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IQP technique provides exact solution but is applicable to only small size systems, while CG is applicable to systems with large sizes but has rounding approximation.
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Optimization results in an IQP that can only be solved for systems with small sizes, then we show application of the CG technique that enables solution of systems with larger sizes.
IQP can only be solved for very small size systems, however, we have been able to decompose IQP to master and pricing sub-problems which may be solved through column generation technique for systems with larger sizes.
It is expected that the storage density of the EPCM would be even greater for plant size TES systems with larger size capsules, without the penalties associated with the limited scale used here.
We determined that the likelihood ratio method is appropriate for estimating gradients at short (transient) times or for systems with small population sizes, whereas finite differencing is better-suited for gradient estimation at long times (steady state) or for systems with large population sizes.
Such results with CSI imperfection due to delay only help to understand the performance of FDD systems with large codebook sizes and TDD systems where limited feedback may not be necessary.
Recurrent selective sweeps have been repeatedly suggested to determine coevolutionary dynamics for parasite or host systems with large population sizes such as bacterial hosts or microbial parasites, where novel mutations are frequent and often directly exposed to selection because of a haploid genetic system.
We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system size.
This advantage becomes more noticeable in OFDMA systems with large FFT size such as 1024-OFDMA 2048-ODMADMA.
A discrete element sample cannot account for all discrete particles contained in the system and therefore ''scaled-up'' elements with larger sizes have to be used to reduce the size of the discrete element model to a reasonable level for the available computer resources.
Furthermore the particle size distribution is important for the system design, because limestone with larger size needs significantly higher residence time in the calcination zone for full conversion.
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