Select Interface Language:
--Select-- Albanian Arabic Bulgarian Catalan Chinese(Simp) Chinese(Trad) Croatian Czech Danish Dutch English Estonian Filipino Finnish French Galician German Greek Hebrew Hindi Indonesian Italian Japanese Korean Latvian Lithuanian Maltese Norwegian Persian ALPHA Polish Portuguese Romanian Russian Serbian Slovak Slovenian Spanish Swedish Thai Turkish Ukrainian Vietnamese
Recent Hits:
• Today:
216
• Yesterday:
710
• Trend:
Yearly Hits:
• 2009:
5,463 • 2010:
70,070 • 2011:
122,282 • 2012:
139,559 • 2013:
279,738 • 2014:
211,936 • 2015:
195,374 • 2016:
153,554 • 2017:
110,448 • 2018:
53,122 • 2019:
28,252 • 2020:
70,563 • 2021:
152,497 • 2022:
555,112 • 2023:
224,993 • 2024:
193,226 • 2025:
188,946 • Total:
2,755,459
Average Hits:
• Hourly: 20
• Daily:
479
• Monthly:
14,578
• Yearly:
174,939
Objective
Golddays v4
briefing Kill the naabs and grab the gold! Axis Objective Descriptions: Primary Objective:**blow the door to access the house. 2 Primary Objective:**build the ladder to get an extra entrance to the
Hits: 5
Total Maps: 85
Top-Ten Countries visiting Fogfighters Hungary 1 United States 2 China 3 Viet nam 4 Russian Federation 5 France 6 Hungary 7 unknown 8 Ukraine 9 Canada 10 United Kingdom 11 Germany 12 Netherlands 13 Poland 14 Italy 15 Taiwan, Province of China 16 Seychelles 17 Australia 18 Romania 19 Indonesia 20 India 21 Thailand 22 Sweden 23 Brazil 24 Japan 25 South Africa 26 Lithuania 27 Argentina 28 Spain 29 Iran, Islamic Republic of 30 Chile 31 Luxembourg 32 Turkey 33 Moldova, Republic of 34 Korea, Republic of 35 Belarus 36 Malaysia 37 Venezuela 38 Switzerland 39 Singapore 40 Colombia 41 Hong Kong 42 Mexico 43 Mongolia 44 Czech Republic 45 Belize 46 Greece 47 Honduras 48 Estonia 49 Latvia 50 Bulgaria View MS-Analysis
Mods: Community: Clans: League: Anticheat: Other:
July
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Google Translate
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services
Babelfish, AOL, Yahoo and MSN the current version uses SYSTRAN.
The next version will use an innovative approach called Statistical
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Nations Documents as a corpus. The corpus is 20 billion words worth of
content. It uses existing source and target language translations (done
by human translators at the U.N.) to find patterns it then uses to build
rules for translating between those languages
See also
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