These newer applications are driven by the need for greater reliability or electrical efficiency to justify the increase in cost.
In wireless communication systems, the most conventional performance metrics focus on the quantification of either link reliability or spectral efficiency [5 8].
Experiments demonstrate that our enhanced scheme can save transmission energy up to 50% over directed diffusion, without any reliability or delivery efficiency being compromised.
In recent years there has been a growing interest in hardware neural networks, which express many benefits over conventional software models, mainly in applications where speed, cost, reliability, or energy efficiency are of great importance.
Objectives of this optimization are for example product quality, raw material and investment cost, energy efficiency, reliability or health, safety, and environmental issues.
Today, unit commitment (UC) models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that has a large penetration of variable renewable resources.
The possibility of manipulating such factors to improve YST efficiency and reliability or of interpreting whitefly catches in YSTs with automated tools is discussed.
A good data structure is vital to the reliability and efficiency of a program or software.
Stability, reliability, and efficiency are important because they make the operation robust to temporary disconnections or high packet loss.
Such devices have found wide application because of their compactness, reliability, power efficiency, and low cost.
