Sentence examples for benchmarks which show from inspiring English sources

The migration has been verified by a set of benchmarks which show high scalability, from which we present the Telescope problem in this paper.

Simulation results are performed on ESESC tool and the SPEC2006 benchmarks which show 47.1% improvement in lifetime reliability of the system as well as 11.22% and 13.57% enhancement in temperature and power consumption compared to the base schedule.

Our first experiment demonstrates that the performance of our method achieves state-of-the-art performance on four public dataset benchmarks, which shows that our method has competitive performance.

We also compare the proposed model with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

The proposed model has been compared with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

We evaluate and compare the models by widely used benchmark tests, which show the third-order convergence rate for all models, and the numerical results are competitive to other exiting models.

Additionally, simulations and comparisons based on PFSSP benchmarks are carried out, which show that our algorithm is both effective and efficient.

Salesforce.com is releasing what it calls The Facebook Ads Benchmark Report, which shows how Facebook ads performed on Salesforce's social advertising service Social.com.

Extensive experiments and comparisons have been done based on the CEC2005 and CEC2014 benchmark suit, which shows that the overall performance of EDEV is superior to several state-of-the-art peer DE variants.

The proposed GAFAT is first tested based on the 13 widely used benchmark functions, which shows that GAFAT is of better or competitive performances when compared with six existing algorithms.

State-of-the-art results namely 94.28%, 98.21% and 95.37% are achieved on three public benchmark datasets: MSRAction3D, MSRGesture3D and SKIG, which show the efficiency of proposed method to capture structural depth information.