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A Diceware word list is any list of 6 5 = 7 776 unique words, preferably ones the user will find easy to spell and to remember. The contents of the word list do not have to be protected or concealed in any way, as the security of a Diceware passphrase is in the number of words selected, and the number of words each selected word could be taken ...
On Wikipedia and other sites running on MediaWiki, Special:Random can be used to access a random article in the main namespace; this feature is useful as a tool to generate a random article. Depending on your browser, it's also possible to load a random page using a keyboard shortcut (in Firefox , Edge , and Chrome Alt-Shift + X ).
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.
Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.
Pages in category "Random text generation" The following 19 pages are in this category, out of 19 total. This list may not reflect recent changes. A. AI Dungeon; B.
A random stimulus is any class of creativity techniques that explores randomization. Most of their names start with the word "random", such as random word, random heuristic, random picture and random sound. In each random creativity technique, the user is presented with a random stimulus and explores associations that could trigger novel ideas.
"google doodles" will result in showing a random playable Google Doodle and also show an archive of other playable Doodles. [citation needed] "google logo history" results in a slideshow of the changes to the Google logo, starting with the logo used today and ending with one of the first logos from 1998. [97]
It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...