Abuse filter log

Details for log entry 137,503

03:38, 30 March 2020: OFOKara84058701 (talk | contribs) triggered filter 0, performing the action "edit" on User:OFOKara84058701. Actions taken: Warn; Filter description: (examine)

Changes made in edit

Action parameters

Variable	Value
Name of the user account `(user_name)`	'OFOKara84058701'
Age of the user account `(user_age)`	7504
Groups (including implicit) the user is in `(user_groups)`	[ 0 => '*', 1 => 'user', 2 => 'autoconfirmed' ]
Page ID `(page_id)`	0
Page namespace `(page_namespace)`	2
Page title (without namespace) `(page_title)`	'OFOKara84058701'
Full page title `(page_prefixedtitle)`	'User:OFOKara84058701'
Action `(action)`	'edit'
Edit summary/reason `(summary)`	''
Old content model `(old_content_model)`	''
New content model `(new_content_model)`	'wikitext'
Old page wikitext, before the edit `(old_wikitext)`	''
New page wikitext, after the edit `(new_wikitext)`	'As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternative fee method that may replace intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to treatment this drawback by using the methods originally developed for the computer-aided analysis for hardware and software program methods, particularly those based mostly on the timed automata. On this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and performance. This paper offers an evaluation of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and [https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/ Bitcoin]. After this course, you’ll know everything you need to be able to separate truth from fiction when reading claims about Bitcoin and different cryptocurrencies. We present the time-various contribution ui(t) of the primary six base networks on figure 2. Normally, ui(t) features a few abrupt changes, partitioning the history of Bitcoin into separate time periods. In the initial phase is excessive, fluctuating around (see Fig. 5), presumably a results of transactions going down between addresses belonging to some lovers trying out the Bitcoin system by transferring cash between their very own addresses.<br><br>Feel free to visit my blog post ... [https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien erfahrungenscout.de]'
Old page size `(old_size)`	0
All external links added in the edit `(added_links)`	[ 0 => 'https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/', 1 => 'https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien' ]
All external links in the new text `(all_links)`	[ 0 => 'https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/', 1 => 'https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien' ]
Links in the page, before the edit `(old_links)`	[]
Unix timestamp of change `(timestamp)`	1585539537


			As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternative fee method that may replace intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to treatment this drawback by using the methods originally developed for the computer-aided analysis for hardware and software program methods, particularly those based mostly on the timed automata. On this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and performance. This paper offers an evaluation of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and [https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/ Bitcoin]. After this course, you’ll know everything you need to be able to separate truth from fiction when reading claims about Bitcoin and different cryptocurrencies. We present the time-various contribution ui(t) of the primary six base networks on figure 2. Normally, ui(t) features a few abrupt changes, partitioning the history of Bitcoin into separate time periods. In the initial phase is excessive, fluctuating around (see Fig. 5), presumably a results of transactions going down between addresses belonging to some lovers trying out the Bitcoin system by transferring cash between their very own addresses.<br><br>Feel free to visit my blog post ... [https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien erfahrungenscout.de]