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Acronymfinder

What does VD stand for?

VD stands for Vertical Distance (airdrop computations)


This definition appears very rarely and is found in the following Acronym Finder categories:

  • Military and Government

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Other Resources:
We have 18 other definitions for VD in our Acronym Attic

Samples in periodicals archive:

Figure 6 shows the measurements taken by varying the vertical distance (Z-axis) from 50 mm lo 300 mm at every increment of 50 mm.
The group intends to walk four to five hours a day, starting at 700m and walking a vertical distance of between 1,000m and 1,200m a day, to cover about 15km a day.
In four experiments aimed at finding "an ideal facial feature arrangement," US and Canadian researchers asked students to compare color photographs of the same woman's face, in which the vertical distance between the eyes and mouth, and horizontal distance between the eyes, had been doctored using Photoshop.
First distance-based method Distance map: * A distance value for each pixel; * If p is a white pixel, the distance value equals the number of pixels between the closest two black pixels on a specified direction; * If p is a black pixel, the distance value is 0; Types of distance maps: * Horizontal distance map (the horizontal direction is considered when searching for the closest two black pixels); * Vertical distance map (the vertical direction is considered when searching for the closest two black pixels); * Arbitrary direction distance map; Combining two or more distance maps: * Very restrictive: * Final map = min(map0, map1, .
2 How to find the separators--The distances approach Distance map: * A distance value for each pixel; * If p is a white pixel, the distance value equals the number of pixels between the closest two black pixels on a specified direction; * If p is a black pixel, the distance value is 0; Types of distance maps: * Horizontal distance map (the horizontal direction is considered when searching for the closest two black pixels); * Vertical distance map (the vertical direction is considered when searching for the closest two black pixels); * Arbitrary direction distance map; Combining two or more distance maps: * Very restrictive: ** Final map = min(map0, map1, mapN); * Less restrictive: ** Final map = max(map0, map1, .
1] the cyclical budget deficit (and the actual deficit) has increased and is now equal to the vertical distance BD.