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A showing that features of the two works are not similar does not bar a finding of substantial similarity, if such similarity as does exist clears the de minimis threshold. [3] The substantial similarity standard is used for all kinds of copyrighted subject matter: books, photographs, plays, music, software, etc. It may also cross media, as in ...
The intrinsic test would decide whether an "ordinary reasonable person" would consider there were substantial similarities in expression. A jury is well fitted to determine this. McDonald's character Mayor McCheese (left) and Sid and Marty Krofft's character H.R. Pufnstuf both are fictional mayors that possess disproportionately large round heads.
The Abstraction-Filtration-Comparison test (AFC) is a method of identifying substantial similarity for the purposes of applying copyright law. In particular, the AFC test is used to determine whether non-literal elements of a computer program have been copied by comparing the protectable elements of two programs.
The test statistic R is calculated in the following way: R = r B − r W M / 2 {\displaystyle R={\frac {r_{B}-r_{W}}{M/2}}} where r B is the average of rank similarities of pairs of samples (or replicates) originating from different sites, r W is the average of rank similarity of pairs among replicates within sites, and M = n ( n − 1)/2 where ...
A full scale X-43 wind tunnel test. The test is designed to have dynamic similitude with the real application to ensure valid results. Similitude is a concept applicable to the testing of engineering models. A model is said to have similitude with the real application if the two share geometric similarity, kinematic similarity and dynamic ...
A very simple equivalence testing approach is the ‘two one-sided t-tests’ (TOST) procedure. [11] In the TOST procedure an upper (Δ U) and lower (–Δ L) equivalence bound is specified based on the smallest effect size of interest (e.g., a positive or negative difference of d = 0.3).
Similarity measures play a crucial role in many clustering techniques, as they are used to determine how closely related two data points are and whether they should be grouped together in the same cluster. A similarity measure can take many different forms depending on the type of data being clustered and the specific problem being solved.
These events can be grouped into two main categories: Intrinsic Recognition and Extrinsic Recognition. [3] Intrinsic Recognition is when cells that are part of the same organism associate. [ 3 ] Extrinsic Recognition is when the cell of one organism recognizes a cell from another organism, like when a mammalian cell detects a microorganism in ...