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The membership function expressions corresponding to the levels 'very poor', 'poor', 'qualified', 'good' and 'excellent' are shown successively in (8)–(12).
High levels of recognition are possible even when those dots are shown for a very brief period of time, when only a sparse sampling of the dots is displayed, and when the dots are shown successively, each for a very brief interval.
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The spacing was expected to produce approximately 75% success in recognition if all dots in the display set were shown successively with a duration of 0.1 ms, and with offset of one dot being followed immediately by onset of the next.
For each experiment the shapes were shown successively, allowing ample time for the subject to provide a name that was judged to be correct or not.
For each condition, a compilation of the concerning videos is made, so that the videos can easily be shown successively.
When the dots were shown successively, recognition declined as a function of the total time that was required to display the dots, and the decline appeared to be approximately linear for each of the shapes.
Previous research from this laboratory has found that one can replace the outer boundary of an object with a spaced set of dots, each being shown successively for only a tenth of a millisecond, and subjects can still name the object at a level that is far above chance [ 2, 3].
Reconstructed phase images from two successively recorded low dose-rate image series are shown in Fig. 4a, b.
The results are shown for an initial population of 1 million, which is successively reduced by excluding those ineligible on the basis of risk, and by noncompliance.
In the latter case, the pores of the wet cellulose fibers have been shown to shrink successively as the moisture content is decreased (an irreversible phenomenon termed 'hornification' [ 21]), resulting in smaller pore sizes and narrowed pore size distribution [ 22], which make the material less susceptible to enzymatic hydrolysis [ 20].
The use of SEM and CEM algorithms successively was shown to avoid sub-optimal solutions [ 17]; this is because the random part of the SEM algorithm avoids being trapped in a local maximum.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com