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 payment methodology which will change intermediaries with cryptographic methods and should be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose [http://bvkrongbong.com/Default.aspx?tabid=120&ch=640752 where to buy bitcoin] treatment this problem by utilizing the methods initially developed for the computer-aided evaluation for hardware and software systems, particularly those based on the timed automata. In this paper we introduce a device to check and analyze the UTXO set, along with a detailed description of the set format and functionality. This paper provides an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you want to be able to separate fact from fiction when studying 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 number of abrupt changes, partitioning the historical past of Bitcoin into separate time periods. Within the initial phase is high, fluctuating round (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a couple fanatics attempting out the Bitcoin system by transferring money between their very own addresses. |
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 payment methodology which will change intermediaries with cryptographic methods and should be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose [http://bvkrongbong.com/Default.aspx?tabid=120&ch=640752 where to buy bitcoin] treatment this problem by utilizing the methods initially developed for the computer-aided evaluation for hardware and software systems, particularly those based on the timed automata. In this paper we introduce a device to check and analyze the UTXO set, along with a detailed description of the set format and functionality. This paper provides an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you want to be able to separate fact from fiction when studying 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 number of abrupt changes, partitioning the historical past of Bitcoin into separate time periods. Within the initial phase is high, fluctuating round (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a couple fanatics attempting out the Bitcoin system by transferring money between their very own addresses.
|
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 payment methodology which will change intermediaries with cryptographic methods and should be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose [http://bvkrongbong.com/Default.aspx?tabid=120&ch=640752 where to buy bitcoin] treatment this problem by utilizing the methods initially developed for the computer-aided evaluation for hardware and software systems, particularly those based on the timed automata. In this paper we introduce a device to check and analyze the UTXO set, along with a detailed description of the set format and functionality. This paper provides an assessment of the present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you want to be able to separate fact from fiction when studying 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 number of abrupt changes, partitioning the historical past of Bitcoin into separate time periods. Within the initial phase is high, fluctuating round (see Fig. 5), presumably a results of transactions taking place between addresses belonging to a couple fanatics attempting out the Bitcoin system by transferring money between their very own addresses.
|
Horodatage Unix de la modification (timestamp) | 1647734320 |
