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 an alternative payment technique which will exchange intermediaries with cryptographic strategies and must be embedded in the research areas of SIGeBIZ and SIGSEC. On this paper we propose to remedy this drawback by utilizing the methods originally developed for the pc-aided evaluation for hardware and software methods, specifically those based mostly on the timed automata. In this paper we introduce a tool to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper supplies an evaluation of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to be able to separate reality from fiction when studying claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. Generally, ui(t) features a few abrupt modifications, partitioning the history of Bitcoin into separate time periods. In the preliminary phase is excessive, fluctuating around (see Fig. 5), presumably a result of transactions happening between addresses belonging to a few enthusiasts attempting out the Bitcoin system by shifting cash between their very own addresses.<br><br>my web blog ... [http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23 http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23] |
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 an alternative payment technique which will exchange intermediaries with cryptographic strategies and must be embedded in the research areas of SIGeBIZ and SIGSEC. On this paper we propose to remedy this drawback by utilizing the methods originally developed for the pc-aided evaluation for hardware and software methods, specifically those based mostly on the timed automata. In this paper we introduce a tool to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper supplies an evaluation of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to be able to separate reality from fiction when studying claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. Generally, ui(t) features a few abrupt modifications, partitioning the history of Bitcoin into separate time periods. In the preliminary phase is excessive, fluctuating around (see Fig. 5), presumably a result of transactions happening between addresses belonging to a few enthusiasts attempting out the Bitcoin system by shifting cash between their very own addresses.<br><br>my web blog ... [http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23 http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23]
|
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 an alternative payment technique which will exchange intermediaries with cryptographic strategies and must be embedded in the research areas of SIGeBIZ and SIGSEC. On this paper we propose to remedy this drawback by utilizing the methods originally developed for the pc-aided evaluation for hardware and software methods, specifically those based mostly on the timed automata. In this paper we introduce a tool to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper supplies an evaluation of the current state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to be able to separate reality from fiction when studying claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. Generally, ui(t) features a few abrupt modifications, partitioning the history of Bitcoin into separate time periods. In the preliminary phase is excessive, fluctuating around (see Fig. 5), presumably a result of transactions happening between addresses belonging to a few enthusiasts attempting out the Bitcoin system by shifting cash between their very own addresses.<br><br>my web blog ... [http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23 http://zadavai-vopsj.ru/index.php?qa=user&qa_1=drawduck23]
|
Horodatage Unix de la modification (timestamp) | 1647821365 |
