical Tools for Designing and Weighting Survey Samples. Springer, 2013.

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16

Practical Tools For Designing And Weighting Survey Samples. Springer-Verlag New York Inc., 2013.

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17

Zardari, Noorul Hassan, Kamal Ahmed, Sharif Moniruzzaman Shirazi, and Zulkifli Bin Yusop. Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management. Springer, 2014.

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18

Zardari, Noorul Hassan, Kamal Ahmed, Sharif Moniruzzaman Shirazi, and Zulkifli Bin Yusop. Weighting Methods and Their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management. Springer, 2015.

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19

Levin, Ines, and Betsy Sinclair. Causal Inference with Complex Survey Designs. Edited by Lonna Rae Atkeson and 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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20

National Survey of Family Growth, Cycle 6: Sample Design, Weighting, Imputation and Variance Estimation (Vital and Health Statistics). Dept. of Health and Human Services Centers fo, 2006.

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21

Makela, Susanna, Yajuan Si, and Andrew Gelman. Graphical Visualization of Polling Results. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.12.

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This chapter argues that it is wasteful to do a large, expensive poll and then just report a few percentages. Statistical modeling allows researchers to make the most effective use of available data, and graphs make it possible to convey more information more directly, both to general audiences and to specialists. Graphs are an invaluable tool at each step of the modeling process: exploring raw data, building and refining the model, and understanding and communicating the results are all made easier with graphs. In addition, graphical methods can be useful to survey researchers to understand weighting and other aspects of survey construction and analysis. The chapter includes several examples.

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22

Streiner, David L., Geoffrey R. Norman, and John Cairney. From items to scales. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199685219.003.0007.

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This chapter discusses various issues that are involved in combining individual items to form a single scale. The topics covered include whether or not to weight the each of the items to reflect its supposed importance. Another consideration is whether items should be weighted differently for each person based on their salience or importance to that individual. Related to this is ‘implicit’ weighting, where various subscales of an instrument have differing numbers of items. The chapter then discusses various ways of transforming the final score in order to normalize them. Finally, it describes different methods of setting cut points based on the distribution and expert judgement.

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23

Stegenga, Jacob. Assessing Medical Evidence. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198747048.003.0007.

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Medical scientists employ ‘quality assessment tools’ to assess evidence from medical research, especially from randomized trials. These tools are designed to take into account methodological details of studies, including randomization, subject allocation concealment, and other features of studies deemed relevant to minimizing bias. There are dozens of such tools available. They differ widely from each other, and empirical studies show that they have low inter-rater reliability and low inter-tool reliability. This is an instance of a more general problem called here the underdetermination of evidential significance. Disagreements about the quality of evidence can be due to different—but in principle equally good—weightings of the methodological features that constitute quality assessment tools. Thus, the malleability of empirical research in medicine is deep: in addition to the malleability of first-order empirical methods, such as randomized trials, there is malleability in the tools used to evaluate first-order methods.

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24

Aderinto, Saheed. The Sexual Scourge of Imperial Order. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252038884.003.0005.

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This chapter argues that sex had broader implications for the future of the British Empire, while also showing that the generalization that women were the moral scourge of the empire whose sexuality needed to be curtailed must be qualified. The African rank-and-file of the colonial army, like women, became another demographic whose sexuality was treated as dangerous. Indeed, the colonialists' perception of the effect of sexual savagery and their methods of dealing with it were class specific and were constantly in a state of flux. This disequilibrium to a large extent was based on the weighting of the medical consequences of gonorrhea and syphilis against other communicable diseases like influenza. The chapter then shows that the medicalization of sex reflected the quest by colonial medics to appropriate the panic over prostitution as a means of repositioning themselves as a vital tool of civilization.

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25

Allen, P. T., and T. R. Lee. Derivation of Weighting Factors for Cost and Radiological Impact for Use in Comparison of Waste Management Methods: Nuclear Science and Technology: Nuclear Science and Technology [series]. European Communities / Union (EUR-OP/OOPEC/OPOCE), 1991.

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