Sentence examples for most implementations are from inspiring English sources

Most implementations are in STEM departments, the majority of which are in institutions that award graduate degrees in their discipline.

More recently, CNNs have been used for end-to-end discriminative text classification tasks involving the identification of high-level concepts prevalent throughout an entire document; however, most implementations are built on top of existing feature engineering and extraction methodologies.

Unfortunately, the use of these concepts is not widespread as most implementations are proofs of concept and fall short with respect to the integration with standard software development tools and processes.

Most of the proposed models [3] [14] employ a control mechanism of cellular growth via artificial gene regulatory networks (GRNs) that abstract biological gene regulatory networks using discrete or continuous formulations, and most implementations are unique.

In count models, most implementations are specified according to models considered by Zeger and Qaqish.

However, most implementations are single level, ignoring the hierarchical data structure of CRTs.

Most implementations were at, or near, newly drilled community-supply boreholes; hence, amelioration of prevalent stagnant ponds elsewhere remains a concern.

The standard choice, used in most implementations, is then the lexicographical ordering.

The two most common implementations are Bonjour [30] from Apple and Avahi [31].

Some modules are used by most implementations and are considered part of the main OpenMRS system, while others are very specific to particular projects.

Differentiated Services architecture (Diffserv) is the most widely deployed IP QOS architecture and hence most router QOS implementations are optimized for Diffserv deployments.