Sentence examples for input with many from inspiring English sources

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Identity cards have been delayed again because of a mix-up with the Indian company hired for data input, with many Albanian names simply spelled wrong.

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Moreover, since the neocortex is apparently responsible for more complex information processing than the rest of the brain, and because RANC outputs with more inputs convey more information than those with few inputs, RANCs with many inputs may be expected to be more abundant than RANCs with few inputs.

Using the minimum path coverage of the input graph as a basis for the subsequent table generation corresponds to finding a maximally compact tabular representation of the original graph, a highly desirable feature, especially for the case of complex input workflows with many pooling and splitting operations.

This multiplexed technology can simultaneously determine expression levels of multiple targets in less than 2 h using sample inputs compatible with many basic science and clinical detection applications.

It can handle data sets with large numbers of input variables, each with many possible values; identify significant high-order interactions among variables; detect and quantify non-linear relations; determine which predictors can be dropped because they contain redundant information; and handle missing values through a process of "surrogate substitution".

(E ) Horizontal optical section showing a typical distribution of inputs in the ventral striatum, with many input neurons in tight clusters.

Today we have a great team driving our performance with input at many levels and with junior people contributing significant ideas.

This implies that for most genes with many inputs, almost all their input TFs have similar effects in the expression level (either almost all being repressors or almost all being activators).

The model's software is built in such a way that, depending on the resolution of the input data, large-scale (single plots or farms) or small-scale (larger areas with many input datasets) yield predictions can be generated very easily.

As BP neural network can simultaneously deal with many input features, instead of dealing with single feature, interdependence between input features is taken into consideration.

This can be accomplished either by several RANCs that have input from a few sensor types or by a few RANCs with many inputs.

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