Abuse filter log

Details for log entry 144,532

07:54, 3 June 2020: ElisabethWindsor (talk | contribs) triggered filter 0, performing the action "edit" on User:ElisabethWindsor. Actions taken: Warn; Filter description: (examine)

Changes made in edit

Action parameters

Variable	Value
Name of the user account `(user_name)`	'ElisabethWindsor'
Age of the user account `(user_age)`	5
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)`	'ElisabethWindsor'
Full page title `(page_prefixedtitle)`	'User:ElisabethWindsor'
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 methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee method that may change intermediaries with cryptographic strategies and must be embedded in the analysis areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this problem by utilizing the methods initially developed for the computer-aided analysis for hardware and software program systems, in particular those based mostly on the timed automata. In this paper we introduce a software to study and analyze the UTXO set, together with a detailed description of the set format and functionality. This paper supplies an assessment of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the things you want to have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the first six base networks on figure 2. Generally, 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), probably a result of transactions happening between addresses belonging to some fans trying out the Bitcoin system by shifting money between their own addresses.<br><br>My web page - [https://sites.google.com/bitcoinloophole.io/bitcoin-loophole/ https://sites.google.com/]'
Old page size `(old_size)`	0
All external links added in the edit `(added_links)`	[ 0 => 'https://sites.google.com/bitcoinloophole.io/bitcoin-loophole/' ]
All external links in the new text `(all_links)`	[ 0 => 'https://sites.google.com/bitcoinloophole.io/bitcoin-loophole/' ]
Links in the page, before the edit `(old_links)`	[]
Unix timestamp of change `(timestamp)`	1591170884


			As anticipated, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee method that may change intermediaries with cryptographic strategies and must be embedded in the analysis areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this problem by utilizing the methods initially developed for the computer-aided analysis for hardware and software program systems, in particular those based mostly on the timed automata. In this paper we introduce a software to study and analyze the UTXO set, together with a detailed description of the set format and functionality. This paper supplies an assessment of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the things you want to have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the first six base networks on figure 2. Generally, 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), probably a result of transactions happening between addresses belonging to some fans trying out the Bitcoin system by shifting money between their own addresses.<br><br>My web page - [https://sites.google.com/bitcoinloophole.io/bitcoin-loophole/ https://sites.google.com/]