Sentence examples for sparse low from inspiring English sources

Dispersion of sparse (low solids content) agglomerates by hydrodynamic shear is addressed both experimentally and theoretically.

Sparse low rank tensor approximation method is used to significantly improve the online computation efficiency when the number of separated terms is large.

While the proposed objective function allows a sparse low rank solution for both linear and non-linear relationships between the input and response matrices, other similar methods in this case are only based on a linear model.

Maintaining and creating optimal suitable habitats for SP characterized by sparse low vegetation in the foredunes areas, and uneven/low-slope beach surfaces, is the proposed conservation scenario to convert anthropic beach restorations and SP populations into a positive feedback without impacting other threatened shorebird species.

When the ZnO seed-layer was dipped in the 2-mL growth medium and soaked for 2 h at room temperature (approx. 25°C), a relatively sparse, low dimension, and poorly alignment ZnO nanorods were synthesized, with an average length of 170 nm (Figure 3a).

Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface.

Dense old-growth forest or vigorous second-growth stands with closed canopies generally have sparse, low-quality forage.

Inner restricted-shelf deposits were characterized by sparse low-diversity communities that tended to be highly endemic (confined to a particular region).

To face this intrinsically difficult problem, we propose a novel generative model, where biclustering is approached from a sparse low-rank matrix factorization perspective.

Compared to radars, whose echo coverage is generally sparse, low-altitude satellite observations can provide density, velocity and precipitation across the polar cap along their track.

Motivated by the fact that the brain is organized with modular structures, in this paper, we propose a novel functional brain network modeling scheme by encoding a modularity prior under a matrix-regularized network learning framework, and further formulate it as a sparse low-rank graph learning problem, which can be solved by an efficient optimization algorithm.