Joomla! is one of the most powerful Open Source Content Management Systems on the planet. It is used all over the world for everything from simple websites to complex corporate applications. Joomla! is easy to install, simple to manage, and reliable.
#— Origin Server —#
cd /home/kevin/engine
git init
git add .
git commit -m “new install” -i *
#– file.txt was update by Clone Server
git reset
#– file.txt: needs to be update
git checkout file.txt
#— Clone Server —#
cd /home/kevin/engine
git init
git pull pacificair.com:/home/kevin
#–change something ex: file.txt and update origin server
git commit -m “ver1″ file.txt
git push –all pacificair.com:/home/kevin/engine
At Cepstral®, Text-to-Speech is our only focus. We make realistic synthetic voices that can say anything, anywhere, with personality and style. From the smallest device to large installations and high-end interactive media, Cepstral voices can bring fresh content to your ears, on demand
Installation
apt-get install unraryum install unrarCompress:
rar a -m5 -v5M -R myarchive /home/rar - starts the program
a - tells program to add files to the archive
-m5 - determine the compression level (0-store (fast)…3-default…5-maximum(slow))
-v5M - determine the size of each file in split archive, in this example you get files with size 5MB
myarchive - name of the archive you are creating
/home/ - is folder of the files you wish to add to the archive
Uncompress Archive
rar x myarchive.part01.rarhttp://www.stonehenge.com/merlyn/UnixReview/col32.html
Stonehenge has been teaching Perl since 1992, and our trainers are the authors of the bestselling tutorial books Learning Perl and Intermediate Perl which are based on our classes.
http://search.cpan.org/~gregfast/Lingua-EN-Syllable-0.251
http://search.cpan.org/dist/Lingua-EN-Fathom
This module analyses English text in either a string or file. Totals are then calculated for the number of characters, words, sentences, blank and non blank (text) lines and paragraphs. Three common readability statistics are also derived, the Fog, Flesch and Kincaid indices. All of these properties can be accessed through individual methods, or by generating a text report. A hash of all unique words and the number of times they occur is generated.
http://en.wikipedia.org/wiki/BM25
http://xapian.org/docs/bm25.html
Okapi BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson, Karen Spärck Jones, and others.
The name of the actual ranking function is BM25. To set the right context, however, it usually referred to as “Okapi BM25″, since the Okapi information retrieval system, implemented at London’s City University in the 1980s and 1990s, was the first system to implement this function.
BM25, and its newer variants, e.g. BM25F (a version of BM25 that can take document structure and anchor text into account), represent state-of-the-art retrieval functions used in document retrieval, such as Web search.
http://en.wikipedia.org/wiki/Levenshtein_distance
In information theory and computer science, the Levenshtein distance is a metric for measuring the amount of difference between two sequences (i.e., the so called edit distance). The Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character. A generalization of the Levenshtein distance (Damerau-Levenshtein distance) allows the transposition of two characters as an operation.
The metric is named after Vladimir Levenshtein, who considered this distance in 1965.[1] It is often used in applications that need to determine how similar, or different, two strings are, such as spell checkers.
http://xapian.org/docs/bm25.html
The tf–idf weight (term frequency–inverse document frequency) is a weight often used in information retrieval and text mining. This weight is a statistical measure used to evaluate how important a word is to a document in a collection or corpus. The importance increases proportionally to the number of times a word appears in the document but is offset by the frequency of the word in the corpus. Variations of the tf–idf weighting scheme are often used by search engines as a central tool in scoring and ranking a document’s relevance given a user query.
Fedora Project Bittorrent Tracker
http://torrent.fedoraproject.org/