Sentence examples for strongly separated from inspiring English sources

Also, it is visible that energy E c is always strongly separated from energies E a and E н.

The Musket Ball Cluster's dark matter, the hot gas, and the individual galaxies are strongly separated from each other because they behave differently during a cluster collision.

Classical Computational Fluid Dynamics (CFD) of long-time processes with strongly separated time scales is computationally extremely demanding if not impossible.

This paper describes the architecture of PsycoTrace, which exploits virtualization to introduce two virtual machines, the monitored and the monitoring virtual machines, to increase both the robustness and the transparency of the monitoring because the machine that implements all the checks is strongly separated from the monitored one.

We study the load balancing problem in a dense wireless multihop network, where a typical path consists of a large number of hops, that is, the spatial scales of a typical distance between source and destination and mean distance between the neighboring nodes are strongly separated.

Ant species composition was strongly separated between spring (September) and summer (December) (R  =  0.796), but temporal turnover was also evident between autumn (March) and summer (December) (R  =  0.685) (Fig. 2E).

The reason is that the geometric models employed in those methods can strongly separate the foreground and background regions.

Use of CAP provided further evidence of the importance of rainfall, strongly separating the three groups (P = 0.0048; see Fig. 2).

We present a framework that integrates an initial attestation and a continuous node monitoring that strongly separates the software of a node from the attestation system by running them in two virtual machines (VMs).

Statistical analysis of measurements of the skulls and teeth strongly separates S. durrelli from specimens of the brown-tailed mongoose.

The model's staging system strongly separates cognitively normal and Alzheimer's disease subjects (maximum classification accuracy of 99%), and predicts conversion from mild cognitive impairment to Alzheimer's disease (maximum balanced accuracy of 77% over 3 years), and from cognitively normal to mild cognitive impairment (maximum balanced accuracy of 76% over 5 years).