Introduction to Level Enhancement
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Level Enhancement sentence examples within Ground Level Enhancement
By using CRaTER data, we identify the lunar CR enhancements, which are similar to the terrestrial ground level enhancements (GLEs).
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High-energy SEPs can sometimes be energetic enough to penetrate all the way down to the surface of the Earth and thus be recorded on the ground as ground level enhancements (GLEs).
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We sought to develop a framework for system-level enhancements to care transitions for older adults.
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We give two numerical examples to validate the proposed models and demonstrate the service-level enhancement under the collaborative supply-chain management in case of an unreliable seller.
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In particular, the partially occulted solar event on 10 September triggered a ground-level enhancement (GLE), the second GLE of cycle 24.
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In some cases, and especially when Earth crosses the HCS sector, a fraction of these particles can reach Earth with a harder energetic particle flux, triggering a ground-level enhancement (GLE).
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We present an overview of the ground-level enhancement (GLE 72) of the cosmic-ray intensity associated with the recent powerful solar flare SOL2017-09-10 (X-ray class X8.
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Moreover, we found that motion VPL is specific to the trained stimulus direction, speed, size, and contrast, diminishing the possibility of non-sensory decision-level enhancements.
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Therefore, we develop a system for nowcasting and forecasting the galactic cosmic ray (GCR) and solar energetic particle (SEP) fluxes at any location in the magnetosphere and ionosphere during ground-level enhancement (GLE) events.
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With the goal of understanding the initiations of solar energetic particle (SEP) (MeV) and ground-level enhancement (GLE) (GeV) particles, we have studied relative timings at?approximately?the Sun between temporal evolutions of the particles and some electromagnetic radiation components representing flares and shocks.
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And thus, we design the "In-Edge AI" framework in order to intelligently utilize the collaboration among devices and edge nodes to exchange the learning parameters for a better training and inference of the models, and thus to carry out dynamic system-level optimization and application-level enhancement while reducing the unnecessary system communication load.
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Patients with high-level enhancement (>68.
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