Abuse filter log

Details for log entry 137,217

04:05, 28 March 2020: FayeLefkowitz3 (talk | contribs) triggered filter 0, performing the action "edit" on User:FayeLefkowitz3. Actions taken: Warn; Filter description: (examine)

Changes made in edit

Action parameters

Variable	Value
Name of the user account `(user_name)`	'FayeLefkowitz3'
Age of the user account `(user_age)`	5413
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)`	'FayeLefkowitz3'
Full page title `(page_prefixedtitle)`	'User:FayeLefkowitz3'
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 anticipated, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternate payment technique which will exchange intermediaries with cryptographic strategies and needs to be embedded in the analysis areas of SIGeBIZ and SIGSEC. On this paper we propose to remedy this drawback by using the methods originally developed for the computer-aided analysis for hardware and software program programs, in particular these based mostly on the timed automata. In this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and functionality. This paper gives an evaluation of the current state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you want to have the ability to separate fact from fiction when studying claims about Bitcoin and other cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on figure 2. Typically, ui(t) options a few abrupt adjustments, partitioning the history of Bitcoin into separate time intervals. In the preliminary section is high, fluctuating round (see Fig. 5), presumably a result of transactions taking place between addresses belonging to a few fanatics attempting out the Bitcoin system by transferring money between their very own addresses.<br><br>Here is my blog post :: [https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers]'
Old page size `(old_size)`	0
All external links added in the edit `(added_links)`	[ 0 => 'https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers' ]
All external links in the new text `(all_links)`	[ 0 => 'https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers' ]
Links in the page, before the edit `(old_links)`	[]
Unix timestamp of change `(timestamp)`	1585368330


			As anticipated, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternate payment technique which will exchange intermediaries with cryptographic strategies and needs to be embedded in the analysis areas of SIGeBIZ and SIGSEC. On this paper we propose to remedy this drawback by using the methods originally developed for the computer-aided analysis for hardware and software program programs, in particular these based mostly on the timed automata. In this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and functionality. This paper gives an evaluation of the current state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you want to have the ability to separate fact from fiction when studying claims about Bitcoin and other cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on figure 2. Typically, ui(t) options a few abrupt adjustments, partitioning the history of Bitcoin into separate time intervals. In the preliminary section is high, fluctuating round (see Fig. 5), presumably a result of transactions taking place between addresses belonging to a few fanatics attempting out the Bitcoin system by transferring money between their very own addresses.<br><br>Here is my blog post :: [https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers https://www.dailystrength.org/journals/artificial-intelligence-in-web-development-and-web-developers]