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An LNS can be considered as a floating-point number with the significand being always equal to 1 and a non-integer exponent. This formulation simplifies the operations of multiplication, division, powers and roots, since they are reduced down to addition, subtraction, multiplication, and division, respectively.
Most database systems maintain some kind of transaction log, which are not mainly intended as an audit trail for later analysis, and are not intended to be human-readable. These logs record changes to the stored data to allow the database to recover from crashes or other data errors and maintain the stored data in a consistent state.
However, log-space reductions are probably weaker than polynomial-time reductions; while any non-empty, non-full language in P is polynomial-time reducible to any other non-empty, non-full language in P, a log-space reduction from an NL-complete language to a language in L, both of which would be languages in P, would imply the unlikely L = NL.
Floating-point representation is similar in concept to scientific notation. Logically, a floating-point number consists of: A signed (meaning positive or negative) digit string of a given length in a given base (or radix). This digit string is referred to as the significand, mantissa, or coefficient.
Thus under some conditions, the major portion of the significant data digits may lie beyond the capacity of the registers. Therefore, the result obtained may have little meaning if not totally erroneous. The Z1, developed by Konrad Zuse in 1936, was the first computer with floating-point arithmetic and
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
A log-structured filesystem is a file system in which data and metadata are written sequentially to a circular buffer, called a log.The design was first proposed in 1988 by John K. Ousterhout and Fred Douglis and first implemented in 1992 by Ousterhout and Mendel Rosenblum for the Unix-like Sprite distributed operating system.
The HyperLogLog has three main operations: add to add a new element to the set, count to obtain the cardinality of the set and merge to obtain the union of two sets. Some derived operations can be computed using the inclusion–exclusion principle like the cardinality of the intersection or the cardinality of the difference between two HyperLogLogs combining the merge and count operations.