Plural values contribute to multiple arrays of expressed preferences.
Convolutional neural networks (CNNs) are designed to process data that come in the form of multiple arrays.
The low cross-correlation also permits the embedding of multiple arrays in the same media, to increase data payload.
Here, an autonomous fabrication of suspended graphene is proposed where it only requires a single transfer which yields multiple arrays of micron-scale suspended graphenes all at once.
More recently, Shen et al. [12] realized a hyperlens utilizing multiple arrays of clamped thin plates similar to membranes with the negative mass density, yielding a hyperbolic dispersion.
The next stage of seismic array observation at volcanoes, then, would use multiple arrays and a 3D velocity structure for the array analysis.
Such families of arrays are ideal for watermarking, where multiple arrays are embedded in the host media, for higher data payload, increased security or lower perceptibility.
Additionally, because of their low cross-correlation, multiple arrays can be embedded in the same frame, to increase the data payload.
A second application is to encrypt information within any digital data by encoding multiple arrays within a local region of the data.
Devices with multiple arrays have shown good specificity (92%), agreement (92%) and sensitivity (87%) for the detection of wheelchair propulsion in observational studies [57].
Due to connectivity in tidal flow it has been hypothesized that the cumulative impact of multiple arrays on sediment dynamics might be non-linear.
