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In this study, the performance of a continuous microwave drying system using a traveling wave applicator was investigated with respect to moisture reduction, power consumption, and overall efficiency.
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Up to 77% reduction in area and 73% reduction in power consumption of the program memory and the associated control logic were obtained.
The reduction of power consumption does not necessarily lead to a reduction of the amount of energy consumed.
As a result of this study, a 95% reduction of memory utilization and a 96% reduction of power consumption of the wireless sensor nodes have been achieved as compared with traditional approaches.
This reduction of redundant packets in turn results in the reduction of power consumption in the individual nodes.
The latest generation has a 94% reduction in power consumption (from 71to4.2.2 mW) and an 82.5% reduction of the propagation delay (from 238 to 42 ps) compared to the first generation design.
The proposed approach is efficient and verified on ISCAS 89 & 85 benchmark circuits; the results indicate a considerable reduction in the test data volume and thus a significant reduction in power consumption.
Simulation of a case study circuit shows a reduction of digital activity by a factor seven, and a significant reduction of power consumption.
The previous tests show that conditional observation can achieve a significant gain in terms of the reduction of the number of transmitted packet and subsequently of the reduction in power consumption of constrained devices.
For the previously found optimal values of δ = 5 and Θ = 8, the reduction in the amount of blocks processed was 67%, leading to an overall 51% reduction in power consumption at a minimal impact in PSNR.
In approximate computing, reducing the precision of arithmetic blocks leads to reduction in power consumption.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com