Sentence examples for computing that may from inspiring English sources

There are a few pockets of Web companies and social computing that may be exceptions.

And when that proves no longer possible, there are new, exotic approaches to computing that may ride to the rescue.The quick switchChipmakers are struggling with both physics and economics.

You type "w" - it computes that you may want "weather" because that's what most people look for when they type "w", and using Google Instant you can actually see the weather forecast without having to finish typing the query.

Neural networks have sometimes been discussed as computing systems that may go beyond Turing-computability (e.g., Smolensky 1988, 3).

Here is a cloud computing feature that may seem a bit odd at first but that does actually have its uses.

Inasmuch as sterilization of women needs somewhat more time, it may be computed that the entire female population of Germany could be sterilized within a period of three years or less.

A science writer and veteran explainer communicates some of the propositions offered by theorists about the virtually unlimited computing power that may follow certain practical triumphs that are not quite in sight.

There has been a growing interest by commercial organisations in providing portable, trusted and secure computing platforms that may be used in the scenarios such as those outlined in the Introduction section.

However, in order to analyze multi-Terabyte EHR databases in cloud, the BDA part in the present system may opt existing significant distributed architecture Hadoop based on programming models like MapReduce, NoSQL, etc., or some new designed approaches based on High Performance Computing (HPC) that may touch most or all of the data.

Thus, the use of classical decision analysis to effect integrative translational research seems unlikely at worst, and challenging at best (but see [ 7] Leal et al., 2007 for a practical computing resource that may yield possible exceptions).

Tissue and organ electrophysiological modelling still requires significant computing power that may not be easily available for routine work [although improvements in hardware and model implementation have reduced this overhead very significantly in recent years (Niederer et al., 2011b)].