Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
The <span>element located on the top left of the Word screen is the Quick Access Toolbar. </span>On the quick access toolbar, you can find some of the common functions that you will need to use on a regular basis, it contains commands that are used most often, for example Redo, Undo and Save etc.
Technology can create or dimish occupations.
Technology can also make the job easier
there are many differences, but the most prominent are that they have different apis (aplication programing interface) and different architecture
also mobile apps tend to use less system resources and are more regulated by services like the google play store, opposed to the fairly unregulated uwp platform used by most windows machines.
ETHERNETis considered to be a dominant protocol for local area networking.
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