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  2. Best–worst scaling - Wikipedia

    en.wikipedia.org/wiki/Best–worst_scaling

    Best–worst scaling (BWS) [1] techniques involve choice modelling (or discrete choice experiment – "DCE") and were invented by Jordan Louviere in 1987 while on the faculty at the University of Alberta. In general with BWS, survey respondents are shown a subset of items from a master list and are asked to indicate the best and worst items (or ...

  3. Scaling (geometry) - Wikipedia

    en.wikipedia.org/wiki/Scaling_(geometry)

    In uniform scaling with a non-zero scale factor, all non-zero vectors retain their direction (as seen from the origin), or all have the direction reversed, depending on the sign of the scaling factor. In non-uniform scaling only the vectors that belong to an eigenspace will retain their direction. A vector that is the sum of two or more non ...

  4. Nonuniform sampling - Wikipedia

    en.wikipedia.org/wiki/Nonuniform_sampling

    The sampling theory of Shannon can be generalized for the case of nonuniform samples, that is, samples not taken equally spaced in time. The Shannon sampling theory for non-uniform sampling states that a band-limited signal can be perfectly reconstructed from its samples if the average sampling rate satisfies the Nyquist condition. [1]

  5. List of semiconductor scale examples - Wikipedia

    en.wikipedia.org/wiki/List_of_semiconductor...

    Listed are many semiconductor scale examples for various metal–oxide–semiconductor field-effect transistor (MOSFET, or MOS transistor) semiconductor manufacturing process nodes. Timeline of MOSFET demonstrations

  6. Multidimensional scaling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_scaling

    An extension of metric multidimensional scaling, in which the target space is an arbitrary smooth non-Euclidean space. In cases where the dissimilarities are distances on a surface and the target space is another surface, GMDS allows finding the minimum-distortion embedding of one surface into another. [5]

  7. Stochastic universal sampling - Wikipedia

    en.wikipedia.org/wiki/Stochastic_universal_sampling

    SUS example. Stochastic universal sampling (SUS) is a selection technique used in evolutionary algorithms for selecting potentially useful solutions for recombination. It was introduced by James Baker. [1] SUS is a development of fitness proportionate selection (FPS) which exhibits no bias and minimal spread.

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  9. Non-dimensionalization and scaling of the Navier–Stokes ...

    en.wikipedia.org/wiki/Non-dimensionalization_and...

    In fluid mechanics, non-dimensionalization of the Navier–Stokes equations is the conversion of the Navier–Stokes equation to a nondimensional form. This technique can ease the analysis of the problem at hand, and reduce the number of free parameters. Small or large sizes of certain dimensionless parameters indicate the importance of certain ...