Sentence examples for classification infrastructure from inspiring English sources

Because innovative industries are often not part of the classification infrastructure, they are invisible in empirical analyses and in government statistics.

Understanding of structural change is compromised because scholars do not clearly articulate the limits of the classification infrastructure (NAICS or GICS) that shapes empirical analysis.

Typical application areas include environment monitoring, community healthcare, surveys with embedded geotagged photos [5], traffic monitoring and transportation planning, garbage classification, infrastructure management, disaster management, public safety and so on [1, 6, 7].

Road data enables GIS applications to facilitate a variety of services which include satellite navigation, route planning, health-care accessibility planning, land cover classification, and infrastructure management.

Bicycle level of traffic stress is a new system of bicycle infrastructure classification for cities that cannot afford existing alternatives such as bicycle level of service which is more data-intensive.

Site observations were made to document characteristics of injury and control sites, and allow route infrastructure classification.

Using the database information, multiple data checks and supplements were applied as well as classifications of the infrastructure improvements and of the sites treated were carried out, in order to define the types of infrastructure improvements suitable for safety evaluation.

Biological classification constitutes the core infrastructure of biological databases (Patterson et al. 2010, 2014).

Deborah McGuinness, the Tetherless World Senior Constellation Professor at Rensselaer Polytechnic Institute, will build the ontological classification systems and the infrastructure behind them, allowing different types of queries and tools to be built more readily into the platform.

Although individually meaningless, these records fit together to form a huge mathematical structure called a directed multigraph, which represents the interconnectedness of the 300m phone numbers known to AT&T's computers.Careful analysis of this information could help with infrastructure planning, customer classification and marketing.

We found that the AERS outcome codes used to record serious patient outcomes in the AERS reporting data correspond well to the CTCAE Grades 3 to 5. Semantic Web OWL rendering of the DDI-ADE dataset provides seamless integration with the CTCAE itself, enabling a standard infrastructure for automatic classification of ADEs based on the severity conditions specified in the CTCAE.