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 expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee method which will change intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we suggest to remedy this drawback through the use of the methods initially developed for the pc-aided analysis for hardware and software program methods, in particular these based mostly on the timed automata. In this paper we introduce a device to review and analyze the UTXO set, together with a detailed description of the set format and functionality. This paper gives an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every thing you need to be able [https://mapleol.com/home.php?mod=space&uid=43691 where to buy bitcoin] separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We show the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. In the initial part is excessive, fluctuating round (see Fig. 5), possibly a results of transactions taking place between addresses belonging [https://diigo.com/0nrfgy where to buy bitcoin] a couple lovers attempting out the Bitcoin system by transferring money between their very own addresses.<br><br>my blog: [https://apk.tw/space-uid-4344977.html apk.tw] |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-%About_Yourself%
+As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee method which will change intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we suggest to remedy this drawback through the use of the methods initially developed for the pc-aided analysis for hardware and software program methods, in particular these based mostly on the timed automata. In this paper we introduce a device to review and analyze the UTXO set, together with a detailed description of the set format and functionality. This paper gives an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every thing you need to be able [https://mapleol.com/home.php?mod=space&uid=43691 where to buy bitcoin] separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We show the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. In the initial part is excessive, fluctuating round (see Fig. 5), possibly a results of transactions taking place between addresses belonging [https://diigo.com/0nrfgy where to buy bitcoin] a couple lovers attempting out the Bitcoin system by transferring money between their very own addresses.<br><br>my blog: [https://apk.tw/space-uid-4344977.html apk.tw]
|
Lignes ajoutées lors de la modification (added_lines) | As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee method which will change intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we suggest to remedy this drawback through the use of the methods initially developed for the pc-aided analysis for hardware and software program methods, in particular these based mostly on the timed automata. In this paper we introduce a device to review and analyze the UTXO set, together with a detailed description of the set format and functionality. This paper gives an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every thing you need to be able [https://mapleol.com/home.php?mod=space&uid=43691 where to buy bitcoin] separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We show the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options a number of abrupt changes, partitioning the history of Bitcoin into separate time intervals. In the initial part is excessive, fluctuating round (see Fig. 5), possibly a results of transactions taking place between addresses belonging [https://diigo.com/0nrfgy where to buy bitcoin] a couple lovers attempting out the Bitcoin system by transferring money between their very own addresses.<br><br>my blog: [https://apk.tw/space-uid-4344977.html apk.tw]
|
Horodatage Unix de la modification (timestamp) | 1647815279 |
