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Our implementation shows that the overhead incurred to implement UPS is very low, and little or no modification is required to adapt existing protocols to the UPS framework.
Our implementation shows that the algorithms are practical and realistic choices for a wide variety of update scenarios.
Actual implementation shows that the intelligent diagnosis model is capable of integrating CART and CBR techniques to examine liver diseases with considerable accuracy.
The system implementation shows that the proposed people-centric sensing system is efficient and cost-effective in health and emergency care.
Results of FPGA-based implementation shows that the hardware can process about 6000 images of size 512×512 per second which is much higher than the video rate of 30 frames per second.
The performance of the DSP implementation shows that the proposed algorithm can practically visualize the final 3D color video sequence in real-time mode.
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The algorithm has been simulated (and verified) using C. Results of hardware implementation show that the design operates at high speed requiring only small space.
The result of the model implementation showed that the compatibility of WGT activities was 80%, the practicability of the model principles was 79.63%, and the independence of WGT was 96.56%.
PRIs evaluation after improvement project implementation showed that the risk associated with these phases decreased significantly following the application of procedures and controls defined in improvement projects, resulting in a reduction of the PRIs between 43% and 100%.
A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images.
The comparison of the results for a subsample of galaxies with smooth particle hydrodynamic (SPH) simulations with chemo-photometric implementation, shows that in most cases the estimated stellar masses obtained with the two different approaches are in good agreement.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com