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Hundreds of functions of a variety of topics, from statistics to string parsing, module utilities to network tools. Everyone's pet library accumulates features over time. My erlang library got big, fast. I often find myself giving functions from it out to other people, and a lot of my other ... [More] libraries are dependant on ScUtil in various ways, so I figured what the hell, let's give it away. This library is believed to be efficiently implemented at all points. Efficiency tips are, however, both appreciated and taken seriously. ScUtil uses the TestErl library for unit, regression and stochastic testing. ScUtil is free and MIT licensed, because the GPL is evil. ScUtil is written by John Haugeland, from http://fullof.bs/ . [Less]

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  0 reviews  |  11 users  |  8,986 lines of code  |  1 current contributor  |  Analyzed 4 days ago
 
 

GNAT is a library and web service capable of performing gene entity NER and normalization of biomedical articles. Mentions of genes and proteins in the articles are linked to to Entrez Gene identifiers. GNAT is available both for local download (suitable for large-scale processing) and as a web ... [More] service (suitable for more limited processing or testing). A combination of local and remote processing is also available, where CPU-heavy operations are performed locally and memory-intensive operations are performed remotely (this is suitable for large-scale processing where a large amount of memory is not available). GNAT uses LINNAEUS (Gerner et al., 2010) for species detection and BANNER (Leaman et al., 2008) in one part of its false positive filtering process. [Less]

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  0 reviews  |  2 users  |  28,354 lines of code  |  1 current contributor  |  Analyzed 9 days ago
 
 

URL Normalizer is the name of URL Normalization or URL canonicalization in this project.Then, it decides if two syntactially different URLs are equivalent. It could avoid that web crawler crawling the same content in different URLs. The detail of URL Normalization and it's algorithm where ... [More] you could study via this link below. http://en.wikipedia.org/wiki/URL_normalization My implementation is based on Wikipedia but normalization based on URL lists is not done yet which is the process of detecting different URLs with similar text via URL not his content automatically. It is a static library for all of the search engine and web crawler. If you have any suggestion or bug reports, contacting to me via jiayunye@gmail.com. Thanks!Enjoy it. [Less]

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  0 reviews  |  0 users  |  8,275 lines of code  |  0 current contributors  |  Analyzed 4 days ago
 
 
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The project aims to provide an easy way for students to learn database normalization in a Web-based environment. Database normalization is a technique for designing relational database tables to minimize duplication of information in order to safeguard the database against certain types of ... [More] logical or structural problems, namely data anomalies. Therefore database normalization is a central topic in database theory, and its correct understanding is crucial for students. Unfortunately, the subject it is often considered to be dry and purely theoretical and is often not well received by students. To help avoid some of the above problems LDBN was developed by Nikolay Georgiev as part of his master's thesis at the University of UmeƄ, Sweden, under the supervision of Stephen J. Hegner. LDBN is a Web-based environment for learning relational-database normalization. LDBN is aiming to improve the understanding and knowledge of relational-database normalization among students, who are learning database theory and are already familiar with the basics of the relational-database normalization. LDBN was developed in order to give students the ability to easily and efficiently test their knowledge of the different normal forms in practice. The environment assists the students by providing them the following functionalities: Allow the student to specify a candidate decomposition of a given relation. Assess the correctness of the student's proposed decomposition relative to many factors; including: Lossless-join property Dependency preservation Specification of keys Correctness of the 2NF, 3NF and BCNF decompositions Provide students with sample decompositions when needed. Allow users to communicate with each other via comments/posts. The students can test their knowledge by solving different assignments, which consist of a relational-database schema in universal-relation form (URF), i.e., all the attributes in a single relation and a set of FDs on the attributes. The user (the student) have to find different decompositions of the relation. The user can check his solution with LDBN. The result is shown in an information window. The user are given small hints were the mistake might be. If the user is still uncertain about the right solution then LDBN can provide him/her with a sample solution as well. Other features of LDBN include an easy way for lecturers to create new assignments. [Less]

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  0 reviews  |  0 users  |  10,736 lines of code  |  0 current contributors  |  Analyzed 3 days ago
 
 

Syntactically different URLs may point to the same resource. So it's necessary to normalize (canonicalize) URLs before serious comparison.

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  0 reviews  |  0 users  |  0 current contributors
 
 

A minimal Windows .Net tool to experiment with image color manipulations. Comes with an very modest set of typical algorithms for color normalization. Implementation: Windows .Net 1.1

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  0 reviews  |  0 users  |  0 current contributors  |  Analyzed 7 days ago
 
 

Dependencies Normalization showed with GWT.

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  0 reviews  |  0 users  |  93 lines of code  |  0 current contributors  |  Analyzed 1 day ago
 
 

Will take the currentms.zip file and process each story in it, quoting it and normalizing its format. Also parses out author and ms# into the database. And a sed-like function to take out boilerplate text added by critique.org.

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  0 reviews  |  0 users  |  0 current contributors
 
 
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  0 reviews  |  0 users  |  4,513 lines of code  |  0 current contributors  |  Analyzed 7 days ago
 
 

A simple web app built on top of Google App Engine that takes as input a set of functional dependencies, and returns a calculated L-minimum cover to this set.

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  0 reviews  |  0 users  |  148 lines of code  |  0 current contributors  |  Analyzed 5 days ago
 
 
 
 

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