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Canonicalization of filenames is important for computer security. For example, a web server may have a restriction that only files under the cgi directory C:\inetpub\wwwroot\cgi-bin may be executed. This rule is enforced by checking that the path starts with C:\inetpub\wwwroot\cgi-bin\ and only then executing it.
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IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...
Text normalization is the process of transforming text into a single canonical form that it might not have had before. Normalizing text before storing or processing it allows for separation of concerns, since input is guaranteed to be consistent before operations are performed on it.
The following normalizations are described in RFC 3986 [1] to result in equivalent URIs: . Converting percent-encoded triplets to uppercase. The hexadecimal digits within a percent-encoding triplet of the URI (e.g., %3a versus %3A) are case-insensitive and therefore should be normalized to use uppercase letters for the digits A-F. [2] Example:
For example, each record in a "Faculty and Their Courses" relation might contain a Faculty ID, Faculty Name, Faculty Hire Date, and Course Code. Therefore, the details of any faculty member who teaches at least one course can be recorded, but a newly hired faculty member who has not yet been assigned to teach any courses cannot be recorded ...
Python's runtime does not restrict access to such attributes, the mangling only prevents name collisions if a derived class defines an attribute with the same name. On encountering name mangled attributes, Python transforms these names by prepending a single underscore and the name of the enclosing class, for example:
In this example, {Manufacturer country} is the functionally dependent attribute which will be removed. Place those partial dependency-dependent attributes (i.e. {Manufacturer country}) in a relation where their corresponding determinant attributes are a candidate key (i.e. {Manufacturer}).