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  2. List of open-source software for mathematics - Wikipedia

    en.wikipedia.org/wiki/List_of_open-source...

    SageMath is designed partially as a free alternative to the general-purpose mathematics products Maple and MATLAB. It can be downloaded or used through a web site. SageMath comprises a variety of other free packages, with a common interface and language. SageMath is developed in Python.

  3. Windows Calculator - Wikipedia

    en.wikipedia.org/wiki/Windows_Calculator

    The Calculator in non-LTSC editions of Windows 10 is a Universal Windows Platform app. In contrast, Windows 10 LTSC (which does not include universal Windows apps) includes the traditional calculator, but which is now named win32calc.exe. Both calculators provide the features of the traditional calculator included with Windows 7 and Windows 8.x ...

  4. md5sum - Wikipedia

    en.wikipedia.org/wiki/Md5sum

    The MD5 hash functions as a compact digital fingerprint of a file. As with all such hashing algorithms, there is theoretically an unlimited number of files that will have any given MD5 hash. However, it is very unlikely that any two non-identical files in the real world will have the same MD5 hash, unless they have been specifically created to ...

  5. bcrypt - Wikipedia

    en.wikipedia.org/wiki/Bcrypt

    The salt is typically a random value. The bcrypt function uses these inputs to compute a 24-byte (192-bit) hash. The final output of the bcrypt function is a string of the form: $2<a/b/x/y>$[cost]$[22 character salt][31 character hash] For example, with input password abc123xyz, cost 12, and a random salt, the output of bcrypt is the string

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    Bubble Mouse Unlock 98 puzzles and 6 locations in this free addictive match 3 bubble saga, which includes power-ups, bubble ring mini-games, leaderboards, and so much more! And as a special NEW ...

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  8. Locality-sensitive hashing - Wikipedia

    en.wikipedia.org/wiki/Locality-sensitive_hashing

    In computer science, locality-sensitive hashing (LSH) is a fuzzy hashing technique that hashes similar input items into the same "buckets" with high probability. [1] ( The number of buckets is much smaller than the universe of possible input items.) [1] Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search.

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