Examiner des modifications individuelles
Cette page vous permet d'examiner les variables générées pour une modification individuelle par le filtre antiabus et de les tester avec les filtres.
Variables générées pour cette modification
| Variable | Valeur |
|---|---|
Si la modification est marquée comme mineure ou non (minor_edit) | |
Nom du compte d’utilisateur (user_name) | GGLCindi649 |
Groupes (y compris implicites) dont l'utilisateur est membre (user_groups) | *
user
autoconfirmed
|
Si un utilisateur est ou non en cours de modification via l’interface mobile (user_mobile) | |
Numéro de la page (article_articleid) | 3218 |
Espace de noms de la page (article_namespace) | 2 |
Titre de la page (sans l'espace de noms) (article_text) | GGLCindi649 |
Titre complet de la page (article_prefixedtext) | Utilisateur:GGLCindi649 |
Action (action) | edit |
Résumé/motif de la modification (summary) | |
Ancien modèle de contenu (old_content_model) | wikitext |
Nouveau modèle de contenu (new_content_model) | wikitext |
Ancien texte de la page, avant la modification (old_wikitext) | %About_Yourself% |
Nouveau texte de la page, après la modification (new_wikitext) | As anticipated, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment method that may change intermediaries with cryptographic strategies and should be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to remedy this downside by utilizing the strategies initially developed for the computer-aided analysis for hardware and software program systems, particularly these based mostly on the timed automata. In this paper we introduce a device to study and analyze the UTXO set, together 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 everything you want to have the ability to separate reality from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-various contribution ui(t) of the first six base networks on figure 2. In most cases, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. Within the preliminary section is excessive, fluctuating around (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a few fanatics attempting out the Bitcoin system by transferring cash between their own addresses.<br><br>My blog - [https://pastelink.net/f8y956j8 pastelink.net] |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-%About_Yourself%
+As anticipated, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment method that may change intermediaries with cryptographic strategies and should be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to remedy this downside by utilizing the strategies initially developed for the computer-aided analysis for hardware and software program systems, particularly these based mostly on the timed automata. In this paper we introduce a device to study and analyze the UTXO set, together 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 everything you want to have the ability to separate reality from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-various contribution ui(t) of the first six base networks on figure 2. In most cases, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. Within the preliminary section is excessive, fluctuating around (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a few fanatics attempting out the Bitcoin system by transferring cash between their own addresses.<br><br>My blog - [https://pastelink.net/f8y956j8 pastelink.net]
|
Lignes ajoutées lors de la modification (added_lines) | As anticipated, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment method that may change intermediaries with cryptographic strategies and should be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to remedy this downside by utilizing the strategies initially developed for the computer-aided analysis for hardware and software program systems, particularly these based mostly on the timed automata. In this paper we introduce a device to study and analyze the UTXO set, together 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 everything you want to have the ability to separate reality from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-various contribution ui(t) of the first six base networks on figure 2. In most cases, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. Within the preliminary section is excessive, fluctuating around (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a few fanatics attempting out the Bitcoin system by transferring cash between their own addresses.<br><br>My blog - [https://pastelink.net/f8y956j8 pastelink.net]
|
Horodatage Unix de la modification (timestamp) | 1647829388 |
