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abstraction
(redirected from Data abstraction)

   Also found in: Dictionary/thesaurus, Legal, Encyclopedia, Wikipedia 0.01 sec.
abstraction /ab·strac·tion/ (ab-strak´shun)
1. the withdrawal of any ingredient from a compound.
2. malocclusion in which the occlusal plane is further from the eye-ear plane, causing lengthening of the face; cf. attraction (2).

ab·strac·tion (b-strkshn, b-)
n.
1. Distillation or separation of the volatile constituents of a substance.
2. Exclusive mental concentration; absent-mindedness.
3. A malocclusion in which the teeth or associated structures are lower than their normal occlusal plane.
4. The selection of a certain aspect of a concept from the whole.

abstraction
[abstrak′shən]
Etymology: L, abstrahere, to drag away
a condition in which teeth or other maxillary and mandibular structures are inferior to their normal position, away from the occlusal plane.

abstraction [ab-strak´shun]
1. the mental process of forming ideas that are theoretical or representational rather than concrete.
2. the withdrawal of any ingredient from a compound.
3. malocclusion in which the occlusal plane is farther from the eye-ear plane, causing lengthening of the face.

abstraction (abstrak´shn),
n teeth or other maxillary and mandibular structures that are inferior to (below) their normal position; away from the occlusal plane.


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By using design data abstraction for strategic planning and the global route engine for guidance and feedback, the user can converge on a successful interconnect solution far faster and more easily than ever before.
The specific tools discussed are the Geospatial Data Abstraction Library with OGR, a collection of application programming interfaces and command-line utilities for raster and vector data; OpenEV for desktop GIS and imagery analysis; UMN MapServer, which includes command-line tools to build CGI web applications; and PostGIS, an extension to the PostgreSQL database management system that allows the user to store and manipulate spatial data alongside tabular data.
Rather than attempting to sort concepts into conventional chapters, Dewhurst has come up with an innovative way to present his material in a list of over 60 "items" specific to individual issues or functions such as data abstraction, polymorphism, new cast operators, copy operators, when pointers are not really pointers, STL function objects, capability queries, array allocation, and templates of various stripes.
 
 
 
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